An artificial neural network approach to transformer fault diagnosis
Journal Article
·
· IEEE Transactions on Power Delivery
- Virginia Polytechnic Inst. and State Univ., Blacksburg, VA (United States). Bradley Dept. of Electrical Engineering
- Doble Engineering Co., Watertown, MA (United States)
This paper presents an artificial neural network (ANN) approach to diagnose and detect faults in oil-filled power transformers based on dissolved gas-in-oil analysis. A two-step ANN method is used to detect faults with or without cellulose involved. Good diagnosis accuracy is obtained with the proposed approach.
- Sponsoring Organization:
- National Science Foundation, Washington, DC (United States)
- OSTI ID:
- 422769
- Report Number(s):
- CONF-960111-; ISSN 0885-8977; TRN: IM9707%%76
- Journal Information:
- IEEE Transactions on Power Delivery, Vol. 11, Issue 4; Conference: IEEE Power Engineering Society (PES) Winter meeting, Baltimore, MD (United States), 21-25 Jan 1996; Other Information: PBD: Oct 1996
- Country of Publication:
- United States
- Language:
- English
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