TD 3.1 - Enhanced Switch & Crossing System Demonstrator
The main objective of the ‘Enhanced Switch & Crossing System’ (TD 3.1) is to improve the operational performance of existing Switch & Crossing (S&C) designs through the delivery of new S&C subsystems with enhanced reliability, availability, maintainability and safety (RAMS), life-cycle costs (LCCs), sensing and monitoring capabilities, self-adjustment, noise and vibration performance, interoperability and modularity.
Implementation within IP3 projects
WP2 - Enhanced switches and crossings
The overall objective of WP2 is to build upon the engineering side of IN2TRACK’s whole-system evaluation of existing European S&C (Switches & Crossings) systems from INNOTRACK, Capacity4Rail and In2Rail to improve both RAMS (Reliability and Maintainability System ) performance and LCC (Life Cycle Cost) enhancements for maintenance approaches and to serve IN2SMART Specific objectives include:
- Analysis of S&C failure modes, root causes and cost drivers based on existing studies;
- Development of an enhanced S&C whole system behaviour models for better understanding and design optimisation. The whole system modelling approach will integrate mechanical, electrical, software and control components to deliver required improved capabilities and performance;
- Development of improved components and technologies to optimise S&C sub-systems (e.g. Points Operating Equipment) for RAMS performance whilst reducing whole system LCC.
- Development of new sustainable materials and repair, maintenance technologies, and methods to minimise deterioration and failures allowing for extended asset life, reduced maintenance intervention and lower LCC;
- Enhanced wheel-rail interaction and related decreases in deterioration through improved S&C designs;
- Enhanced inspection, monitoring and measurement through intelligent use of embedded and integrated sensors for self-diagnostics and remote condition monitoring to quantify asset condition, deterioration and performance as a whole;
- Use of whole system design and an enhanced sensor system to enable intelligent switch control, for self-adjustment, to maintain optimised performance and safety limits;
- Enhanced S&C control for self-maintenance and improved RAMS performance.
WP1 - Enhanced Switch and Crossing system demonstrator
The main objective of this WP is to support TD3.1 to improve the operational performance of existing S&C designs through the delivery of new and/or enhanced S&C sub-systems with enhanced RAMS, LCC, sensing and monitoring capabilities, self-adjustment, N&V performance, interoperability and modularity.
The research activities aim at results ranging from TRL5-6, while it is anticipated that successful demonstration in operational environment even touches TRL7.
WP1 - Enhanced S&C system demonstrator
The main objective of WP1 is to bring the Technical Demonstrators within TD3.1: “Enhanced Switches and Crossings” to the next level of maturity. WP1 transits the results of the projects IN2TRACK and IN2TRACK2 to higher TRL (up to TRL7) in order to enhance the RAMS performance of the system S&C design but also its subcomponents. The overall aim is to develop more reliable components, extend their operational life, improve LCC while increasing the railway infrastructure availability. The project research goals are:
• Enhance the understanding of the performance of the components based by means of the whole-system modelling approach and empirical analysis based on data from real operations in field
• Roll out hybrid testing and validation technologies to minimise in-situ testing
• Validate the whole system modelling approach with measured data from operational environment (in-track full assessment)
• Validation of performance of demonstrators in real operational environment o VARS Demonstrator
• SNCF (optimised manganese frog)
• Evaluate the developed condition monitoring methods and maintenance procedures: novel sensor systems and procedures assessing their impact on the maintenance strategies, maintenance of components
TD 3.2 - Next Generation Switch & Crossing System Demonstrator
The ‘Next Generation Switch & Crossing System’ (TD 3.2) aims to provide radical, novel system solutions that deliver new methods for directing trains to change tracks with the aim of increasing capacity, while reducing maintenance needs, traffic disturbances and LCCs.
Implementation within IP3 projects
WP1 - Best practices, elicitation of requirements and horizon scanning
1.1 Determine standard operating parameters and definitions
1.2 Identify current performance and best practice for S&C technologies
1.3 Elicit user and technical requirements
1.4 Identify and assess applicable technologies and processes from rail and other industries
1.5 Perform horizon scanning to form future S&C concepts in order to set a long term roadmap for S&C development and technology integration
WP2 - Overall system architecture and initial high level design
2.1 Select and refine the design principles to be used throughout all developments
2.2 Create an overall modular system architecture that reduces complexity
2.3 Develop high level design and integration concepts for next generation control, monitoring and sensor systems
2.4 Develop high level design and integration for next generation concepts, materials and components
2.5 Develop high level design and integration for next generation kinematic systems
2.6 Identify key principles for next generation installation and logistics
WP3 - Next generation control: monitoring and sensing systems
3.1 Development and integration of data and sensor systems to support the elimination of manual inspection and maintenance interventions
3.2 Development and integration of intelligent self-diagnostic systems capable of monitoring the current state-ofheath (and future states) which take account of the environment and external factors
3.3 Design of fault-tolerant control systems that support self- adjustment, self-correction, self-repair and self-heal
WP4 - Next generation design: materials and components
4.1: Investigate novel materials and additive manufacturing approaches
4.2: Identify designs that reduce complexity and result in fewer components
4.2: Optimise the wheel-rail interface to support new switching mechanisms
4.3: Review innovative solutions for support
4.4: Whole level system optimisation
4.5: Evaluate solutions in relation to logistics and installation
WP5 - Next Generation kinematic systems: actuators and mechatronics
5.1 Development of a completely new switch actuation mechanism
5.2 Design of radically different switch actuation and locking components
5.3 Application of mechatronic technologies to S&C
WP6 - System integration and concept validation
6.1: To validate the prototype subsystems and components developed in WP3 to 5.
WP7 - Evaluation, impact and future development
7.1 Evaluate improvements in capacity
7.2 Evaluate improvements in reliability
7.3 Evaluate safety implications
7.4 Evaluate investment cost and LCC reductions
WP2 - Next Generation Switches & Crossings
The overall objective of WP2 is to design and build a series of component and sub-system prototypes (up to TRL5) to evaluate a number of radically different concepts for future S&C systems.
WP2 - Next Generation Switches & Crossings Demonstrator
The overall objective is to radically improve the performance of S&C by eliminating or reducing a significant number of existing failure modes. The challenge therefore is to develop technology and designs for S&C, targeting a time horizon of around forty years beyond current state-of-the-art, capable of providing a step-change in reliability, availability, maintainability and safety (RAMS) performance improvement, with a significant reduction in life cycle costs. Next generation solutions will also implement technologies to minimise environmental impact and carbon footprint, with lower levels of noise and vibration and improve system resilience against climate change. WP2 will demonstrate, through a combination of both sub-system modelling and physical component/sub-system prototypes, how advances in design, manufacturing and materials will contribute to a future step-change in S&C performance. This step-change in performance will meet the overall project objectives; to reduce lifecycle costs, improve reliability and punctuality, whilst increasing capacity, enhancing interoperability and improving the customer experience.
TD 3.4 - Next Generation Track System
The ‘Next-Generation Track System’ (TD 3.4) aims to drastically improve the track system, targeting a time range some 40 years beyond the present state of the art. This implies that step changes in performance are to be highly prioritised. The TD process will follow a tightly integrated chain, setting out by initially identifying the long-term needs of the railway and the potential solutions for meeting these.
Implementation within IP3 projects
WP4 - Next Generation Track
The overall objective of WP4 is to improve the track system substantially, targeting a time horizon of some 40 years beyond current state-of-the art, in order to provide a step change in performance. Prototypes and virtual demonstrators (up to TRL5) will be provided.
WP02 - State of the art and technical specification for a next generation transition zone
WP03 - Detailed design of the next generation transition zone
WP04 - Numerical modelling of transition zones to support the validation of designs
WP05 - Resilience based monitoring of transition zones
WP06 - Large-scale laboratory testing of a next generation transition zone
WP4 - Next Generation Track
The overall challenge is to develop technology and integrated technology demonstrators for next generation track systems, targeting a time horizon of around forty years beyond current state-of-the-art. The objective of WP4 is to identify and develop solutions that will deliver step changes in the performance of the current state-of-the-art track, building on the various work packages in IN2RAIL, IN2TRACK, IN2TRACK2 and IN2SMART. The design will be developed for the next generation track sub-systems and components, which will aim to reduce deterioration mechanisms and eradicate failure modes; thus improving the performance of the system. In addition, autonomous inspection and maintenance techniques will be developed to further improve the performance of the track asset. The development of materials and components, combined with more efficient and targeted maintenance processes, will support the project specific objectives of a step change in track system performance. This will be delivered by contribution towards the overall Shift2Rail KPIs through reduced LCC, lower maintenance, low noise, high RAMS performance and environmental sustainability. The work will demonstrate the expected benefits of the innovations through identified KPIs and contribute to Shift2Rail targets related to capacity, reliability and life cycle costs.
