Abstract
The importance of early fault detection in electric motors has attracted the attention of research groups, as the detection of incipient faults can prevent damage spreading and increase the lifetime of the motor. At present, studies have focused their attention on optimization procedures used for fault detection in induction machines to achieve a quick and easy-to-interpret assessment at an industrial level. This paper proposes an alternative approach based on the Continuous Wavelet Transform (CWT) for broken bar diagnosis in squirrel cage induction motors. This work uses the Motor Current Signature Analysis (MCSA) method to acquire the current signal of the induction motor. The novelty of this study lies in broken bar detection in electric machines operating at non-load by analyzing variations in the spectrum of the motor’s current signal. This way, the faults are presented as oscillations in the current signal spectrum. Additionally, a quantification of broken bars for the same type of motors operating at fullload is performed in this study. An experimental validation and the comparison with the Fast Fourier Transform (FFT) technique are provided to validate the proposed technique.
Highlights
Three-phase motors are widely used in the industry due to their ease of manufacture and low maintenance [1]
In order to prevent the premature failure of induction motors [37], the Motor Current Signature Analysis (MCSA) method and signal processing techniques are applied for early broken bar detection in three-phase induction motors
This paper presents the analysis of motors with broken bars using the MCSA method and the Continuous Wavelet Transform (CWT) processing technique to identify features associated with this fault
Summary
Three-phase motors are widely used in the industry due to their ease of manufacture and low maintenance [1]. The diagnosis and fault detection methods used in induction motors are based on the effective analysis, in the frequency domain, of the induction machine electrical parameters [2,14,15] This analysis is usually performed by Fast Fourier Transform (FFT) [10,14] and Hilbert Transform [2,16]. The Morlet-CWT signal processing technique applied for detection of broken bars in electric machines is used to represent time-domain motor current signals in the time-frequency spectrum. In order to prevent the premature failure of induction motors [37], the MCSA method and signal processing techniques are applied for early broken bar detection in three-phase induction motors. This paper presents the analysis of motors with broken bars using the MCSA method and the CWT processing technique (i.e., time-frequency spectrum) to identify features associated with this fault.
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