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Development of an early seismic damage detection technology for civil infrastructures

民用基础设施早期震害检测技术的开发

基本信息

批准号：
18360211
负责人：
YOKOYAMA Koichi
金额：
$ 9.93万
依托单位：
Ibaraki University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (B)
财政年份：
2006
资助国家：
日本
起止时间：
2006 至 2007
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-18360211/
关键词：
seismic damage diagnosis optical fiber sensing piezoelectric sensor monitoring soundness detection crack measurement structural identification thermal strain 圧電フィルム

项目摘要

1. Development of the broadband optical fiber sensor for seismic damage detectionA novel packaged long-gage FBG (Fiber Bragg Grating) sensor for health monitoring of civil structure has been developed and verified to have the ability to obtain effective macro-strain distributions. Moreover, temperature fluctuation poses a great obstacle in damage identification and structural health monitoring (SEM) of civil structures. A new compensation method of temperature effects on strain measurement has been modeled by using Multiple Regression and Neural Networks (NN) analysis based on temperature and strain distribution measured at a bridge model2. Development of the broadband memory sensor for seismic damage detectionExperimental study on application of PVDF (polarized polyvinylindene fluoride) film as a crack detection sensor was conducted to detect occurrence and propagation of cracks in aluminum specimen and RC beams. It is confirmed that the PVDF film sensor is able to catch the generation of micro-crack and provide information of strain distribution better than those of traditional strain gauge sensors. A wireless acceleration sensor system has been developed and was used for a rudimentary vibration experiment. The experimental results showed that the wireless acceleration sensor system is applicable vibration measurement for structural damage monitoring.3. Development of seismic soundness diagnosis and analysis systemIn order to monitor the soundness for real-time, a two-level strategy was proposed far damage detection in flexural structures using modal parameters extracted from dynamic macro-strain responses. And, a neural network system, which consists of multi-inputs and multi-outputs, was proposed as the damage detection technique of long-span cable-stayed bridge. The neural network system which was built based on response information of multiple locations is able to grasp damage location and damage extents.

1.用于地震损伤检测的宽带光纤传感器研制开发了一种用于土木结构健康监测的新型封装式长应变计光纤布拉格光栅（FBG）传感器，并验证了该传感器能够获得有效的宏观应变分布。此外，温度波动对土木结构的损伤识别和结构健康监测（SEM）造成了很大的障碍。基于桥梁模型的温度和应变测量结果，采用多元回归和神经网络分析方法，建立了温度对应变测量影响的补偿方法。用于地震损伤检测的宽频带记忆传感器的研制利用PVDF（polarized polyvinylindene fluoride）薄膜作为裂纹检测传感器，对铝试件和钢筋混凝土梁的裂纹发生和扩展进行了检测实验研究。实验结果表明，PVDF薄膜传感器比传统的应变片传感器能更好地捕捉微裂纹的产生和提供应变分布信息。无线加速度传感器系统已经开发出来并用于基本的振动实验。实验结果表明，无线加速度传感器系统适用于结构损伤监测的振动测量.为了实时监测结构的健康状况，提出了一种基于动态宏观应变响应提取模态参数的两级结构损伤检测策略。提出了一种多输入多输出的神经网络系统作为大跨度斜拉桥损伤识别技术。基于多个位置的响应信息建立的神经网络系统能够准确地把握损伤位置和损伤程度。