Research And Implementation Of Refinery Equipments Corrosion Prediction Technology

In recent years,with the development of our country’s economy,China’s oil refining industry is developing rapidly,at the same time due to the equipment corrosion,the security problem is increasingly serious.Leakage and explosion happened from time to time.So accurately and effectively predict the corrosion rate of the refining equipment and remaining life is of great significance.First,this paper summarizes the research status of corrosion prediction,compares the advantages and disadvantages of different methods.Considering the influence factors of corrosion is complex,the traditional mathematical modeling methods has certain difficulty and insufficiency.So from the aspect of data analysis,the SVR method is proposed to address the corrosion predict,and the problem description,the model formulation are provided orderly.Secondly,the key part of this paper is to obtain the reasonable and optimal parameters for the SVR model.Firstly,the trial and error method is proposed to get the ranges of parameters(C,ε,g)and GA SVR is proposed to get the best parameters.Moreover,the comparison with the BP neural network and AR methods are done to illustrate the advantage of GA_SVR.Choosing GA SVR as the main algorithm of system implementation.Then,because the remaining life is affected by the corrosion rate,according to the prediction of corrosion rate,using the monte carlo method testing the failure probability of the equipment and obtain the remaining life.Finally,the system requirements analysis and design is developed for the equipment corrosion prediction system.Implements the corrosion rate prediction based on SVR method and remaining life prediction based on monte carlo method.