Autonomous Corrosion Assessment of Reinforced Concrete Structures: Feasibility Study

Abstract

In this work, technological feasibility of autonomous corrosion assessment of reinforced concrete structures is studied. Corrosion of reinforcement bars (rebar), induced by carbonation or chloride penetration, is one of the leading causes for deterioration of concrete structures throughout the globe. Continuous nondestructive in-service monitoring of carbonation through pH and chloride ion (Cl−) concentration in concrete is indispensable for early detection of corrosion and making appropriate decisions, which ultimately make the lifecycle management of RC structures optimal from resources and safety perspectives. Critical state-of-the-art review of pH and Cl− sensors revealed that the majority of the sensors have high sensitivity, reliability, and stability in concrete environment, though the experiments were carried out for relatively short periods. Among the reviewed works, only three attempted to monitor Cl− wirelessly, albeit over a very short range. As part of the feasibility study, this work recommends the use of internet of things (IoT) and machine learning for autonomous corrosion condition assessment of RC structures.

The application of “deep learning” in construction site management: scientometric, thematic and critical analysis

“…Wu et al (2019b) have incorporated deep learning algorithms into edge devices for assessment and damage detection to achieve quick inference and low memory demands through transfer learning and network pruning. Another research has studied the technological feasibility of autonomous corrosion assessment of reinforced concrete structures, in which the use of IoT and machine learning for autonomous corrosion condition assessment of RC structures were recommended (Taffese and Nigussie, 2020). Maraveas and Bartzanas (2021) have studied another type of structure through using various sensors for accurate and real-time monitoring of agricultural building structures, including electrochemical, ultrasonic, fiber-optic, CI 22,3 piezoelectric, wireless, fiber Bragg grating sensors and self-sensing concrete.…”

Corrosion Assessment in Reinforced Concrete Structures by Means of Embedded Sensors and Multivariate Analysis—Part 1: Laboratory Validation

“…However, their result interpretation is not easy because minor changes in humidity or temperature significantly affect the taken measurements. Besides, these sensors' stability has been studied only for relatively short periods [67].…”