基于二维DFT的钢丝绳局部缺陷检测方法

漏磁检测方法广泛应用于钢丝绳无损检测场景中，但受检测环境和绳股结构影响，往往难以直接从漏磁信号中提取缺陷特征。文中提出一种基于二维离散傅里叶变换的局部缺陷检测方法，利用环形霍尔传感器阵列采集钢丝绳的径向漏磁场，采用通道均衡及通道插值方法将漏磁信号转换为二维漏磁图像进行处理。对漏磁图像进行二维离散傅里叶变换（Two-dimensional Discrete Fourier Transform, 2D-DFT），并采用2D-DFT分析其频域特征，通过设置滤波器抑制漏磁图像中的股波及其他低频噪声信号。最后设置阈值获取二值化图像，提升局部缺陷的对比度，提取损伤特征并定位损伤位置。与基于一维离散傅里叶变换及基于斜向重采样的处理方法的对比结果表明，该方法更能有效抑制漏磁图像中的股波噪声，提升处理速度，识别钢丝绳局部损伤位置，为钢丝绳的局部缺陷检测提供了一种新的解决途径。

A Local Flaw Detection Method for Metal Wire Ropes Based on Two-dimensional Discrete Fourier Transform

The magnetic flux leakage (MFL) detection method is widely used in nondestructive test scenarios of the metal wire rope. However, it is difficult to directly extract defect features from the MFL signals due to the influence of the detection environment and the rope strands structure. A local flaw (LF) detection method based on two-dimensional discrete Fourier transform (2D-DFT) is proposed in this paper. The annular Hall sensor array is used to collect radial MFL signals from the wire rope, which are converted into two-dimensional MFL images by channel equalization and interpolation. 2D-DFT is used to analyze the frequency domain characteristics of the MFL image, and the strand wave effects and other low-frequency noise in the MFL image are suppressed by filter. Finally, by setting a threshold, the 0-1 output method is employed to improve the contrast of local flaw, extract damage features and obtain the LF location. Compared with the processing methods based on one-dimensional discrete Fourier transform (1D-DFT) and oblique resampling, the proposed method can more effectively suppress the strand noise in the MFL image, improve the processing speed and identify the LF position of the wire rope, which provides a new solution to LF detection of wire ropes.