Tremendous pressure is being imposed on railway operators to enhance service reliability and infrastructure maintenance to reduce disruption arising from train, track and overhead power line failures. This requires condition-monitoring systems that can effectively and continuously monitor mission-critical components to produce big data in respect of railway asset maintenance for the development of advanced fault identification and prediction techniques.
The research team led by Prof. Tam Hwa-yaw, Associate Director of the Photonics Research Institute (PRI), developed the world’s first optical fibre-based data-driven predictive maintenance system that enables railway industry to shift from costly and inefficient scheduled maintenance regimes to predictive maintenance. The system identifies defects in rail tracks, overhead power lines, wheel flats, and cracks in bogies and carriages. Five systems were installed in MTR Hong Kong and two in SMRT lines in Singapore in 2014 and 2016, respectively. The system monitors developing faults and had successfully predicted broken power line along the Amsterdam-Schiphol Airport Line in 2015, several weeks in advance. The goal is to herald a safer railway industry with reduced maintenance cost, and high quality of service.
Please check the link for his interview with a TV programme :
https://www.youtube.com/watch?v=POcPJfU8VDc (Chinese Only)
| Research Units | Photonics Research Institute |
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