Petrochemical equipment corrosion prediction based on BP artificial neural network

Petrochemical equipment corrosion prediction based on BP artificial neural network

Type	Conference Paper
Author	Jiao Li
Author	Gongqian Liang
URL	http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=7237489&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D7237489
Pages	238-242
Date	August 2015
Conference Name	2015 IEEE International Conference on Mechatronics and Automation (ICMA)
Abstract	Researchers constructed a BP neural network corrosion prediction model on petrochemical equipment as a way to avoid refinery accidents due to petrochemical equipment corrosion, Their model can better express the relationship of the corrosive medium factors (PH, CL-, H2S, NH3N) and the corrosion products(Fe2+ and Fe3+). Simulation results demonstrated that the predicted data are close to the monitored data. The model can be useful in predicting corrosion in petrochemical equipment.