Durability Simulation and Life Prediction Algorithm for Anti-corrosion Coatings

Aiming at the problem of durability and life prediction of anticorrosive coatings in practical application, this article aims to propose a new method of durability simulation and life prediction by combining simulation technology with deep learning algorithm. In terms of methods, this article first constructs a durability simulation model of anti-corrosion coating based on the influence of many factors, and carries out accelerated aging experiments on the coating performance by simulating the actual use environment. Secondly, the deep learning algorithm is used to process and analyze a large number of data obtained from simulation experiments, and the mapping relationship between coating performance and service life is established, thus realizing the accurate prediction of service life. The results show that the method proposed in this article can evaluate the durability of anti-corrosion coatings and accurately predict their service life. Compared with other methods, this method has obvious advantages in prediction accuracy and generalization ability. In addition, through the comparative analysis of different coating samples, the practicability and reliability of this method are further verified. This method has broad prospects and social value in practical application.