基于多元变分模态分解与改进小波阈值的矿用电缆局放去噪方法

Mine cable partial discharge denoising method based on multivariate variational mode decomposition and improved wavelet threshold

  • 摘要: 矿用电缆的绝缘状态对矿井供电系统的稳定运行起着重要作用,局部放电在线监测是电缆绝缘状态监测的重要手段。针对矿用电缆局放信号极易淹没于现场白噪声与周期性窄带干扰中,以及降噪方法适应性普遍不强等问题,提出了基于多元变分模态分解与改进小波阈值的局放去噪方法。首先,以最小平均包络熵作为适应度函数,采用麻雀搜索算法实现多元变分模态分解模态数和惩罚因子的自动寻优,从而以分解出最大确定性程度的局放特征信号为目标,准确分解局放含噪信号。其次,计算各本征模态函数的峭度值,区分局放主导分量与噪声主导分量,利用维纳滤波可通过局部方差自适应调节滤波效果的特性,准确提取局放主导分量中的局放特征信号,通过3σ准则归类局放特征信号为粗大误差,反向抑制噪声主导分量中的高斯白噪声与窄带干扰信号,将局放主导分量与噪声主导分量进行重构得到局放重构信号。最后,构建指数衰减型小波阈值函数,该阈值函数在克服硬阈值函数的不连续性与软阈值函数的恒定偏差的基础上,能够快速逼近硬阈值函数,利用新型改进小波阈值算法对局放重构信号进行去噪,得到局放去噪信号。将该方法与常见的几种方法进行比较,结果表明,该方法对仿真局放信号与实测局放信号均具有较好的降噪效果,且算法运行效率表现良好。

     

    Abstract: The insulation state of the mine cable plays an important role in the stable operation of the mine power supply system. Partial discharge on-line monitoring is an important means of cable insulation state monitoring. Aiming at the problems that the mine cable partial discharge signal is easily submerged in the field white noise and periodic narrowband interference, and the adaptability of the noise reduction method is generally not strong, a partial discharge denoising method based on multivariate variational mode decomposition and improved wavelet threshold is proposed. Firstly, the minimum average envelope entropy is used as the fitness function, and the sparrow search algorithm is used to realize the automatic optimization of the decomposition mode number and penalty factor of multivariate variational mode decomposition. Secondly, the kurtosis value of each intrinsic mode function is calculated, and the partial discharge dominant component and the noise dominant component are distinguished. Using the characteristics of Wiener filtering that can adaptively adjust the filtering effect through local variance, the partial discharge characteristic signal in the partial discharge dominant component is accurately extracted. The partial discharge characteristic signal is classified as gross error by 3 σ criteria, and the Gaussian white noise and narrow-band interference signal in the noise dominant component are inversely suppressed. The partial discharge dominant component and the noise dominant component are reconstructed to obtain the partial discharge reconstruction signal. Finally, the exponential decay wavelet threshold function is constructed, which can quickly approximate the hard threshold function on the basis of overcoming the discontinuity of the hard threshold function and the constant deviation of the soft threshold function. The new improved wavelet threshold algorithm is used to denoise the partial discharge reconstruction signal, and the partial discharge denoising signal is obtained. The proposed method is compared with several common methods. The results show that the proposed method has a good noise reduction effect on the simulated partial discharge signal and the measured partial discharge signal, and the operation efficiency of the algorithm is good.

     

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