作者：王勇勇¹, 孙全德², 王恪典^1,3, 原鹏¹

作者单位：1. 新疆大学机械工程学院，新疆 乌鲁木齐 830047;
2. 新疆维吾尔自治区特种设备检验研究院，新疆 乌鲁木齐 830047;
3. 西安交通大学机械工程学院，陕西 西安 710049

关键词：角焊缝;涡流热成像;图像处理;缺陷检测

摘要：

压力管道中由于部分焊缝结构复杂、所处位置特殊，导致缺陷检测漏检率较大，对压力管道安全运行带来严重隐患。该文采用电涡流热成像技术研究带腐蚀层角焊缝表面裂纹检测的可行性。实验通过对T型角焊缝两道自然裂纹的检测，证明该方法对角焊缝表面裂纹检测有效。为进一步提高涡流热成像技术的检测灵敏度，利用主成分分析算法增强原始图像中的缺陷特征，减小不均匀加热的影响。结果表明：通过电涡流热成像与主成分分析相结合，可以实现角焊缝腐蚀金属表面自然裂纹的检测。

Research on eddy current thermal imaging test of surface cracks in fillet welds
WANG Yongyong¹, SUN Quande², WANG Kedian^1,3, YUAN Peng¹
1. College of Mechanical Engineering, Xinjiang University, Urumqi 830047, China;
2. Xinjiang Uygur Autonomous Region Special Equipment Inspection and Research Institute, Urumqi 830047, China;
3. College of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710049, China
Abstract: Due to the complex structure and special location of some welds in the pressure pipeline, the defect detection rate is relatively high, which brings serious hidden trouble to the safe operation of the pressure pipeline. In this paper, eddy current thermal imaging technology is used to study the feasibility of detecting hidden cracks on the weld surface of corroded layer. The experimental results show that the method is effective for the detection of natural cracks in T-fillet weld with corroded layer. In order to further improve the detection sensitivity of eddy current thermal imaging technology, the principal component analysis feature extraction algorithm is used to enhance the defect features in the original image and reduce the influence of non-uniform heating. The results show that the eddy current thermal imaging and principal component analysis can be used to detect the natural cracks on the corroded metal surface of diagonal welds.
Keywords: fillet weld;eddy current thermal imaging;image processing;defect detection
2021, 47(5):11-15  收稿日期: 2020-07-30;收到修改稿日期: 2021-08-31
基金项目: 新疆维吾尔自治区自然基金项目（2020D01A104）
作者简介: 王勇勇(1994-),男,山东德州市人,硕士研究生,专业方向为红外无损检测
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