基于改进MOMEDA的齿轮箱复合故障诊断

Fault Diagnosis of Gearbox Based on Improved MOMEDA

总体经验模态分解(ensemble empirical mode decomposition,简称EEMD)对信号分解时由于白噪声选取不当,常造成能量泄露;通过计算多点峭度可以提取冲击性故障周期,但在强噪声环境下其追踪效果并不理想;考虑到多点最优最小熵反褶积(multipoint optimal minimum entropy deconvolution adjuste,简称MOMEDA)提取故障时准确度受到故障周期区间范围的影响,提出了基于组合模态函数-多点最优最小熵反褶积(combined mode function-multipoint optimal minimum entropy deconvolution adjuste,简称CMF-MOMEDA)的自适应齿轮箱复合故障特征提取方法。首先,通过EEMD对信号分解,将信号按高低频依次分开;其次,取与原信号相关性强的本征模态函数,通过组合模态函数(combined mode function,简称CMF)将原信号分解为高低两个频带C_h和C_L,分别求其多点峭度谱图,提取故障周期成分;然后,设定合适的周期范围,通过MOMEDA提取故障特征;最后,将该方法应用于齿轮箱故障特征提取,以验证其可行性。

In critical working conditions,the feature extraction of the composite faults in the gearbox is difficult to be realized.Generally,it is easy for the fault characteristics to escape diagnosis or be misdiagnosed by the improper selection of the method.Due to improper selection of white noise,there will be energy leakage situation when the signal is decomposed by ensemble empirical mode decomposition(EEMD).By calculating the multi-point kurtosis(MKurt)can extract the impact fault cycles,but the tracking effect is not ideal in the strong noise environment.Considering that the accuracy of using multipoint optimal minimum entropy deconvolution adjusted(MOMEDA)to extract fault components is affected by the range of the fault cycle,a self-adaptive fault feature extraction method based on CMF-MOMEDA is proposed in this paper.Firstly,the EEMD is used to decompose the signal into a series of intrinsic mode functions(IMFs)at high and low frequencies.Secondly,the original signal is decomposed into high and low frequency bands C_h and C_L by the combined use of IMFs with strong a correlation with the original signal and the combined mode function(CMF).Finally,the MKurt spectrums of C_h and C_L are obtained to extract the fault cycle components,then the appropriate cycle ranges are set and the fault characteristics are extracted by MOMEDA.The feasibility of this method is verified by the application of the fault feature extraction of gearbox.