Next Article in Journal
Permutation Entropy for the Characterisation of Brain Activity Recorded with Magnetoencephalograms in Healthy Ageing
Next Article in Special Issue
Is Turbulence a State of Maximum Energy Dissipation?
Previous Article in Journal
Ionic Liquids Confined in Silica Ionogels: Structural, Thermal, and Dynamical Behaviors
Previous Article in Special Issue
Physical Intelligence and Thermodynamic Computing
Open AccessArticle

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
*
Author to whom correspondence should be addressed.
Academic Editor: Dawn E. Holmes
Entropy 2017, 19(4), 137; https://doi.org/10.3390/e19040137
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)
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
Show Figures

Figure 1

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.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop