Research On Transformer Fault Diagnosis Method Analysis

With the rapid development of the national economy, the safe operation of the power system needs reliable technology to provide protection. Therefore, analysis and research distribution network transformer fault diagnosis problem that highlights its significance. In a complex power system and substation seem important, and plays an important role in this process is the transformer. It is the low pressure and high pressure into each other, while reducing power consumption in the transport, on the other hand reduces the power transmission process caused dangerous. Therefore, the distribution network for fault diagnosis of transformer appears and ensure their safe operation is especially important.This paper analyzes the distribution network transformers many common faults, such as short-circuit fault, the discharge failure, insulation failure, etc., depending on the type of fault, this paper gives and gives the corresponding fault detection method, by gas chromatography detection, current detection winding and milliammeter universal fault detection, fault distribution network transformer fault analysis and diagnosis from the phenomenon, causes and mechanism are. For a variety of internal power transformer fault exists, considering the transformer internal firmware and external environmental factors. Through the research on power transformer common faults, analyze the advantages and disadvantages of various diagnostic methods, mainly targeted for the transformer common fault analysis and examples of the theoretical analysis. Transformer fault diagnosis, the methods described in this article has a practical application of significance.This article is unique in that, according to the traditional transformer fault diagnosis theory, put forward a new method of feasible - Comprehensive diagnostics. Transformer Fault Diagnosis method not only in the actual case can manually analyze the test data, but also can make use of modern automated computer program for real-time online monitoring and analysis, greatly improving the reliability of transformer fault diagnosis.