基于VMD的相控阵超声信号降噪方法研究

针对超声检测在钢板板边和轮对可能存在漏检的问题，采用相控阵超声检测技术对钢板板边裂纹缺陷和轮对孔缺陷进行成像检测；针对钢板和轮对缺陷散射信号信噪比低的问题，提出了一种参数优化的变分模态分解（VMD）算法，避免了人为主观影响，通过选择对应频带的本征模态函数（IMF）分量表征原始信号特征，并通过比较VMD分解后各本征模态函数（IMF）分量与原始信号的信噪比与均方根误差来评价（VMD）算法的效果，最终实现缺陷成像检测。实验结果表明：与原始信号相比，该方法处理后的缺陷信号具有较好的保真度，信噪比与平滑度，均方根误差降低，不易出现模态混叠现象，有良好的分解效果。处理后成像结果更为清晰，缺陷的大小、位置及形状都能够完整展示出来，可以实现孔缺陷和裂纹缺陷的定位检测。

Research on Noise Reduction Method of Phased Array Ultrasonic Signal Based on VMD

Aiming at the problem that ultrasonic detection may be missed on the edges and wheelsets of steel plates, phased array ultrasonic detection technology is used to image and detect crack defects and wheel-to-wheel hole defects of steel plates, and for the problem of low signal-to-noise ratio of steel plate and wheel pair defect scattering signals, a parameter-optimized variational modal decomposition (VMD) algorithm is proposed, which avoids human subjective influence and characterizes the original signal characteristics by selecting the eigenmodal function (IMF) component of the corresponding frequency band. The effect of the (VMD) algorithm is evaluated by comparing the signal-to-noise ratio and root mean square error of each eigenmodal function (IMF) component of the VMD decomposition with the signal-to-noise ratio of the original signal, and finally the defect imaging detection is realized. The experimental results show that compared with the original signal, the defective signal processed by the method has good fidelity, signal-to-noise ratio and smoothness, the rms error is reduced, and the modal aliasing phenomenon is not easy to occur, and there is a good decomposition effect. After processing, the imaging results are clearer, and the size, position and shape of the defects can be fully displayed, which can realize the positioning and detection of hole defects and crack defects.