摘要
通过对某石化公司循环冷却水系统生产运行数据的分析,选取了对腐蚀速率影响较大的水质参数,借助神经网络良好的非线性能力,基于BP神经网络建立了腐蚀速率的预测模型。利用该模型对循环冷却水系统一定周期腐蚀速率的预测结果较好。
After analyzing the operation data of circulating cooling water system in a petrochemical company,the corrosion rate-related water quality parameters were selected to build corrosion rate prediction model based on BP neural network which boasting of a good non-linear ability.The prediction results show that this model is applicable.
出处
《化工自动化及仪表》
CAS
北大核心
2011年第6期676-678,共3页
Control and Instruments in Chemical Industry
基金
天津市科技创新专项资金项目(05FZZDGX00300)
天津市教委滨海新区双百科技特派员科技专项(SB20080070)
关键词
循环冷却水
腐蚀速率
预测模型
神经网络
circulating cooling water
corrosion rate
prediction model
neural network
