不同配比Ni-Cr系涂层非线性动力学系统的抗腐蚀性能研究  

Corrosion Resistant Properties of Different Proportions of Ni-Cr Coatings by Nonlinear Dynamics System

作　　者：董艳艳[1] 王新宇[2] 李薇[1] 王灵志 张宏亮 

机构地区：[1]华北电力大学区域能源系统优化教育部重点实验室,北京102206 [2]华北电力大学电气与电子工程学院,北京102206 [3]广东电网有限责任公司电力科学研究院,广州510080

出　　处：《材料导报》2016年第20期162-166,共5页Materials Reports

基　　金：国家自然科学基金面上项目(61471171);环保公益项目(201509010);中央高校基本科研业务费专项资金(2015ZZD08)

摘　　要：采用非线性动力学系统的BP数据网络进行管材涂层腐蚀性能预测。首先采用增重法获取9种腐蚀工况下的增重数据,将获取的数据用于构建BP神经网络模型,通过传输和反演操作设置拓扑结构为6×15×1的BP神经网络,然后基于90组实验数据用于验证和评价BP神经网络预测模型,最后通过对优选出的涂层进行Ni-Cr系涂层的机理分析,从而解决生物质电站锅炉"四管"的腐蚀问题,研发的抗腐蚀涂层具有较好的经济性和实用性。BP neural network that belongs to nonlinear dynamics system was used to predict corrosion property of pipe coatings in this experiment.Firstly desiccant method was adopted to obtain the weight data of 9 corrosion conditions,then the data was used to build BP neural network model.The BP neural network model with the topological structure of 6×15×1 was set up through transmission and inverse operation.Based on the experimental data,90 groups of them were used to verify and evaluate the BP neural network model.At last,the mechanism of the best NiCr coating was analyzed,so as to solve the corrosion problems of ＂four tubes＂ in biomass power plant boiler.And the corrosion resistance coating devised in this research is more economical and practical.

关 键 词：非线性动力学系统 BP神经网络 验证与评价 Ni-Cr涂层 机理分析 

分 类 号：TG174[金属学及工艺—金属表面处理]