title: Identification of significant intrinsic mode functions for the diagnosis of induction motor fault.
abstract: For the analysis of non-stationary signals generated by a non-linear process like fault of an induction motor, empirical mode decomposition (EMD) is the best choice as it decomposes the signal into its natural oscillatory modes known as intrinsic mode functions (IMFs). However, some of these oscillatory modes obtained from a fault signal are not significant as they do not bear any fault signature and can cause misclassification of the fault instance. To solve this issue, a novel IMF selection algorithm is proposed in this work.
authors.affiliation: School of Electrical Engineering, University of Ulsan, 93 Daehak-ro, Nam-gu, Ulsan, 680-749, South Korea sjcho75@ulsan.ac.kr, m.rifat@ieee.com, upchong@ulsan.ac.kr.
authors.forename: Sangjin
authors.initials: S
authors.lastname: Cho
authors.affiliation: School of Electrical Engineering, University of Ulsan, 93 Daehak-ro, Nam-gu, Ulsan, 680-749, South Korea sjcho75@ulsan.ac.kr, m.rifat@ieee.com, upchong@ulsan.ac.kr.
authors.forename: Md Rifat
authors.initials: MR
authors.lastname: Shahriar
authors.affiliation: School of Electrical Engineering, University of Ulsan, 93 Daehak-ro, Nam-gu, Ulsan, 680-749, South Korea sjcho75@ulsan.ac.kr, m.rifat@ieee.com, upchong@ulsan.ac.kr.
authors.forename: Uipil
authors.initials: U
authors.lastname: Chong