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Entropy 2017, 19(4), 137; doi:10.3390/e19040137

Impact Location and Quantification on an Aluminum Sandwich Panel Using Principal Component Analysis and Linear Approximation with Maximum Entropy

Department of Mechanical Engineering, Universidad de Chile, Beauchef 851, Santiago 8370456, Chile
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Academic Editor: Dawn E. Holmes
Received: 4 January 2017 / Revised: 7 March 2017 / Accepted: 19 March 2017 / Published: 25 March 2017
(This article belongs to the Special Issue Maximum Entropy and Its Application II)
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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 impacts as they occur. This article presents an improved impact identification algorithm that uses principal component analysis (PCA) to extract features from the monitored signals and an algorithm based on linear approximation with maximum entropy to estimate the impacts. The proposed methodology is validated with two experimental applications, which include an aluminum plate and an aluminum sandwich panel. The results are compared with those of other impact identification algorithms available in literature, demonstrating that the proposed method outperforms these algorithms. View Full-Text
Keywords: impact identification; barely visible impact damage; principal component analysis; linear approximation; maximum entropy; sandwich panel impact identification; barely visible impact damage; principal component analysis; linear approximation; maximum entropy; sandwich panel
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MDPI and ACS Style

Meruane, V.; Véliz, P.; López Droguett, E.; Ortiz-Bernardin, A. Impact Location and Quantification on an Aluminum Sandwich Panel Using Principal Component Analysis and Linear Approximation with Maximum Entropy. Entropy 2017, 19, 137.

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