一种空间轴承的自适应共振解调故障诊断方法
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摘要
针对传统共振解调故障诊断方法中需依赖主观经验和反复调试选取合适带通滤波器参数的问题,以及包络信号频谱中随机成分对分辨故障特征频率的干扰问题,提出一种空间精密轴承的自适应共振解调故障诊断方法.一方面,根据振动信号功率谱计算重心频率和频率标准差,进而以此确定带通滤波器的中心频率和带宽,实现自适应带通滤波;另一方面,通过频谱平均方法弱化包络信号频谱中的随机成分,使得故障特征谱线清晰度加强.模拟故障信号和实测振动信号的诊断结果表明该方法算法简单,效率高,对保持架磨损故障诊断效果良好,验证了其可行性和有效性.
The traditional resonance demodulation fault diagnosis based method relies on subjective experience and repeated adjustments to select the appropriate band-pass filter. And the random components in the spectrum of the envelope signal have interference to the distinguishing of the fault characteristic frequencies. Aiming at the above mentioned problems,an adaptive resonance demodulation based fault diagnosis method for aerospace precise bearing is proposed. On the one hand,the center frequency and bandwidth of the band-pass filter are calculated according to the power spectrum of the vibration signal,so as to realize the adaptive band-pass filtering. On the other hand,the spectrum averaging method is used to diminish the amplitudes of the random components in the spectrum of the envelope signal,so that the sharpness of the line at the fault characteristic frequency is enhanced. The advantages that the proposed method is simple and efficient,and that the fault diagnosis is effective are indicated by the fault diagnosis results of both the simulated fault signals and the measured vibration signals,which verify its feasibility and effectiveness.
The traditional resonance demodulation fault diagnosis based method relies on subjective experience and repeated adjustments to select the appropriate band-pass filter. And the random components in the spectrum of the envelope signal have interference to the distinguishing of the fault characteristic frequencies. Aiming at the above mentioned problems,an adaptive resonance demodulation based fault diagnosis method for aerospace precise bearing is proposed. On the one hand,the center frequency and bandwidth of the band-pass filter are calculated according to the power spectrum of the vibration signal,so as to realize the adaptive band-pass filtering. On the other hand,the spectrum averaging method is used to diminish the amplitudes of the random components in the spectrum of the envelope signal,so that the sharpness of the line at the fault characteristic frequency is enhanced. The advantages that the proposed method is simple and efficient,and that the fault diagnosis is effective are indicated by the fault diagnosis results of both the simulated fault signals and the measured vibration signals,which verify its feasibility and effectiveness.
引文
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[3]刘文洋,王虹,刘红星,等.基于噪声的轻载滚动轴承保持架故障诊断方法[J].振动与冲击,2016,35(S):200-202.LIU W Y,WANG H,LIU H X,et al.A fault diagnosis method of light load rolling bearing cages based on the noise[J].Journal of Vibration and Shock,2016,35(S):200-202.
[4]潘阳,陈安华,蒋伶莉,等.基于自适应共振解调技术的滚动轴承故障诊断[J].机械科学与技术,2015,34(2):238-241.PAN Y,CHEN A H,JIANG L L,et al.Fault diagnosis of rolling bearing based on adaptive resonance demodulation technique[J].Mechanical Science and Technology for Aerospace Engineering,2015,34(2):238-241.
[5]阳建宏,黎敏,丁福焰.滚动轴承诊断现场实用技术[M].北京:机械工业出版社,2015.
[6]刘金朝,丁夏完,王成国.自适应共振解调法及其在滚动轴承故障诊断中的应用[J].振动与冲击,2007,26(1):38-41.LIU J Z,DING X W,WANG C G.Adaptive Resonance demodulation method and its application to fault diagnosis of freight car rolling bearings[J].Journal of Vibration and Shock,2007,26(1):38-41.
[7]刘永强,杨绍普,廖英英,等.一种自适应共振解调方法及其在滚动轴承早期故障诊断中的应用[J].振动工程学报,2016,29(2):366-370.LIU Y Q,YANG S P,LIAO Y Y,et al.The adaptive resonant demodulation method and its application in failure diagnosis of rolling bearing early faults[J].Journal of Vibration Engineering,2016,29(2):366-370.
[8]邓四二,王勇,王恒迪.基于IHT的共振解调技术的滚动轴承故障诊断方法[J].航空动力学报,2012,27(1):69-74.DENG S E,WANG Y,WANG H D.Resonance demodulation technique based on IHT for rolling bearings fault diagnosis[J].Journal of Aerospace Power,2012,27(1):69-74.
[9]梅宏斌.滚动轴承振动监测与诊断[M].北京:机械工业出版社,1995.
[10]周智,朱永生,张优云,等.基于EEMD和共振解调的滚动轴承自适应故障诊断[J].振动与冲击,2013,32(2):76-80.ZHOU Z,ZHU Y S,ZHANG Y Y,et al.Adaptive fault diagnosis of bearing based on EEMD and demodulated resonance[J].Journal of Vibration and Shock,2013,32(2):76-80.
[11]杨国安.机械设备故障诊断实用技术[M].北京:中国石化出版社,2013.