Corrosion brings serious losses to the economy annually. Therefore, various corrosion protection and detection techniques are widely used in the daily maintenance of large metal engineering structures. The emergence of image recognition technology has brought a more convenient and faster way for nondestructive testing. Existing image recognition technology can be divided into two categories according to the algorithm: traditional image recognition technology and image recognition technology based on deep learning. These two types of technologies have been widely used in the three fields of metal, coating, and electrochemical data images. A large amount of work has been carried out to identify defects in metals and coatings, and deep learning-based methods also show potential for identifying electrochemical data images. Matching electrochemical images with the detection of defect morphology will bring a deeper understanding of image recognition techniques for metals and coatings. A database of accumulated morphology and electrochemical parameters will make it possible to predict the life of steel and coatings using image recognition techniques.

This study investigated the degradation of aluminum-based sacrificial anodes caused by sulfate-reducing bacteria (SRB) in marine mud. Through self-discharge tests simulating real cathodic protection conditions, alongside macroscopic observations, electrochemical analysis, and microscopic characterization, we systematically elucidated the corrosion behavior and mechanisms of the anodes with and without SRB. The results showed that the electrochemical capacity of anodes in SRB-inoculated mud was only 1281.28 Ah·kg⁻¹ (efficiency: 44.82%), failing to meet the design requirement of ≥1500 Ah·kg⁻¹. In contrast, in sterile mud, the capacity was 1972.84 Ah·kg⁻¹ (efficiency: 69.01%), which met the standard. SRB promoted the formation of discrete corrosion pits with depths reaching up to 0.43 mm, 3.07 times deeper than those observed under sterile conditions. The local pH within the pits dropped to 3–4, accelerating the selective dissolution of active elements such as Al and Zn. Mechanistic analysis revealed that the sulfides produced by SRB not only disrupt the passive film but also exacerbate the inefficient consumption of the anode through a positive feedback loop involving “acidic corrosion and electron consumption”. This led to a reduction in the protective current density, accompanied by significant fluctuations. This study provides the underlying mechanisms by which SRB degrade the performance of sacrificial anodes and valuable insights for optimizing the design of cathodic protection systems for steel structures in marine mud environments.