Study on Fault Diagnosis Method for Rotating Machinery Based on Adaptive Stochastic Resonance and AMD
SHI Pei-ming1,SU Cui-jiao1,ZHAO Na1,HAN Dong-ying2,TIAN Guang-jun1
1. Institute of Electrical Engineering, Yanshan University, Qinhuangdao, Hebei 066004, China
2. Institute of of Vehicles and Energy, Yanshan University, Qinhuangdao, Hebei 066004, China
Abstract：Aiming at the problem of fault diagnosis for rotating machinery with very low signal-to-noise ratio under strong noise background, a fault diagnosis method for rotating machinery based on AMD and stochastic resonance is proposed. If the frequency components of the signal are known, signal with different frequency components can be decomposed into single frequency signal using the AMD method, especially to decompose a signal with closely spaced frequency components. For the fault feature frequency can be predicted in rotating machinery fault diagnosis, AMD method is used to extract fault feature frequency signal in mechanical vibration signal and add low intensity noise to the signal firstly. Then, the signal with noise is put into the optimal stochastic resonance system and denoising and enhancing the signal. Finally the spectrum of the signal is obtained, if the frequency spectrum contains the fault feature frequency, it shows that the faults exist in mechanical vibration signal. Through the extraction of the rolling bearing fault signal feature proved that the method has a good effect.
时培明,苏翠娇,赵娜,韩东颖,田广军. 基于AMD和自适应随机共振的旋转机械故障诊断方法研究[J]. 计量学报, 2017, 38(1): 112-116.
SHI Pei-ming,SU Cui-jiao,ZHAO Na,HAN Dong-ying,TIAN Guang-jun. Study on Fault Diagnosis Method for Rotating Machinery Based on Adaptive Stochastic Resonance and AMD. Acta Metrologica Sinica, 2017, 38(1): 112-116.
2017, Vol. 38 
