Computer Vision-Based Bridge Inspection and Monitoring: A Review

Abstract

Bridge inspection and monitoring are usually used to evaluate the status and integrity of bridge structures to ensure their safety and reliability. Computer vision (CV)-based methods have the advantages of being low cost, simple to operate, remote, and non-contact, and have been widely used in bridge inspection and monitoring in recent years. Therefore, this paper reviews three significant aspects of CV-based methods, including surface defect detection, vibration measurement, and vehicle parameter identification. Firstly, the general procedure for CV-based surface defect detection is introduced, and its application for the detection of cracks, concrete spalling, steel corrosion, and multi-defects is reviewed, followed by the robot platforms for surface defect detection. Secondly, the basic principle of CV-based vibration measurement is introduced, followed by the application of displacement measurement, modal identification, and damage identification. Finally, the CV-based vehicle parameter identification methods are introduced and their application for the identification of temporal and spatial parameters, weight parameters, and multi-parameters are summarized. This comprehensive literature review aims to provide guidance for selecting appropriate CV-based methods for bridge inspection and monitoring.

An Improved Mask R-CNN Micro-Crack Detection Model for the Surface of Metal Structural Parts

“…However, the traditional convolutional layer or fully connected layer can never escape information loss and depletion during information transfer, and directly increasing the depth of the CNN can easily cause the phenomenon of gradient disappearance and gradient explosion, i.e., the model is degraded. To address the above problems, He [ 28 ] pioneered the ResNet.…”

Vision-Based Structural Monitoring: Application to a Medium-Span Post-Tensioned Concrete Bridge under Vehicular Traffic

“…The experimental measure of displacements through video processing for the purpose of structural monitoring in civil engineering infrastructures has attracted much attention in the past decade. Hundreds of research articles, mostly focusing on the dynamic response monitoring of bridges, were reviewed in recent comprehensive analyses of the state-of-theart [1][2][3][4][5] and more articles continue to appear, e.g., [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23]. The reasons for such interest can be explained by considering the appealing characteristics of such technology, namely:…”

“…Possible integration within the same video hardware of different applications such as structural static and dynamic monitoring together with inspection, surface damage detection, and integrity evaluation, e.g., [5,[31][32][33][34], as well as security and/or traffic surveillance, e.g., [7], opening the way to cost-effective multi-purpose permanent installations.…”

CLensRimVision: A Novel Computer Vision Algorithm for Detecting Rim Defects in Contact Lenses

“…In recent times, with the advent of the computer, there has been a paradigm shift in how inspections are conducted in various industries [13][14][15][16][17][18]. Automated defect detection systems have demonstrated high levels of accuracy and consistency, surpassing human capabilities in certain cases.…”