Displacement Estimation Performance of a Cost-Effective 2D-LiDAR-Based Retaining Wall Displacement Monitoring System

Monitoring the displacement of retaining walls is essential for maintaining their stability. Traditional displacement monitoring by inclinometer is costly and time-consuming, owing to the need for manual measurements. A recently developed 2D-LiDAR-based retaining wall displacement monitoring system...

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Main Authors: Jun-Sang Kim, Young Suk Kim
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Remote Sensing
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Online Access:https://www.mdpi.com/2072-4292/16/24/4644
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author Jun-Sang Kim
Young Suk Kim
author_facet Jun-Sang Kim
Young Suk Kim
author_sort Jun-Sang Kim
collection DOAJ
description Monitoring the displacement of retaining walls is essential for maintaining their stability. Traditional displacement monitoring by inclinometer is costly and time-consuming, owing to the need for manual measurements. A recently developed 2D-LiDAR-based retaining wall displacement monitoring system offers advantages over traditional methods, such as easy installation and dismantling, as well as the cost-effective monitoring of three-dimensional displacement compared to terrestrial laser scanners (TLSs). However, a previous study did not account for the actual deformation of the retaining wall, potentially compromising the reliability of the displacement estimation. This study aims to assess the displacement estimation performance of the system by using a retaining wall that simulates real-world deformations, considering key parameters related to the displacement estimation algorithm and the quality of point cloud data. Using the multiple model-to-model cloud comparison algorithm and a developed algorithm for filtering duplicate point cloud data, the system’s average performance across various deformation types yielded mean absolute error (MAE), <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi mathvariant="normal">M</mi><mi mathvariant="normal">A</mi><mi mathvariant="normal">E</mi></mrow><mrow><msub><mrow><mi>D</mi></mrow><mrow><mi>m</mi><mi>a</mi><mi>x</mi></mrow></msub></mrow></msub></mrow></semantics></math></inline-formula>, and compound error values of 1.7, 2.2, and 2.0 mm, respectively. The results demonstrate that even a 2D-LiDAR, which has lower precision than a TLS, can effectively monitor retaining wall displacement through the post-processing of point cloud data.
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spelling doaj-art-73ea19729689413cb80992c0322c70dc2025-08-20T02:01:21ZengMDPI AGRemote Sensing2072-42922024-12-011624464410.3390/rs16244644Displacement Estimation Performance of a Cost-Effective 2D-LiDAR-Based Retaining Wall Displacement Monitoring SystemJun-Sang Kim0Young Suk Kim1Industrial Science and Technology Research Institute, Inha University, Incheon 22212, Republic of KoreaDepartment of Architectural Engineering, Inha University, Incheon 22212, Republic of KoreaMonitoring the displacement of retaining walls is essential for maintaining their stability. Traditional displacement monitoring by inclinometer is costly and time-consuming, owing to the need for manual measurements. A recently developed 2D-LiDAR-based retaining wall displacement monitoring system offers advantages over traditional methods, such as easy installation and dismantling, as well as the cost-effective monitoring of three-dimensional displacement compared to terrestrial laser scanners (TLSs). However, a previous study did not account for the actual deformation of the retaining wall, potentially compromising the reliability of the displacement estimation. This study aims to assess the displacement estimation performance of the system by using a retaining wall that simulates real-world deformations, considering key parameters related to the displacement estimation algorithm and the quality of point cloud data. Using the multiple model-to-model cloud comparison algorithm and a developed algorithm for filtering duplicate point cloud data, the system’s average performance across various deformation types yielded mean absolute error (MAE), <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi mathvariant="normal">M</mi><mi mathvariant="normal">A</mi><mi mathvariant="normal">E</mi></mrow><mrow><msub><mrow><mi>D</mi></mrow><mrow><mi>m</mi><mi>a</mi><mi>x</mi></mrow></msub></mrow></msub></mrow></semantics></math></inline-formula>, and compound error values of 1.7, 2.2, and 2.0 mm, respectively. The results demonstrate that even a 2D-LiDAR, which has lower precision than a TLS, can effectively monitor retaining wall displacement through the post-processing of point cloud data.https://www.mdpi.com/2072-4292/16/24/4644retaining wallstructural health monitoringLiDARdisplacementperformance evaluation
spellingShingle Jun-Sang Kim
Young Suk Kim
Displacement Estimation Performance of a Cost-Effective 2D-LiDAR-Based Retaining Wall Displacement Monitoring System
Remote Sensing
retaining wall
structural health monitoring
LiDAR
displacement
performance evaluation
title Displacement Estimation Performance of a Cost-Effective 2D-LiDAR-Based Retaining Wall Displacement Monitoring System
title_full Displacement Estimation Performance of a Cost-Effective 2D-LiDAR-Based Retaining Wall Displacement Monitoring System
title_fullStr Displacement Estimation Performance of a Cost-Effective 2D-LiDAR-Based Retaining Wall Displacement Monitoring System
title_full_unstemmed Displacement Estimation Performance of a Cost-Effective 2D-LiDAR-Based Retaining Wall Displacement Monitoring System
title_short Displacement Estimation Performance of a Cost-Effective 2D-LiDAR-Based Retaining Wall Displacement Monitoring System
title_sort displacement estimation performance of a cost effective 2d lidar based retaining wall displacement monitoring system
topic retaining wall
structural health monitoring
LiDAR
displacement
performance evaluation
url https://www.mdpi.com/2072-4292/16/24/4644
work_keys_str_mv AT junsangkim displacementestimationperformanceofacosteffective2dlidarbasedretainingwalldisplacementmonitoringsystem
AT youngsukkim displacementestimationperformanceofacosteffective2dlidarbasedretainingwalldisplacementmonitoringsystem