Performance Evaluation of AI-based Algorithms for Condition Assessment of Power Components-Reference-Cited by-同舟云学术

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Performance Evaluation of AI-based Algorithms for Condition Assessment of Power Components

Published:2022-11-13 Issue: Volume: Page:
ISSN:
Container-title:2022 9th International Conference on Condition Monitoring and Diagnosis (CMD)
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Author:

Kumar Haresh¹,Shafiq Muhammad²,Kauhaniemi Kimmo¹

Affiliation:

1. University of Vaasa

2. Tallinn University of Technology

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9991244/9991271/09991719.pdf?arnumber=9991719

Reference16 articles.

1. Characteristic Pulse Pattern Features of Different Types of Partial Discharge Sources in Power Cables

2. Classification of PD Faults Using Features Extraction and K-Means Clustering Techniques

3. Supervised Machine Learning Algorithm Selection for Condition Monitoring of Induction Motors

4. Classification of Partial Discharge Sources in XLPE Cables by Artificial Neural Networks and Support Vector Machine

5. Research on insulation defect diagnosis method of XLPE AC cable based on partial discharge image feature

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Emerging Technologies based Use Case Development for Condition Monitoring and Predictive Maintenance of MV Cables;2023 IEEE PES Innovative Smart Grid Technologies Latin America (ISGT-LA);2023-11-06

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