Abstract
In order to monitor the brake performance degradation state of the in-service train pneumatic brake system, a data fusion method based on data processing and correlation analysis is proposed in this paper. By using the principal component analysis and analytic hierarchy process to analyze the historical on-board data of one subway line in China, five major indicators of the brake cylinder pressure curve based on seven principal signals are extracted, and the analytic hierarchy model of pneumatic brake system is established. Meanwhile, a standard brake cylinder pressure curve fast fitting tool programmed with MATLAB can realize the rapid curve fitting of historical on-board data under different vehicles, loads, and stations for a domestic subway line, and the algorithm has been validated by the normal and degradation data. By this way, the in-service train pneumatic brake performance degradation state is monitored through the deviation analysis between the standard curve and the fitting one. The method proposed in this paper is also suitable for the analysis of the pneumatic brake system performance of other rail transit trains.
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