Automated Processing and Deviation Analysis of 3D Pipeline Point Clouds Based on Geometric Features
Shaofeng Jin, Kangrui Fu, Chengzhen Yang, Huanhuan Rui

TL;DR
This paper introduces an automated system for analyzing 3D pipeline point clouds in aircraft engines, improving measurement accuracy and efficiency.
Contribution
The study introduces a unified framework with automated algorithms and a three-dimensional extended DP algorithm for efficient pipeline inspection.
Findings
The framework automatically detects five pipeline deviations with high accuracy.
The system improves processing efficiency and measurement reliability for complex pipelines.
The platform offers intuitive visualization and report generation for inspection tasks.
Abstract
To meet the strict non-contact measurement requirements for the assembly of aircraft engine pipelines and to overcome the limitations of the traditional three-dimensional laser scanning workflow, this study proposes an automated pipeline point cloud processing and deviation analysis framework. Through a standardized three-dimensional laser scanning procedure, high-resolution pipeline point clouds are obtained and preprocessed. Based on the geometric characteristics of the pipeline, automated algorithms for point cloud feature segmentation, axis extraction, and model registration are developed. Particularly, the three-dimensional extended Douglas–Peucker (DP) algorithm is introduced to achieve efficient point cloud downsampling while retaining necessary geometric and structural features. These algorithms are fully integrated into a unified software platform, supporting one-click…
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Taxonomy
Topics3D Surveying and Cultural Heritage · Optical measurement and interference techniques · Advanced Measurement and Metrology Techniques
