New Machine Learning Model-Based Fault Diagnosis of Induction Motors Using Thermal images
Author:
Affiliation:
1. Cardiff University,Wolfson Centre for Magnetics,Cardiff,UK,CF24 3AA
2. Cardiff University,High-Value Manufacturing Group,Cardiff,UK,CF24 3AA
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9823381/9823413/09823832.pdf?arnumber=9823832
Reference22 articles.
1. Suitable features selection for monitoring thermal condition of electrical equipment using infrared thermography
2. Diagnosis of the three-phase induction motor using thermal imaging
3. Recognition of Thermal Images of Direct Current Motor with Application of Area Perimeter Vector and Bayes Classifier
4. Recent Industrial Applications of Infrared Thermography: A Review
5. Image quality assessment based on local variance and structure similarity;wang;Guangdianzi Jiguang/Journal of Optoelectronics Laser,2008
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1. Unraveling Induction Motor State through Thermal Imaging and Edge Processing: A Step towards Explainable Fault Diagnosis;Eksploatacja i Niezawodność – Maintenance and Reliability;2023-07-29
2. Fault diagnosis of radio frequency circuit using heterogeneous image fusion;Optical Engineering;2023-03-19
3. Identification of asynchronous motor and transformer situations in thermal images by utilizing transfer learning-based deep learning architectures;Measurement;2023-02
4. Thermal Image-Based Fault Detection Using Machine Learning and Deep Learning in Industrial Machines: Issues-Challenges and Emerging Trends;Fourth International Conference on Image Processing and Capsule Networks;2023
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