Abstract: Due to the abundant information contained in multichannel data, a multichannel fusion method based on coupled hidden Markov models (CHMMs) is presented for rolling- element-bearing’s fault diagnosis. A double-chain CHMM is adopted to combine the horizontal and vertical vibration signals from bearings. An experiment was carried out to validate the proposed method. The experimental results show that the proposed method can improve the diagnostic accuracy when compared with the conventional hidden Markov model (HMM) based method.

Key words: vibration and wave, coupled hidden Markov model, fault diagnosis, rolling element bearing

摘要： 由于多通道数据包含了丰富的信息，有效融合多通道数据可以得到更加准确可靠的诊断结果。鉴于此，提出一种基于耦合隐马尔可夫模型的滚动轴承多通道融合故障诊断方法。该方法利用含两条链的耦合隐马尔可夫模型融合轴承水平方向和垂直方向的振动信号来进行故障诊断。通过对滚动轴承常见故障的诊断分析表明，与常用的基于隐马尔可夫模型的故障诊断方法相比，该方法可以更加准确地诊断轴承的故障。

关键词: 振动与波, 耦合隐马尔可夫模型, 故障诊断, 滚动轴承