Diagnosing the type and location of the transformer fault by analyzing the dissolved gas using fuzzy logic

There are many methods to diagnose transformer faults, including dissolved gas analysis (DGA), done in two conventional and smart ways. This paper presents a new method based on fuzzy logic and 5 DGA methods (key gas method, Durenberg's ratio method, Rogerˊs ratio method, IEC method, and Duval triangle method) to evaluate the condition of power transformers. At first, it is determined whether the transformer is healthy or defective. This step is performed based on key gas methods and Durenberg's ratio method with a fuzzy logic approach. Then, if it is detected that the transformer is defective, the type of error is detected using Rogers and IEC methods. If the error detection by these two methods reaches the same result, the error type detection is terminated and if the result is not the same, the Duval triangle method with fuzzy logic approach is used to detect the error type. The presented algorithm has been tested on 30 transformer devices and the results confirm its high accuracy (96.7%) in fault detection. In this article, in addition to detecting the type of fault, the location of the fault has been investigated and diagnosed using the CO2/CO ratio and the key gas method with a fuzzy logic approach.