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Optimal sensor placement on a large-scale civil structure


Reference:

Meo, M. and Zumpano, G., 2004. Optimal sensor placement on a large-scale civil structure. Proceedings of SPIE - The International Society for Optical Engineering, 5394 (108).

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Official URL:

http://dx.doi.org/10.1117/12.540308

Abstract

Health monitoring systems set up to assure the safe operation of structures require linking sensors with computational tools able to interpret sensor data in terms of structural performance. Although intensive development continues on innovative sensor systems, there is still considerable uncertainty in deciding on the number of sensors required and their location in order to obtain adequate information on structural behavior. This paper considers the problem of locating sensors on a bridge structure with the aim of maximizing the data information so that structural dynamic behavior can be fully characterised. Four different optimal sensor placement techniques, two based on the maximisation of the Fisher Information Matrix and two on energetic approaches, have been investigated. Mode shape displacements are taken as the measured data set and two comparison criteria were employed. The first was based on the mean square error between the FE model and the cubic spline interpolated mode shapes. The second criterion measured the information content of each sensor location to investigate on the strength of the acquired signals and their ability to withstand the noise pollution keeping intact the information relative to the structure properties. The results highlight that the Effective Independence Driving-Point Residue (EFI-DPR) method provides an effective method for optimal sensor placement to identify vibration characteristics of the studied bridge.

Details

Item Type Articles
CreatorsMeo, M.and Zumpano, G.
DOI10.1117/12.540308
DepartmentsFaculty of Engineering & Design > Mechanical Engineering
RefereedNo
StatusPublished
ID Code22985
Additional InformationHealth Monitoring and Smart Nondestructive Evaluation of Structural and Biological Systems III. 15-19 March 2004. San Diego, California, USA.

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