Multi-faceted Maintenance Strategy for Electronic Devices in Shanghai Rail Transit Communication and Signaling System
Journal Title: Urban Mass Transit - Year 2024, Vol 27, Issue 11
Abstract
Objective As the failure rate of electronic devices in Shanghai rail transit system keeps on increasing, traditional maintenance approaches—characterized by slow speed of self-repair, high costs of factory repair, long repair cycle, and substantial inventory requirements—result in significant waste of maintenance resources. To address these issues, an electronic device based multi-faceted maintenance strategy consisting of rapid detection, in-depth repair, and predictive maintenance is proposed. Method A comprehensive power module testing platform is established to enable rapid detection on power modules and precise fault localization, thereby enhancing repair efficiency. For outdated display units, in-depth repairs are performed, with LED new technology for replacement and upgrade to optimize power consumption and extend service life. Predictive maintenance is carried out using deep learning techniques to build models predicting the remaining service life based on electronic device fundamental information, daily maintenance data, operation monitoring data, and historical fault. Through conducting scientific and reasonable dynamic adjustments of maintenance cycles, the issues of adopting fixed repair cycle in conventional preventive maintenance mode are addressed, avoiding excessive repair or maintenance insufficiency. Result & Conclusion In practical applications, the self-designed comprehensive power module testing platform significantly improves fault localization accuracy and increases repair efficiency by 83%. After retrofitting the TOD (train operator display) units with LED light strips, the power consumption is decreased by 30%, significantly improving the display quality and extending the service life. In the remaining service life prediction using bullet camera, the accuracy rate reaches 96.4%. The predicative maintenance enables precise adjustment of maintenance cycles, resulting in a 53% reduction in operation-maintenance costs and a 64% decrease in fault rates, demonstrating substantial effectiveness.
Authors and Affiliations
Songjie ZHANG, Siyuan GU, Yangjing DAI
Keywords
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- EP ID EP751197
- DOI 10.16037/j.1007-869x.2024.11.024
- Views 14
- Downloads 0
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