3D reconstruction of welded joints from an unordered point cloud

Various fatigue assessment methods have been proposed to achieve more accurate fatigue life estimations over the past decades. However, most of these methods are proposed and developed based on idealized geometries of welded joints. Even slight variations in geometry details will significantly influence the precision of fatigue life estimations. Both global and local geometries should be taken into consideration to address this challenge. In this poster, we present a framework for 3D reconstruction of welded joints from an unordered point clouds. A high-resolution laser scanner was used to obtain the point cloud from a cruciform welded joint with capturing the geometry details. The point cloud was then sliced along the welding direction to obtain a series of sub-volume point clouds. In each sub-volume, the point cloud was ordered by using KD-Tree and then fitted with a quadratic B-Spline curve. 2D cross section models along the welding direction were reconstructed as an intermediate step. Based on the reconstructed 2D models, a 3D model was finally reconstructed using iso-surface extraction method. Finite element simulations were conducted on the reconstructed 3D model. The proposed framework supports stress analysis and fatigue assessment based on the as-built geometries of welded joints. Future work will focus on evaluations of different fatigue assessment methods with the aid of this framework.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-24
DOI
https://doi.org/10.5281/zenodo.15077020
Primary Topic
Optical measurement and interference techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

3D reconstruction of welded joints from an unordered point cloud

Zenodo (CERN European Organization for Nuclear Research)
Optical measurement and interference techniques
article

3D reconstruction of welded joints from an unordered point cloud

article en

Abstract

Various fatigue assessment methods have been proposed to achieve more accurate fatigue life estimations over the past decades. However, most of these methods are proposed and developed based on idealized geometries of welded joints. Even slight variations in geometry details will significantly influence the precision of fatigue life estimations. Both global and local geometries should be taken into consideration to address this challenge. In this poster, we present a framework for 3D reconstruction of welded joints from an unordered point clouds. A high-resolution laser scanner was used to obtain the point cloud from a cruciform welded joint with capturing the geometry details. The point cloud was then sliced along the welding direction to obtain a series of sub-volume point clouds. In each sub-volume, the point cloud was ordered by using KD-Tree and then fitted with a quadratic B-Spline curve. 2D cross section models along the welding direction were reconstructed as an intermediate step. Based on the reconstructed 2D models, a 3D model was finally reconstructed using iso-surface extraction method. Finite element simulations were conducted on the reconstructed 3D model. The proposed framework supports stress analysis and fatigue assessment based on the as-built geometries of welded joints. Future work will focus on evaluations of different fatigue assessment methods with the aid of this framework.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 55%
Optical measurement and interference techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.