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      A Multiscale Approach to the Smart Deployment of Micro-Sensors over Lightweight Structures

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          Abstract

          A topology optimization approach has been recently proposed to maximize the sensitivity to damage of measurements, collected through a network of sensors to be deployed over thin plates for structural health monitoring purposes. Within such a frame, damage is meant as a change in the structural health characterized by a reduction of relevant stiffness and load-carrying properties. The sensitivity to a damage of unknown amplitude and location is computed by comparing the response to the external actions of the healthy structure and of a set of auxiliary damaged structures, each one featuring reduced mechanical properties in a small region only. The topology optimization scheme has been devised to properly account for the information coming from all of the sensors to be placed on the structure and for damage depending on its location. In this work, we extend the approach within a multiscale frame to account for three different length scales: a macroscopic one, linked to the dimensions of the whole structure to be monitored; a mesoscopic one, linked to the characteristic size of the damaged region; a microscopic one, linked to the size of inertial microelectromechanical systems (MEMS) to be used within a marginally-invasive health monitoring system. Results are provided for a square plate and for a section of fuselage with stiffeners, to show how the micro-sensors have to be deployed to maximize the capability to detect a damage, to assess the sensitivity of the results to the measurement noise and to also discuss the speedup in designing the network topology against a standard single-scale approach.

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          Most cited references 37

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          On the optimal sensor placement techniques for a bridge structure

           G. Zumpano,  M Meo (2005)
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            Optimal sensor placement methodology for parametric identification of structural systems

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              Structural health monitoring of smart composite materials by using EFPI and FBG sensors

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                Author and article information

                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                15 July 2017
                July 2017
                : 17
                : 7
                Affiliations
                [1 ]Dipartimento di Ingegneria Civile e Ambientale, Politecnico di Milano, Piazza L. da Vinci 32, 20133 Milano, Italy; giovanni.capellari@ 123456polimi.it (G.C.); matteo.bruggi@ 123456polimi.it (M.B.)
                [2 ]Dipartimento di Chimica, Materiali e Ingegneria Chimica “Giulio Natta”, Politecnico di Milano, Piazza L. daVinci 32, 20133 Milano, Italy; francesco.caimmi@ 123456polimi.it
                Author notes
                [* ]Correspondence: stefano.mariani@ 123456polimi.it ; Tel.: +39-02-2399-4279
                [†]

                These authors contributed equally to this work.

                Article
                sensors-17-01632
                10.3390/s17071632
                5539583
                28714888
                © 2017 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

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