&lt;title&gt;Distributed computing and sensing for structural health monitoring systems&lt;/title&gt;

Mitchell, Kyle; Sana, Sridhar; Liu, Pengxiang; Cingirikonda, Krishnamohan; Rao, V. Sree Hari; Pottinger, Hardy J.

doi:10.1117/12.388896

Cited by 4 publications

(2 citation statements)

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“…The differences between the measured values and the trained values result from the environmental influences, such as temperature change. The four values composed another input vector x(θ 1 , θ 2 , θ 3 , θ 4 ) = x (6,1,4,26). By the squared Euclidean distance formula,…”

Section: Resultsmentioning

confidence: 99%

“…The authors used wireless communications to transfer sensor measurements to a centralized data acquisition server. Mitchell et al [6] proposed the use of distributed computing and sensing to detect damage in critical locations. Their systems made use of wireless communication technologies, either radiofrequency (RF) communication links or commercial wireless cellular phone networks.…”

Section: Introductionmentioning

confidence: 99%

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A wireless sensor network node designed for exploring a structural health monitoring application

Yuan

Zhao

et al. 2007

Smart Mater. Struct.

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This paper presents a wireless sensor network node designed for building a structural health monitoring (SHM) application. To develop a low-cost, low-power, dedicated wireless sensor node for a composite SHM system, a modular approach is taken in the design of the wireless sensor node. Three functional modules are adopted, including a sensor input unit, processing core and wireless communication. Different from existing wireless sensor nodes, the signal conditioning circuit is designed on this developed node for two typical SHM sensors, the piezoelectric sensor and the strain gauge. The developed wireless sensor nodes can be expediently used to deploy the dedicated wireless sensor network for SHM application. A two-tier wireless sensor network is deployed adopting the designed wireless sensor nodes to verify the efficacy of developing SHM systems. An embedding pattern matching method and a directed diffusion routing algorithm are developed to monitor the strain distribution or the bolt loosening position successfully.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%