东南大学学报（自然科学版）2016，Vol.18Issue(3)：457-463,7.DOI:10.3969/j.issn.1001-0505.2016.03.001
一种自适应 Morlet 小波滤波方法及其在滚动轴承早期故障特征提取中的应用
An adaptive Morlet wavelet filter method and its application in detecting early fault feature of ball bearings
摘要
Abstract
Considering the early fault of ball bearings being weak and the difficulty of detecting the fault feature,an adaptive Morlet wavelet filter method based on shuffled frog leaping algorithm (SF-LA)is proposed.First,the auto-correlation analysis is utilized to filter the broadband random noise. Then,the optimal center frequency and the filter bandwidth under the minimum information entropy are acquired by optimizing the filtering parameters of Morlet wavelet through SFLA.The filtered sig-nal can be obtained by applying the adaptive Morlet wavelet filter,and the impulse features can be well highlighted.Finally,the filtered signal is analyzed by the envelope spectrum to extract the fault frequencies of the ball bearings.Experimental results indicate that the proposed method can success-fully detect the periodic impact features from the low signal-to-noise ratio (SNR)signal.Further-more,in the processing of the early fault vibration signals of the ball bearings,the proposed method can be adopted to obtain the impulse feature frequencies effectively,which is used to diagnose the early fault of ball bearings.关键词
滚动轴承/特征提取/早期故障/Morlet 小波/混洗蛙跳算法Key words
ball bearing/feature detection/early fault/Morlet wavelet/shuffled frog leaping algorithm分类
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张菀,贾民平,朱林..一种自适应 Morlet 小波滤波方法及其在滚动轴承早期故障特征提取中的应用[J].东南大学学报（自然科学版）,2016,18(3):457-463,7.基金项目
国家社科基金重大项目“城市哲学和城市批评史研究”（11&ZD089）成果之一。 （）
