Title: Corrosion of reinforcement detection system based on wireless sensor network and multi-sensor data fusion

Authors: Ziyang Shang; Along Yu; Hongbing Sun; Lei Huang

Addresses: School of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing, Jiangsu, China ' School of Physics and Electronic Electrical Engineering, Huaiyin Normal University, Haikou, Huaian, China ' School of Physics and Electronic Electrical Engineering, Huaiyin Normal University, Haikou, Huaian, China ' School of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing, Jiangsu, China

Abstract: In order to monitor the internal status of steel bars in a timely manner and improve the monitoring system, this article proposes a data fusion method based on improved Beetle Antenna Search Algorithm based on Back Propagation to predict steel bar corrosion. Combined with wireless sensing technology, the algorithm improves the single beetle optimised in the Beetle whisker algorithm (IBAS-BP) to a group of beetles. The improved algorithm was compared with the other three algorithms in terms of training and testing, and the results showed that the IBAS-BP algorithm-based prediction model for steel corrosion in reinforced concrete had faster convergence speed and higher prediction accuracy. And through the Raspberry Pi gateway, a steel bar corrosion monitoring system was built using the built-in Python processing algorithm. The experimental results show that the system can effectively monitor the corrosion of reinforcing steel bars in concrete, which can provide a reliable basis for timely and effective maintenance.

Keywords: improved BAS-BP algorithm; monitoring system; wireless sensor network; multi-sensor.

DOI: 10.1504/IJWMC.2026.153169

International Journal of Wireless and Mobile Computing, 2026 Vol.30 No.3, pp.233 - 244

Received: 01 Mar 2023
Accepted: 10 Dec 2023
Published online: 25 Apr 2026 *

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