无载调压变压器绕组匝间绝缘状态评估模型

Evaluation Model of Turn to Turn Insulation State of no-Load Tap Changer

无载调压变压器绕组故障定位易受到噪声干扰,导致绕组匝间绝缘状态评估准确率下降。为此引入模糊理论,建立了绕组匝间绝缘状态评估模型。构建非线性回归SVM预测模型,实现无载调压变压器绕组热点温度预测。根据Hausdorff距离衡量等效励磁电感波形的差异性,采用小波熵滤噪方法实现绕组温度等数据的去噪处理,进而准确定位绕组匝间短路故障。通过模糊关联矩阵描述故障原因与表现的关联性,采用二级模糊综合评估方法构建绝缘状态评估模型。仿真结果证明,研究方法能获得精准的故障定位与绝缘状态评估结果,且评估效率高,可为后续的维修与改进提供有利参考。

The winding fault location of the no-load voltage regulating transformer is easy to be disturbed by noise,leading to the decline of the accuracy rate of assessment for insulation state.Therefore,the fuzzy theory was introduced to construct the evaluation model of the winding interturn insulation state.The SVM prediction model based on nonlinear regression was constructed to realize the hot-spot temperature prediction of no-load voltage regulating transformer winding.According to Hausdorff distance,the difference of equivalent excitation inductance waveform was measured.Moreover,the wavelet entropy filtering method was used to remove the noise from the winding temperature and other data,and thus to accurately locate the interturn short-circuit fault of winding.The fuzzy correlation matrix was adopted to describe the correlation between fault cause and performance.Finally,the second-degree fuzzy comprehensive evaluation method was used to build the model of evaluating insulation state.Following conclusions can be drawn from simulation results.The researched method can obtain accurate fault location and evaluation results of insulation state.The evaluation efficiency is high.This method can provide a useful reference for subsequent maintenance and improvement.