Signal Processing for Remote Condition Monitoring of Railway Points

Abstract:  The dependability of railway points (turnouts or switches) is a key part of any railway system; the Potters Bar crash (10 May 2002) in the UK, which led to seven fatalities is a key example of a failure of this subsystem. Present maintenance of points involves overly frequent inspection by maintenance staff. A remote condition monitoring approach would lead to more efficient inspection routines and directed anticipatory maintenance trips. To assist the creation of a suitable fault-detection algorithm, the authors analysed existing force and current data for the 'as commissioned' case of a turnout and for situations with different fault conditions. Signal processing of this data revealed several different methods that can be used to distinguish between fully functioning points, and different fault conditions of the points. Specifically, clustering of statistical parameters and their application to wavelet levels and coefficients, provided clear discrimination of most critical faults. This demonstrates a good first step towards a condition monitoring-based maintenance regime for points that is both safer for passengers and maintenance personnel and that has the potential to be more effective and economical.     

监控作业中信号检察反应时间与信源数量关系的研究

通过模拟实验，考察了采用多个仪表显示的监控作业中信号检察反应时间与信源数量的关系。信源数量的变化范围为2-8个同时呈现的仪表，每种实验条件下的监控作业持续80min，等分为4个时间段，每个时间段为20min。实验结果表明：信源数量对信号检察反应时间有明显影响，随着信源数量的增加，反应时间也随之延长；信源数量与时间段之间存在着显的交互作用，信源数量越多，各时间段之间的差异也越大。