基于局部保持映射和隐马尔科夫模型的模拟电路故障诊断方法

针对模拟电路信号的非线性特征,提出一种基于局部保持映射和隐马尔科夫模型的故障模式识别新方法. 首先提取模拟电路的信号特征构成原始高维特征样本空间;然后采用LPP算法将原始高维故障数据映射至低维空间,提取数据的内在流形特征作为特征矢量;最后通过构建混合HMM反映系统的真实状态,并作为分类器实现对各状态的分类识别. 通过仿真分析,将该方法与其他方法进行对比,结果表明,LPP-HMM方法可以有效识别早期故障特征,具有较高的故障识别率. 

Analog Circuit Fault Diagnosis Based on Locality Preserving Projection and Hidden Markov Model

Aiming at the non-linear characteristics of analog circuit, a fault diagnosis method of analog circuit based on locality preserving projection (LPP) and hidden Markov model (HMM) was presented. Firstly, the high-dimensional space was constructed by extracting the signal characteristics of analog circuit. Secondly, the LPP was used to compress the feature samples and the intrinsic manifold feature in data set was extracted as characteristic vector. Finally, the classification and recognition of all status were implemented with HMM constructed for reflecting the real status of the system. Simulation analysis results show that, compared with other methods, the LPP-HMM can effectively identify incipient faults, and possess higher rate of fault identification.