PMSM Stator Winding Fault Detection and Classification Based on Bispectrum Analysis and Convolutional Neural Network
Author:
Affiliation:
1. Department of Electrical Machines, Drives and Measurements, Wrocław University of Science and Technology, Wrocław, Poland
Funder
Narodowe Centrum Nauki
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Control and Systems Engineering
Link
http://xplorestaging.ieee.org/ielx7/41/10005867/09829204.pdf?arnumber=9829204
Reference31 articles.
1. Identification of Intermittent Electrical and Mechanical Faults in Permanent-Magnet AC Drives Based on Time–Frequency Analysis
2. Effectiveness Analysis of PMSM Motor Rolling Bearing Fault Detectors Based on Vibration Analysis and Shallow Neural Networks
3. Short-Circuit Detection by Means of Empirical Mode Decomposition and Wigner–Ville Distribution for PMSM Running Under Dynamic Condition
4. Stator short circuits detection in PMSM by means of Hilbert-Huang transform and energy calculation
5. An Investigation Into Fault Diagnosis of Planetary Gearboxes Using A Bispectrum Convolutional Neural Network
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