Abstract
This paper deals with the problem of fault detection in induction motors using the discrete wavelet transform (DWT) method. The DWT is a mathematical method used to extract different frequency components from a given signal. It is based on the decomposition of the processed signals into wavelet approximation and detail coefficients. In order to detect inter-turns short-circuit (ITSC) and broken rotor bars (BRBs) faults, the DWT is applied on two different signals: the current envelope and the current Park’s vector modulus. This study is performed using experimental tests carried-out on a 3 kW squirrel cage induction motor. The energy evaluation of known bandwidth details allows defining a fault severity factor (FSF). This FSF is used to show which signals, wavelet type and wavelet order are more sensitive for the fault detection task.
Published Version
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