基于改进HMM的模拟电路早期故障识别和诊断  

Recognition and diagnosis of incipient faults in analog circuit using improved HMM

作　　者：张继军[1] 马登武[2] 王琳[1] 

机构地区：[1]海军航空工程学院研究生管理大队,山东烟台264001 [2]海军航空工程学院兵器科学与技术系,山东烟台264001

出　　处：《计算机工程与应用》2014年第3期261-264,共4页Computer Engineering and Applications

摘　　要：针对模拟电路运行过程中存在的不确定性,对传统的隐马尔可夫模型(HMM)进行了改进,将模型中满足不变性的状态转移概率矩阵改为时变状态转移概率矩阵,使之更符合实际情况。在状态初期为了防止状态转移概率发生过度更新,设置了更新概率控制因子。采用线性辨别分析(LDA)方法对测量信号进行特征提取,用于HMM的训练和测试,从而实现模拟电路早期故障的识别和诊断。仿真结果表明,改进后的HMM具有更强的故障识别和诊断能力。Due to the uncertainties that exist in the running of the analog circuits, the traditional Hidden Markov Model （HMM）approach is improved. The state transition probability matrix of the traditional model is replaced by time-varying one that more satisfies the actual situation. An updating control factor is introduced for avoiding the excess updating of the state transition probability in the initial stage of each state. The Linear Discriminant Analysis（LDA）is used to reduce dimensionality and remove redundancy of the voltage feature vectors, which are for HMM’s training and testing in order to achieve recognition and diagnosis of the incipient faults in analog circuit. The experimental results indicate that the improved HMM has better fault recognition capability than the traditional HMM.

关 键 词：隐马尔可夫模型 故障诊断 线性辨别分析 模拟电路 

分 类 号：TP277[自动化与计算机技术—检测技术与自动化装置]