关键词: 隐马尔可夫模型, 故障诊断, 空间结构性

Abstract: The Hidden Markov Model (HMM) quoted in mechanical fault diagnosis was ignored the spatial structure features among mechanical components. To solve this problem, a complete fault diagnosis model was established by compensating HMM with the spatial structure features among mechanical components. Behavior-structure gene expression and mechanism gene self-correlation matrix were proposed to describe the spatial structure features, so that the original faults of mechanical equipment were diagnosed. Through gene-mutation operation, the mechanical spatial structure was divided into lots of HMMs, and by combining HMM parameters algorithm with mechanism-statue gene expression operations, the original mechanical faults were diagnosed and debugged quickly. The improved model was more suitable for actual conditions and computational efficiency was also increased by decomposing and diagnosing mechanical spatial structure. The proposed fault diagnosis model was validated by a real oxygen turbine example and the result demonstrated its effectiveness.

Key words: hidden Markov model, fault diagnosis, spatial structure feature, gene expression