A Review of In-Service Coating Health Monitoring Technologies: Towards “Smart” Neural-Like Networks for Condition-Based Preventive Maintenance

Abstract

In line with the recent industrial trends of hyperconnectivity, 5G technology deployment, the Internet of Things (IoT) and Industry 4.0, the ultimate goal of corrosion prevention is the invention of smart coatings that are able to assess their own condition, predict the onset of corrosion and alert users just before it happens. It is of particular interest to tackle corrosion that occurs in non-accessible areas where human inspectors or handheld devices are useless. To accomplish this, a variety of technologies that are embedded or could potentially be embedded into the coatings are being developed to monitor coating condition, which are based, for instance, on the evolution of electrochemical or mechanical properties over time. For these technologies to be fully embedded into the coatings and work remotely, solutions are needed for connectivity and power supply. A paradigm shift from routine prescheduled maintenance to condition-based preventive maintenance could then become a reality. In this work, the technologies that enable the in-service monitoring of organic anticorrosion coatings were compiled. Soon, some of them could be integrated into the sensing elements of autonomous, connected neural-like networks that are capable of remotely assessing the condition of the anticorrosion protection of future infrastructures.