TD 3.5 - Proactive Bridge and Tunnel Assessment, Repair and Upgrade Demonstrator
The main objective of the ‘Proactive Bridge and Tunnel Assessment, Repair and Upgrade’ (TD 3.5) is to improve inspection methods and repair techniques to reduce costs, improve quality and extend their service life, if possible. Moreover, the reduction of noise and vibrations are prioritised objectives.
Implementation within IP3 projects
The objective of WP4 is to:
- develop faster and more accurate methods for inspection and assessment of tunnels and bridges including improved repeatability, reproducibility, quality and effectiveness.
- develop new repair, strengthening and upgrading techniques which result in reduced traffic disruption and fast installation with short track access time
- set the base for future development of noise and vibration damping methods for structures
WP5 - Assessment and Improvement of Tunnels and Bridges
1The WP aims at providing new tools for monitoring and to extend the life of structures. In addition the WP will work on finding motivated requirements for bridges to be built for high speed traffic.
The WP1 aims at identifying and developing the most appropriate monitoring technologies addressing bridges and tunnels. A special focus is placed on subsurface defect detection, noise/vibration monitoring, geometrical and visual scanning, and other specific measurements. Firstly, the three subtasks will cooperate to identify what parameters need to be monitored, and how. Secondly, the appropriate technology for this purpose (sensors, etc.) will be identified and prepared. The resulting hardware/software technologies will serve for testing in the next WPs.
In order to speed up the coarse scanning of the asset for quick assessment, visualization and data geo-registration purposes, this WP will complement traditional sensing equipment with autonomous inspection robots. These systems, when possible, will act as a carrier platforms equipped with laser scanning, and visible and thermal cameras providing. From the other side, software will be developed for real time, automated and continuous data collection and further management at local and centralized levels, allowing the integration with the management platform to be developed in WP2 for further data processing, management of each individual sensor from the platform and building of 3D representations. The interface of the system will enable in a web platform with a powerful GIS viewer to allow its access from any computer equipment and without the need to install any software.
WP02 - Information Modelling
The main purpose of this Work Package is developing an integrated platform for information modelling of tunnels and bridges. An existing 3D/4D/5D/6D BIM project management and analysis platform, BEXEL Manager, with its inherent, all-encompassing approach to information integration will be further extended to include all additional information related to measuring and monitoring tunnels and bridges, as will be described. The resulting platform will contain all current capabilities - a 3D BIM model carrying geometry, design information, quantities etc., together with relevant linked documents, 5D costs, 6D maintenance plans and similar, with an additionally developed layer of information on top, containing all sensory information and data relevant to examination technologies, measuring and monitoring systems. The sensory layer will be integrated inside the BIM platform in the same manner as other aspects of a BIM model, as well as interface horizontally with other mentioned modules. This will enable an abundance of interlinked information, all present within an integral container, for facilitating and enhancing decision making and potentially enabling additional analyses.
WP03 - Fatigue Consuption Assessment
WP3 will develop a robust tool for evaluation of fatigue consumption of infrastructure components, with focus on bridges. The robustness aim is defined by the ability to utilize all typical input data types provided by traffic management, on-board monitoring data, wayside train monitoring data and structural monitoring systems, while handling different situations of data availability. In the process, different measurement results (influence lines, axle load histories, dynamic contact forces, etc.) will be merged and used to update fatigue assessment of structural components to improve its accuracy. Specific Objectives:
- Develop software tool for evaluation of fatigue consumption of structural components using robust algorithms
- Propose and implement methods for data-based, section-specific evaluation of load histories
- Develop methods for monitoring-based, structure-specific updating of fatigue assessment
- Propose method for estimation of confidence interval for fatigue consumption
- Create BIM-Interface for data import and result export
- Use modular architecture that makes different data streams optional, not mandatory
- Demonstrate the system in relevant environment (TRL 6)
WP04 - Intervention Measures Implementation
An aim of this WP is to prepare a proper framework for the implementation of intervention measures within the Asset Information Model (AIM). Thus a proper comparative analysis of intervention measures and the asset performance identifications are needed. The objectives of WP4 are:
- to review and benchmark the existing intervention technologies for railway bridges and tunnel,
- development of noise dampers,
- development of method for cleaning of long tunnels drainage pipes.
The latter two objectives are especially highlighted within this WP as they are answering technical challenges of TD3.5, which requests to improve the inspection methods and repair techniques for bridges and tunnels. Those objectives are closely linked to the sensing activities within WP1, as a proper monitoring system is needed also to assess the effectiveness of intervention measure.
WP05 - Validation Workstream
The objective of WP5 is to validate the results of the previous WPs, namely: models, algorithms, software, devices, prototypes, sensors and integrated systems by testing them in relevant environments which can be either simulated environments and/or operational environments closer to reality. The proven technology should reach a minimum TRL of 5-6 depending of the case. The objectives are divided in 2:
1.Validation within the consortium-provided test sites, which employ the facilities provided by the stakeholders involved in the Assets4Rail consortium. This includes:
- Task 5.1 Pre-validation in simulated environments (TRL5)
- Task 5.2 Bridge validation test section (TRL5-6)
- Task 5.3 Tunnel validation test section (TRL5-6)
2.Validation within Shift2Rail of the results of the project Assets4Rail The objective of this part is to carry out validation in relevant environments provided by the members of S2R in consonance with the technical demonstrators TD3.5 and TD3.7. This should be enabled by signing a Collaboration Agreement with the project holder of S2R-CFM-IP3-01-2018.
WP5 - Assessment and Improvement of Tunnels and Bridges
The WP aims at providing new solutions for monitoring and improvements to extend the economical service life of existing tunnel and bridge structures. Ongoing and potential deterioration shall be found earlier or with improved information in order to allow for remedial actions with reduced disturbances in train operations. In addition, the WP will work on finding relevant criteria, motivated requirements and representative behaviours for new bridges to be built for high speed traffic. Here the aim is to avoid unnecessary and expensive solutions not needed to achieve a uniform and decidable safety. Work will build upon the successful outcome of IN2TRACK2 and will demonstrate results up to TRL7.
TD 3.6 - Dynamic Railway Information Management System (DRIMS) Demonstrator
The ‘Dynamic Railway Information Management System (DRIMS)’ (TD 3.6) aims to define an innovative system for the management, processing and analysis of railway data. The activities in this TD will be strongly linked with the other two TDs in the area of information capturing and management. DRIMS is intended to collect information from the Railway Integrated Measuring and Monitoring System (RIMMS – TD 3.7) and to provide high-quality input to the Intelligent Asset Management Strategies (IAMS – TD 3.8).
Implementation within IP3 projects
WP07 - DRIMS Open Standard Interfaces
3The objective of this WP is to develop a guideline for Open Standard Interfaces for Maintenance Data including models and data exchange by exploring the current state of the art concerning the acquisition, integration, fusion, transformation, distribution, and processing of data, available in various heterogeneous data sources. The goal is to implement software to demonstrate the feasibility of the developed interfaces, complementing the work done in IN2RAIL WP8 and WP9 for TMS and related Open Calls.
WP08 - DRIMS Data Mining & Predictive Analytics
This WP will be centred on the study, design and development of innovative approaches for data processing, data analysis, data correlation, data mining and logistics centred on:
- Big Data analytics;
- Machine learning, including anomalies detection and data clustering;
- Process Mining;
- Prognostics and diagnostics for degrading railway infrastructures.
This work will be structured and organised in a case-study driven way. These case-studies will concern relevant assets, whose malfunction and maintenance policies have an impact on the KPI’s targeted by the Shift2Rail program, and not included into IN2RAIL dynamic modelling activities.
WP4 - Smart contracts for Railway Data Transactions
The aim of the WP4 is to provide to IN2DREAMS the smart contracts framework for Railway Data Transactions Exchange. The need for such framework is driven by the progressive liberalization of the railway sector, which is creating a complex ecosystem composed of several actors that need to manage a fragmented infrastructure. The usage of innovative decentralized technologies may enhance efficiency and reduce costs, therefore it is necessary to include them in the research. This WP includes definition, development and testing of a novel data transactions framework in a full self-executing logic for contracts, namely smart contracts, covering technical, business and regulatory aspects in a full integrated vision. The main specific objectives are:
- To identify the data transactions scenarios and the main business cases
- To define the smart contracts reference architecture for the data transactions, figuring out all the technical and business aspects and also defining the acceptance criteria for the data exchange framework
- To design and implement a Proof of Concept which demonstrate the high potential of the technology
- To achieve the comprehension of regulatory reference framework, to prepare potential application of the technology in a real-world scenario
WP5 - KNOWLEDGE EXTRACTION FOR RAILWAY DATA
The general objective of WP5 is to study, design and develop data analytics solutions for knowledge extraction from railway asset data. This objective will be achieved through the following tasks:
- Definition of data analytics scenarios.
