On‐line detection and estimation of harmonics components in induction motors rotor fault through a modified Prony's method

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Abstract
The diagnosis of electrical motor for broken rotor bars faults through frequency signatures of the stator current method has been widely explored. In fact, a high‐resolution spectrum analysis based on the multiple signal classification (MUSIC) method has been widely applied to detect induction machine faults for that purpose. Moreover, MUSIC is a powerful tool that extracts significant frequencies from the signal, but cannot give precise amplitude information of the fault indicator frequency. Nevertheless, the MUSIC algorithm takes a long‐time acquisition to find many frequencies. To solve these problems, the short‐time least square Prony's technique is developed. The technique is based on a modified Prony's method for the estimation of amplitudes certain harmonics and frequencies of broken rotor bar fault. The main objective in this context is the reduction in the samples of measurement data with shorter time to allow a clearer view of the fault harmonics components when the motor turns at low load. It allows determining the characteristic frequencies and amplitudes of the lateral bands around the fundamental frequency component with great precision. Additionally, using this proposed method for the magnitude modulation of stator current envelope spectrum is produced and induces current harmonics by the rotor fault at frequency. It is based on tracking the amplitude of harmonics of the stator current envelope. The effectiveness of the proposed method is tested in simulation and a real‐time implementation on experimental validation.

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