Damage Detection in Composites By Artificial Neural Networks Trained By Using in Situ Distributed Strains
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Damage Detection in Composites By Artificial Neural Networks Trained By Using in Situ Distributed Strains America Califano 1,2 & Neha Chandarana 2,3 & Luigi Grassia 1 & Alberto D’Amore 1 & Constantinos Soutis 2,4 Received: 26 June 2020 / Revised: 26 June 2020 / Accepted: 21 July 2020 # The Author(s) 2020
Abstract
In this paper, a passive structural health monitoring (SHM) method capable of detecting the presence of damage in carbon fibre/epoxy composite plates is developed. The method requires the measurement of strains from the considered structure, which are used to set up, train, and test artificial neural networks (ANNs). At the end of the training phase, the networks find correlations between the given strains, which represent the ‘fingerprint’ of the structure under investigation. Changes in the distribution of these strains is captured by assessing differences in the previously identified strain correlations. If any cause generates damage that alters the strain distribution, this is considered as a reason for further detailed structural inspection. The novelty of the strain algorithm comes from its independence from both the choice of material and the loading condition. It does not require the prior knowledge of material properties based on stress-strain relationships and, as the strain correlations represent the structure and its mechanical behaviour, they are valid for the full range of operating loads. An implementation of such approach is herein presented based on the usage of a distributed optical fibre sensor that allows to obtain strain measurement with an incredibly high resolution. Keywords Structural health monitoring . Composite materials . Machine learning . Optical fibres . Distributed strain sensing
* America Califano [email protected]; [email protected] * Constantinos Soutis [email protected]
1
Department of Engineering, University of Campania “Luigi Vanvitelli”, Aversa 81031, Italy
2
i-Composites Lab, The University of Manchester, Manchester, UK
3
Henry Royce Institute, The University of Manchester, Manchester, UK
4
Aerospace Research Institute, The University of Manchester, Manchester, UK
Applied Composite Materials
1 Introduction Fibre reinforced composite materials exhibit superior mechanical properties, in terms of specific strength and modulus, compared to metallic materials. They are desirable for use in the aeronautical and aerospace industries due to the increasing demand for lightweight structures. The content of composites in aircraft structures has increased from less than 5% in the late 80 s to more than 50% in recent years [1]. The design of composite structures is often complex due to the challenges associated with their manufacture and the effect on the resulting mechanical properties. The manufacturing process may introduce defects such as voids, resin rich regions, and misalignment of fibres. The design of composite structures becomes more critical where the concerned structures are subjected to anomalous or cyclic loadi
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