- Development and demonstration of tools and methodologies aiming at extracting knowledge from data analytics algorithms, contemporarily making them interpretable in an easier way.
- Study and proof-of-concept of metrics and methods/tools to measure the accuracy of analytics algorithms.
Firstly, some scenarios and use-cases will be defined and developed in order to accomplish the main WP5 objectives. This work will focus on relevant railway assets whose malfunction and maintenance policies have an impact on the KPI’s targeted by the Shift2Rail program.
Secondly, data analytics algorithms aiming at extracting the knowledge hidden into railway asset data will be studied, designed and developed, keeping in mind that the possibility of understanding how the data analytics algorithms have gathered that information is also becoming more and more interesting. Indeed, this feature allows reconstructing the behaviour of a system or delineate a phenomenon in a more precise way, and improves decision-making processes. Therefore, a specific goal of WP5 will be to deliver to the railway sector a set of methodologies that can enable the endusers of the data analytics algorithms to get rich insights from their outputs.
Finally, the assessment of the performance of data analytics algorithms in asset management scenarios will be carried out through state-of-the-art statistical methodologies, and through the definition of novel validation metrics specifically intended for asset management. For the proof-of-concept, algorithms will be validated on historical data, and subsequently on the field.
These activities are extensive and complex, requiring a holistic approach and system-of-system thinking in order to develop and provide generic solutions, which can easily be adapted to a specific context.
WP04 - Italian Urban Metro System IAMS: design and deployment
Starting from the findings of IN2SMART and in synergy with WP3, the objectives of WP4 are Tuning the generic architecture and functions for urban metro; Design and deploy a field installation covering mainly TD 3.7. The data collected will be the main input for the tactical and operational levels demonstrator in WP5; Design and implementation of Data Analytics platform and Decision Support framework covering TD 3.6 and TD 3.8.
The final goal will be minimising maintenance costs, optimising the use of resources while maximising network availability and reliability.
WP4 will be based on IN2SMART WP2 requirements and global functional system architecture for a IAMS ant its further evolution in IN2SMART2 WP3, IN2RAIL and IN2SMART developments towards a CDM and its further evolution in IN2SMART2 WP3. Other inputs will be IN2SMART signalling proxy developed in WP5; IN2SMART Weight in Motion, dynamic impact and wheel defects fiber optics based technologies, models and algorithms developed in WP6; IN2SMART data analytics algorithms of WP8 and IN2SMART decision support methodologies of WP9.
Therefore, WP4 will focus on: Definition of system requirements to be validated in WP5 and synthesised at WP3; Installation plan definition for on-board signalling devices, wayside signalling devices, vehicles’ parameters, data processing system; Equipment procurement and installation of monitoring and data collections systems; Data analytics design and first implementation of nowcasting, anomaly detection and forecasting; Decision Support framework design and links with data analytics; First setup and data collection of monitoring systems; Equipment procurement and installation of data processing system; First setup of data processing system.
WP05 - Italian Urban Metro System IAMS: In field validation
The objective of WP5 is to fine tune installation, integrate analytics platform and DSS framework, and validate a demonstrator at the tactical and operational levels covering all TDs (3.6, 3.7 and 3.8) aimed at minimising maintenance costs, optimising the use of resources while maximising network availability and reliability. WP5 will be based on WP4 results and continuous interaction with WP3.
Therefore, WP5 will focus on: Fine tuning and optimisation of monitoring and data collection systems installed in WP4; Deployment of a complete IAMS architecture and CDM data exchange in line with WP3; Implementation and testing of data analytic methods with a focus on nowcasting, anomaly and prediction of asset status based on multiple data sources for the same asset (looking at several different assets); Implementation and testing of Decision Support Methodologies and algorithms including scheduling (of teams and machinery) optimisation, integration of logistics aspects such as spare parts, multimodal transportation and dynamic HMIs adaptable to user needs; Overall system validation in line with WP3 defined methodology and KPIs.
WP06 - Digital twin for railway asset management: Application to the French and Spanish railway network
The objective of the WP proposed is to create digital twins of new track sections and a new catenary system section of the railway infrastructure, and to develop processes to register and digitalise their evolution as it is being built (called the “As Built Records”, or “ABR”). The use case will deliver a demonstrator at a TRL level of 7, i.e. a digital twin and the “as built records” of real works performed on the French and Spanish Railway Network.
The demonstrator will be carried out in 2022 on 2 segments of the SNCF-R railway according to the planning of the worksite scheduled in 2021, respectively, for the catenary: line Paris Nord – Lille, UIC class 3, segment between station “Gannes” and “Ailly Sur Noye”; for the track: line Arras – Dunkerque, UIC class 4, segment between station “Lens” and “Bethune”. It is expected to perform a Proof of the concept in 2020 before implementing the demonstrator in 2022. The level of TRL of the demonstrator is expected to reach 7. Additionally, a construction phase demonstrator will be carried out in Spain, in order to develop a streamlined methodology for the digitalisation of new assets not designed using BIM methodology.
WP07 - Anomaly detection for rail fastener systems
The objective for this WP is to develop a demonstrator at the operational level covering the TDs 3.6 and 3.7 aimed at minimising maintenance costs, optimising the use of resources while maximising network availability and reliability. More in detail, the UC will integrate (and whenever needed refine/further develop) the following IN2SMART developments: TD3.6: Analytics platform architecture data analytics algorithms for fastener anomaly detection; TD3.7: on-board mounted equipment for data collection on rail fasteners.
The WP is an expansion in size and technological challenges of technology developed and validated in the IN2SMART project using a state-of-the art eddy-current sensor mounted on the vehicle. The sensor is optimised to measure the surface of any conductive material below the sensor. The measurement is analysed by computing an algorithm developed to extract any anomaly for the rail fastener systems.
This WP will also develop a decision support data access system in accordance with the objectives for TD 3.8 by develop a cloud-based front end for operators to access appropriate decision support data for maintenance planning on the rail fasteners systems. The outcome of the WP will be tested and validated on site using in-service trains thus reaching TRL 6-7.
WP08 - Remote Condition Monitoring Maintenance Reduction Interventions and Decisions: Design and Deployment
The overall objective is to improve the quality of asset management decision making by identifying the asset alarms generated by outside factors, such as weather and maintenance activity to enable Operators to prioritise their workload and respond to alarms. This will ensure that serious issues are not lost in the ‘noise’ generated by a large number of simultaneous anomalous alarms and generate a better record of the performance of an asset, ensuring that Whole Life Costing Models utilise a fairer assessment of the reliability of assets, and providing additional knowledge for maintenance optimisation algorithms.
The objective of this work package is a development (in size and technological challenges) of a platform for the prototypes developed for Thales Use Cases from IN2SMART WP8 (Anomaly Detection and Compensation for Weather Effects) and WP9 (Remote Condition Monitoring Intervention Decision Support), related to TD3.6 and TD3.8 respectively. This platform will be loaded with historical data and validated against a subset of the data. The work will link with X2RAIL-2 WP6 as the data will be available in the Integration Layer and accessible via the Core Operator Workstation HMI. The work will also include the Points Fault Classifier Algorithm identified in WP6 of the Transforming Transport GA 731932 project. The work package will cover: The environment of Network Rail, specifically the Transpennine Route. The route section is a 122Km route from Manchester to York via Leeds in the North of England. The specific assets to be used on this route are to be determined with Network Rail but there are 304Km of track and 236 switches and crossings available; Performing big data analysis of historical data including raw points and track circuit data, weather data and all possession and fault management systems logs; Working with Infrastructure Managers to perform a big data analysis on the available data to develop the additional ‘Asset Inter-dependencies’ and ‘Alarms Due to Maintenance’ to create the inputs for the Fault Tree Model; Using historical and a live Weather data interfaces to associate weather stations to asset location.
WP09 - Remote Condition Monitoring Maintenance Reduction Interventions and Decisions: In Field Validation
The overall objective is to enhance the Platform, as specified and tested in WP8, to create a Real World demonstrator (TRL 6) through connection to live data collection sources for a minimum period of 12 months.
