基于高斯过程分类的串联直流电弧故障检测

随着可再生能源和电力电子技术的飞速发展,直流系统在各个领域都得到了广泛应用。但由绝缘损坏、接头松动等原因引起的直流电弧故障是威胁直流系统正常运行的主要因素。为了解决直流电弧故障由于不存在过零点和平肩现象而难以检测的问题,文中将高斯过程模型引入电弧故障研究,进行不同负载下串联直流电弧故障试验。通过提取电流差均值、谐波能量和组成特征向量,利用高斯过程分类进行电弧故障训练、预测分类。试验结果表明,该检测方法能够准确识别电弧故障。

Detection Method of Series DC Arc Fault Based on Gaussian Process Classification

With the rapid development of renewable and energy power electronics,the DC system has been widely used in various fields.However,the DC arc fault caused by insulation damage and loose joint is the main factor threatening the normal operation of the DC system.In order to solve the problem that DC arc fault is difficult to detect due to the absence of zero crossing and shoulder phenomenon,the Gaussian process model is introduced into the arc fault research,and the series DC arc fault tests under different loads are carried out.Feature vectors are extracted from current signal including the mean of difference of current and the sum of harmonic energy at first.Then Gauss process classification is applied to arc fault training and prediction classification.Finally test results show that presented detection method can identify DC arc fault accurately under different load condition.