PMNIDEA · Predictive Maintenance employing Non-intrusive Inspection & Data Analysis

The environmental, societal, and economic drivers of an efficient urban transport system are well acknowledged and are reflected in the local transport plans of all major urban areas. The overall concept of the project is to facilitate the achievement of this goal by generating solutions to currently identified barriers that form the project imperatives, which have been 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. The project will develop an intelligent image acquisition and analysis system to enable more comprehensive and objective inspection of the track without the need for the increasingly unsafe and subjective track walking inspection. The project will also develop track sub-components with self monitoring capabilities to promote timely and knowledge based intervention for maintenance and renewal, while giving greater visibility of residual life and the need for future investments. These innovative developments are directed towards increasing the effective availability of the track infrastructure, increasing the life of new or renovated asset, reducing the cost of maintenance by timely intervention based on objective measurement of degradation and thereby provide a high quality reliable service to the end user.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 known as a “signature tune”. Both these drivers promote the use of urban transport, and tramways in particular, which contributes to lowering congestion and the impact on the environment.