Rotor failure detection of induction motors by wavelet transform and Fourier transform in non-stationary condition. (July 2015)

• Record Type: Journal Article
• Authors: da Costa, Cesar; Kashiwagi, Masamori; Mathias, Mauro Hugo
• Is Part Of: Case studies in mechanical systems and signal processing. Volume 1(2015)
• Page Start: 15
• Page End: 26
• Publication Date: 2015-07
• Subjects: Rotating electrical machine -- Diagnostic -- Digital signal processing; Mechanical engineering -- Case studies -- Periodicals; Industrial engineering -- Case studies -- Periodicals; Signal processing -- Case studies -- Periodicals; 620.105
• DOI: 10.1016/j.csmssp.2015.05.001
• Languages: English
• ISSNs: 2351-9886

Abstract

Abstract: This case study presents two diagnostic methods for the detection of broken bars in induction motors with squirrel-cage type rotors: FFT method and wavelet method. The FFT method allows detecting broken rotor bar when the motor operates under a load, but if the machine is decoupled from the mechanical load, the side band components associated with broken bars do not appear. The WT is a powerful signal-processing tool used in power systems and other areas. New wavelet-based detection methods that are focused on the analysis of the startup current have been proposed for the detection of broken bars. Since the transient stator current signal is not periodic, it is not amenable to analyze the signal by FFT method. In addition, it is impossible to estimate the time of the fault occurrence using the FFT. In this paper, our main goal is to find out the advantages of wavelet transform method compared to Fourier transform method in rotor failure detection of induction motors.