应用BP网络预测混凝土中的钢筋锈蚀量  

Prediction for Corrosive Degree of Reinforcement in Concrete by Neural Network

作　　者：张耀庭[1] 罗菡[1] 胡兴源[1] 

机构地区：[1]华中科技大学土木建筑工程学院,湖北武昌430074

出　　处：《混凝土》2001年第2期56-59,53,共5页Concrete

摘　　要：钢筋锈蚀是影响混凝土结构耐久性的重要因素之一。本文通过建立BP网络模型对钢筋的锈蚀量进行计算和预测 ,并与目前常用的鉴别和检测方法相比较 ,结果表明建立BP网络是一种可以定量分析、简便易行的预测方法。Corrosive degree of reinforcement in concrete is one of the main factors wihich influences the durability of the structure.In this paper,the corrosive degree can be evaluated and forecasted by the model of BP neural network,which is compared with the methods used usually in ur country.The conclusion is that setting BP neural network is a convenient forecasting method which can be used to analyze in number.

关 键 词：钢筋 锈蚀 BP网络 预测 混凝土结构 

分 类 号：TU375[建筑科学—结构工程]