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[] Cost-benefit optimization of sensor networks for SHM applications

1 Politecnico di Milano
2 ETH Zürich
3 Politecnico di Milano
* Author to whom correspondence should be addressed.
14 November 2017
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Abstract

Structural health monitoring (SHM) is aimed to obtain information about the structural integrity of a system, e.g. via the estimation of its mechanical properties through observations
collected with a network of sensors. In the present work, we provide a method to optimally design sensor networks in terms of spatial configuration, number and accuracy of sensors. The utility of the sensor network is quantified through the expected Shannon information gain of the measurements with respect to the parameters to be estimated. At assigned number of sensors to be deployed over the structure, the optimal sensor placement problem is ruled by the objective function computed and maximized by combining surrogate models and stochastic optimization algorithms. For a general case, two formulations are introduced and compared: (i) the maximization of the information obtained through the measurements, given the appropriate constraints (i.e. identifiability, technological and budgetary ones); (ii) the maximization of the utility efficiency, defined as the ratio between the information provided by the sensor network and its cost. The method is applied to a large-scale structural problem, and the outcomes of the two different approaches are discussed.

Keywords

Structural health monitoring; Bayesian inference; cost-benefit analysis; stochastic optimization; information theory

Cite this article as

Capellari, G.; Chatzi, E.; Mariani, S. Cost-benefit optimization of sensor networks for SHM applications. In Proceedings of the 4th Int. Electron. Conf. Sens. Appl., 15–30 November 2017; ; doi:10.3390/ecsa-4-04891

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