The scope of the Prototype is at the operational level (IAMP) covering all TDs (3.6, 3.7 and 3.8) and is aimed at reducing the number of Track Circuits alarms that are raised anomalously due to weather effects and reducing the number of alarms raised due to maintenance work. These outputs will be available in the S2R Integration Layer and displayed as asset status information, prioritised lists, alarm views and KPI views within the Core Operator Workstation (X2RAIL2 WP6). The data is also available via the Integration Layer for use in the Tactical Level (AMP, SAMP) by providing additional asset knowledge for maintenance optimisation algorithms. The work package shall cover the following work on the platform: Load with historical data and the algorithms tested and validated against the full historical data; Connect to live data sources for raw points and track circuit data, weather data and all possession and fault management systems; Combine the previously processed historical data with the live data feeds to collect data for up to 12 Months, with regular monitoring and analysis of the results to provide additional and improved asset knowledge for the maintenance optimisation algorithms; For the identified section of Network Rail infrastructure, the team responsible for scheduling, fault finding, and maintenance will be engaged with, with the aim to understanding and quantifying the potential impact this prototype may have in the real world.
WP10 - SMART maintenance on rail freight corridor Rhine-Alpine
This WP will continue the work of IN2SMART and will include results of the OC Asset4Rails. The goal is to demonstrate condition-based maintenance and asset management on real sections of the Rhine-Alpine Rail Freight Corridor (RFC1).
WP 10 focuses on: Creation of a digital description of the track (digital twin) in terms of design, components, condition (historical /actual), defects, maintenance, behaviour, load, environment and models; Monitoring and inspection of the track and S&Cs; Development and application of data analytics for anomaly detection, quality management, identification and classification of defects, root cause analysis and prediction of degradation; Development and application of decision support tools for LCC and RAMS based decision including maintenance, renewal and improvements; Maintenance execution including lean tamping and combined maintenance activities; Comparison and assessment of different maintenance or asset management strategies.
WP11 - Integrated Asset Management for Civils
The objective of WP11 is to extend one use case developed and validated in IN2SMART (D8.2 Section 4.3 Anomalies in Track Geometry Degradation) in addition to another developed through Transforming Transport GA 731932 (Track Interface Tamping), with the aim of integrating these UC components into a decision support system at operational, tactical and strategic levels for civils assets: Machine Learning models of track geometry degradation and tamping effectiveness have been deployed in a TRL 3 “Tamping Planning Concept”. This displays the current track geometry condition and by employing predictive models identifies priority tamping operations in a 1-2-year time window. The IN2SMART2 Tactical Demonstrator would support identification of the most appropriate maintenance action for track geometry (tamp/stone-blow) and enable the formulation of prioritised plans. Crucial drivers around network access will be explored. The Demonstrator will align with industry KPIs classed as“Good-Track-Geometry” (GTG) and “Poor-Track-Geometry” (PTG). The objective is a maintenance plan that sustains track geometry condition metrics;IN2SMART also developed a life cycle engineering (LCE) prognosis tool providing short/medium forecasts (12 - 50 years) maintenance and reinvestment/replacement measures and costs for the existing bridges of Wiener Linien (WL). Different maintenance strategies, preventive maintenance versus “do minimum”, were analysed and evaluated. The IN2SMART2 Strategic Demonstrator will include more in-depth budget analysis and calibrate degradation models. Key objectives will be: To establish the optimum intervention plan for a given budget (‘design to cost’); better integration of the tool with established WL information systems.
WP12 - Operational Asset Management in a Dutch environment
This work package is an integrated demonstrator showing the operational asset management in a real life demonstration in a Dutch environment. Work is based on individual building blocks started in IN2SMART. It shows, based on some examples, the integrated approach how to come from data acquisition, data analytics and decision support to the actual logistical execution of the interventions. Strukton Control Centre is an essential linking pin between monitoring the network and the daily practice and execution of the work. Scope of the integrated demonstrator is the tactical and operational levels, with a strong focus on the latter, in the asset management process, covering all TD’s (3.6, 3.7 and 3.8) of the intelligent maintenance pillar.
The more specific objectives are:
Data Acquisition: within this work package the following data sources will be developed/used: improved switch engine current measurements; local measurements (e.g. temp, vibration), provided by IoT sensors; video images of track; ABA (Axle Box Accelerators); additional data sets (e.g. provided by the flexible measurement unit under development), Sensor data fusion will further enhance the data quality;
Data analytics: Development and Application of improved deterioration / prediction models of specific assets such as Rail, Rail Joints, Railway Switches etc. Extension and further optimisation of the approaches developed in IN2SMART for data-driven anomaly detection, the development of transparent diagnostic models and asset status predictions based on (un)supervised approaches; Aim is to automate inspection by development of enhanced tooling for analysis of train bound and wayside datasets in order to reduce/eliminate the need for field inspection (foot patrol);
Decision Support: based on defining the severity / risk assessment and translation into maintenance actions; Planning of maintenance actions (logistics) and planning of work in general (capacity) in a service organisation.
WP14 - Track maintenance decision support tool for a Swedish heavy haul railway line
The main objective of this work package is to develop a decision support tool for railway track maintenance. These objectives can be divided into the following sub-objectives: To collect, measure and detect the track status and precursors of track degradation based on work IN2SMART WP3, WP4, WP6 and WP8; To integrate the prediction model of the behaviour of track degradation for segments developed in IN2SMART WP8 with predictive models with the possibility to including isolated defects; To implement and adopt the integrated RAMS, LCC and Risk framework for generating maintenance plans for maintenance schedules, previously developed in IN2SMART WP9; To define specifications and requirements for an Integrated Maintenance Decision Support Platform and to incorporate the human factor guidelines developed in IN2SMART WP2.
WP02 - Prescriptive Analytics
WP03 - Multi-Objective Decision Optimisation
WP04 - Context-driven HMI
WP06 - Requirements definition, validation and evaluation
TD 3.7 - Railway Integrated Measuring and Monitoring System (RIMMS) Demonstrator
The ‘Railway Integrated Measuring and Monitoring System (RIMMS)’ (TD 3.7) is to provide innovative tools and techniques for capturing information on the current status of assets, in a non-intrusive and fully integrated manner. To this end, the TD will focus on asset status data collection in close interaction with TD3.1 through TD3.5.
Implementation within IP3 projects
WP03 - RIMMS Satellites & Autonomous Intelligent Monitoring Systems
The WP3 objective is to carry out a feasibility study that will be done in strong cooperation with In2Track project,for autonomous measuring systems based on UAV’s, satellites or unmanned/robot vehicles to monitor railway infrastructure assets and the environmental condition near them. This will be carried out with the following activities:
- Describe the monitoring performances, determined for example in other industrial fields, of various measuring systems based on satellites, UAVs and robots implementation;
- Identify the most key assets, according to S2R KPI, to be monitored and their related parameters and items to be measured, for which these kind of measuring system are particularly relevant;
- Propose application cases for each of the measuring vehicles considered;
- Select the most relevant monitoring system for each of the key assets to be monitored with autonomous system;
- Identify post-processing methods required to monitor the relevant parameters;
- Identify gaps that need to be overcome: normative context and security issues, technology improvement;
- Finally, implement proof of concepts for drone and robotics monitoring systems.
- The work carried out in this work package is a first coordinate approach among European railway networks about these autonomous monitoring systems, leading to agreed use cases.
WP04 - RIMMS Track and Switch & Crossings Monitoring
The objectives of this WP are:
- To develop calibrated prototypes of integrated monitoring systems for track and Switches & Crossings which can be installed on inservice trains;
- To identify and to validate the technology to monitor lateral and other important parameters of track geometry;
- To develop vehicle movements modelling on S&C, complementary non-destructive testing methods and to extend recording capabilities and processes for switch maintenance parameters.
- To develop the technology to identify surface errors in the rail tread, which are important for degradation of track geometry and S&C’s;
- To check that the implemented technologies are able to provide input for root cause identification and prediction of degradation and
- To point out the benefit of monitoring for smart and intelligent maintenance and asset management.
WP05 - RIMMS Signalling & telecommunications
The objective of this WP is to develop a framework toolset to be used by any party to develop a converter proxy for diagnostic data into a format defined by this project as an open standard IF. Collection of data could be performed using either “embedded” or “remote” monitoring solutions. Using a proxy for gathering data will reduce the risk of violating the safety case of the connected existing legacy signalling system and thus enable fast deployment. Create an in-lab demonstration of the proxy converter to conduct a proof-of-concept of the framework.
The WP objective is to achieve an integrated solution for monitoring the trains and their impact on the infrastructure which must be standardized, easy to be installed, low cost and compliant with the maintenance process proposed by the S2R project.
