Spectral analysis for diagnosis of bearing defects in induction machine drives
Author:
Affiliation:
1. Department of Electrical EngineeringFaculty EngineeringShahed UniversityTehranIran
Publisher
Institution of Engineering and Technology (IET)
Subject
Electrical and Electronic Engineering
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-epa.2018.5226
Reference23 articles.
1. A review of vibration and acoustic measurement methods for the detection of defects in rolling element bearings
2. Models for Bearing Damage Detection in Induction Motors Using Stator Current Monitoring
3. Survey on high‐frequency models of PWM electric drives for shaft voltage and bearing current analysis
4. Diagnosis of Bearing Faults in Induction Machines by Vibration or Current Signals: A Critical Comparison
5. Incipient Bearing Fault Detection via Motor Stator Current Noise Cancellation Using Wiener Filter
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2. A Novel Physics-Informed Hybrid Modeling Method for Dynamic Vibration Response Simulation of Rotor–Bearing System;Actuators;2023-12-11
3. Bearing Fault Diagnosis for an Induction Motor Controlled by an Artificial Neural Network—Direct Torque Control Using the Hilbert Transform;Mathematics;2022-11-14
4. Fault diagnosis of rolling element bearing using ACYCBD based cross correlation spectrum;Journal of the Brazilian Society of Mechanical Sciences and Engineering;2021-09-08
5. Rapid evaluation of the mechanical fault severity in induction motors using the model‐based diagnosis technique;IET Electric Power Applications;2021-01-18
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