Introduction to Grey system theory
The Journal of Grey System
Expert Systems with Applications: An International Journal
Fault diagnosis of power transformer based on support vector machine with genetic algorithm
Expert Systems with Applications: An International Journal
Association rule mining-based dissolved gas analysis for fault diagnosis of power transformers
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Data mining for oil-insulated power transformers: an advanced literature survey
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
An innovative blemish detection system for curved LED lenses
Expert Systems with Applications: An International Journal
Hi-index | 12.06 |
This paper proposes a method for incipient fault diagnosis in oil-immersed transformers using grey clustering analysis (GCA). Incipient faults can produce hydrocarbon molecules and carbon oxides due to the thermal decomposition of oil, cellulose, and other solid insulation. The power transformers can be detected and monitor abnormal conditions with dissolved gas analysis (DGA). Various artificial intelligent (AI) techniques have been proposed for transformer fault diagnosis; however they have some limitations such as accuracy of diagnosis, requirement of inference rules, and determination of the detection architecture. IEC/Cigre standard and GCA are applied to diagnose internal faults including thermal faults, electrical faults, and faults with cellulosic insulation degrading. Compared with other diagnostic techniques, numerical tests with practical gas records were conducted to show the effectiveness of the proposed model, and are easy to implement with the portable device and hardware device.