CMAC_based fault diagnosis of power transformers

Proceedings of the International Joint Conference on Neural Networks

Volumn 1, Issue , 2002, Pages 986-991

  Lin, Wei Song ^a   Hung, Chin Pao ^a   Wang, Mang Hui ^a  

^a NATIONAL TAIWAN UNIVERSITY   (Taiwan)

Author keywords

CMAC; Dissolved gas analysis (DGA); Neural network; Transformer fault diagnosis

Indexed keywords

ELECTRIC TRANSFORMER TESTING; FUZZY SETS; LEARNING SYSTEMS; NEURAL NETWORKS; STANDARDIZATION;

CEREBELLAR MODEL ARTICULATION CONTROLLER; DISSOLVED GAS ANALYSIS; POWER TRANSFORMER; TRANSFORMER FAULT DIAGNOSIS;

EXPERT SYSTEMS;

EID: 0036072902     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (17)

1. Transformer fault diagnosis by dissolved-gas analysis
2. IEEE and IEC codes to interpret faults in transformers, using gas in oil analysis
3. Monitoring oil cooling transformers by gas analysis
4. An expert system for transformer fault diagnosis using dissolved gas analysis
5. An artificial neural network approach to transformer fault diagnosis
6. A combined ANN and expert system tool for transformer fault diagnosis
7. Application of fuzzy equivalent matrix for fault diagnosis of oil-immersed insulation
8. A fuzzy dissolved gas analysis method for the diagnosis of multiple incipient faults in a transformer
9. Transformer oil diagnosis using fuzzy logic and neural networks
10. Fuzzy learning vector quantization networks for power transformer condition assessment
11. DGA based insulation diagnosis of power transformer via ANN
12. Statical and neural network analysis of dissolved in power transformers
13. 1
14. Learning convergence in the cerebellar model articulation controller
15. Integrating neural networks and knowledge-based systems for intelligent robotic control