LiDAR Applications in Structural Health Monitoring of Cable-Stayed Bridges: A Systematic Review Nain Dhaniarti Raharjo (a*), Lalu Muhamad Jaelani (b)
a) Department of Geomatics Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia
b) Department of Geomatics Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia
Abstract
Structural Health Monitoring (SHM) is increasingly being recognized as an important area for monitoring the structural health and safety of large structures such as cable-stayed bridges under the influence of different loading scenarios and structural vibrations. This in-depth review of literature aims to investigate the use of Light Detection and Ranging (LiDAR) technology focusing on structural health monitoring (SHM) of cable-stayed bridges. The aim of this review is to analyze the LiDAR for geometric mapping, deformation monitoring, and the role of LiDAR in numerical models and machine learning. The study is a PRISMA compliant compilation of a variety of studies. There are still challenges remain including data validation, ambient noise, and integration of a real-time system into an operational system. It is important that these issues be considered as part of the initial health review for new, LiDAR-based bridge applications in order to enhance maintenance strategies. has become increasingly important in managing the structural integrity and safety of large structures, such as cable-stayed bridges, under a variety of loading conditions and structural actions. This SLR targets Light Detection and Ranging (LiDAR) applied for structural health monitoring (SHM) of cable-stayed bridges. In accordance with the PRISMA guidelines, the review integrates the results obtained in several works, performing a compilation in order to contribute to evaluate that LiDAR for geometric mapping, deformation detection and its connection with numerical models and machine learning. However, there are still challenges such as data validation, environmental noise and real-time integration into a working system. Early health monitoring of new LiDAR applications to bridges needs to solve these problems and to help the better maintenance.
