DPC-based subway train door system performance degradation detection method

Abstract

The invention discloses a DPC-based subway train door system performance degradation detection method. The method comprises the following steps: (1) acquiring main line data of operation of a subway train door system through a motor sensor, and preprocessing the main line data and eliminating noise data; (2) performing piecewise feature extraction for the preprocessed data, analyzing time-domain characteristics through a univariate statistical analysis method, and obtaining a feature set which can completely embody states of the subway train door system; (3) based on a density peak clusteringalgorithm, building a system multi-door health initial state model for extracted system features; (4) identifying a degradation process of each train door performance in the multi-door system throughEuclidean distance. The DPC-based subway train door system performance degradation detection method provided by the invention can detect and judge whether train door system performance degrades, can reduce repetitive experimental design and data acquisition works, cannot be affected by train door types and types of locking devices, and has good universality.

Description

technical field [0001] The invention relates to a method for detecting a subway car door, in particular to a DPC-based method for detecting performance decline of a subway car door system. Background technique [0002] The door is one of the most important components in rail transportation, and its health status directly affects the efficiency of train operation and the personal safety of passengers. Especially in the operation process of subway vehicles, due to the frequent opening and closing of the doors and the numerous interference factors of passengers, frequent failures of passenger compartment doors occur. According to statistics, the number of door failures accounts for more than 30% of the total bus system failures. Therefore, knowing the decline process of the door system in time, detecting abnormal doors, and performing system maintenance in advance can greatly reduce or avoid the occurrence of catastrophic failures, which is of great significance for improving ...

AI Technical Summary

Problems solved by technology

The existing performance degradation prediction methods of other systems, such as the research on the performance degradation of fuel cells, mainly measure the AC impedance and compare the measured AC impedance value with the degradation reference value to evaluate t

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