一种改进粒子群优化HMM的故障诊断方法  

A Fault Diagnosis Method Based on Improved Particle Swarm Optimization HMM

作　　者：吴琼琼 李英顺 戴喜生 刘胜永 Wu Qiongqiong;Li Yingshun;Dai Xisheng;Liu Shengyong(School of Electrical&Information Engineering,Guangxi University of Science&Technology,Liuzhou 545000,China;School of Control Science&Engineering,Dalian University of Technology,Dalian 116204,China)

机构地区：[1]广西科技大学电气与信息工程学院,广西柳州545000 [2]大连理工大学控制科学与工程学院,辽宁大连116024

出　　处：《兵工自动化》2021年第10期10-15,25,共7页Ordnance Industry Automation

基　　金：国家自然科学基金项目(No.71801196);辽宁省兴辽英才计划(XLYC1903015)。

摘　　要：针对传统故障诊断方法不能准确定位故障位置的问题,提出一种改进粒子群优化隐马尔科夫模型(hidden markov model,HMM)的故障诊断方法。应用HMM识别综合传动装置故障模式,用模糊集定义模式研究电压信号特征提取方法,并根据特征值的敏感程度进行优化选择;应用3种HMM对综合传动装置在不同运行状态下的故障信号进行故障诊断,并且对诊断结果进行对比。结果表明:改进粒子群优化的HMM模型能快速有效地识别综合传动装置中磨损、损坏等故障模式,适用性良好,可应用于实际综合传动装置系统的故障诊断。The traditional fault diagnosis methods can not locate the fault location accurately.Therefore,an improved particle swarm optimization hidden Markov mode(HMM)fault diagnosis method is proposed.The HMM l is used to identify the fault mode of the integrated transmission device,the fuzzy set is used to define the mode to study the voltage signal feature extraction method,and the optimal selection is made according to the sensitivity of the eigenvalue;3 HMM are applied to analyze the fault signals of the integrated transmission device under different operating conditions.And the diagnosis results are compared.The results show that the improved particle swarm optimization HMM model can quickly and effectively identify the wear,damage and other fault modes in the integrated transmission,and has good applicability,which can be applied to the fault diagnosis of the actual integrated transmission system.

关 键 词：隐马尔科夫模型 综合传动装置 电压信号 故障诊断 

分 类 号：E923.12[军事—军事装备学] TP274.5[兵器科学与技术—武器系统与运用工程]