Fault diagnostics in oil filled electrical equipment: Review of duval triangle and possibility of alternatives
Author:
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/7541933/7548553/07548688.pdf?arnumber=7548688
Cited by 10 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. New Insights into Gas-in-Oil-Based Fault Diagnosis of Power Transformers;Energies;2024-06-12
2. Discernment of transformer oil stray gassing anomalies using machine learning classification techniques;Scientific Reports;2024-01-03
3. Improvement of Power Transformer Faults Diagnosis Using Random Search with Classification and Regression Tree;2023 5th Asia Energy and Electrical Engineering Symposium (AEEES);2023-03-23
4. Transformer Fault Diagnosis Technology Based on Maximally Collapsing Metric Learning and Parameter Optimization Kernel Extreme Learning Machine;IEEJ Transactions on Electrical and Electronic Engineering;2022-02-14
5. Development of an Integrated Approach Based on a Neural Network and Dempster–Schaefer Theory to Diagnose Industrial Equipment;SMART Automatics and Energy;2022
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