Final Report Summary - PMNIDEA (Predictive maintenance employing non-intrusive inspection & data analysis)
The project focused on the development of non intrusive track inspection systems to increase track availability, increase life span and reduce life cycle costs of track components, and improve the safety of both workers and users of urban rail systems. The project has utilised and developed existing innovative technologies to monitor the health status and the rate of degradation of track components to provide visibility of future maintenance and renewal requirements. The project has delivered six Key Innovations that are aimed at improving the integrity of urban rail transport and mainline networks through the deployment of intelligent design and sensor technologies into cost effective products and targeted non-intrusive monitoring processes.
The project recognises the environmental, societal, and economic drivers of an efficient urban and mainline transport system that are reflected in transport plans. The overall concept of the project is to facilitate the achievement of this goal by generating solutions to some of the currently identified barriers to efficient and cost effective track maintenance. These project imperatives were established through close consultation with operators, maintainers and suppliers. In particular, the project is focussed on adoption and further development of novel inspection and sensor technologies whose technical principles have been well established, those that have been successfully employed in other industry sectors or which are emerging from University research programmes but need research into their application for the complexities of the railway environment.
The project has been driven by commercial principles to lower the risk and reduce the period to implementation of developed solutions. The project has two key drivers; firstly to contribute towards the realisation of a 24 x 7 railway by minimising the disruption caused by activities such as inspection, remedial and reactive maintenance, and track renewal. Secondly, the introduction of novel sensor and inspection technologies that focuses more on the monitoring of degradation through the measurement of deviation from identified benchmark data henceforth known as a "signature tune". Both these drivers reduced the cost of urban transport, and tramways in particular, which contributes to lowering congestion and the impact on the environment.
The design and optimisation of a cost effective image acquisition system capable of very high image quality and resolution, which can easily be mounted on the bogie of a tramway, metro, or a mainline service or maintenance vehicle has been completed. The images captured have been used to develop the algorithms for different track features. This work has achieved significant success in developing the algorithms for a number of key track features and rail head defects. An achievement of particular note is the ability to detect and characterise the running band on the rail head and deviations thereof that are indicative of discrete track irregularities. The developed system has been mounted on both Stagecoach Supertram and Warsaw tramway vehicles and has undertaken extended trial runs to acquire live images of the track infrastructure to validate the algorithms developed. Two further deliverables have been achieved from this WP. Firstly, a comprehensive catalogue of track components has been collated identifying the causes of their degradation. It is a very useful reference source that will be useful for both urban and mainline industry. Secondly, the synergistic benefit that can be obtained from the combination of the outputs of the intelligent image analysis with that of the vehicle mounted MEMS based accelerometers and gyroscopes.
A laser-sensor dimensional measuring system has been developed. This is an evolutionary technique used to reconstruct the three-dimensional shape from linear measurements. Test-runs have been successfully carried out on the Rome metro (ATAC).
A library of object recognition algorithms and analysis techniques for the identification of track components such Pandrol fastening clips, fish plates, and the interface between the road and polymer has been developed.
The project recognises the environmental, societal, and economic drivers of an efficient urban and mainline transport system that are reflected in transport plans. The overall concept of the project is to facilitate the achievement of this goal by generating solutions to some of the currently identified barriers to efficient and cost effective track maintenance. These project imperatives were established through close consultation with operators, maintainers and suppliers. In particular, the project is focussed on adoption and further development of novel inspection and sensor technologies whose technical principles have been well established, those that have been successfully employed in other industry sectors or which are emerging from University research programmes but need research into their application for the complexities of the railway environment.
The project has been driven by commercial principles to lower the risk and reduce the period to implementation of developed solutions. The project has two key drivers; firstly to contribute towards the realisation of a 24 x 7 railway by minimising the disruption caused by activities such as inspection, remedial and reactive maintenance, and track renewal. Secondly, the introduction of novel sensor and inspection technologies that focuses more on the monitoring of degradation through the measurement of deviation from identified benchmark data henceforth known as a "signature tune". Both these drivers reduced the cost of urban transport, and tramways in particular, which contributes to lowering congestion and the impact on the environment.
The design and optimisation of a cost effective image acquisition system capable of very high image quality and resolution, which can easily be mounted on the bogie of a tramway, metro, or a mainline service or maintenance vehicle has been completed. The images captured have been used to develop the algorithms for different track features. This work has achieved significant success in developing the algorithms for a number of key track features and rail head defects. An achievement of particular note is the ability to detect and characterise the running band on the rail head and deviations thereof that are indicative of discrete track irregularities. The developed system has been mounted on both Stagecoach Supertram and Warsaw tramway vehicles and has undertaken extended trial runs to acquire live images of the track infrastructure to validate the algorithms developed. Two further deliverables have been achieved from this WP. Firstly, a comprehensive catalogue of track components has been collated identifying the causes of their degradation. It is a very useful reference source that will be useful for both urban and mainline industry. Secondly, the synergistic benefit that can be obtained from the combination of the outputs of the intelligent image analysis with that of the vehicle mounted MEMS based accelerometers and gyroscopes.
A laser-sensor dimensional measuring system has been developed. This is an evolutionary technique used to reconstruct the three-dimensional shape from linear measurements. Test-runs have been successfully carried out on the Rome metro (ATAC).
A library of object recognition algorithms and analysis techniques for the identification of track components such Pandrol fastening clips, fish plates, and the interface between the road and polymer has been developed.
