Pitted Corrosion Detection of Thermal Sprayed Metallic Coatings Using Fiber Bragg Grating Sensors

Prediction Method of Steel Corrosion Rate Based on the Helix Distributed Sensor

Corrosion of steel bars is of great significance for safety and service life of reinforced concrete structures. This work develops a prediction method for steel corrosion mass loss rate before the crack of concrete structure based on a spiral distributed fiber optic sensor. Reinforced concrete sample instrumented with a spiral distributed fiber optic sensor were prepared. The mathematic relationship between the corrosion mass loss rate of steel bar and the spiral distributed strain is theoretically derived. Meanwhile, numerical analysis by MATLAB shows that these parameters such as the protective layer thickness, corrosion mass loss rate, bar diameter, corrosion expansion coefficient have a remarkable influence on spiral distributed strain. Additionally, electrical accelerated corrosion experiment was performed on the reinforced concrete specimens. The helix strain along the distributed sensor was used to evaluate the corrosion mass loss of steel bar. Further, the influencing factors on the corrosion sensitivity are illustrated here and the corrosion mass loss rate before concrete crack is also quantified. This research provides insights into the corrosion deteriorate mechanism.

Monitoring Epoxy Coated Steel under Combined Mechanical Loads and Corrosion Using Fiber Bragg Grating Sensors

Fiber Bragg grating (FBG) sensors have been applied to assess strains, stresses, loads, corrosion, and temperature for structural health monitoring (SHM) of steel infrastructure, such as buildings, bridges, and pipelines. Since a single FBG sensor measures a particular parameter at a local spot, it is challenging to detect different types of anomalies and interactions of anomalies. This paper presents an approach to assess interactive anomalies caused by mechanical loading and corrosion on epoxy coated steel substrates using FBG sensors in real time. Experiments were performed by comparing the monitored center wavelength changes in the conditions with loading only, corrosion only, and simultaneous loading and corrosion. The theoretical and experimental results indicated that there were significant interactive influences between loading and corrosion for steel substrates. Loading accelerated the progress of corrosion for the epoxy coated steel substrate, especially when delamination in the epoxy coating was noticed. Through the real-time monitoring from the FBG sensors, the interactions between the anomalies induced by the loading and corrosion can be quantitatively evaluated through the corrosion depth and the loading contact length. These fundamental understandings of the interactions of different anomalies on steel structures can provide valuable information to engineers for better management of steel structures.

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

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.

Corrosion Behavior Evaluation of Coated Steel Using Fiber Bragg Grating Sensors

Coatings, either soft or hard, are commonly used to protect steel against corrosion for longer service life. With coatings, assessing the corrosion behavior and status of the substrate is challenging without destructive analysis. In this paper, fiber Bragg (FBG) grating sensors were proposed to nondestructively evaluate the corrosion behavior of steel coated with two popular coatings, including the polymeric and wire arc sprayed Al-Zn coating. Laboratory accelerated corrosion tests demonstrated that the embedded FBG sensors inside both the soft and hard coatings can effectively quantify the corrosion rate, monitor the corrosion progress, and detect the coating damages and crack propagation of coated steel in real time. The laboratory electrochemical corrosion test on the wire arc sprayed Al-Zn coating validated the proposed embedded FBG sensor method with a good agreement in comparison. The proposed sensing platform provides an alternative nondestructive real-time corrosion assessment approach for coated steel in the field.

Extended-bandwidth frequency sweeps of a distributed feedback laser using combined injection current and temperature modulation

This article details the generation of an extended-bandwidth frequency sweep using a single, communication grade distributed feedback (DFB) laser. The frequency sweep is generated using a two-step technique. In the first step, injection current modulation is employed as a means of varying the output frequency of a DFB laser over a bandwidth of 99.26 GHz. A digital optical phase lock loop is used to lock the frequency sweep speed during current modulation, resulting in a linear frequency chirp. In the second step, the temperature of the DFB laser is modulated, resulting in a shifted starting laser output frequency. A laser frequency chirp is again generated beginning at this shifted starting frequency, resulting in a frequency-shifted spectrum relative to the first recorded data. This process is then repeated across a range of starting temperatures, resulting in a series of partially overlapping, frequency-shifted spectra. These spectra are then aligned using cross-correlation and combined using averaging to form a single, broadband spectrum with a total bandwidth of 510.9 GHz. In order to investigate the utility of this technique, experimental testing was performed in which the approach was used as the swept-frequency source of a coherent optical frequency domain reflectometry system. This system was used to interrogate an optical fiber containing a 20 point, 1-mm pitch length fiber Bragg grating, corresponding to a period of 100 GHz. Using this technique, both the periodicity of the grating in the frequency domain and the individual reflector elements of the structure in the time domain were resolved, demonstrating the technique's potential as a method of extending the sweeping bandwidth of semiconductor lasers for frequency-based sensing applications.