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A maximum entropy supervised learning algorithm for the identification of skin/core debonding in honeycomb aluminium panels

  • April 11, 2020
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The Twelfth International Conference on Computational Structures Technology (CST2014) 2 – 5 September 2014, Naples, Italy Proceedings of CST2014 Civil-Comp Press, Stirlingshire, UK, Paper 120, 2014 V. Meruane, V. del Fierro and A. Ortiz-Bernardin Abstract Honeycomb sandwich structures are used in a wide variety of applications. Nevertheless, due to manufacturing defects or impact loads, these

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Accepted Paper: Impact location and quantification on an aluminum sandwich panel using principal component analysis and linear approximation with maximum entropy

  • March 30, 2017
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Paper Accepted for Publication in Entropy V. Meruane, P. Véliz, E. López Droguett, A. Ortiz-Bernardin, “Impact location and quantification on an aluminum sandwich panel using principal component analysis and linear approximation with maximum entropy.” ABSTRACT To avoid structural failures it is of critical importance to detect, locate and quantify impact damage as soon as it

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Impact location and quantification on an aluminum sandwich panel using principal component analysis and linear approximation with maximum entropy

  • March 30, 2017
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Entropy Vol. 19, No. 4, pp. 137, 2017 V. Meruane, P. Véliz, E. López Droguett, A. Ortiz-Bernardin Abstract To avoid structural failures it is of critical importance to detect, locate and quantify impact damage as soon as it occurs. This can be achieved by impact identification methodologies, which continuously monitor the structure, detecting, locating, and quantifying

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Accepted Paper: A novel impact identification algorithm based on a linear approximation with maximum entropy

  • August 8, 2016
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Paper Accepted for Publication in Smart Materials and Structures N. Sanchez, V. Meruane, A. Ortiz-Bernardin, “A novel impact identification algorithm based on a linear approximation with maximum entropy.” ABSTRACT This article presents a novel impact identification algorithm that uses a linear approximation handled by a statistical inference model based on the maximum-entropy principle, termed linear

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A novel impact identification algorithm based on a linear approximation with maximum entropy

  • August 8, 2016
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Smart Materials and Structures Vol. 25, No. 9, pp. 095050, 2016 N. Sanchez, V. Meruane, A. Ortiz-Bernardin Abstract This article presents a novel impact identification algorithm that uses a linear approximation handled by a statistical inference model based on the maximum-entropy principle, termed linear approximation with maximum entropy (LME). Unlike other regression algorithms as Artificial

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Paper Accepted: A Maximum Entropy Approach to Assess Debonding in Honeycomb Aluminium Plates

  • May 23, 2014
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Paper Accepted for Publication in Entropy V. Meruane, V. del Fierro, A. Ortiz-Bernardin, “A maximum entropy approach to assess debonding in honeycomb aluminium plates.” ABSTRACT Honeycomb sandwich structures are used in a wide variety of applications. Nevertheless, due to manufacturing defects or impact loads, these structures can be subject to imperfect bonding or debonding between

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