基于VMD及广义分形维数矩阵的滚动轴承故障诊断
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摘要
提出基于变分模态分解及广义分形维数矩阵的滚动轴承故障诊断方法。对信号进行变分模态分解得到若干模态函数,根据不同权重因子计算得到每个模态函数的广义分形维数序列,排列构成广义分形维数矩阵,最后通过分析待测信号和各样本信号的广义分形维数矩阵的相关系数判断故障状态。实验结果表明该方法能精确、稳定提取故障特征,区分不同状态的信号。
A method of bearing fault diagnosis based on variational mode decomposition(VMD) and generalized fractal dimension was proposed. A number of mode functions were obtained through the decomposition to the signal by VMD method. Then the generalized fractal dimension of each mode functions were calculated according to the different weighting factors, and arranged to construct the generalized fractal dimension matrix. Finally, according to the correlation coefficient of the signals generalized fractal dimension matrix and the sample signals, the fault status could be diagnosed. The experiment results showed that the method could extract fault feature accurately and stably, and distinguish signals of different status and identify the faults with close frequency.
A method of bearing fault diagnosis based on variational mode decomposition(VMD) and generalized fractal dimension was proposed. A number of mode functions were obtained through the decomposition to the signal by VMD method. Then the generalized fractal dimension of each mode functions were calculated according to the different weighting factors, and arranged to construct the generalized fractal dimension matrix. Finally, according to the correlation coefficient of the signals generalized fractal dimension matrix and the sample signals, the fault status could be diagnosed. The experiment results showed that the method could extract fault feature accurately and stably, and distinguish signals of different status and identify the faults with close frequency.
引文
[1]谭善文,秦树人,汤宝平.小波基时频特性及其在分析突变信号中的应用[J].重庆大学学报(自然科学版),2001,24(2):12-17.
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[3]孟宗,李姗姗,王亚超.基于LMD和局域时频熵的旋转机械故障诊断方法[J].计量学报,2015,36(1):77-81.
[4]Yang Y,Cheng J S,Zhang K.An ensemble local means decomposition method and its application to local rubimpact fault diagnosis of the rotor systems[J].Measurement,2012,45(3):561-570.
[5]时培明,李庚,韩东颖,等.基于延拓和窗函数的HHT端点效应改进方法[J].计量学报,2013,34(5):491-496.
[6]Wu Z H,Huang N E.Ensemble empirical mode decomposition:a noise assisted data analysis method[J].Advances in Adaptive Data Analysis,2009,1(1):1-41.
[7]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.
[8]Dragomiretskiy K,Zosso D.Variational mode decomposition[J].Signal Processing,IEEE Transactions on,2014,62(3):531-544.
[9]Mohanty,Gupta K K,Raju K S.Bearing Fault Analysis using VariationalMode Decomposition[J].Journal of Instrumentation Technology&Innovations,2014,4(2):20-27.
[10]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.
[11]徐玉秀,钟建军,闻邦椿.旋转机械动态特性的分形特征及故障诊断[J].机械工程学报,2005,41(12):186-189.
[12]韩东颖,李庚,时培明.基于EMD和分形盒维数的旋转机械耦合故障诊断方法研究[J].振动与冲击,2013,32(15):209-214.
[13]郝研,王太勇,万剑,等.基于级联双稳随机共振和多重分形的机械故障诊断方法研究[J].振动与冲击,2012,13(8):181-185.
[14]刘长良,武英杰,甄成刚.基于变分模态分解和模糊C均值聚类的滚动轴承故障诊断[J].中国电机工程学报,2015,35(13):3358-3365.
[15]徐玉秀,侯荣涛,杨文平.广义分形维数在旋转机械故障诊断中的应用研究[J].中国机械工程,2003,14(21):18-20.
[2]罗志增,袁飞龙,高云园.小波和希尔伯特变换在脑电信号消噪中的对比研究[J].计量学报,2013,34(6):567-572.
[3]孟宗,李姗姗,王亚超.基于LMD和局域时频熵的旋转机械故障诊断方法[J].计量学报,2015,36(1):77-81.
[4]Yang Y,Cheng J S,Zhang K.An ensemble local means decomposition method and its application to local rubimpact fault diagnosis of the rotor systems[J].Measurement,2012,45(3):561-570.
[5]时培明,李庚,韩东颖,等.基于延拓和窗函数的HHT端点效应改进方法[J].计量学报,2013,34(5):491-496.
[6]Wu Z H,Huang N E.Ensemble empirical mode decomposition:a noise assisted data analysis method[J].Advances in Adaptive Data Analysis,2009,1(1):1-41.
[7]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.
[8]Dragomiretskiy K,Zosso D.Variational mode decomposition[J].Signal Processing,IEEE Transactions on,2014,62(3):531-544.
[9]Mohanty,Gupta K K,Raju K S.Bearing Fault Analysis using VariationalMode Decomposition[J].Journal of Instrumentation Technology&Innovations,2014,4(2):20-27.
[10]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.
[11]徐玉秀,钟建军,闻邦椿.旋转机械动态特性的分形特征及故障诊断[J].机械工程学报,2005,41(12):186-189.
[12]韩东颖,李庚,时培明.基于EMD和分形盒维数的旋转机械耦合故障诊断方法研究[J].振动与冲击,2013,32(15):209-214.
[13]郝研,王太勇,万剑,等.基于级联双稳随机共振和多重分形的机械故障诊断方法研究[J].振动与冲击,2012,13(8):181-185.
[14]刘长良,武英杰,甄成刚.基于变分模态分解和模糊C均值聚类的滚动轴承故障诊断[J].中国电机工程学报,2015,35(13):3358-3365.
[15]徐玉秀,侯荣涛,杨文平.广义分形维数在旋转机械故障诊断中的应用研究[J].中国机械工程,2003,14(21):18-20.