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

作　　者：李思崎 关博 

机构地区：[1]波士顿大学,文理学院,美国 波士顿 [2]上海地铁第一运营有限公司,上海

出　　处：《应用数学进展》2023年第12期5050-5060,共7页Advances in Applied Mathematics

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。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.

关 键 词：地铁设施设备 数据分析 K均值聚类 应对策略 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]