Computational methods for wireless structural health monitoring of cultural heritages

Abstract : The structural health monitoring of cultural heritages is addressed in this paper. The arising inverse problem is solved through the Learning-by-Examples (LBE) paradigm, exploiting data collected by a Wireless Sensor Network (WSN). More in detail, low-cost and low-size sensing devices are spread over the scenario to be monitored, allowing environmental data as well as acceleration and vibration information to be acquired and processed by means of a Support Vector Machine (SVM) in order to detect the presence/absence of a damage in the monitored structure. The proposed approach has been preliminary validated in a laboratory controlled environment, demonstrating promising performance.
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Article dans une revue
Journal of Physics: Conference Series, IOP Publishing, 2018, 1131, pp.1-7
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https://hal.archives-ouvertes.fr/hal-01962630
Contributeur : Andrea Massa <>
Soumis le : jeudi 20 décembre 2018 - 17:07:04
Dernière modification le : jeudi 21 février 2019 - 10:50:27

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  • HAL Id : hal-01962630, version 1

Citation

Michael Bertolli, Massimo Donelli, Andrea Massa, Giacomo Oliveri, Alesandro Polo, et al.. Computational methods for wireless structural health monitoring of cultural heritages. Journal of Physics: Conference Series, IOP Publishing, 2018, 1131, pp.1-7. 〈hal-01962630〉

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