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Materials 2016, 9(11), 946; doi:10.3390/ma9110946

A Bayesian Approach for Sensor Optimisation in Impact Identification

1
Department of Architecture, University of Ferrara, Via Quartieri 8, 44121 Ferrara, Italy
2
Department of Aeronautics, Imperial College London, London SW7 2AZ, UK
*
Author to whom correspondence should be addressed.
Academic Editor: Dirk Lehmus
Received: 15 September 2016 / Revised: 25 October 2016 / Accepted: 9 November 2016 / Published: 22 November 2016
(This article belongs to the Special Issue Advances in Structural Health Monitoring for Aerospace Structures)
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Abstract

This paper presents a Bayesian approach for optimizing the position of sensors aimed at impact identification in composite structures under operational conditions. The uncertainty in the sensor data has been represented by statistical distributions of the recorded signals. An optimisation strategy based on the genetic algorithm is proposed to find the best sensor combination aimed at locating impacts on composite structures. A Bayesian-based objective function is adopted in the optimisation procedure as an indicator of the performance of meta-models developed for different sensor combinations to locate various impact events. To represent a real structure under operational load and to increase the reliability of the Structural Health Monitoring (SHM) system, the probability of malfunctioning sensors is included in the optimisation. The reliability and the robustness of the procedure is tested with experimental and numerical examples. Finally, the proposed optimisation algorithm is applied to a composite stiffened panel for both the uniform and non-uniform probability of impact occurrence. View Full-Text
Keywords: probability of detection; sensor malfunctioning; genetic algorithm; non-linear finite element method; artificial neural network; structural health monitoring probability of detection; sensor malfunctioning; genetic algorithm; non-linear finite element method; artificial neural network; structural health monitoring
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Mallardo, V.; Sharif Khodaei, Z.; Aliabadi, F.M.H. A Bayesian Approach for Sensor Optimisation in Impact Identification. Materials 2016, 9, 946.

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