Artifical neural network technology for the data processing of high temperature sulfur corrosion

Artificial neural network (ANN) method for the data processing of high temperature sulfur corrosion is proposed after analyzing the general method for high temperature sulfur corrosion. A metabolism model for predicting the corrosion life by ANN is presented, which does not need all kinds of materials and environment parameters, and only needs to know a little data about environment parameters (including temperature, sulphur content and materials) and corrositivity in - service. The feasibility of this model was verified by the data from McConomy and Coaper Gorman curves. It is proved that ANN technology is applicable to the evaluation of the complicated system of high temperature sulphur corrosion, and also gives a base to develop the expert system and residual life evaluation system for high temperature sulphur corrosion.