WP1 - User requirements and technology
The first objective of this WP is to understand user requirements in relation with inspection and monitoring tasks of railway assets. Based on the collected information, we will analyse the state of the art for all technologies and regulations potentially relevant for the tasks to be accomplished. We will focus on the identification of the key technology challenges and bottlenecks. Ultimately, we will indicate for each demonstrator the solution achieving the best balance between data quality, cost, and safety. The results of this WP will be used as input to WP2.
WP2 - Multiscale-Monitoring methodology & tools
The WP objective is to design the overall MOMIT solution taking into account inputs coming from WP1. The WP will define the services and product to be developed in terms of technology to be used for which purpose, and to obtain which kind of information and which level of detail. A major attention will be put on the definition of operational workflows where the designed solution could be integrated.
WP3 - Automated Data Processing & Post Processing
Automated Data Processing & Post Processing (led by CTTC), whose objective, by elaborating the requirements identified in WP1 and the technical specification from WP2, is to select optimal Data processing and post-processing methods, as well as data fusion approaches, deriving algorithms and automated SW chain prototypes. A platform prototype, with a suite of tools providing functionalities, including visualisation, analytics and information extraction capabilities, interfaces to access data, will also be developed. The integration and testing procedure will take into account the feedback from the demonstration cases.
WP4 - Application cases demonstration
The WP objective is to define and implement the six Application Cases foreseen in the Project. The first part of the activity will be focused on the definition of the scenarios, receiving in input the requirements of WP1 and the technical specification of WP2. The second part deals with the implementation of the scenario specification for each of the six demonstrators, adopting data processing and post-processing methods developed in WP3.
WP06 - Benchmarks And Specifications
- Provide the approaches and the current status of the relevant S2R running projects;
- Provide the state of the art of relevant technologies and benchmark products for the subsequent developments of train monitoring system in WP7, sensor system for track geometry monitoring in WP8 and data collection for diagnostics from signalling components in WP9;
- Definition of requirement specifications for subsequent developments and test specifications for laboratory testing and pilots in the railway environments.
WP07 - Train Monitoring Solutions
This Work Package aims at the development of an integral autonomous wayside monitoring station for detecting the prioritised rolling stock failures, by integrating the following technologies and solutions:
- Risk assessment methods to generate a priority list of the critical rolling stock components in terms of effects on infrastructure, where the monitoring actions should focus
- RFID technologies for the unique identification of rolling stock to ensure the correct assignment of the detected failures to the monitored vehicles
- Computer vision techniques to automatically capture images of the prioritised rolling stock components
- Big data solutions for the storage and management of images
- Image recognition for automatic detections of the prioritised detects at the early stage to not only reduce the costs of inspections and maintenance, but also provide users with the capability to make predictive, condition-based maintenance decisions rather than having to rely solely on visual inspection, allowing a better planning of short and long term proactive maintenance actions.
The potential RFID read/write applications will be investigated by defining different scenarios, in conjunction with the developed monitoring system.
A reference image database of failures of rolling stock components will be created, taking into account big data management solutions, to gain knowledge on failures. Besides, the effects of rolling stock failures on infrastructure will be quantified by the proposed risk assessment methods and the analytical models. This information will be fed into the asset management system to help advice maintenance needs.
WP08 - Sensor System to Support Track Geometry
This Work Package aims at the development of an on-board sensor system able to measure the transversal position of the wheel in relation to the rail in order to support track geometry measurements, including the following specific objectives:
- Select and assess the relevant candidate sensors for measurements according to the required features;
- Proof that the selected sensor could be operated under a large set of weather and environmental conditions (dust, rain, snow, etc.) and be active on in-service trains at 60-200 km/h in a simulated environment;
- Setup of a data acquisition system with easy and safe installation process on different typologies of bogies;
- Setup of energy supply system for the equipment taking into account the intended period of application aligned with existing rolling stock maintenance schemes
- Process data into a specific format that is compliant with the track geometry monitoring system developed in the complementary project and define communication interface in collaboration.
WP09 - Data Collection from Fail-safe Systems
The objective of this work package is to design and propose a set of acquisition and data collection schemes for safetycritical systems. These schemes must be developed for the on board systems and for the trackside, although the approach can be slightly different for both locations.
These set of monitoring, inspection and data collection systems shall be designed in a way that does not thread the safety critical functionalities of the “under inspection” equipment of data and does not jeopardize the performance of the system.
The proposed solution will be a mixed hardware and software platform capable to be integrated within the equipment to be monitored. Special care should be paid to the following on-board systems for train diagnostics: brakes and steering. The expected results will be:
- The specification of requirements for the acquisition and data collection systems suitable to manage the safety requirements of the safety-critical systems
- Development and validation in real environment of the above proposed acquisition systems (pilot test with an expected TRL of 5)
WP10 - Validation and Demonstration
This Work Package will validate the complete functionality of the developed train monitoring system in WP7, the sensor system for track geometry monitoring in WP8 and the data collection system in WP9 in a TRL 5/6 environment. The information collected from the pilots will be used to provide feedback on the technical performance and any bugs of the integrated technologies (i.e. installation, initial deployment, operation and communication). This validation exercise will produce input also for preparing documentation such as technical documentation, manual and user guides. Finally, the impact of the development systems on infrastructure maintenance will be evaluated, which paves the way for the system integration in S2R TD 3.7 and providing the data/information required to S2R TD 3.6 and S2R TD 3.8.
WP04 - Italian Urban Metro System IAMS: design and deployment
Starting from the findings of IN2SMART and in synergy with WP3, the objectives of WP4 are Tuning the generic architecture and functions for urban metro; Design and deploy a field installation covering mainly TD 3.7. The data collected will be the main input for the tactical and operational levels demonstrator in WP5; Design and implementation of Data Analytics platform and Decision Support framework covering TD 3.6 and TD 3.8.
The final goal will be minimising maintenance costs, optimising the use of resources while maximising network availability and reliability.
WP4 will be based on IN2SMART WP2 requirements and global functional system architecture for a IAMS ant its further evolution in IN2SMART2 WP3, IN2RAIL and IN2SMART developments towards a CDM and its further evolution in IN2SMART2 WP3. Other inputs will be IN2SMART signalling proxy developed in WP5; IN2SMART Weight in Motion, dynamic impact and wheel defects fiber optics based technologies, models and algorithms developed in WP6; IN2SMART data analytics algorithms of WP8 and IN2SMART decision support methodologies of WP9.
Therefore, WP4 will focus on: Definition of system requirements to be validated in WP5 and synthesised at WP3; Installation plan definition for on-board signalling devices, wayside signalling devices, vehicles’ parameters, data processing system; Equipment procurement and installation of monitoring and data collections systems; Data analytics design and first implementation of nowcasting, anomaly detection and forecasting; Decision Support framework design and links with data analytics; First setup and data collection of monitoring systems; Equipment procurement and installation of data processing system; First setup of data processing system.
WP05 - Italian Urban Metro System IAMS: In field validation
The objective of WP5 is to fine tune installation, integrate analytics platform and DSS framework, and validate a demonstrator at the tactical and operational levels covering all TDs (3.6, 3.7 and 3.8) aimed at minimising maintenance costs, optimising the use of resources while maximising network availability and reliability. WP5 will be based on WP4 results and continuous interaction with WP3.
Therefore, WP5 will focus on: Fine tuning and optimisation of monitoring and data collection systems installed in WP4; Deployment of a complete IAMS architecture and CDM data exchange in line with WP3; Implementation and testing of data analytic methods with a focus on nowcasting, anomaly and prediction of asset status based on multiple data sources for the same asset (looking at several different assets); Implementation and testing of Decision Support Methodologies and algorithms including scheduling (of teams and machinery) optimisation, integration of logistics aspects such as spare parts, multimodal transportation and dynamic HMIs adaptable to user needs; Overall system validation in line with WP3 defined methodology and KPIs.
WP06 - Digital twin for railway asset management: Application to the French and Spanish railway network
The objective of the WP proposed is to create digital twins of new track sections and a new catenary system section of the railway infrastructure, and to develop processes to register and digitalise their evolution as it is being built (called the “As Built Records”, or “ABR”). The use case will deliver a demonstrator at a TRL level of 7, i.e. a digital twin and the “as built records” of real works performed on the French and Spanish Railway Network.
The demonstrator will be carried out in 2022 on 2 segments of the SNCF-R railway according to the planning of the worksite scheduled in 2021, respectively, for the catenary: line Paris Nord – Lille, UIC class 3, segment between station “Gannes” and “Ailly Sur Noye”; for the track: line Arras – Dunkerque, UIC class 4, segment between station “Lens” and “Bethune”. It is expected to perform a Proof of the concept in 2020 before implementing the demonstrator in 2022. The level of TRL of the demonstrator is expected to reach 7. Additionally, a construction phase demonstrator will be carried out in Spain, in order to develop a streamlined methodology for the digitalisation of new assets not designed using BIM methodology.
