摘要
为预防桥梁坍塌所造成的损失,设计一种以静力应变数据作为损伤识别因子的识别方法,并以实际桥梁的有限元模型为研究对象,通过有限元分析获取该模型的静力应变数据,训练并测试BP神经网络。MATLAB仿真测试表明:基于BP神经网络结构损伤识别算法能够准确地识别损伤位置和损伤程度,同时将该方法用于实际桥梁能够反映桥梁的健康状况。
BP neural network is used to identify the structural damage of bridges in this paper.Taking the finite element model of a real bridge as research object,static strain data is obtained through the finite element analysis as the damage identification factor,and the BP neural network is built based on the above data for training and testing.The research results can be demonstrated by MATLAB simulation test which shows that the structural damage identification algorithm based on BP neural network can accurately identify the damage location and damage degree,and the method can reflect health status of bridges when it is applied to actual bridges.
作者
崔宝影
程权成
CUI Bao-ying;CHENG Quan-cheng(Department of Engineering Technology, Liaodong University,Dandong 118009, Liaoning, China;School of Huafu Meters, Liaoning Mechatronics College, Dandong 118009, Liaoning, China)
出处
《承德石油高等专科学校学报》
CAS
2022年第1期61-64,共4页
Journal of Chengde Petroleum College
基金
辽宁机电职业技术学院院级科研项目(基于单片机的以太网通信系统设计与研究):2017010
辽宁机电职业技术学院院级科研项目(非线性系统跟踪控制器设计与研究):2019009。
关键词
有限元模型
BP神经网络
结构损伤识别
静力应变数据
finite element model
BP neural network
structural damage identification
static strain data
