基于高阶累积量的暂态电能质量扰动分类研究

为提高暂态电能质量扰动分类识别的精度,提出了一种基于高阶累积量与支持向量机的暂态电能质量扰动信号的分类识别算法。该算法利用高阶累积量提取脉冲暂态与振荡暂态2类扰动的3阶与4阶统计特征,并选取各阶统计结果中的极大值个数、极小值个数以及最大值、最小值共8个特征量作为支持向量机的输入。利用Matlab产生仿真数据对此方法进行了仿真验证,结果表明,高阶累积量可以有效表征暂态扰动特征,且受噪声影响小;结合支持向量机可有效分类识别这2类暂态扰动,在训练样本为50组,核函数选择为线性核函数时,识别率可达到99%;当混合有其他扰动分量时,该方法也有效。

Classification of Transient Power Quality Disturbances Based on High-Order Cumulants

To improve the precision of classification and recognition of transient power quality disturbances,a new classification and recognition algorithm for transient power quality disturbance signals,which is based on high-order cumulants(HOC) and support vector machine(SVM),is proposed.In the proposed algorithm,the 3-order and 4-order impulse statistical characteristics of two kinds of disturbances,i.e.,the impulse transient and oscillation transient,are extracted from HOC,and eight characteristic quantities,i.e...