The Fault Diagnosis for Rotating Machinery Based on BSS and AR Spectrum Estimation
MENG Zong1,2,LIANG Zhi1,3
1. Institute of Electrical Engineering, Yanshan University, Qinhuangdao, Hebei 066004, China;
2. Key Laboratory of Measurement Technology and Instrumentation of Hebei Province, Qinhuangdao, Hebei 066004, China;
3. Guangxi Special Equipment Supervision and Inspection Institute, Nanning, Guangxi 530219, Chin
Abstract：The accurate AR model can reveal the changing state characteristics inherent in the signal, however the AR model is sensitive to the changes in the state of the system, and the multiple of dynamic source signal coupling is bound to affect the estimated results. The method of blind source separation is reconstruct mechanical vibration source signals. Then the non-stationary fault signal is decomposed into several stationary signals which suit to establish AR model. Finally, the AR model of stationary intrinsic mode function is constructed to extract the characteristics of fault vibration signal. The results of simulation and experiment are presented to verify the theory analysis.
孟宗,梁智. 基于盲源分离和AR谱估计的旋转机械故障诊断方法[J]. 计量学报, 2015, 36(3): 289-294.
MENG Zong,LIANG Zhi. The Fault Diagnosis for Rotating Machinery Based on BSS and AR Spectrum Estimation. Acta Metrologica Sinica, 2015, 36(3): 289-294.
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2015, Vol. 36 
