基于多维关联规则的车辆故障码解耦方法研究  

Research on Vehicle Diagnostic Trouble Code Decoupling Method Based on Multidimensional Association Rule

作　　者：胡杰[1] 卿海华 魏敏 耿黄政 张潇[1] 陈林[1] Hu Jie;Qing Haihua;Wei Min;Geng Huangzheng;Zhang Xiao;Chen Lin(Wuhan University of Technology,Hubei Key Laboratory of Modern Auto Parts Technology,Hubei Collaborative Innovation Center for Automotive Components Technology,Hubei Research Center for New Energy&Intelligent Connected Vehicle,Wuhan 430070;SAIC General Wuling Automobile Co.,Ltd.,Liuzhou 545000)

机构地区：[1]武汉理工大学,现代汽车零部件技术湖北省重点实验室,现代零部件技术湖北省协同创新中心,新能源与智能网联车湖北工程技术研究中心,武汉430070 [2]上汽通用五菱汽车股份有限公司,柳州545000

出　　处：《汽车工程》2024年第1期161-169,共9页Automotive Engineering

摘　　要：本文提出一种针对车辆复杂耦合故障的故障码(DTC)解耦方法。首先由车辆故障自诊断原理及故障信号传播过程分析故障码的复杂关联性,结合关联规则技术挖掘故障码间强关联关系,并定义故障码多维关联规则;其次由故障码数据集特征,改进适用于故障码多维关联规则挖掘的FP-Growth算法;最后由多维关联规则构建故障码关联知识图谱,结合图论实现复杂故障码解耦。结果表明,该方法能有效降低故障码的数量及复杂度,提升基于故障码检修故障的效率。A DTC decoupling method for complex coupling faults of vehicles is proposed in this paper.Firstly,by analyzing the complex association of DTCs through the principle of vehicle fault self-diagnosis and the propagation process of fault signals,the strong association relationship between DTCs is mined combined with the association rule technology and the multidimensional association rules of DTC are defined.Secondly,the FP-Growth algorithm for DTC multidimensional association rule mining is improved by the characteristics of the DTCs dataset.Finally,the DTC association knowledge graph is constructed by multidimensional association rules to realize com⁃plex DTCs decoupling by combining graph theory.The results show that this method can effectively reduce the num⁃ber and complexity of DTCs,and improve the efficiency of troubleshooting faults based on DTCs.

关 键 词：故障码 解耦 多维关联规则 知识图谱 

分 类 号：U472[机械工程—车辆工程]