基于统计分析的列车车门故障预测性诊断及分析方法

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中图分类号：U270.38 文献标志码：B doi：10.20214/j.cnki. zhgdjt.2025.05.014

Preventive Diagnosis and Analysis Method for Train Door Faults Based on Statistical Analysis

HOU Ying

（BeijingMetro OperationCo.，Ltd.，Beijingloolo3，China

Abstract：This article proposes a data-driven fault predictionand inteligent maintenance method to address the highfault rate of urban rail vehicle doorswhich seriously afects the operational safety and efficiency.Through the analysis of long-term operating dataof door controlers，itwas found that the occurrence of faults has obvious characteristic trends.The data mining technologywas adopted to establish a mathematical model，realizing the accurate prediction of door faults.Meanwhile，theanalysis ofoperating records of door controlers allowed to establish a fault probability model anda database for analyzing the service lifeof vulnerableparts，providing support for making decisionson preventivemaintenance.The article innovatively proposes to transform theconventional regular maintenance mode into a state-based maintenance modeand implement an optimized replacement strategy for components byseting afault rate threshold.Theresults show that this method can efectively predict door faults， reduce train operation and maintenance costs，significantly extend the service life of components and reduce the maintenance workload.Thisstudy provides a practical and feasible solution for the inteligent operationand maintenance of urban rail vehicles which has important engineering application value.

Key words：door fault；big data mining；Fourier transform；fault probability model

随着我国城市轨道交通规模的快速增长，地铁列车的维护和检修工作成为保证地铁安全、准时可靠运营的主要手段，目前主要依靠人工经验以及定期检查地铁列车各系统的零部件，即日检、周检、月修、里程修，定期地更换主要零部件[1]。（剩余5448字）