Development of Full-Automatic Transformer Fault Detection System Based on Gas Chromatography Analysis

Abstract

In the long-term operation of transformers, some small amounts of gases will be produced in the transformer oil, which will lead to the fault of power transformers. The content of some small amounts of gases can reflect the fault types of power transformers to a certain extent. This study takes transformer as the research object and uses gas chromatographic analysis to detect its fault. First, this study introduces the basic knowledge of the gas chromatography and uses the chromatographic column to separate the measured gap, then converts the concentration of different components into a corresponding voltage signal and analyzes and processes the electrical signal, the fault detection of transformer is made by using neural network and fuzzy mathematics algorithm. Finally, each module of the system is analyzed, and the development of the full-automatic transformer fault detection system based on gas chromatography analysis is completed.