基于双尺度分形盒维数的电能质量扰动信号识别

Power quality disturbance analysis based on dual-scale fractal box counting dimension

提出一种电能质量PQ(Power Quality)扰动信号时域分析方法。在PQ扰动信号分析中,分形维数用来描述信号的不规则性和复杂度。由于引起各种PQ扰动的来源不同,致使扰动信号在不规则性和复杂度上体现出差异,为PQ扰动信号分析提供依据。平面离散信号的传统分形盒维数计算通常基于正方形盒,而对于PQ扰动信号,时间和幅值是完全不同的物理概念,采用基于时间和幅值的双尺度长方形盒对PQ扰动信号计算盒维数,根据PQ扰动信号的周期或准周期特性推导无标度区的长方形盒尺度确定经验公式,并通过具体波形简单验证。典型的PQ扰动信号分析的结果表明,其描述的特征量明显,可以识别扰动。盒维数的简单统计结果可以作为PQ神经网络分类器的输入特征量。

A new time-domain based method for power quality （PQ） analysis is brought forward. Fractal dimension is a mean to characterize the abnormity and complexity of PQ disturbance. The producers of PQ disturbance are different which result in the difference of abnormity and complexity, so fractal analysis is potential for PQ disturbance analysis. Traditional fractal box counting dimension is based on the square which confuses the coordinate physical meaning. The dual-scale fractal box counting dimension is based on the rectangle in which time and range of PQ disturbance are included, The formulae for fractal scaleless range is developed based on the periodic or approaching periodic characteristic of PQ disturbance. The effectiveness of formulae is tested by simple waveform. Fractal box counting dimension of typical PQ disturbances depict the PQ disturbances well especially in identification. After simple statistics, the dimension can act as the input vector of ANN for PQ classification.