期刊文献+

旋转机械升降速过程的双谱-FHMM识别方法 被引量:22

Study on Bispectrum-FHMM Recognition Method in Speed-up and Speed-down Process of Rotating Machinery
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摘要 结合双谱和因子隐 Markov模型 ,提出了一种基于双谱的特征提取建立机组各状态相应的因子隐 Markov模型状态识别法 ,并成功地应用到旋转机械升降速过程的故障诊断中 ,同时还与基于双谱的特征提取的 HMM状态识别法进行了比较 ,实验结果表明该方法是有效的。 Bispectrum is a useful tool for processing non-Gaussian signal and nonlinear system. Factorial hidden Markov models (FHMM), which is a generalization of HMM, is superior to HMM, and has a capability of pattern recognitaion baseded on time series, particularly suitable for signal which is non-stationary, bad repetition and reappearance. An approach of fault diagnosis using speed-up and spped-down process of rotating machinery, combining bispectrum with FHMM, is proposed, which is that bispectrum is used as a fault feature, and FHMM as a classifier. This approach is compared with another classfication approach in which bispectrum is used as a fault feature, HMM as a classifier. Experiment results show that this approach is very effective.
出处 《振动工程学报》 EI CSCD 北大核心 2003年第2期171-174,共4页 Journal of Vibration Engineering
基金 国家自然科学基金资助项目 (编号 :5 0 0 75 0 79)
关键词 旋转机械 故障诊断 升速过程 降速过程 因子隐Markov模型 双谱 FHMM识别方法 fault diagnosis rotating machinery bispectrum factorial hidden Markov models (FHMM)
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二级参考文献2

  • 1Dong suk Yuk,IEEE Proc,1996年,3358页
  • 2童进,大型旋转机械升降速过程故障诊断 HMMFFT 方法研究

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同被引文献170

引证文献22

二级引证文献178

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