WP07 - Anomaly detection for rail fastener systems
The objective for this WP is to develop a demonstrator at the operational level covering the TDs 3.6 and 3.7 aimed at minimising maintenance costs, optimising the use of resources while maximising network availability and reliability. More in detail, the UC will integrate (and whenever needed refine/further develop) the following IN2SMART developments: TD3.6: Analytics platform architecture data analytics algorithms for fastener anomaly detection; TD3.7: on-board mounted equipment for data collection on rail fasteners.
The WP is an expansion in size and technological challenges of technology developed and validated in the IN2SMART project using a state-of-the art eddy-current sensor mounted on the vehicle. The sensor is optimised to measure the surface of any conductive material below the sensor. The measurement is analysed by computing an algorithm developed to extract any anomaly for the rail fastener systems.
This WP will also develop a decision support data access system in accordance with the objectives for TD 3.8 by develop a cloud-based front end for operators to access appropriate decision support data for maintenance planning on the rail fasteners systems. The outcome of the WP will be tested and validated on site using in-service trains thus reaching TRL 6-7.
WP08 - Remote Condition Monitoring Maintenance Reduction Interventions and Decisions: Design and Deployment
The overall objective is to improve the quality of asset management decision making by identifying the asset alarms generated by outside factors, such as weather and maintenance activity to enable Operators to prioritise their workload and respond to alarms. This will ensure that serious issues are not lost in the ‘noise’ generated by a large number of simultaneous anomalous alarms and generate a better record of the performance of an asset, ensuring that Whole Life Costing Models utilise a fairer assessment of the reliability of assets, and providing additional knowledge for maintenance optimisation algorithms.
The objective of this work package is a development (in size and technological challenges) of a platform for the prototypes developed for Thales Use Cases from IN2SMART WP8 (Anomaly Detection and Compensation for Weather Effects) and WP9 (Remote Condition Monitoring Intervention Decision Support), related to TD3.6 and TD3.8 respectively. This platform will be loaded with historical data and validated against a subset of the data. The work will link with X2RAIL-2 WP6 as the data will be available in the Integration Layer and accessible via the Core Operator Workstation HMI. The work will also include the Points Fault Classifier Algorithm identified in WP6 of the Transforming Transport GA 731932 project. The work package will cover: The environment of Network Rail, specifically the Transpennine Route. The route section is a 122Km route from Manchester to York via Leeds in the North of England. The specific assets to be used on this route are to be determined with Network Rail but there are 304Km of track and 236 switches and crossings available; Performing big data analysis of historical data including raw points and track circuit data, weather data and all possession and fault management systems logs; Working with Infrastructure Managers to perform a big data analysis on the available data to develop the additional ‘Asset Inter-dependencies’ and ‘Alarms Due to Maintenance’ to create the inputs for the Fault Tree Model; Using historical and a live Weather data interfaces to associate weather stations to asset location.
WP09 - Remote Condition Monitoring Maintenance Reduction Interventions and Decisions: In Field Validation
The overall objective is to enhance the Platform, as specified and tested in WP8, to create a Real World demonstrator (TRL 6) through connection to live data collection sources for a minimum period of 12 months.
The scope of the Prototype is at the operational level (IAMP) covering all TDs (3.6, 3.7 and 3.8) and is aimed at reducing the number of Track Circuits alarms that are raised anomalously due to weather effects and reducing the number of alarms raised due to maintenance work. These outputs will be available in the S2R Integration Layer and displayed as asset status information, prioritised lists, alarm views and KPI views within the Core Operator Workstation (X2RAIL2 WP6). The data is also available via the Integration Layer for use in the Tactical Level (AMP, SAMP) by providing additional asset knowledge for maintenance optimisation algorithms. The work package shall cover the following work on the platform: Load with historical data and the algorithms tested and validated against the full historical data; Connect to live data sources for raw points and track circuit data, weather data and all possession and fault management systems; Combine the previously processed historical data with the live data feeds to collect data for up to 12 Months, with regular monitoring and analysis of the results to provide additional and improved asset knowledge for the maintenance optimisation algorithms; For the identified section of Network Rail infrastructure, the team responsible for scheduling, fault finding, and maintenance will be engaged with, with the aim to understanding and quantifying the potential impact this prototype may have in the real world.
WP10 - SMART maintenance on rail freight corridor Rhine-Alpine
This WP will continue the work of IN2SMART and will include results of the OC Asset4Rails. The goal is to demonstrate condition-based maintenance and asset management on real sections of the Rhine-Alpine Rail Freight Corridor (RFC1).
WP 10 focuses on: Creation of a digital description of the track (digital twin) in terms of design, components, condition (historical /actual), defects, maintenance, behaviour, load, environment and models; Monitoring and inspection of the track and S&Cs; Development and application of data analytics for anomaly detection, quality management, identification and classification of defects, root cause analysis and prediction of degradation; Development and application of decision support tools for LCC and RAMS based decision including maintenance, renewal and improvements; Maintenance execution including lean tamping and combined maintenance activities; Comparison and assessment of different maintenance or asset management strategies.
WP11 - Integrated Asset Management for Civils
The objective of WP11 is to extend one use case developed and validated in IN2SMART (D8.2 Section 4.3 Anomalies in Track Geometry Degradation) in addition to another developed through Transforming Transport GA 731932 (Track Interface Tamping), with the aim of integrating these UC components into a decision support system at operational, tactical and strategic levels for civils assets: Machine Learning models of track geometry degradation and tamping effectiveness have been deployed in a TRL 3 “Tamping Planning Concept”. This displays the current track geometry condition and by employing predictive models identifies priority tamping operations in a 1-2-year time window. The IN2SMART2 Tactical Demonstrator would support identification of the most appropriate maintenance action for track geometry (tamp/stone-blow) and enable the formulation of prioritised plans. Crucial drivers around network access will be explored. The Demonstrator will align with industry KPIs classed as“Good-Track-Geometry” (GTG) and “Poor-Track-Geometry” (PTG). The objective is a maintenance plan that sustains track geometry condition metrics;IN2SMART also developed a life cycle engineering (LCE) prognosis tool providing short/medium forecasts (12 - 50 years) maintenance and reinvestment/replacement measures and costs for the existing bridges of Wiener Linien (WL). Different maintenance strategies, preventive maintenance versus “do minimum”, were analysed and evaluated. The IN2SMART2 Strategic Demonstrator will include more in-depth budget analysis and calibrate degradation models. Key objectives will be: To establish the optimum intervention plan for a given budget (‘design to cost’); better integration of the tool with established WL information systems.
WP14 - Track maintenance decision support tool for a Swedish heavy haul railway line
The main objective of this work package is to develop a decision support tool for railway track maintenance. These objectives can be divided into the following sub-objectives: To collect, measure and detect the track status and precursors of track degradation based on work IN2SMART WP3, WP4, WP6 and WP8; To integrate the prediction model of the behaviour of track degradation for segments developed in IN2SMART WP8 with predictive models with the possibility to including isolated defects; To implement and adopt the integrated RAMS, LCC and Risk framework for generating maintenance plans for maintenance schedules, previously developed in IN2SMART WP9; To define specifications and requirements for an Integrated Maintenance Decision Support Platform and to incorporate the human factor guidelines developed in IN2SMART WP2.
TD 3.8 - Intelligent Asset Management Strategies Demonstrator (IAMS)
The vision of the ‘Intelligent Asset Management Strategies (IAMS)’ (TD 3.8) is a holistic, whole-system approach of asset management employing collected and processed data provided by TD3.6 and TD3.7. This includes putting long-term strategies in the context of day-to-day execution of the maintenance and other maintenance activities.
Implementation within IP3 projects
WP09 - IAMS Asset Management and Decision Support
The objective of WP9 is to design and study a generic framework for the decision-making process when planning maintenance and interventions, which is an important functional block of asset management in railway infrastructures.
This framework will put solutions from DRIMS and RIMMS into a common context to establish Intelligent Asset Management Strategies (IAMS). The framework completes the processing chain from gathering data (RIMMS), extracting meaningful information and knowledge (DRIMS) by turning them into decisions.
Specific objectives of this WP include the detailed description of the framework for the IAMS process:
- the guiding principles of predictive, risk- and condition-based, opportunistic, reliability-centred, integrative maintenance decision support
- the "building blocks" of the IAMS process, their respective functionalities and interaction, the workflow and the flow of information within the framework.
