Towards a FOSS Automatic Classification of Defects for Bridges Structural Health Monitoring

Abstract

Bridges are among the most important structures of any road network. During their service life, they are subject to deterioration which may reduce their safety and functionality. The detection of bridge damage is necessary for proper maintenance activities. To date, assessing the health status of the bridge and all its elements is carried out by identifying a series of data obtained from visual inspections, which allows the mapping of the deterioration situation of the work and its conservation status. There are, however, situations where visual inspection may be difficult or impossible, especially in critical areas of bridges, such as the ceiling and corners. In this contribution, the authors acquire images using a prototype drone with a low-cost camera mounted upward over the body of the drone. The proposed solution was tested on a bridge in the city of Turin (Italy). The captured data was processed via photogrammetric process using the open-source Micmac solution. Subsequently, a procedure was developed with FOSS tools for the segmentation of the orthophoto of the intrados of the bridge and the automatic classification of some defects found on the analyzed structure. The paper describes the adopted approach showing the effectiveness of the proposed methodology.

WITHDRAWN: Combining UAV-LiDAR and UAV-Photogrammetry for Bridge Assessment and Infrastructure Monitoring

“…Over the years, Unmanned Aerial Vehicles (UAVs) have become a popular and cost-effective method for inspecting and monitoring bridges non-destructively (Pinto et al, 2020). These innovative techniques offer a safer and less expensive alternative to traditional methods, particularly under challenging conditions (Belcore et al, 2021). With the support of an organized flight and survey plan, UAV-based methods can provide a wealth of information and data that can be integrated with traditional instrumentation in conventional workflows.…”

Computer Vision and Image Processing in Structural Health Monitoring: Overview of Recent Applications

“…For example, in [37], estimated displacements were compared with actuator-generated movements and stationary targets. In [39,47,63], only a comparison between algorithms was performed. In [40,45,52,[56][57][58]62,69,72,[77][78][79][80]85] a comparison with damage, deformation, and, in general, real-world manual measurements was performed.…”

“…In contrast, the authors of [39,46,47,52,56,68,79,[83][84][85] tested the proposed solution only directly on real scenarios. The authors of [48] also mentioned an in-field experiment (i.e., estimation of building vibration using a video recorded from the roof of a building).…”

Enhanced Algorithms to Extract Decay Forms of Concrete Infrastructures From Uav Photogrammetric Data

“…In literature, different approaches are tested for this aims but they are principally applied to extract and analyse cracks (Ioli et al, 2022, Rau et al, 2017, Prasanna et al, 2012. Other studies, which use Object-Based Image Analysis (OBIA), can automatically extract and classify not only cracks but also other decay forms (Zollini et al, 2020, Belcore et al, 2022. The aim of this work was to test innovative algorithms to enhance the extraction of features such as cracks, spalling areas, exposed rebars, and washout of reinforced and pre-stressed concrete viaduct.…”