安全、健康和环境2025，Vol.25Issue(10)：19-27,9.DOI:10.3969/j.issn.1672-7932.2025.10.003
融合点云局部几何特征与双阶段聚类的点蚀检测方法
A Pitting Detection Method Integrating the Local Geometric Features of Point Clouds and Two-Stage Clustering
摘要
Abstract
To address the challenge of quantitative evaluation of pitting corrosion in petrochemical equip-ment,a pitting corrosion detection method integrating the local geometric features of point clouds and a two-stage clustering algorithm is proposed.High-precision point cloud data of the equipment surface is obtained u-sing laser structured light scanning technology.After preprocessing the point cloud data through noise filtering and data downsampling,local geometric features such as the normal vector and curvature of each point are ex-tracted,and screen out the combinations that are scensitive to pitting corrosion.The detection workflow first em-ploys K-Means clustering for coarse segmentation of pitting and non-pitting regions,followed by rapid Euclidean clustering to precisely locate individual pitting units and calculate their depths.The pitting edge contour is ex-tracted through secondary clustering,and the precise quantification of the opening area is achieved based on the convex hull algorithm and ellipse fitting.The experimental results showed that the average absolute error for measuring the pitting depth of 304/316 stainless steel using this method was 0.019 mm,and the maximum error was controlled within 0.047 mm.It can synchronously output multi-dimensional parameters,including pitting density,opening size,and depth distribution,effectively solving the problems of low efficiency in traditional manual measurement and the lack of depth information in two-dimensional images.关键词
点蚀/三维扫描/点云/局部几何特征/无监督聚类Key words
pitting corrosion/three-dimensional scanning/point cloud/local geometric features/unsuper-vised clustering分类
金属材料引用本文复制引用
申志远,杨锋,刘媛双,任刚,吕伟,屈定荣,周昊,李杰,陈文武..融合点云局部几何特征与双阶段聚类的点蚀检测方法[J].安全、健康和环境,2025,25(10):19-27,9.基金项目
国家重点研发计划(2022YFC3004502),氯碱化工生产装备隐蔽性损伤检测技术及装备研发 （2022YFC3004502）
中国石油化工股份公司科技部项目(325012),非平面点蚀结构光三维检测技术及腐蚀穿孔预测方法研究. （325012）
