Machine learning-based identification of cellulose particle pre-bridging and bridging stages in transformer oil
The deterioration of transformer oil quality is influenced by factors including the presence of acids, water, and other contaminates such as cellulose particles and metal dust. The dielectric strength of the oil decreases over time and depending on the service conditions. This study introduces an ef...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | en |
| Published: |
Science and Information Organization
2025
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| Online Access: | http://eprints.utem.edu.my/id/eprint/29354/2/0075804092025153459.pdf http://eprints.utem.edu.my/id/eprint/29354/ https://thesai.org/Downloads/Volume16No3/Paper_37-Machine_Learning_Based_Identification_of_Cellulose_Particle.pdf |
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