WP10 - IAMS Maintenance execution, work methods and tools
WP10 develops technologies for enhanced maintenance execution through two core tasks: Integrate
WP04 - Italian Urban Metro System IAMS: design and deployment
Starting from the findings of IN2SMART and in synergy with WP3, the objectives of WP4 are Tuning the generic architecture and functions for urban metro; Design and deploy a field installation covering mainly TD 3.7. The data collected will be the main input for the tactical and operational levels demonstrator in WP5; Design and implementation of Data Analytics platform and Decision Support framework covering TD 3.6 and TD 3.8.
The final goal will be minimising maintenance costs, optimising the use of resources while maximising network availability and reliability.
WP4 will be based on IN2SMART WP2 requirements and global functional system architecture for a IAMS ant its further evolution in IN2SMART2 WP3, IN2RAIL and IN2SMART developments towards a CDM and its further evolution in IN2SMART2 WP3. Other inputs will be IN2SMART signalling proxy developed in WP5; IN2SMART Weight in Motion, dynamic impact and wheel defects fiber optics based technologies, models and algorithms developed in WP6; IN2SMART data analytics algorithms of WP8 and IN2SMART decision support methodologies of WP9.
Therefore, WP4 will focus on: Definition of system requirements to be validated in WP5 and synthesised at WP3; Installation plan definition for on-board signalling devices, wayside signalling devices, vehicles’ parameters, data processing system; Equipment procurement and installation of monitoring and data collections systems; Data analytics design and first implementation of nowcasting, anomaly detection and forecasting; Decision Support framework design and links with data analytics; First setup and data collection of monitoring systems; Equipment procurement and installation of data processing system; First setup of data processing system.
WP05 - Italian Urban Metro System IAMS: In field validation
The objective of WP5 is to fine tune installation, integrate analytics platform and DSS framework, and validate a demonstrator at the tactical and operational levels covering all TDs (3.6, 3.7 and 3.8) aimed at minimising maintenance costs, optimising the use of resources while maximising network availability and reliability. WP5 will be based on WP4 results and continuous interaction with WP3.
Therefore, WP5 will focus on: Fine tuning and optimisation of monitoring and data collection systems installed in WP4; Deployment of a complete IAMS architecture and CDM data exchange in line with WP3; Implementation and testing of data analytic methods with a focus on nowcasting, anomaly and prediction of asset status based on multiple data sources for the same asset (looking at several different assets); Implementation and testing of Decision Support Methodologies and algorithms including scheduling (of teams and machinery) optimisation, integration of logistics aspects such as spare parts, multimodal transportation and dynamic HMIs adaptable to user needs; Overall system validation in line with WP3 defined methodology and KPIs.
WP07 - Anomaly detection for rail fastener systems
The objective for this WP is to develop a demonstrator at the operational level covering the TDs 3.6 and 3.7 aimed at minimising maintenance costs, optimising the use of resources while maximising network availability and reliability. More in detail, the UC will integrate (and whenever needed refine/further develop) the following IN2SMART developments: TD3.6: Analytics platform architecture data analytics algorithms for fastener anomaly detection; TD3.7: on-board mounted equipment for data collection on rail fasteners.
The WP is an expansion in size and technological challenges of technology developed and validated in the IN2SMART project using a state-of-the art eddy-current sensor mounted on the vehicle. The sensor is optimised to measure the surface of any conductive material below the sensor. The measurement is analysed by computing an algorithm developed to extract any anomaly for the rail fastener systems.
This WP will also develop a decision support data access system in accordance with the objectives for TD 3.8 by develop a cloud-based front end for operators to access appropriate decision support data for maintenance planning on the rail fasteners systems. The outcome of the WP will be tested and validated on site using in-service trains thus reaching TRL 6-7.
WP08 - Remote Condition Monitoring Maintenance Reduction Interventions and Decisions: Design and Deployment
The overall objective is to improve the quality of asset management decision making by identifying the asset alarms generated by outside factors, such as weather and maintenance activity to enable Operators to prioritise their workload and respond to alarms. This will ensure that serious issues are not lost in the ‘noise’ generated by a large number of simultaneous anomalous alarms and generate a better record of the performance of an asset, ensuring that Whole Life Costing Models utilise a fairer assessment of the reliability of assets, and providing additional knowledge for maintenance optimisation algorithms.
The objective of this work package is a development (in size and technological challenges) of a platform for the prototypes developed for Thales Use Cases from IN2SMART WP8 (Anomaly Detection and Compensation for Weather Effects) and WP9 (Remote Condition Monitoring Intervention Decision Support), related to TD3.6 and TD3.8 respectively. This platform will be loaded with historical data and validated against a subset of the data. The work will link with X2RAIL-2 WP6 as the data will be available in the Integration Layer and accessible via the Core Operator Workstation HMI. The work will also include the Points Fault Classifier Algorithm identified in WP6 of the Transforming Transport GA 731932 project. The work package will cover: The environment of Network Rail, specifically the Transpennine Route. The route section is a 122Km route from Manchester to York via Leeds in the North of England. The specific assets to be used on this route are to be determined with Network Rail but there are 304Km of track and 236 switches and crossings available; Performing big data analysis of historical data including raw points and track circuit data, weather data and all possession and fault management systems logs; Working with Infrastructure Managers to perform a big data analysis on the available data to develop the additional ‘Asset Inter-dependencies’ and ‘Alarms Due to Maintenance’ to create the inputs for the Fault Tree Model; Using historical and a live Weather data interfaces to associate weather stations to asset location.
WP09 - Remote Condition Monitoring Maintenance Reduction Interventions and Decisions: In Field Validation
The overall objective is to enhance the Platform, as specified and tested in WP8, to create a Real World demonstrator (TRL 6) through connection to live data collection sources for a minimum period of 12 months.
The scope of the Prototype is at the operational level (IAMP) covering all TDs (3.6, 3.7 and 3.8) and is aimed at reducing the number of Track Circuits alarms that are raised anomalously due to weather effects and reducing the number of alarms raised due to maintenance work. These outputs will be available in the S2R Integration Layer and displayed as asset status information, prioritised lists, alarm views and KPI views within the Core Operator Workstation (X2RAIL2 WP6). The data is also available via the Integration Layer for use in the Tactical Level (AMP, SAMP) by providing additional asset knowledge for maintenance optimisation algorithms. The work package shall cover the following work on the platform: Load with historical data and the algorithms tested and validated against the full historical data; Connect to live data sources for raw points and track circuit data, weather data and all possession and fault management systems; Combine the previously processed historical data with the live data feeds to collect data for up to 12 Months, with regular monitoring and analysis of the results to provide additional and improved asset knowledge for the maintenance optimisation algorithms; For the identified section of Network Rail infrastructure, the team responsible for scheduling, fault finding, and maintenance will be engaged with, with the aim to understanding and quantifying the potential impact this prototype may have in the real world.
WP10 - SMART maintenance on rail freight corridor Rhine-Alpine
This WP will continue the work of IN2SMART and will include results of the OC Asset4Rails. The goal is to demonstrate condition-based maintenance and asset management on real sections of the Rhine-Alpine Rail Freight Corridor (RFC1).
WP 10 focuses on: Creation of a digital description of the track (digital twin) in terms of design, components, condition (historical /actual), defects, maintenance, behaviour, load, environment and models; Monitoring and inspection of the track and S&Cs; Development and application of data analytics for anomaly detection, quality management, identification and classification of defects, root cause analysis and prediction of degradation; Development and application of decision support tools for LCC and RAMS based decision including maintenance, renewal and improvements; Maintenance execution including lean tamping and combined maintenance activities; Comparison and assessment of different maintenance or asset management strategies.
WP11 - Integrated Asset Management for Civils
The objective of WP11 is to extend one use case developed and validated in IN2SMART (D8.2 Section 4.3 Anomalies in Track Geometry Degradation) in addition to another developed through Transforming Transport GA 731932 (Track Interface Tamping), with the aim of integrating these UC components into a decision support system at operational, tactical and strategic levels for civils assets: Machine Learning models of track geometry degradation and tamping effectiveness have been deployed in a TRL 3 “Tamping Planning Concept”. This displays the current track geometry condition and by employing predictive models identifies priority tamping operations in a 1-2-year time window. The IN2SMART2 Tactical Demonstrator would support identification of the most appropriate maintenance action for track geometry (tamp/stone-blow) and enable the formulation of prioritised plans. Crucial drivers around network access will be explored. The Demonstrator will align with industry KPIs classed as“Good-Track-Geometry” (GTG) and “Poor-Track-Geometry” (PTG). The objective is a maintenance plan that sustains track geometry condition metrics;IN2SMART also developed a life cycle engineering (LCE) prognosis tool providing short/medium forecasts (12 - 50 years) maintenance and reinvestment/replacement measures and costs for the existing bridges of Wiener Linien (WL). Different maintenance strategies, preventive maintenance versus “do minimum”, were analysed and evaluated. The IN2SMART2 Strategic Demonstrator will include more in-depth budget analysis and calibrate degradation models. Key objectives will be: To establish the optimum intervention plan for a given budget (‘design to cost’); better integration of the tool with established WL information systems.
