Design of a real-time hull anode corrosion monitoring system based on microcontroller technology

Corrosion of hull anodes poses a persistent challenge in the maintenance of ocean-going vessels. Traditional detection methods often suffer from inefficiency, poor real-time performance, and high operational costs. This paper presents a real-time monitoring system for hull sacrificial anode degradation, developed on a microcontroller (MCU) platform. The system utilizes an STC89C52 MCU and an ADC0809 analog-to-digital converter to construct a distributed electrochemical potential sensing network. An LCD1602 display module and a machine learning prediction algorithm are integrated to facilitate dynamic status tracking and failure forecasting of the anodes. The system incorporates high-precision Cu/CuSO₄ reference electrodes, current density probes, and environmental sensors (temperature, salinity, and hydrostatic pressure) to enable multidimensional real-time data acquisition. Experimental results under simulated seawater conditions show that the system achieves a potential monitoring accuracy of ±0.5 mV and provides failure warnings up to 60 days in advance. The model yields a mean absolute error (MAE) of 2.7%, reducing prediction error by 45% compared to conventional techniques, and cutting maintenance costs to 20% of traditional levels. This research offers a cost-effective, high-precision framework for intelligent corrosion management in maritime applications.