基于概率幅值解调的机械故障诊断方法研究

李志农1,刘晓雨1,许巧巧1,谷士鹏2,马亚平2

振动与冲击 ›› 2022, Vol. 41 ›› Issue (14) : 218-225.

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振动与冲击 ›› 2022, Vol. 41 ›› Issue (14) : 218-225.
论文

基于概率幅值解调的机械故障诊断方法研究

  • 李志农1,刘晓雨1,许巧巧1,谷士鹏2,马亚平2
作者信息 +

Mechanical fault diagnosis method based on probability amplitude demodulation

  • LI Zhinong1, LIU Xiaoyu1, XU Qiaoqiao1, GU Shipeng2, MA Yaping2
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摘要

针对机械设备发生故障时存在大量的调幅调频信号,提出了一种基于概率幅值解调的机械故障诊断方法,在提出的方法中,利用概率理论,将解调转化成成推理过程,通过已有的先验知识对不确定性问题进行推理,达到推理解调的目的。仿真结果表明,提出的方法明显优于传统的希尔伯特包络解调方法,解调后的包络线与原信号拟合程度高。最后,滚动轴承故障故障诊断的实验进一步验证了提出的方法的有效性,提出的方法能有效地提取出滚动轴承故障特征。
关键词:概率幅值解调;故障诊断;贝叶斯推理;滚动轴承

Abstract

Based on a large number of AM and FM signals in mechanical equipment when mechanical faults occur, a mechanical fault diagnosis method based on probability amplitude demodulation is proposed. In the proposed method, probability theory is used to transform demodulation into a reasoning process. Then some prior knowledge is used to infer the uncertain problems to achieve the purpose of inference and demodulation. The simulation results show that the proposed method is significantly better than the traditional Hilbert envelope demodulation method. and the demodulated envelope obtained by the proposed method has a high degree of fitting with the original signal. Finally, the experiment of rolling bearing’s fault diagnosis further verifies the effectiveness of the proposed method, and the proposed method can effectively extract the fault features of rolling bearing.
Key words: Probability amplitude demodulation; Bayesian inference; fault diagnosis; rolling bearing.

关键词

概率幅值解调 / 故障诊断 / 贝叶斯推理 / 滚动轴承

Key words

Probability amplitude demodulation / Bayesian inference / fault diagnosis / rolling bearing.

引用本文

导出引用
李志农1,刘晓雨1,许巧巧1,谷士鹏2,马亚平2. 基于概率幅值解调的机械故障诊断方法研究[J]. 振动与冲击, 2022, 41(14): 218-225
LI Zhinong1, LIU Xiaoyu1, XU Qiaoqiao1, GU Shipeng2, MA Yaping2. Mechanical fault diagnosis method based on probability amplitude demodulation[J]. Journal of Vibration and Shock, 2022, 41(14): 218-225

参考文献

[1] 于德介, 程军圣, 杨宇.机械故障诊断的HILBERT-HUANG变换方法[M]. 科学出版社, 2006.
YU De-jie,CHENG Jun-sheng,YANG Yu.The Manchine Fault Diagnosis Approach Based on theHilbert-HuangTransform[M].Beijing:Science Press,2006.75-76
[2] C. Chatfield. The Analysis of Time Series: An Introduction. Chapman & Hall/CRC,sixth edition, July 2003. ISBN 1584883170.
[3] 王惠中, 张岳.基于改进希尔伯特黄变换的电机故障特征提取方法研究[J].自动化与仪器仪表, 2014(07): 42-48.
Wang huizhiong, Zhang yue.Based on the improved Hilbert huang transform motor fault feature extraction method of research[J].Automation and instrumentation, 2014(07): 42-48.
[4] Turner R E. Statistical models for natural sounds[D]. University College London, 2010.
[5] Turner R E, Sahani M. Probabilistic amplitude demodulation[C]//International Conference on Independent Component Analysis and Signal Separation. Springer, Berlin, Heidelberg, 2007: 544-551
[6] Turner R E, Sahani M. Probabilistic amplitude and frequency demodulation[C]// Proceedings of the 24th International Conference on Neural Information Processing Systems.[S.l.] :NIPS,2011.
[7] Turner R E, Sahani M. Demodulation as Probabilistic Inference[J]. Audio Speech & Language Processing IEEE Transactions on, 2011, 19(8):2398-2411.
[8] Turner R E, Sahani M. Decomposing signals into a sum of amplitude and frequency modulated sinusoids using probabilistic inference[C]// 2012 IEEE International Conference on Acoustics, Speech and Signal Processing. Kyoto: IEEE, 2012.
[9] Turner R E, Sahani M. Statistical inference for single- and multi-band Probabilistic Amplitude Demodulation[C]// IEEE International Conference on Acoustics Speech & Signal Processing. IEEE, 2010:5466-5469.
[10] Vamoş C, Crăciun M. Numerical demodulation of a Gaussian white noise modulated in amplitude by a deterministic volatility[J]. European Physical Journal B, 2013, 86(4):1-8.
[11] C. E. Rasmussen & C. K. I. Williams, Gaussian Processes for Machine Learning[M]. Cambridge:MIT Press, 2006.
[12]万广通. 基于 LMD 和带通滤波解调变工下滚动轴承故障特征提取方法的研究[D]. 北京交通大学, 2018.
Wan guangtong.Based on LMD and band-pass filtering demodulation conditions of rolling bearing fault feature extraction method is studied[D].Beijing jiaotong university,2018.
[13]王平, 廖明夫. 滚动轴承故障诊断的自适应共振解调技术[J]. 航空动力学报, 2005, 20(4):606-612.
Wangping,Liao mingfu.,Adaptive Demodulated Resonance Technique for the Rolling Bearing Fault Diagnosis[J].Journal of Aerospace Power, 2005, 20(4):606-612.
[14]Hariprasad J, Roy U M, Ramasangu H. Design and Implementation of Universal Digital Demodulator Using Neural Network Approaches[M]//Emerging Trends in Photonics, Signal Processing and Communication Engineering. Springer, Singapore, 2020: 133-139.


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