WP12 - Operational Asset Management in a Dutch environment
This work package is an integrated demonstrator showing the operational asset management in a real life demonstration in a Dutch environment. Work is based on individual building blocks started in IN2SMART. It shows, based on some examples, the integrated approach how to come from data acquisition, data analytics and decision support to the actual logistical execution of the interventions. Strukton Control Centre is an essential linking pin between monitoring the network and the daily practice and execution of the work. Scope of the integrated demonstrator is the tactical and operational levels, with a strong focus on the latter, in the asset management process, covering all TD’s (3.6, 3.7 and 3.8) of the intelligent maintenance pillar.
The more specific objectives are:
Data Acquisition: within this work package the following data sources will be developed/used: improved switch engine current measurements; local measurements (e.g. temp, vibration), provided by IoT sensors; video images of track; ABA (Axle Box Accelerators); additional data sets (e.g. provided by the flexible measurement unit under development), Sensor data fusion will further enhance the data quality;
Data analytics: Development and Application of improved deterioration / prediction models of specific assets such as Rail, Rail Joints, Railway Switches etc. Extension and further optimisation of the approaches developed in IN2SMART for data-driven anomaly detection, the development of transparent diagnostic models and asset status predictions based on (un)supervised approaches; Aim is to automate inspection by development of enhanced tooling for analysis of train bound and wayside datasets in order to reduce/eliminate the need for field inspection (foot patrol);
Decision Support: based on defining the severity / risk assessment and translation into maintenance actions; Planning of maintenance actions (logistics) and planning of work in general (capacity) in a service organisation.
WP13 - Robotic and automated LEAN execution
In IN2SMART WP10, a concept demonstrator (TRL 4) of a robotic platform for maintenance was developed. The objective of WP13 is to use this work to further develop the robotic command and control aspect to TRL 7.
It will be demonstrated to command and control a small wheeled vehicle with robotic maintenance capability, designed to operate during track possessions (no service trains running). This will be extended to an example for a specific use/application (end effector) for the robot. The example chosen is a high-pressure waterjet cutting machine.
WP14 - Track maintenance decision support tool for a Swedish heavy haul railway line
The main objective of this work package is to develop a decision support tool for railway track maintenance. These objectives can be divided into the following sub-objectives: To collect, measure and detect the track status and precursors of track degradation based on work IN2SMART WP3, WP4, WP6 and WP8; To integrate the prediction model of the behaviour of track degradation for segments developed in IN2SMART WP8 with predictive models with the possibility to including isolated defects; To implement and adopt the integrated RAMS, LCC and Risk framework for generating maintenance plans for maintenance schedules, previously developed in IN2SMART WP9; To define specifications and requirements for an Integrated Maintenance Decision Support Platform and to incorporate the human factor guidelines developed in IN2SMART WP2.
WP15 - Strategical and tactical track asset management for the North Line in Portugal & New Tram Depot Design with smart IAMS approach
Starting from the findings of IN2SMART the objectives of WP15 are: Design and implementation of a data analytics platform using already developed algorithms (from Past EU projects, IN2SMART, IM degradation models in use, etc.) for track degradation models; Design and implementation of a detailed tactical mid-term maintenance and renewal planning tool with focus on track assets. It will be based on the North Line in Portugal, managed by IP, with a length of 336,079 km connecting Lisbon and Oporto, acting as the main North-South corridor; Design and implementation of a strategical decision support tool based on the tactical planning tool (simulation-based approach) to support the assessment of the IM asset management strategic KPIs; Development of a standard depot design fitted to Zaragoza’s tram concept, including the definition of basic requirements, sizing of elements and spaces, as well as a detailed design and technical specification of the building. This information, fed by de data collection from infrastructure, will be included as rules in BIM methodology for depots designs, with the aim of get a basis design to be customise afterwards to the real case; Based on simulation the defined target KPIs will be evaluated and lessons learned are collected.
WP15 will be based on IN2SMART data analytics algorithms of WP8, decision support methodologies of WP9 and good practices for smart depot design as use case in WP9 as well as the requirements and global functional system architecture for a IAMS of WP2 and its further evolution in IN2SMART2 WP3.
WP02 - Autonomy functions
WP03 - Autonomous Operations
WP04 - Wearable Robot Mechatronic Design
WP05 - Human-Robot Interaction
TD 3.11 - Future Stations Demonstrator
The primary objective of the ‘Future Stations’ (TD 3.11) is the provision of improved customer experience at stations. The TD is organised around four identified key functional demands: two demands relate to improving capacity and security in large stations, one demand relates to the design of small stations with the objective of reducing whole life costs and standardising design, where possible, and the final demand relates to accessibility.
Implementation within IP3 projects
WP06 - Crowd Management in High Capacity Stations
The overall objective of this Work Package is to significantly improve both the customer experience and security in large and high capacity stations during both standard use and in emergency situations. A realistic 3D simulation system based off real-time data will be used to help enable this, leading to a TRL6 complete solution.
WP07 - Improved Station Designs and Components
This work Package aims to significantly improve the design of low-capacity stations and optimise the design process, from concept to construction. This will enable a reduction in construction and operational costs.
WP08 - Improved Accessibility to Trains - Platform Train Interface
This work package will achieve the following objectives:
- Improved accessibility to trains for all passenger groups by addressing issues with Platform-Train Interface (PTI).
- Develop solutions that allow safe and inclusive access to trains of varying heights without significantly impacting on the train’s dwell time at the platform
- Analysing specific PTI issues like differing train heights and curved platforms and how this may affect accessibility.
- Develop new PTI strategies for identified typical conditions in existing stations.
WP09 - Safety Management in Public Areas
Work Package 9 seeks to develop solutions for improving the safety and resilience of railway stations through developing models, risk assessments and a security manual that can be used to mitigate the impacts of a bomb blast. It will also analyse options for advanced CCTV technology that will analyse specific human behaviours, providing pre-emptive biometric information.
WP2 - User Needs & Expectations and Human Factors
For developing efficient systems user needs, requirements, expectations and experiences must be taken into consideration. WP2 will define all needs of rail passengers. The objective of WP2 is to collect data on the characteristics that influence train, PTI and station design. It applies a combination of social and technical analysis to determine and therefore postulate the link between passenger needs and their interaction with the train, PTI and station features. The word user in the context of this project refers to station users in general which mostly includes passenger (customers), but may also include station staff or other people who use the station facilities.
WP3 - Benchmarking of Station Designs and Accessibility
The first objective of this work package is to collect and analyse data and information from past research and studies. This is with a view to create a clear depiction of today’s knowledge level and to identify research gaps and needs, which will be the basis for developing future multi-modal and multi-functional high-capacity rail stations that provide for good crowd flow, accessibility, and inherently secure. Industry (train operators, infrastructure managers, door access systems) will be strongly involved in this work package, in order to provide guidance on the realistic state-of-the-art. An inventory of what constitutes today’s complex stations will be developed.
The second objective of WP3 is (using a gap analysis) to identify and categorise factors that drive design of future stations.
WP4 - Crowd Flow Analysis
- To study the crowd flow in large stations and describe the main behaviours and characteristics in the movement of people.
- To develop the modelling of multiple people flows in large stations and the ways to manage crowds particularly in emergency situations which are causing evacuation.
- Identify available enabling technologies to analyse crowd management and people’s movement in stations.
- Validation of the crowd flow model.
WP5 - Design and Conceptualisation
Iterative design process, with emphasis on security and inclusion of PRMs. A systems approach where the station design, PTI and door access will be designed as an integrated system optimised for smooth passenger flow and the station with enhanced security for improved safety and customer satisfaction.
The design will take into account compliance with the new legal requirements and standards in the EU such as the TSI PRM 2014 and CEN in the context of the extension of the of the trans-European rail network (TEN). The General conditions / boundary conditions are given by complex European and national legislations and technical regulations, such as the European Accessibility Act (on the basis of the UN Convention on Persons with Disabilities), the Passenger Rights Regulation and TSI PRM 2014.