基于K均值算法的设备故障分析与应对策略

Equipment Fault Analysis and Response Strategies Based on K-Means Algorithm

摘要: 针对如何通过维护保障管理手段提高设施设备安全运行的问题，本文以地铁车辆设备为研究对象，提出使用K均值聚类法对2014~2022年之间的故障数据进行对比分析；其次，利用调查问卷的方式，分别对维保专业内的9位检修组长和18位检修员的日常维护保障行为，进行数据采集；最后，基于应用K均值聚类算法以及调查问卷结果，提出基于数理统计耦合心理分析的设施设备维保管理应对策略。

Abstract: Regarding the issue of how to improve the safe operation of facilities and equipment through maintenance and management measures, this article takes subway vehicle equipment as the re-search object and proposes to use K-means clustering method to compare and analyze fault data between 2014 and 2022; secondly, using a survey questionnaire, data was collected on the daily maintenance and support behaviors of 9 maintenance team leaders and 18 maintenance personnel in the maintenance profession; finally, based on the K-means clustering algorithm and survey ques-tionnaire results, a facility and equipment maintenance response strategy based on mathematical statistics coupled psychological analysis is proposed.