Detection of Structure Deformation and Insulation Condition for Transformer Windings Based on High-Voltage Oscillating Wave

Zhenyu Wu, Jianxiong Tao, Yongbin Liu, Tao He, Siliang Lu

Abstract: The efficient and accurate detection of the mechanical structure and insulation condition of transformer windings is a key prerequisite for condition assessment and maintenance. However, an effective detection method for latent interturn insulation faults has yet to be developed. Moreover, the existing routine tests vary and are time-consuming. The test conditions of different test items also vary remarkably, leading to the corresponding replacement of the detection device and the test cable, which makes the detection time of a single project often insufficient, thus seriously affecting the test results. Therefore, this study proposes an integrated detection method based on high-voltage oscillating waves. First, the principle of latent interturn insulation fault diagnosis is theoretically analyzed, and the integrated detection steps of winding mechanical structure, insulation resistance, dielectric loss, and leakage current are further introduced. Second, a model test platform of a proportional transformer is constructed to simulate various faults. A traditional detection method and oscillating wave detection are conducted, and the detection results are compared and analyzed. Finally, high-voltage oscillating wave detection is performed for the actual 110-kV transformer with defects. Results show that the proposed detection method has high fault sensitivity for turn-to-turn insulation faults, mechanical deformation, and main insulation faults. The detection results are consistent with the traditional detection methods, thus verifying the feasibility of the method and the sensitivity of fault diagnosis.