作者：邱忠超^1,2, 洪利¹, 蔡建羡¹, 姚振静¹, 高志涛¹

作者单位：1. 防灾科技学院电子科学与控制工程学院，河北 廊坊 065201;
2. 北京理工大学机械与车辆学院，北京 100081

关键词：漏磁检测;数学形态学;信号消噪;基线漂移

摘要：

漏磁检测是一种广泛应用于铁磁材料表面裂纹检测的磁性无损检测技术，漏磁信号的质量直接关系到裂纹定量识别的准确性和精度。针对漏磁信号的噪声特性，提出一种基于数学形态学滤波的漏磁信号预处理方法，即利用改进的中值滤波法剔除信号中的奇异点，采用多项式拟合法消除信号趋势项，使用形态滤波法对漏磁信号进行消噪处理。结果表明：该方法对漏磁信号中的干扰噪声具有较强的抑制能力，不仅剔除了漏磁信号中的干扰噪声，而且完整地保留原始信号的具体细节，提高降噪速度。

Research on magnetic flux leakage signal preprocessing method based on mathematical morphology filtering
QIU Zhongchao^1,2, HONG Li¹, CAI Jianxian¹, YAO Zhenjing¹, GAO Zhitao¹
1. School of Electronic Science and Control Engineering, Institute of Disaster Prevention, Langfang 065201, China;
2. School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China
Abstract: Magnetic flux leakage detection is an electromagnetic non-destructive testing method widely used to detect surface crack defects in ferromagnetic materials. The quality of magnetic flux leakage signals is directly related to the precision and accuracy of crack identification. Aiming at the noise characteristics of magnetic flux leakage signal, a preprocessing method of magnetic flux leakage signal based on mathematical morphology filtering is proposed. Firstly, the improved singular point in the signal is eliminated by the improved median filtering method, and then the signal trend term is eliminated by polynomial fitting method. Finally, the morphological filtering method is used to denoise the magnetic flux leakage signal. The results show that the proposed method has strong suppression ability for noise in the magnetic flux leakage signal. It not only removes the noise in the signal, but also preserves the details of the original signal and improves the noise reduction speed.
Keywords: magnetic flux leakage detection;mathematical morphology;signal denoising;baseline drift
2020, 46(3):1-5  收稿日期: 2019-07-05;收到修改稿日期: 2019-09-22
基金项目: 防灾科技学院教育研究与教学改革项目（JY2019B02）；国家重点研发计划项目（2018YFC1503801）；河北省高等学校科学技术研究项目（Z2019017）
作者简介: 邱忠超(1987-),男,山东济宁市人,讲师,博士,专业方向为漏磁检测、磁记忆检测
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