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Multiple Pipe Systems01:21

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Multipipe systems consist of complex configurations of interconnected pipes designed to transport fluids efficiently across intricate networks. They are essential in engineering applications requiring precise control over flow distribution, pressure, and head loss. They are categorized into series, parallel, loop, and network configurations, each distinguished by unique flow characteristics and applications.
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Automatic Detection and Modeling of Underground Pipes Using a Portable 3D LiDAR System.

Ahmad K Aijazi1, Laurent Malaterre1, Laurent Trassoudaine1

  • 1Institut Pascal, UMR 6602, Université Clermont Auvergne, CNRS, SIGMA Clermont, F-63000 Clermont-Ferrand, France.

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Summary
This summary is machine-generated.

This study presents an automated 3D mapping solution for underground pipes in open trenches. The system achieves high accuracy in registration, segmentation, and modeling, proving effective for infrastructure projects.

Keywords:
3D point cloudLiDARautomatic detectionpipesportable 3D scanning systemsegmentation

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Area of Science:

  • Geomatics Engineering
  • Computer Vision
  • Geographic Information Systems

Background:

  • Accurate underground infrastructure mapping is crucial for urban planning, construction, and safety.
  • Existing methods face technical and operational challenges, especially during installation or renovation.

Purpose of the Study:

  • To develop a portable, automated system for 3D mapping and modeling of underground pipe networks in open trenches.
  • To provide a solution for real-time infrastructure data acquisition during installation.

Main Methods:

  • Utilizing a portable scanner to capture 3D trench data.
  • Employing a modified global Iterative Closest Point (ICP) algorithm for 3D scan registration.
  • Applying fuzzy C-means clustering for pipe segmentation and a nested M-estimator Sampling Consensus (MSAC) algorithm for pipe modeling.

Main Results:

  • Achieved an overall registration error of less than 7%.
  • Demonstrated an overall segmentation accuracy of 85% for pipe-like structures.
  • Reported an overall modeling error of less than 5% for the underground pipe network.

Conclusions:

  • The proposed automated system is effective and suitable for 3D mapping and modeling of underground pipes in open trenches.
  • The method offers a robust solution for infrastructure projects requiring accurate spatial data.
  • The system's performance on real-world data validates its practical applicability.