Machinery Fault Diagnoses in High-Voltage Circuit Breakers Using Empirical Mode Decomposition-Support Vector Machine Model-Reference-Cited by-同舟云学术

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Machinery Fault Diagnoses in High-Voltage Circuit Breakers Using Empirical Mode Decomposition-Support Vector Machine Model

Published:2024-04-26 Issue: Volume: Page:1-4
ISSN:
Container-title:2024 Third International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)
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Author:

Al-Farouni Mohammed¹,Sudhakar A.V.V.²,G Divya³,V. Bala Dhandayuthapani⁴,Shivakanth Gandla⁵

Affiliation:

1. Department of Computers Techniques Engineering, College of Technical Engineering The Islamic University,Najaf,Iraq

2. Department of Electrical and Electronics Engineering SR University,Warangal,India

3. Department of ECE Nitte Meenakshi Institute of Technology,Bengaluru,India

4. Department of IT, College of Computing and Information Sciences University of Technology and Applied Sciences,Shinas campus Shinas,Oman

5. Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation,Hyderabad,Telangana,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10548017/10548035/10549320.pdf?arnumber=10549320

Reference12 articles.

1. Transient fault identification method for bipolar short‐circuit fault on MMC‐HVDC overhead lines based on hybrid HVDC breaker

2. Machine Learning Techniques to Improve the Success Rate in In-Vitro Fertilization (IVF) Procedure

3. Significance of fault-current-limiters and parameters optimization in HVDC circuit breakers for increased capacity of VSC-HVDC transmission networks application

4. Development and prospect of direct‐current circuit breaker in China

5. Large‐scale system identification using self‐adaptive penguin search algorithm

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