Long-term structural response prediction models for concrete structures using weather data, fiber-optic sensing, and convolutional neural network

作者：

Highlights：

• A long-term strain prediction model for concrete structures is presented.

• The networks identify the relationship between weather and the strain data.

• The trained CNN can predict the strain using only weather data.

• The models are applied to predict the strain of a real concrete bridge.

摘要

•A long-term strain prediction model for concrete structures is presented.•The networks identify the relationship between weather and the strain data.•The trained CNN can predict the strain using only weather data.•The models are applied to predict the strain of a real concrete bridge.

论文关键词：Structural health monitoring,Concrete structure,Long-term monitoring,Air temperature,Relative humidity,Fiber-optic strain sensor,Convolutional neural network

论文评审过程：Received 20 October 2021, Revised 2 February 2022, Accepted 30 March 2022, Available online 7 April 2022, Version of Record 21 April 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.117152