RPCNNet: A Deep Learning Approach to Sense Minor Stator Winding Interturn Fault Severity in Induction Motor Under Variable Load Condition
Author:
Affiliation:
1. Electrical Engineering Department, Jadavpur University, Kolkata, India
2. Jalpaiguri Government Engineering College, Jalpaiguri, India
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Instrumentation
Link
http://xplorestaging.ieee.org/ielx7/7361/10043099/10014695.pdf?arnumber=10014695
Reference28 articles.
1. A New Convolutional Neural Network-Based Data-Driven Fault Diagnosis Method
2. Highly Accurate Machine Fault Diagnosis Using Deep Transfer Learning
3. Turn‐to‐turn short circuit of motor stator fault diagnosis in continuous state based on deep auto‐encoder
4. Real-Time Motor Fault Detection by 1-D Convolutional Neural Networks
5. An Experimental Comparative Evaluation of Machine Learning Techniques for Motor Fault Diagnosis Under Various Operating Conditions
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