Research on Fault Diagnosis and Prediction Technology of Transformer Test Data Based on Artificial Intelligence Technology

With the rapid development of power systems, transformers, as key equipment in power transmission and distribution, play a crucial role in the stability and reliability of the entire system. As technology advances, transformer fault diagnosis and prediction technologies have become hot topics in power system research. This paper reviews the current research status of fault diagnosis technologies based on transformer test data. It introduces in detail the common test types and data characteristics of transformers, including electrical tests and oil chromatographic analysis. The paper elaborates on fault diagnosis technologies based on traditional methods and modern intelligent algorithms, analyzing their advantages and disadvantages. Additionally, it discusses the issues existing in current research and proposes prospects for future development trends, aiming to provide references for improving the accuracy and reliability of transformer fault diagnosis.