噪声信号的检测精度直接决定了电网非稳态畸变信号计量的准确性,为了提高噪声信号的检测精度,提出了一种基于小波变换与正弦曲线拟合的非稳态畸变噪声检测方法。首先利用小波变换对电网非稳态畸变信号进行分解与重构,得到基波信号,再通过傅里叶级数将重构得到的基波信号进行正弦拟合,最后通过非稳态畸变信号与正弦信号相减,得到噪声信号。以电网冲击信号模型和电网连续脉冲信号模型为例对本文方法进行验证。实验结果为:在不同分解层数之间,本文方法得到的基波信号、噪声信号与原始信号之间的相关系数始终都在0.95以上,均高于单独小波方法所得信号的相关系数,且受分解层数不同的影响更小,说明文中方法降低了检测精度受分解层数不同的影响,且具有更高的噪声检测精度。
The detection accuracy of noise signal directly determines the accuracy of grid non-stationary distortion sig- nal measurement. In order to improve the detection accuracy of noise signal, this paper presents a non-stationary dis- tortion noise detection method based on wavelet transform and sine curve fitting. First of all, the grid non-stationary distorted signals are decomposed and reconstructed by wavelet transform to obtain the fundamental signal, and then, the reconstructed fundamental signal is fitted by the Fourier series. The non-stationary distorted signal minus sine sig- nal is the non-stationary distortion noise signal. The method of this paper is validated by the models of the grid impact signal and the grid continuous pulse signal. The experimental results show that among the different decomposition lev- els, the correlation coefficient between the obtained fundamental signal, noise signal and the original signal is above 0.95, the correlation coefficient is higher than that of the wavelet transform method, and less affected by different de- composition levels. The results show that this method reduces the impact on the detection accuracy by different decom- position levels and has higher noise detection accuracy.