Work

Identification of significant intrinsic mode functions for the diagnosis of induction motor fault

Year: 2014

Type: article

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.

Source: The Journal of the Acoustical Society of America

DOI: 10.1121/1.4885541

Authors: Sangjin Cho, Md. Rifat Shahriar, Uipil Chong

Institution: University of Ulsan

Language: English

Topic: Machine Fault Diagnosis Techniques

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: bronze

Funder: University of Ulsan

OpenAlex ID: W1976018698