基于VMD和对称差分能量算子解调的滚动轴承故障诊断方法
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摘要
针对滚动轴承早期故障振动信号非平稳、强噪声,故障频率难提取的问题,提出了基于变分模态分解(Variational Mode Decomposition,VMD)和对称差分能量算子解调的滚动轴承故障诊断方法。首先,利用VMD方法将滚动轴承待分析信号分解成若干个模态分量;其次,根据峭度最大准则来选取被对称差分能量算子解调的模态分量,解调后获取待分析信号的幅值、频率信息并计算包络谱。实验结果表明:与传统能量算子相比,所提方法能突显故障特征频率并有效抑制虚假干扰频率,更有利于滚动轴承故障诊断。
Aiming at the problem of rolling bearing early fault vibration signals non-stationary and high noise,failure frequency is difficult to extract. A fault diagnosis method of rolling bearings based on the Variational Mode Decomposition( VMD) and symmetric difference energy operator is proposed. First of all,the rolling bearing vibration signals are decomposed by VMD algorithm,a number of modal components are got. Secondly,according to the maximum kurtosis criterion,the modal component demodulated by symmetric difference energy operator is selected. Finally,a demodulated signal amplitude and frequency information are obtained and the envelope spectrum is calculated. The experimental results show that compared with the traditional energy operator,the proposed method can effectively extract the fault feature,and can restrain the false interference frequency and highlight the fault characteristic frequency,more conducive to roller bearing fault diagnosis.
Aiming at the problem of rolling bearing early fault vibration signals non-stationary and high noise,failure frequency is difficult to extract. A fault diagnosis method of rolling bearings based on the Variational Mode Decomposition( VMD) and symmetric difference energy operator is proposed. First of all,the rolling bearing vibration signals are decomposed by VMD algorithm,a number of modal components are got. Secondly,according to the maximum kurtosis criterion,the modal component demodulated by symmetric difference energy operator is selected. Finally,a demodulated signal amplitude and frequency information are obtained and the envelope spectrum is calculated. The experimental results show that compared with the traditional energy operator,the proposed method can effectively extract the fault feature,and can restrain the false interference frequency and highlight the fault characteristic frequency,more conducive to roller bearing fault diagnosis.
引文
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[7]WANG Yanxue,MARKERT Richard,XIANG Jiawei,et al.Research on variational mode decomposition and its application in detecting rub-impact fault of the otor system[J].Mechanical Systems and Signal Processing,2015,60-61:243-251.
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[10]武和雷,朱善安,林瑞仲,等.基于能量算子解调法的滚动轴承故障诊断[J].农业机械学报,2003,34(1):118-120.
[11]胥永刚,陆明,谢志聪.基于固有时间尺度分解的能量算子解调法及故障诊断应用[J].海军工程大学学报,2013,25(1):27-31.
[12]孟宗,季艳.基于DEMD和对称差分能量算子解调的滚动轴承故障诊断[J].中国机械工程,2015,26(12):1658-1664.
[13]孟宗,李姗姗,季艳.基于对称差分能量算子解调的局部均值分解端点效应抑制方法[J].机械工程学报,2014,50(13):80-87.
[14]唐贵基,王晓龙.参数优化变分模态分解方法在滚动轴承早期故障诊断中的应用[J].西安交通大学学报,2015,49(5):73-81.
[2]王天金,冯志鹏,郝如江,等.基于Teager能量算子的滚动轴承故障诊断研究[J].振动与冲击,2012,31(2):1-5.
[3]张超,陈建军,徐亚兰.基于EMD分解和奇异值差分谱理论的轴承故障诊断方法[J].振动工程学报,2011,24(5):539-545.
[4]孙伟,熊邦书,黄建萍,等.小波包降噪与LMD相结合的滚动轴承故障诊断方法[J].振动与冲击,2012,31(18):153-156.
[5]DRAGOMIRETSKIY K,ZOSSO D.Variational mode decomposition[J].IEEE Transactions on Signal Processing,2014,62(3):531-544.
[6]武英杰,甄成刚,刘长良.变分模态分解在风电机组故障诊断中的应用[J].机械传动,2015,39(10):129-132.
[7]WANG Yanxue,MARKERT Richard,XIANG Jiawei,et al.Research on variational mode decomposition and its application in detecting rub-impact fault of the otor system[J].Mechanical Systems and Signal Processing,2015,60-61:243-251.
[8]PENG Z K,PETER W T,CHU F L.Acomparison study of improved Hilbert-Huang transform and wavelet transform:Application to fault diagnosis for rolling bearing[J].Mechhanical Systems&Signal Process,2005,19(5):974-985.
[9]任达千,杨世锡,吴昭同,等.信号瞬时频率直接计算法与Hilbert变换及Teager能量法比较[J].机械工程学报,2013,49(9):42-48.
[10]武和雷,朱善安,林瑞仲,等.基于能量算子解调法的滚动轴承故障诊断[J].农业机械学报,2003,34(1):118-120.
[11]胥永刚,陆明,谢志聪.基于固有时间尺度分解的能量算子解调法及故障诊断应用[J].海军工程大学学报,2013,25(1):27-31.
[12]孟宗,季艳.基于DEMD和对称差分能量算子解调的滚动轴承故障诊断[J].中国机械工程,2015,26(12):1658-1664.
[13]孟宗,李姗姗,季艳.基于对称差分能量算子解调的局部均值分解端点效应抑制方法[J].机械工程学报,2014,50(13):80-87.
[14]唐贵基,王晓龙.参数优化变分模态分解方法在滚动轴承早期故障诊断中的应用[J].西安交通大学学报,2015,49(5):73-81.