基于小波理论和HT-LMD的电能质量扰动检测方法

针对含噪声的暂态电能质量扰动检测问题,提出了一种基于小波自适应去噪的改进HT-LMD(HilbertHuang and Local Mean Decomposition)分解检测方法。分析了局部均值分解检测扰动的优缺点以及噪声对LMD检测方法的影响,提出了采用小波分解与重构和自适应阈值技术以及基于正交性判据(Orthogonality Criterion,OC)新的HT-LMD检测方法。小波自适应去噪技术能减弱噪声对LMD分解影响,正交性判据能减少分解的迭代次数。典型暂态电能质量扰动模拟信号和实测信号的检测结果表明,所提方法能在有效提高LMD方法检测电能质量扰动效果同时很好地保留原有暂态扰动信号奇异性特征,提高了检测和定位精度。

Power quality disturbance detection method based on HT-LMD and wavelet theory

Aiming at the transient power quality disturbance detection problem under noisy conditions , this paper pro-poses an improved HT-LMD ( Hilbert Huang and local mean decomposition ) decomposition detection method by using adaptive wavelet denoising techniques .After analyzing the advantages and disadvantages of local mean decomposition and the influence of noise , a new HT-LMD detection method using wavelet decomposition and reconstruction , adaptive threshold technology , and the orthogonality of criterion ( orthogonality criterion , OC) is presented .Adaptive wavelet denoising technique abates the noise impact on the LMD decomposition , and orthogonality criterion method reduces the number of decomposition iterations .The results from the typical transient power quality disturbance simulation sig-nals and the detection of measured signals show that the proposed method improves the LMD ability in detection of power quality disturbance and retains the singularity characteristics of the original transient disturbance signals , which help boost locating and detection precision .