混凝土在开裂瞬间由于裂纹表面电荷的振荡产生电磁信号。针对电磁信号容易受环境噪声的影响，信噪比低的问题，提出一种混凝土开裂电磁信号的去噪方法。文中给出一种新的复合判定指数作为灰狼算法(grey wolf algorithm, GWO)的优化目标，确定变分模态分解（variational mode decomposition，VMD）的最优模态分量个数和惩罚因子。对原始电磁信号进行分解，通过峭度原则选取适合的模态分量。结合小波去噪（wavelet transform， WT）对信号进行重构，得到去噪后的电磁信号。仿真及实验结果表明：与传统电磁信号去噪方法相比，文中方法处理信号的信噪比更高，均方差更低，波形相似度更高，对非平稳混凝土开裂电磁信号的适应能力更强。
英文摘要:
In the moment of concrete cracking, electromagnetic signals are generated due to the oscillation of surface charges on the cracks. Aiming at the issue of electromagnetic signals being susceptible to environmental noise interference and having a low signal-to-noise ratio, this paper presents a denoising method for electromagnetic signals generated during concrete cracking. A novel composite criterion is introduced as the optimization objective for the grey wolf algorithm (GWO). This criterion is used to determine the optimal number of modes and the penalty factor for variational mode decomposition (VMD). Subsequently, the original electromagnetic signal is decomposed, and suitable modes are selected based on the kurtosis criterion. Wavelet transform (WT) is employed to reconstruct the signal, resulting in a denoised electromagnetic signal. Simulation and experimental results demonstrate that, in comparison to traditional denoising methods for electromagnetic signals, the proposed approach yields a higher signal-to-noise ratio, lower mean squared error, and greater waveform similarity. This method exhibits stronger adaptability for denoising non-stationary electromagnetic signals generated during concrete cracking.
