一种基于EMD和典型谱峭图的改进型共振解调方法
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摘要
针对传统共振解调方法中带通滤波器带宽和中心频率的选取缺乏自适应性的问题,提出了一种基于EMD和典型谱峭图的改进型共振解调方法。该方法借助EMD优良的降噪效果,结合典型谱峭图方法,不但可以自适应地优化带通滤波器参数,还可以提高信噪比,增强故障冲击信号。通过对含典型故障的滚动轴承振动信号进行分析,验证了该方法在提取微弱故障特征上的有效性。
In order to solve the selection of band pass filter bandwidth and center frequency lack of adaptability in traditional resonance demodulation method,an improved resonance demodulation method is proposes based on EMD and typical kurtogram. With the aid of excellent denoising effect of EMD and typical kurtogram method,the method not only self-adaptively optimizes band pass filter parameters,but also improves signal-to-noise ratio,enhancing fault impact signal. The effectiveness of the proposed method in extracting a weak fault feature is verified through analysis of vibration signal of rolling bearings with typical fault.
In order to solve the selection of band pass filter bandwidth and center frequency lack of adaptability in traditional resonance demodulation method,an improved resonance demodulation method is proposes based on EMD and typical kurtogram. With the aid of excellent denoising effect of EMD and typical kurtogram method,the method not only self-adaptively optimizes band pass filter parameters,but also improves signal-to-noise ratio,enhancing fault impact signal. The effectiveness of the proposed method in extracting a weak fault feature is verified through analysis of vibration signal of rolling bearings with typical fault.
引文
[1]汤宝平,蒋永华,张祥春.基于形态奇异值分解和经验模态分解的滚动轴承故障特征提取方法[J].机械工程学报,2010,46(5):37-42.
[2]马新娜,杨绍普.典型快速谱峭图算法的研究及应用[J].振动与冲击,2016,35(15):109-114.
[3]苏文胜,王奉涛,张志新,等.EMD降噪和谱峭度法在滚动轴承早期故障诊断中的应用[J].振动与冲击,2010,29(3):18-21.
[4]DYWER R F.Detection of non-gaussian signals by frequency domain kurtosis estimation[C]∥Acoustic,Speech,and Signal Processing,IEEE International Conference on ICASSP,1983(8):607-610.
[5]RANDALL R B,ANTONI J.Rolling element bearing diagnostics—a tutorial[J].Mechanical System and Signal Process,2011,25(2):485-520.
[6]张志刚,石晓辉,施全,等.基于改进EMD和谱峭度法滚动轴承故障特征提取[J].振动、测试与诊断,2013,33(3):478-482.
[7]ANTONI J,RANDALL R B.The spectral kurtosis:a useful tool for characterizing non-tationary signals[J].Mechanical Systems and Signal Processing,2006,20(6):282-307.
[8]ANTONI J,RANDALL R B.The spectral kurtosis:application to the vibratory surveillance and diagnostics of rotating machines[J].Mechanical Systems&Signal Processing,2006,20(2):308-331.
[9]ANTONI J.Fast computation of the kurtogram for the detection of transient faults[J].Mechanical Systems&Signal Processing,2007,21(1):108-124.
[10]彭畅,柏林,谢小亮.基于EEMD、度量因子和快速峭度图的滚动轴承故障诊断方法[J].振动与冲击,2012,31(20):143-146.
[11]马新娜,杨绍普.典型谱峭图在共振解调方法中的应用[J].振动、测试与诊断,2015,35(6):1140-1144.
[12]丁康,黄志东,林慧斌.一种谱峭度和Morlet小波的滚动轴承微弱故障诊断方法[J].振动工程学报,2004,27(1):128-135.
[13]姚海妮,王珍,邱立鹏,等.基于经验模态分析的故障诊断方法及应用研究[J].计算机测量与控制,2015,23(12):3980-3982.
[2]马新娜,杨绍普.典型快速谱峭图算法的研究及应用[J].振动与冲击,2016,35(15):109-114.
[3]苏文胜,王奉涛,张志新,等.EMD降噪和谱峭度法在滚动轴承早期故障诊断中的应用[J].振动与冲击,2010,29(3):18-21.
[4]DYWER R F.Detection of non-gaussian signals by frequency domain kurtosis estimation[C]∥Acoustic,Speech,and Signal Processing,IEEE International Conference on ICASSP,1983(8):607-610.
[5]RANDALL R B,ANTONI J.Rolling element bearing diagnostics—a tutorial[J].Mechanical System and Signal Process,2011,25(2):485-520.
[6]张志刚,石晓辉,施全,等.基于改进EMD和谱峭度法滚动轴承故障特征提取[J].振动、测试与诊断,2013,33(3):478-482.
[7]ANTONI J,RANDALL R B.The spectral kurtosis:a useful tool for characterizing non-tationary signals[J].Mechanical Systems and Signal Processing,2006,20(6):282-307.
[8]ANTONI J,RANDALL R B.The spectral kurtosis:application to the vibratory surveillance and diagnostics of rotating machines[J].Mechanical Systems&Signal Processing,2006,20(2):308-331.
[9]ANTONI J.Fast computation of the kurtogram for the detection of transient faults[J].Mechanical Systems&Signal Processing,2007,21(1):108-124.
[10]彭畅,柏林,谢小亮.基于EEMD、度量因子和快速峭度图的滚动轴承故障诊断方法[J].振动与冲击,2012,31(20):143-146.
[11]马新娜,杨绍普.典型谱峭图在共振解调方法中的应用[J].振动、测试与诊断,2015,35(6):1140-1144.
[12]丁康,黄志东,林慧斌.一种谱峭度和Morlet小波的滚动轴承微弱故障诊断方法[J].振动工程学报,2004,27(1):128-135.
[13]姚海妮,王珍,邱立鹏,等.基于经验模态分析的故障诊断方法及应用研究[J].计算机测量与控制,2015,23(12):3980-3982.