Feature Extraction and Motion Tracking of Planar Fillet Weld Seams Based on 3D Point Cloud

doi:10.12068/j.issn.1005-3026.2025.20239074

Abstract

Abstract:

A feature extraction and trajectory planning strategy for planar fillet welds based on 3D point cloud was proposed to solve the automatic identification of weld seams and automatic robot tracking welding. Firstly， the workpiece to be welded was extracted based on the difference point cloud segmentation method， and the point cloud pre-processing was performed. Secondly， in order to obtain the feature points of the weld seam， the workpiece structure segmentation feature extraction algorithm was proposed. Then a path fitting method based on NURBS curves was fitted. Finally， a robot position estimation method for welding points was proposed to obtain the position of each path point for welding. This strategy is applicable to the weld seams of straight lines and various planar curves. The experimental results showed that the strategy can accurately extract the position of the fillet weld seam and generate the required position of track points， with the maximum error of each axis controlled within 1 mm and the total time consumed no more than 18 s， which provides a valuable reference for efficient automated welding.

Key words: 3D point cloud, fillet weld seam, feature extraction, position estimation, automatic welding

CLC Number:

TP 242

Hai-bin WU, Wu-kai HUANG. Feature Extraction and Motion Tracking of Planar Fillet Weld Seams Based on 3D Point Cloud[J]. Journal of Northeastern University(Natural Science), 2025, 46(6): 93-101.

Figures/Tables 14

Fig.1 Typical workpieces for planar fillet weld seams

Fig.2 Overall scheme for the fillet weld seam extraction system

Fig.3 Effect of point cloud filtering algorithm

Fig.4 Effect of differential point cloud segmentation algorithm

Fig.5 Schematic diagram of plane curve fillet weld seam extraction

Fig.6 Schematic diagram of the edge detection algorithm

Fig.7 Weld path point extraction

Fig.8 Position estimation diagram

Fig.9 Experimental platform for fillet weld seam extraction

Table 1 Measurement error of simple straight line weld seam under different pre-processing algorithms mm

误差类型	本文算法	传统算法
X轴最大误差	0.514	0.718
Y轴最大误差	0.476	0.606
Z轴最大误差	0.458	0.801
X轴平均误差	0.233	0.237
Y轴平均误差	0.088	0.219
Z轴平均误差	0.080	0.120
平均距离偏差	0.287	0.388

Fig.10 Experimental effect of various workpieces

Table 2 Measurement errors for different fillet welds

焊缝类型	ME/mm			RMSE/mm
焊缝类型	X轴	Y轴	Z轴	X轴	Y轴	Z轴
简单直线	0.514	0.476	0.458	0.275	0.113	0.101
平面圆柱	0.944	0.570	0.653	0.323	0.189	0.198
平面折线	0.927	0.893	0.869	0.326	0.570	0.407
平面曲线	0.886	0.823	0.815	0.314	0.558	0.396
平面曲面	0.876	0.802	0.811	0.325	0.512	0.384

Table 3 Running time of pre-processing and artifact

步骤名称	运行时间/s
预处理	7.015
工件提取	8.359

Table 4 Algorithm running time after workpiece

焊缝类型	运行时间/s
简单直线	0.804
平面圆柱角接	0.594
平面折线	2.118
平面曲线	2.026
平面曲面	1.954

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