基于混沌分形理论的故障电弧诊断方法研究

Arc fault diagnosis method based on chaos and fractal theories

引入混沌分形理论,从混沌空间域角度分析故障电弧的内在演化规律和电弧特性,提出一种基于混沌分形理论的故障电弧诊断方法。通过重构相空间和盒维数、关联维数、最大Lyapunov指数等对电弧电流的混沌分形特性进行定性、定量分析,形成电弧的空间域特征向量,构建故障电弧诊断模型。针对低压用电系统中空气压缩机、开关电源等负载线路,对故障电弧发生前后线路电流的混沌分形特性进行分析,验证方法的有效性。实验结果可见,线路电流的分形结构和混沌分形特征参数随着电气线路运行状态的变化而有所差异,且与线路负载性质有关。基于此特征建立的电弧诊断模型电弧检测的准确率超过90%,同时当线路正常运行时,诊断模型能够实现负载辨识,辨识率可达到90%。

Based on the chaos fractal theories,the characteristics and the internal evolution of arc fault were analyzed,and an arc fault diagnosis method was put forward.The chaos and fractal characteristics of arc were qualitatively and quantitatively analyzed by using the reconstruction phase space theory and chaotic and fractal feature parameters,such as box dimension,correlation dimension and Lyapunov index.Then the spatial domain eigenvectors and the diagnosis model of arc fault were constructed.The chaos and fractal characteristics of current pre-and post-arc fault were analyzed to verify validity for low-voltage power systems with air compressors and switching power supplies.Experimental results show that the fractal structures and the characteristic parameters of chaotic fractal of current are different in the change of running state and load.Different evolution trend between normal current and arc current,and the chaos and fractal characteristic parameters show different rules.The accuracy of arc diagnosis model based on this feature is more than 90%.Meanwhile,the load identification rate is more than 90% under normal operation.