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随着输电电压等级的提高,电晕放电已成为影响高压、特高压输电线路安全稳定运行的重要因素。鉴于此,提出了基于经验模式分解(empirical mode decomposition,EMD)的电晕放电辐射信号阈值降噪处理方法,首先利用EMD算法对采集到的电晕放电辐射信号做分解处理,得到不同的基本模态分量,然后利用阈值函数和给定阈值对各分量做降噪处理,并对处理后的分量重构,得到降噪后的信号。研究结果表明:与小波降噪和EMD时空降噪相比,基于EMD的阈值降噪方法不存在基函数选取和分解层数选取等问题,其降噪过程是完全由信号特征决定的自适应降噪,同时该方法保留了小波降噪中对各分量进行阈值处理来降噪的优点,并且在对信号的降噪过程中去除了可能存在于信号中的趋势项干扰,因而该方法更有利于对电晕放电辐射信号的降噪处理。
With the increase of transmission voltage level, corona discharge has become an important factor that affects the safe and stable operation of high voltage and UHV transmission lines. In view of this, a threshold noise reduction method based on empirical mode decomposition (EMD) is proposed. Firstly, EMD algorithm is used to decompose corona discharge radiation signals to obtain different basic modes Then the threshold function and the given threshold are used to denoise each component, and the processed components are reconstructed to obtain a denoised signal. The results show that compared with wavelet denoising and EMD spatio-temporal noise reduction, the EMD-based threshold denoising method does not exist such as the selection of basis functions and the number of decomposition layers, and the noise reduction process is adaptively controlled by signal characteristics This method preserves the advantage of noise reduction by thresholding the components in the wavelet denoising and removes the trend term interference that may exist in the signal during noise reduction, Noise reduction of corona discharge radiation signal.