Modulation Sideband Separation Using the Teager–Kaiser Energy Operator for Rotor Fault Diagnostics of Induction Motors

Li Li,Zhen Zhen,Ball Ball,Gu Gu,Wang Wang

doi:10.3390/en12234437

Li Li, Zhen Zhen + Show 3 more

Open Access

https://doi.org/10.3390/en12234437

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Abstract

Broken rotor bar (BRB) faults are one of the most common faults in induction motors (IM). One or more broken bars can reduce the performance and efficiency of the IM and hence waste the electrical power and decrease the reliability of the whole mechanical system. This paper proposes an effective fault diagnosis method using the Teager–Kaiser energy operator (TKEO) for BRB faults detection based on the motor current signal analysis (MCSA). The TKEO is investigated and applied to remove the main supply component of the motor current for accurate fault feature extraction, especially for an IM operating at low load with low slip. Through sensing the estimation of the instantaneous amplitude (IA) and instantaneous frequency (IF) of the motor current signal using TKEO, the fault characteristic frequencies can be enhanced and extracted for the accurate detection of BRB fault severities under different operating conditions. The proposed method has been validated by simulation and experimental studies that tested the IMs with different BRB fault severities to consider the effectiveness of the proposed method. The obtained results are compared with those obtained using the conventional envelope analysis methods and showed that the proposed method provides more accurate fault diagnosis results and can distinguish the BRB fault types and severities effectively, especially for operating conditions with low loads.

Highlights

Broken rotor bars (BRB) are frequent faults that represent around 9%, according to the IEEE, among all kinds of induction motor (IM) faults [1]
The proposed method has been validated by simulation and experimental studies that tested the IMs with different BRB fault severities to consider the effectiveness of the proposed method
By applying proposed the main component the motor current removed, By applying the proposed method, the main supply component of the motor current signal is thereby reducing the adverse effect of its spectral leakage in the accurate fault feature extraction, removed, for thereby reducing the when adverse of operating its spectral leakage thewith accurate fault feature especially the fault diagnosis theeffect

Summary

Introduction

Broken rotor bars (BRB) are frequent faults that represent around 9%, according to the IEEE, among all kinds of induction motor (IM) faults [1]. The variation of rotor resistance caused by BRB faults can affect the motor current directly and enhance its modulation characteristics. Motor current signal analysis (MCSA) is widely used to detect BRB faults based on modulation characteristic analysis [3]. With the advantages of non-invasion, low cost, and the ability to operate without needing any extra sensors installed, MCSA has successfully attracted researchers’ attention for detecting BRB faults with various kinds of measurements, such as vibration, acoustic, and temperature, et al [4,5]. Spectral analysis based on fast Fourier transform (FFT) is a conventional method that has been widely applied in MCSA.

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Discussion

Conclusion