[1]徐长哲,余庆林,杨青松.基于BP神经网络的结构损伤识别技术[J].应用科技,2020,47(3):63-68.[doi:10.11991/yykj.202004001]
 XU Changzhe,YU Qinglin,YANG Qingsong.Structural damage identification technology based on BP neural network[J].Applied science and technology,2020,47(3):63-68.[doi:10.11991/yykj.202004001]
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基于BP神经网络的结构损伤识别技术(/HTML)
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《应用科技》[ISSN:1009-671X/CN:23-1191/U]

卷:
第47卷
期数:
2020年3期
页码:
63-68
栏目:
机电工程
出版日期:
2020-07-05

文章信息/Info

Title:
Structural damage identification technology based on BP neural network
作者:
徐长哲 余庆林 杨青松
中国核动力研究设计院,四川 成都 610213
Author(s):
XU Changzhe YU Qinglin YANG Qingsong
Nuclear Power Institute of China, Chengdu 610213, China
关键词:
健康监测损伤识别神经网络信息融合网络构建损伤敏感特征数据增强模态分析
Keywords:
health monitoringdamage identificationneural networkinformation fusionnetwork constructiondamage sensitive featuresdata enhancementmodal analysis
分类号:
TP183
DOI:
10.11991/yykj.202004001
文献标志码:
A
摘要:
基于对结构安全性的高要求,以各种不同监测技术为基础的结构健康监测系统得到广泛研究与应用,而结构损伤识别系统是结构健康监测系统的核心组成部分之一。本文以某悬臂梁为工程背景,研究结合信息融合的基于BP神经网络的结构损伤识别技术,通过MATLAB软件构建BP神经网络,训练完成的神经网络损伤识别准确率高于90%。本文对基于神经网络的结构损伤识别技术的可靠性进行讨论,总结了结合信息融合与神经网络的损伤识别技术的优缺点。网络识别结果证明了该技术的可行性,为工程结构损伤识别应用的进一步研究提供了参考。
Abstract:
Based on the high requirements of structural safety, the structural health monitoring system based on various monitoring technologies has been widely studied and applied. The structural damage identification system is one of the core components of the structural health monitoring system. In this paper, taking a cantilever beam as the engineering background, the structural damage identification technology is studied based on the BP neural network combined with information fusion. The BP neural network is constructed by MATLAB software, the accuracy of neural network damage identification after training is higher than 90%. The reliability of the structural damage identification technology based on neural network is discussed. The advantages and disadvantages of the damage identification technology combined with information fusion and neural network are summarized. The result of network identification proves feasibility of the technology, providing a reference for the application and further study of damage identification of engineering structures.

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备注/Memo

备注/Memo:
收稿日期:2020-04-01。
作者简介:徐长哲,男,助理研究员;余庆林,男,高级工程师
通讯作者:徐长哲,E-mail:xuchangzhe2011@163.com
更新日期/Last Update: 2020-08-05