A method for broken bar fault diagnosis in three phase induction motor drive system using Artificial Neural Networks-Reference-Cited by-同舟云学术

A method for broken bar fault diagnosis in three phase induction motor drive system using Artificial Neural Networks

Published:2021-06-16 Issue: Volume: Page:1-7
ISSN:0143-0750
Container-title:International Journal of Ambient Energy
language:en
Short-container-title:International Journal of Ambient Energy

Author:

Senthil Kumar R.¹,Gerald Christopher Raj I.²,Suresh K. P.¹,Leninpugalhanthi P.¹,Suresh M.³,Panchal Hitesh⁴^ORCID,Meenakumari R.⁵,Sadasivuni Kishor Kumar⁶

Affiliation:

1. Department of Electrical and Electronics Engineering, Sri Krishna College of Technology, Coimbatore, India

2. Department of Electrical and Electronics Engineering, PSNA College of Engineering and Technology, Dindigul, India

3. Department of Electronics and Communication Engineering, Kongu Engineering College (Autonomous), Perundurai, India

4. Department of Mechanical Engineering, Government Engineering College, Patan, India

5. Department of Electrical and Electronics Engineering, Kongu Engineering College Autonomous), Perundurai, India

6. Centre for Advanced Materials, Qatar University, Doha, Qatar

Publisher

Informa UK Limited

Subject

Building and Construction,Renewable Energy, Sustainability and the Environment

Link

https://www.tandfonline.com/doi/pdf/10.1080/01430750.2021.1934117

Reference39 articles.

1. Induction motor broken rotor bar fault location detection through envelope analysis of start-up current using Hilbert transform

2. Discrete wavelet transform and energy eigen value for rotor bars fault detection in variable speed field-oriented control of induction motor drive

3. The detection of rotor faults in the manufacturing of submersible induction motor

4. Vector control for induction motor drives based on adaptive variable structure control algorithm

5. Advances in Diagnostic Techniques for Induction Machines

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