Embedded data processing in wireless sensor networks for structural health monitoring
Embedded data processing in wireless sensor networks for structural health monitoring
复制标题
无线传感器网络中的嵌入式数据处理用于结构健康监测
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
N. Battista
中科院分区：
文献类型：
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作者：
N. Battista
八个配备能量收集太阳能电池板的无线加速计传感器节点 (Imote2) 在新加坡一座正在运行的人行天桥上连续部署了两周。每个节点使用一种新颖的嵌入式数据处理算法（称为滤波 Hilbert-Huang 变换）定期处理振动数据，从而减少了 96[%] 的数据。根据节点传输到基站的处理结果，可以得出结论，行人行走激励的共振响应导致高峰使用时间的振动水平增加。记录的最大峰值和RMS加速度分别为52mg和35mg，这在几个主要设计指南允许的限度内。这种无线传感器网络部署展示了分散式嵌入式数据处理在民用基础设施无线中长期结构健康监测方面的潜力。
Eight wireless accelerometer sensor nodes (Imote2) equipped with energy harvesting solar panels were deployed continuously on an operational pedestrian footbridge in Singapore for two weeks. Each node periodically processed vibration data using a novel embedded data processing algorithm, referred to as the Filtered Hilbert-Huang transform, which resulted in a data reduction of 96[%]. From the processed results which the nodes transmitted to the base station, it was possible to conclude that resonant response from pedestrian walking excitation led to increased vibration levels during peak usage times. The maximum recorded peak and RMS acceleration were 52mg and 35mg respectively, which are within the limits allowed by several major design guidelines. This wireless sensor network deployment demonstrated the potential of decentralised, embedded data processing for wireless medium- and long-term structural health monitoring of civil infrastructure.