Abstract
Induction motors (IMs) are widely used in many manufacturing processes and industrial applications. The harsh work environment, long-time enduring, and overloads mean that it is subjected to broken rotor bar (BRB) faults. The vibration signal of IMs with BRB faults consists of the reliable modulation information used for fault diagnosis. Cyclostationary analysis has been found to be effective in identifying and extracting fault feature. The estimators of cyclic modulation spectrum (CMS) and fast spectral correlation (FSC) based on the short-time fourier transform (STFT) have higher cyclic frequency resolution, which has proven efficient in demodulating second order cyclostationary (CS2) signals. However, these two estimators have limitations of processing the maximum cyclic frequency αmax that is smaller than Fs/2 (Fs is the sampling frequency) according to Nyquist’s Theorem. In addition, they have lower carrier frequency resolution due to the fixed window size used in STFT. In order to resolve the initial shortcomings of the CMS and FSC methods, in this paper, we extended the analysis of CMS algorithm based on the continuous wavelet transform (CWT), which enlarged the maximum cyclic frequency range to Fs/2 and provides higher carrier frequency resolution because the CWT has the advantage of multi-resolution analysis. The reliability and applicability of the proposed method for fault components localization were validated by CS2 simulation signals. Compared to CMS and FSC methods, the proposed approach shows better performance by analyzing vibration signals between healthy motor and faulty motor with one BRB fault under 0%, 20%, 40%, and 80% load conditions.
Highlights
Induction motor (IM) is one of the most popular pieces of mechanical equipment and plays an important part in industrial applications
When the Broken rotor bar (BRB) fault occurs, a torque ripple and a speed oscillation will be generated at frequency 2 sf, which is modulated on the rotation frequency components
The spectrum obtained from cyclic modulation spectrum (CMS)-continuous wavelet transform (CWT) has the ability to clearly identify and present the approximate range of carrier frequency components modulated by the cyclic frequency related to BRB faults
Summary
Induction motor (IM) is one of the most popular pieces of mechanical equipment and plays an important part in industrial applications. Broken rotor bar (BRB) in IMs represents 8–9% of IM faults but they bring serious breakdown and lead to loss of productivity [1]. This needs to be solved, otherwise it can cause multiple BRB faults, mechanical eccentricity, and thermal stress because of localized heating. The detection of this type of fault has been a key issue of studies which aims to develop more advanced techniques to minimize the breakdown and maintenance cost of IMs. Several sensing techniques have been researched in the field of BRB fault diagnosis. Motor current signature analysis (MCSA) [2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17] is the mainstream technique, and the motor vibration
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
