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--
- Journal Information:
- IEEE Transactions on Power Delivery, Journal Name: IEEE Transactions on Power Delivery Journal Issue: 4 Vol. 11; ISSN 0885-8977; ISSN ITPDE5
- Country of Publication:
- United States
- Language:
- English
Similar Records
ANN based transformer fault diagnosis using gas-in-oil analysis
Fault diagnosis in nuclear power plants using an artificial neural network technique
Nuclear power plant fault-diagnosis using artificial neural networks
Conference
·
Sun Oct 01 00:00:00 EDT 1995
·
OSTI ID:103711
Fault diagnosis in nuclear power plants using an artificial neural network technique
Conference
·
Thu Dec 31 23:00:00 EST 1992
· Transactions of the American Nuclear Society; (United States)
·
OSTI ID:7128927
Nuclear power plant fault-diagnosis using artificial neural networks
Conference
·
Wed Dec 30 23:00:00 EST 1992
·
OSTI ID:10140171