Corrosion Assessment in Reinforced Concrete Structures by Means of Embedded Sensors and Multivariate Analysis—Part 2: Implementation

Abstract

The economic cost of repairing corrosion-affected reinforced concrete structures (RCSs) means that reliable and accurate assessment and early detection methods must be sought after. Conventional techniques, such as visual inspections, or measuring either cover layer resistivity or the corrosion potential, are methods that require accessibility and involve personnel having to travel to take in situ measurements. Monitoring by embedded sensors is a much more efficient approach that allows early detection by remote sensing. This work presents the implementation of a new measurement protocol regarding the existing monitoring system called INESSCOM (Integrated Sensor Network for Smart Corrosion Monitoring). Along with the corrosion intensity measurement in embedded sensors, it also proposes monitoring the double layer capacity of the sensors’ responses. It aims to determine, along with the rebars’ corrosion rate, the triggering agent of the corrosion process. This study was carried out using three reinforced concrete scaled columns that were exposed to different environments. The results demonstrate with this new protocol that the remote INESSCOM monitoring system can establish the corrosion rate and identify the precursor agent of corrosion (carbonation or chlorides), even when the recorded corrosion rates are similar.