Research on deformation detection algorithm of cold water pipe based on improved point cloud registration

Nana Zhao; Yunsong Feng; Yexin Huang; Yucheng Wang

doi:10.1117/12.3033187

5 July 2024 Research on deformation detection algorithm of cold water pipe based on improved point cloud registration

Nana Zhao, Yunsong Feng, Yexin Huang, Yucheng Wang

Proceedings Volume 13184, Third International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024); 131846T (2024) https://doi.org/10.1117/12.3033187
Event: 3rd International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024), 2024, Kuala Lumpur, Malaysia

Abstract

An improved Gaussian mixture model-based adaptive point cloud registration algorithm is proposed to address the challenge of diverse and random surface appearances that hinder quick and accurate detection of deformations in coldwater pipes. The algorithm uses improved Gaussian mixture model to assign probability values for point-to-surface distances of the input point cloud, optimizes the likelihood function, and uses an adaptively adjusted parameter randomized sampling consensus algorithm to obtain the transformation matrix between the input point cloud and the design model point cloud. After feature extraction between the registered input point cloud and the design model point cloud, points exceeding a threshold are extracted separately based on normal vector features to detect deformities in the pipes. Experimental results demonstrate that this improved algorithm can rapidly and accurately detect various types of deformations in cold-water pipes with deformations less than 2mm, achieving a detection accuracy of over 99%.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Nana Zhao, Yunsong Feng, Yexin Huang, and Yucheng Wang "Research on deformation detection algorithm of cold water pipe based on improved point cloud registration", Proc. SPIE 13184, Third International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024), 131846T (5 July 2024); https://doi.org/10.1117/12.3033187

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KEYWORDS

Point clouds

Pipes

Deformation

Detection and tracking algorithms

Matrices

Mixtures

Data modeling

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