李志农, 熊俊伟. 基于无限因子隐Markov模型的旋转机械故障识别方法[J]. 失效分析与预防, 2016, 11(3): 133-138. DOI: 10.3969/j.issn.1673-6214.2016.03.001
    引用本文: 李志农, 熊俊伟. 基于无限因子隐Markov模型的旋转机械故障识别方法[J]. 失效分析与预防, 2016, 11(3): 133-138. DOI: 10.3969/j.issn.1673-6214.2016.03.001
    LI Zhi-nong, XIONG Jun-wei. Fault Recognition Method of Rotating Machinery Based on Infinite Factor Hidden Markov Model[J]. Failure Analysis and Prevention, 2016, 11(3): 133-138. DOI: 10.3969/j.issn.1673-6214.2016.03.001
    Citation: LI Zhi-nong, XIONG Jun-wei. Fault Recognition Method of Rotating Machinery Based on Infinite Factor Hidden Markov Model[J]. Failure Analysis and Prevention, 2016, 11(3): 133-138. DOI: 10.3969/j.issn.1673-6214.2016.03.001

    基于无限因子隐Markov模型的旋转机械故障识别方法

    Fault Recognition Method of Rotating Machinery Based on Infinite Factor Hidden Markov Model

    • 摘要: 在机械故障识别方面,因子隐Markov模型是目前常用的识别工具。无限因子隐Markov模型(IFHMM)是因子隐Markov模型(FHMM)的一种扩展形式,克服了因子隐Markov模型链条数往往事先假定的缺点。本研究将无限因子隐Markov模型(IFHMM)运用到旋转机械的升降速过程故障的诊断当中,提出了使用IFHMM作为诊断工具的旋转机械故障诊断方法,并与基于因子隐Markov模型的旋转机械故障诊断方法进行了对比,最后将提出的方法成功地应用到旋转机械的故障中。实验结果表明,提出的方法明显优于FHMM识别方法。

       

      Abstract: In terms of mechanical fault diagnosis, factor hidden Markov model is the common tool for recognition at present. Infinite factor hidden markov model (IFHMM), which is a generalization of factor hidden markov model (FHMM), overcomes the deficiency of FHMM, i.e. chain number is often assumed. Here, IFHMM is introduced to fault diagnosis of rotating machinery, a fault diagnosis method based on IFHMM is propose, and compared with the FHMM recognition method. Finally, the proposed method had been successfully applied in the fault recognition of rotating machinery. The experiment results showed that the proposed method has obvious superior to the fault recognition method based on FHMM.

       

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