Mixed Eccentricity Fault Detection for Induction Motors Based on Time Synchronous Averaging of Vibration Signals

被引：19

作者：

Alimardani, Ramin ^{[1
]}

Rahideh, Akbar ^{[1
]}

Hedayati Kia, Shahin ^{[2
]}

机构：

[1] Shiraz Univ Technol, Dept Elect Engn, Shiraz 1387671557, Iran

[2] Univ Picardie Jules Verne, MIS Lab, UR4290, F-80039 Amiens, France

来源：

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS | 2024年 / 71卷 / 03期

关键词：

Eccentricity; fault detection; induction motor; time synchronous averaging (TSA); vibrations signal; DISCRETE WAVELET TRANSFORM; FLUX-BASED DETECTION; AIRGAP-ECCENTRICITY; ROTOR FAULTS; GEAR FAULT; DIAGNOSIS; COMBINATION; MACHINES; SCHEME; MODEL;

D O I：

10.1109/TIE.2023.3266589

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This article presents a method based on vibration signals to diagnose rotor mixed eccentricity faults in three-phase squirrel cage induction motors (SCIMs). Rotor eccentricity is a typical fault in SCIMs that significantly affects the performance of electrical machines and results in unwanted vibrations. The time synchronous averaging (TSA) signal, which consists of the harmonics components generated by the fault, is obtained via the characteristic frequency of the eccentricity fault. TSA is decomposed into two signals: TSA-regular and TSA-difference, which are respectively similar to approximate and details of the wavelet transform. Based on the fault index, which is the maximum FFT value of the TSA-difference signal, the healthy and faulty motors can be distinguished. The proposed approach is evaluated on an experimental test rig equipped with a 1.5 kW SCIM supplied directly from the power grid under various load conditions. The results illustrate the effectiveness of the proposed approach in detecting the rotor mixed eccentricity faults.

引用

页码：3173 / 3181

页数：9

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