Functional Link Neural Network for Predicting Crystallization Temperature of Ammonium Chloride in Air Cooler System

作者：Jin Haozhe,Gu Yong,Ren Jia,Wu Xiangyao,Quan Jianxun,Xu Linfengyi

摘要：The air cooler is an important equipment in the petroleum refining industry.Ammonium chloride(NH4 Cl)deposition-induced corrosion is one of its main failure forms.In this study,the ammonium salt crystallization temperature is chosen as the key decision variable of NH4 Cl deposition-induced corrosion through in-depth mechanism research and experimental analysis.The functional link neural network(FLNN)is adopted as the basic algorithm for modeling because of its advantages in dealing with non-linear problems and its fast-computational ability.A hybrid FLNN attached to a small norm is built to improve the generalization performance of the model.Then,the trained model is used to predict the NH4 Cl salt crystallization temperature in the air cooler of a sour water stripper plant.Experimental results show the proposed improved FLNN algorithm can achieve better generalization performance than the PLS,the back propagation neural network,and the conventional FLNN models.

发文机构：The Institute of Flow-Induced Corrosion Faculty of Mechanical Engineering&Automation

关键词：aircoolerNH4ClsaltcrystallizationtemperatureDATA-DRIVENfunctionallinkneuralnetworkparticleswarmoptimization

分类号： TG1[金属学及工艺—金属学]