基于分布式无线智能传感器网络的结构模态识别

Q3 Engineering
Jingzhou Lu, S. Sim, B. Jin, B. Spencer
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引用次数: 1

摘要

本文采用伊利诺斯州结构健康监测项目(ISHMP)研制的ISM400无线智能传感器对简支胶合板进行了振动试验。采用分散式数据聚合(DDA)和集中式数据收集(CDC)进行数据采集和处理。将自然激励技术(NExT)与特征系统实现算法(ERA)相结合的时域算法应用于板的模态参数识别,并将识别结果与有限元结果进行比较。模态参数(即利用DDA方法从实验数据中识别出的固有频率和模态振型不仅与CDC方法的固有频率和模态振型相吻合,而且与数值仿真结果吻合,表明基于DDA方法的无线智能传感器网络(WSSN)是合理有效的。与传统的集中式处理技术相比,分布式wsn具有集成度高、电能节约等特点,使得在大型土木结构上部署密集的传感器阵列既可行又经济。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Structural modal identification based on distributed wireless smart sensor networks
This paper presents the vibration test of a simply supported plywood plate using ISM400 wireless smart sensor developed by the Illinois Structural Health Monitoring Project(ISHMP).Decentralized data aggregation(DDA)as well as centralized data collection(CDC)was used for data acquisition and processing.Then a time domain algorithms integrating natural excitation technique(NExT)and eigensystem realization algorithm(ERA),was applied to identify modal parameters of the plate and the identification result was compared with the finite element result.The modal parameters(i.e.natural frequency and mode shape)identified from experimental data using DDA is not only in accordance with that using CDC,but also in accordance with the numerical simulation result,which shows that the wireless smart sensor networks(WSSN)based on DDA is reasonable and effective.Compared with conventional centralized processing technique,the unique features offered by distributed WSSN,including high integration and electrical energy saving,make deployment of a dense array of sensors on large civil structures both feasible and economical.
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来源期刊
应用基础与工程科学学报
应用基础与工程科学学报 Engineering-Engineering (all)
CiteScore
1.60
自引率
0.00%
发文量
2784
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