title: A Rolling Element Bearing Fault Diagnosis Approach Based on Multifractal Theory and Gray Relation Theory.
abstract: Bearing failure is one of the dominant causes of failure and breakdowns in rotating machinery, leading to huge economic loss. Aiming at the nonstationary and nonlinear characteristics of bearing vibration signals as well as the complexity of condition-indicating information distribution in the signals, a novel rolling element bearing fault diagnosis method based on multifractal theory and gray relation theory was proposed in the paper. Firstly, a generalized multifractal dimension algorithm was developed to extract the characteristic vectors of fault features from the bearing vibration signals, which can offer more meaningful and distinguishing information reflecting different bearing health status in comparison with conventional single fractal dimension. After feature extraction by multifractal dimensions, an adaptive gray relation algorithm was applied to implement an automated bearing fault pattern recognition. The experimental results show that the proposed method can identify various bearing fault types as well as severities effectively and accurately.
authors.affiliation: College of Electronic and Information Engineering, Shanghai Dianji University, Shanghai, China.
authors.forename: Jingchao
authors.initials: J
authors.lastname: Li
authors.affiliation: College of Power and Energy Engineering, Harbin Engineering University, Harbin, China.
authors.forename: Yunpeng
authors.initials: Y
authors.lastname: Cao
authors.affiliation: School of Energy and Mechanical Engineering, Shanghai University of Electric Power, Shanghai, China.|Shanghai Electric Gas Turbine Co., Ltd., Shanghai, China.
authors.forename: Yulong
authors.initials: Y
authors.lastname: Ying
authors.affiliation: College of Power and Energy Engineering, Harbin Engineering University, Harbin, China.
authors.forename: Shuying
authors.initials: S
authors.lastname: Li
mesh_terms: D000465:Algorithms; D004868:Equipment Failure; D019544:Equipment Failure Analysis / Q000379:methods*; D017709:Fractals; D033181:Information Dissemination / Q000379:methods; D010363:Pattern Recognition, Automated / Q000379:methods*; D012815:Signal Processing, Computer-Assisted; D014732:Vibration