基于CHMM的齿轮箱状态识别研究

滕红智;赵建民;贾希胜;张星辉;王正军

振动与冲击 ›› 2012, Vol. 31 ›› Issue (5) : 92-96.

PDF(1456 KB)
PDF(1456 KB)
振动与冲击 ›› 2012, Vol. 31 ›› Issue (5) : 92-96.
论文

基于CHMM的齿轮箱状态识别研究

  • 滕红智,赵建民,贾希胜,张星辉,王正军
作者信息 +

Research on gearbox State recognition based on continue hidden markov model

  • TENG Hong-zhi,ZHAO Jian-min,JIA Xi-sheng,ZHANG Xing-hui,WANG Zheng-jun
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摘要

针对离散隐Markov模型(HMM)在状态识别中的不足,结合齿轮箱全寿命实验数据,研究了基于连续隐Markov模型(CHMM)的状态识别方法。建立了基于齿轮箱原始振动信号的CHMM状态识别框架,提出了基于K均值算法和交叉验证相结合的状态数优化方法,通过计算待确定观测数据的极大似然概率值来确定齿轮箱当前状态。结果表明,用原始振动信号作为CHMM的输入可以实现状态识别,验证了模型的有效性,为齿轮箱基于状态的维修提供了科学依据。

Abstract

Combined with full lifetime experiment of gearbox, state recognition based on Continue Hidden Markov Model is researched. The flow of State recognition based on Continue Hidden Markov Model using original vibration signal is founded. Virtue and defect of existing classification methods which classify state in full life cycle are analyzed. State number optimization model is established based on K means and cross validation. Gearbox’s operating state is determined by calculating the maximal log-likelihood. The results of recognition show that the method of state recognition based on Continue Hidden Markov Model using original vibration signal is feasible. The results prove that this kind of method is effective.

关键词

连续隐马尔科夫模型 / K均值 / 交叉验证

Key words

continue hidden markov model / k means / cross validation

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导出引用
滕红智;赵建民;贾希胜;张星辉;王正军. 基于CHMM的齿轮箱状态识别研究[J]. 振动与冲击, 2012, 31(5): 92-96
TENG Hong-zhi;ZHAO Jian-min;JIA Xi-sheng;ZHANG Xing-hui;WANG Zheng-jun . Research on gearbox State recognition based on continue hidden markov model[J]. Journal of Vibration and Shock, 2012, 31(5): 92-96

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