A reinforced corrosion assessment method based on a new magnetic sensor and improved adaptive filtering

Abstract Corrosion assessment of reinforced concrete structures is the basis for subsequent corrosion repair and early warning of structural hazards. Aiming at the problem of accurately measuring the corrosion degree of reinforced concrete structures in coastal area, a new Magnetic Sensor (NMS) based on the theory of magnetic medium is designed in this paper. A functional model of the relationship between magnetic induction intensity change and reinforcement mass loss based on multi-point detection is constructed, and an improved adaptive filtering Least Mean Square (LMS) algorithm is proposed to realize damage identification and quantitative calculation of reinforcement corrosion comprehensively. Through numerical simulation experiments, the feasibility of designing the sensor is verified. The measured corrosion test of the sensor prototype shows that the calculated corrosion rates of different steel corrosion degrees are in good agreement with the actual values, with an average relative error of 1.64 %. The sensor provides a new method for corrosion monitoring of reinforced concrete structures.