[1]滕军,卢伟.基于多类型传感器信息的结构损伤识别方法[J].东南大学学报(自然科学版),2010,40(3):538-542.[doi:10.3969/j.issn.1001-0505.2010.03.020]
　Teng Jun,Lu Wei.Structural damage identification method based on multi-type sensors[J].Journal of Southeast University (Natural Science Edition),2010,40(3):538-542.[doi:10.3969/j.issn.1001-0505.2010.03.020]
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基于多类型传感器信息的结构损伤识别方法()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
40
期数:
2010年第3期
页码:
538-542
栏目:
土木工程
出版日期:
2010-05-20

文章信息/Info

Title:
Structural damage identification method based on multi-type sensors
作者:
滕军;  卢伟
哈尔滨工业大学深圳研究生院, 深圳 518055
Author(s):
Teng Jun;  Lu Wei
Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen 518055, China
关键词:
结构健康监测;  损伤识别;  数据融合;  神经网络;  D-S证据理论
Keywords:
structural health monitoring;  damage identification;  data fusion;  neural network;  D-S evidence theory
分类号:
TU393.3
DOI:
10.3969/j.issn.1001-0505.2010.03.020
摘要:
计算2组基于径向基神经网络的结构损伤程度识别结果,一组神经网络输入是加速度传感器信息,另一组神经网络输入是应变传感器信息; 以2组识别结果及其可靠性为基础,提出采用D-S证据理论数据融合方法的结构损伤程度综合识别方法.以网壳结构为研究对象,建立结构损伤模型和神经网络样本库及输入输出向量,并对不同噪声水平下结构损伤程度识别结果进行计算.计算结果显示,基于多类型传感器信息的结构损伤程度综合识别结果的误差明显小于基于单类型传感器的识别结果,并在神经网络输入有噪声的情况下,仍保持较好的效果.因此,基于多类型传感器信息的结构损伤程度识别方法在合理应用结构多类型响应信息的基础上,能够获得更优的结构损伤程度识别结果.
Abstract:
Two groups of structural damage extent identification results based on neural networks are calculated, the inputs of which are acceleration sensor information and strain sensor information respectively; the structural damage extent identification results using D-S evidence theory data fusion is described based on the two groups of identification results mentioned above and their reliability. A shell structure is used to explain the method. The structural damage models are established. The samples for neural networks and the input and output vectors are chosen. The structural damage extent identification results are calculated at different noise levels. It can be known from the calculation results that the error of structural damage extent identification based on multi-type sensors is less than that based on single-type sensor; the same result can be obtained with the inputs under different noise levels. So the structural damage extent identification method based on multi-type sensors can obtain much better results than the method based on single-type sensors.

参考文献/References:

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备注/Memo

备注/Memo:
作者简介: 滕军(1962—),男,博士,教授,博士生导师,tengj@hit.edu.cn.
基金项目: 国家自然科学基金资助项目(50678052).
引文格式: 滕军,卢伟.基于多类型传感器信息的结构损伤识别方法[J].东南大学学报:自然科学版,2010,40(3):538-542. [doi:10.3969/j.issn.1001-0505.2010.03.020]
更新日期/Last Update: 2010-05-20