Engineering Center for Intelligent Energy Technology CTGU
针对噪声环境下暂态电能质量扰动检测困难的问题,文中提出了一种基于小波模极大值(Wavelet Modulus Maximum,WMM)与分层自适应阈值函数(Hierarchical Adaptive Threshold Function,HATF)相结合的检测方法(WMM+HATF)。首先为了有效对扰动信号降噪,即保证降噪后信号的平滑度以及保留突变点信息,采用自适应调节的HATF,该函数在阈值处和小波域内均可导,避免了传统与其他改进阈值函数不能或过度降噪的缺陷。其次,基于WMM通过细节系数的模极大值点位置对降噪后的暂态电能质量扰动进行定位。基于含噪的单一和复合扰动信号仿真及对比分析可见：HATF降噪优势明显,WMM+HATF通用性好,定位准确率高。
Aiming at the difficulty of detecting transient power quality disturbances in noisy environments,this paper proposes a detection method based on the combination of Wavelet Modulus Maximum and Hierarchical Adaptive Threshold Function. Firstly,in order to effectively reduce the noise of the disturbance signal,ensure the smoothness of the signal after noise reduction and retain the mutation point information,the adaptively adjusted HATF is adopted. The function is derivable at the threshold and in the wavelet domain,avoiding the defect that traditional or improved threshold functions cannot or excessively de-noising. Secondly,based on the WMM method,the transient power quality disturbance after noise reduction is located by the position of the modulus maximum point in the detail coefficient. Based on the simulation and comparative analysis of noisy single and composite disturbance signals,it can be seen that HATF has obvious advantages in noise reduction,and WMM+HATF has good versatility and high positioning accuracy.