An optimal filter length selection method for MED based on autocorrelation energy and genetic algorithms

• Published in: ISA transactions Vol. 109; pp. 269 - 287
• Main Authors: He, Zhiyuan, Chen, Guo, Hao, Tengfei, Liu, Xiyang, Teng, Chunyu
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 01.03.2021
• Subjects: Fault diagnosis; Filter length; Minimal Entropy Deconvolution (MED); Rolling bearings; Weak periodic impulses; Filter length; Fault diagnosis; Minimal Entropy Deconvolution (MED); Weak periodic impulses; Rolling bearings
• ISSN: 0019-0578; 1879-2022
• DOI: 10.1016/j.isatra.2020.10.010

This paper proposed a method for exact selecting the optimal filter length of minimal entropy deconvolution (MED) to solve it recovering a single random pulse when the filter length is not improper. The energy ratio of autocorrelation between the filtered signal and the residual signal is adopted to measure the salience of periodic impulses. Then this index is used as an objective function of genetic algorithms (GA) to form an adaptive optimal selection method of filter length. The proposed method is verified by two different rolling bearing fault experiments. The results show that the proposed method reveals the periodic impulses successfully from the casing signals. Compared with other MED-based methods, the proposed method has better performance in detecting the weak fault signal. [Display omitted] •An index that can measure the characteristics of periodic impulse is proposed.•A method of selecting the optimal filter length of MED based on genetic algorithm is proposed.•The proposed method can eliminate the effect of the transmission path.•The proposed method can accurately extract the early weak fault features of rolling bearings.