Remote inspection of RC structures using unmanned aerial vehicles and heuristic image processing

• Type: Article in International Scientific Journal
• Date: 2020

Authors

Ribeiro, D (Author) Other; Santos, R (Author) Other; Shibasaki, A (Author) Other; Pedro Aires Montenegro (Author) FEUP; Carvalho, H (Author) Other; Rui Calçada (Author) FEUP

Journal

Title: Engineering Failure Analysis

Vol. 117

ISSN: 1350-6307

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 36 Citations

Scopus - 44 Citations

Other information

Authenticus ID: P-00S-KE0

DOI: 10.1016/j.engfailanal.2020.104813

Abstract (EN): This article describes an innovative methodology for remote inspection of reinforced concrete (RC) structures using Unmanned Aerial Vehicles (UAVs) and based on advanced digital image processing. The use of specific heuristic feature-extraction methods, developed in MATLAB(C), allows the automatic identification of various types of RC pathologies, particularly, biological colonies, efflorescences, cracks and exposed steel rebars. The developed inspection methodology is applied to the Monte da Virgem telecommunications tower, which has a total height of 177 m and is the highest structure of this kind in Portugal. The results demonstrate the efficiency and robustness of the methodology in: i) its ability to accurately locate and characterize the existing pathologies, ii) visualizing the full extent of pathologies in 3D photogrammetric reconstitutions of the structure, and iii) integrating the identified pathologies into a Building Information Modeling (BIM) model. The regular use of the proposed methodology over time will allow accurate monitoring of the evolution of pathologies to assess the condition of the structure. Additionally, the integration of the inspection results into BIM digital models will help infrastructure managers to decide on the implementation of the most adequate facility management strategies in order to optimize the scheduling of maintenance, rehabilitation and retrofitting interventions.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 15