title: Envelope analysis with a genetic algorithm-based adaptive filter bank for bearing fault detection.
abstract: This paper proposes a fault detection methodology for bearings using envelope analysis with a genetic algorithm (GA)-based adaptive filter bank. Although a bandpass filter cooperates with envelope analysis for early identification of bearing defects, no general consensus has been reached as to which passband is optimal. This study explores the impact of various passbands specified by the GA in terms of a residual frequency components-to-defect frequency components ratio, which evaluates the degree of defectiveness in bearings and finally outputs an optimal passband for reliable bearing fault detection.
authors.affiliation: School of Electrical, Electronics, and Computer Engineering, University of Ulsan, Ulsan, Republic of Korea.
authors.forename: Myeongsu
authors.initials: M
authors.lastname: Kang
authors.affiliation: School of Electrical, Electronics, and Computer Engineering, University of Ulsan, Ulsan, Republic of Korea.
authors.forename: Jaeyoung
authors.initials: J
authors.lastname: Kim
authors.affiliation: Department of Energy and Mechanical Engineering, Gyeongsang National University, Tongyeong City, Republic of Korea ilmareboy@mail.ulsan.ac.kr, kim7097@mail.ulsan.ac.kr, bgchoi@gnu.ac.kr, jmkim07@ulsan.ac.kr.
authors.forename: Byeong-Keun
authors.initials: BK
authors.lastname: Choi
authors.affiliation: School of Electrical, Electronics, and Computer Engineering, University of Ulsan, Ulsan, Republic of Korea.
authors.forename: Jong-Myon
authors.initials: JM
authors.lastname: Kim