Early fault feature of rolling bearing is very weak and affected by environment noise seriously, so it is difficult to draw fault feature. Aiming at solving this problem, maximum correlated kurtosis deconvolution was introduced to the field of fault diagnosis for rolling bearing and combined with the 1.5 dimension spectrum, then feature extraction method for rolling bearing incipient fault based on maximum correlated kurtosis deconvolution and 1.5 dimension spectrum was proposed. Firstly, fault signal was processed by MCKD method and envelope signal of deconvolution signal was calculated, then analyzed the envelope signal using 1.5 dimension spectrum method and 1.5 dimension envelope spectrum of deconvolution signal was obtained, finally, bearing fault was judged by analyzing the frequency components of 1.5 dimension envelope spectrum. Analysis results of simulated and measured fault signal of rolling bearing showed that this method could effectively extract the feature frequency information of incipient fault and has a certain reliability.
Tang Guiji,Wang Xiaolong.
Feature Extraction Method for Rolling Bearing Incipient Fault Based on Maximum Correlated Kurtosis Deconvolution and 1.5 Dimension Spectrum[J]. Journal of Vibration and Shock, 2015, 34(12): 79-84
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