基于混沌关联积分的暂态电能质量扰动分类

关联积分曲线基于时间序列重构,能够更全面反映时间序列扰动变化,并且作为扰动识别的特征量,可以避开关联维无标度区间确定这一问题。根据暂态电能质量信号在不同扰动下其关联积分曲线所呈现出的特有形态特征,将关联积分曲线作为扰动识别的特征量。不同扰动信号的关联积分曲线区别较大,直观明了。该方法操作简单方便,可以省去烦琐的数值分析,且具有较高的精确度和实用性。对几种典型的暂态扰动信号进行识别和分类,仿真结果证明了其有效性和优越性。

Transient power quality disturbance classification based on chaos-correlation-integral

Based on time-series reconstruction, correlation integral curve can fully reflect the disturbance changes in the time series, and as the disturbance recognition feature, it can avoid the problem of determining the scale free zone in correlation dimension analysis. According to the fact that correlation integral curve of transient power quality signals under different disturbances could show unique morphological feature, the correlation integral curve is used as the characteristic quantity for disturbance recognition. The correlation integral curves of different disturbance signals could be distinguished more intuitively and obviously. This new method is simple and convenient to operate without using tedious numerical analysis, and has high accuracy and practicality. The recognition and classification of several typical disturbance signals were conducted; and the simulation results prove the effectiveness and superiority of the proposed method.