期刊名称：IOP Conference Series: Earth and Environmental Science
印刷版ISSN：1755-1307
电子版ISSN：1755-1315
出版年度：2019
卷号：242
期号：6
页码：1-9
DOI：10.1088/1755-1315/242/6/062075
出版社：IOP Publishing
摘要：In order to study the relationship between ambient temperature and girder deflection quantitatively, realize the deflection prediction, a BP neural network deflection prediction method based on correlation analysis is proposed in this paper. The correlation between ambient temperature and girder deflection is analysed, and the BP neural network method is used to fit the samples with non-linear correlation quantitatively. Based on the quantitative relationship between ambient temperature and girder deflection, the prediction of girder deflection is realized. Taking Nanjing Yangtze River 3rd Bridge as an example, the feasibility of this method is verified based on monitoring data for four consecutive years. The results show that the non-linear mapping relationship between girder deflection at mid-span and ambient temperature is accurate and has good prediction effect. The method proposed in this paper provides a basis for the evaluation and early warning of the deflection.
