Title :
An Expert System for Incipient Fault Diagnosis and Condition Assessment in Transformers
Author :
Malik, Hasmat ; Tarkeshwar ; Jarial, R.K.
Author_Institution :
Electr. Eng. Dept., NIT Hamirpur, Hamirpur, India
Abstract :
The gases generated in oil filled transformer can be used for determination of incipient faults. Dissolved gas analysis (DGA) of transformer oil has been one of the most power full methods to detect the faults. The various methods such as liquid chromatography, acoustic analysis, and transformer function techniques are require some experience to interpret observations. The researchers have used artificial intelligence (AI) approach to encode these diagnostic techniques. This paper presents fuzzy-logic application and an overview of ANN techniques which can diagnose multiple faults in a transformer. Theoretical and practical fuzzy-logic (FL) information model and various researchers´ ANN based experimental conclusion have been presented. This paper includes a demonstration of the application of the FL technique for transformer incipient fault diagnosis.
Keywords :
condition monitoring; expert systems; fault diagnosis; fuzzy logic; neural nets; oils; power engineering computing; power transformers; acoustic analysis; artificial intelligence approach; condition assessment; expert system; fuzzy-logic application; incipient fault diagnosis; liquid chromatography; oil filled transformer; transformer function techniques; transformer oil dissolved gas analysis; Artificial neural networks; Fault diagnosis; Gases; IEC; Oil insulation; Power transformers; Thermal analysis; Artificial neural networks (ANN); Dissolved gas analysis; Expert system; Fuzzy-logic diagnostic; Transformer;
Conference_Titel :
Computational Intelligence and Communication Networks (CICN), 2011 International Conference on
Conference_Location :
Gwalior
Print_ISBN :
978-1-4577-2033-8
DOI :
10.1109/CICN.2011.27