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

Meruane, Viviana; Véliz, Pablo; Droguett, Enrique López; Ortiz-Bernardin, Alejandro

doi:10.3390/e19040137

Cited by 6 publications

(9 citation statements)

References 29 publications

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“…In view of the optimization problem posed in Equation (24) for supervised learning, maximizing the entropy requires a weight solution that commits the least to all of the database samples [53].…”

Section: Principal Component Analysismentioning

confidence: 99%

See 1 more Smart Citation

Modal Strain Energy-Based Debonding Assessment of Sandwich Panels Using a Linear Approximation with Maximum Entropy

Meruane

Lasen

Droguett

et al. 2017

Entropy

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Sandwich structures are very attractive due to their high strength at a minimum weight, and, therefore, there has been a rapid increase in their applications. Nevertheless, these structures may present imperfect bonding or debonding between the skins and core as a result of manufacturing defects or impact loads, degrading their mechanical properties. To improve both the safety and functionality of these systems, structural damage assessment methodologies can be implemented. This article presents a damage assessment algorithm to localize and quantify debonds in sandwich panels. The proposed algorithm uses damage indices derived from the modal strain energy method and a linear approximation with a maximum entropy algorithm. Full-field vibration measurements of the panels were acquired using a high-speed 3D digital image correlation (DIC) system. Since the number of damage indices per panel is too large to be used directly in a regression algorithm, reprocessing of the data using principal component analysis (PCA) and kernel PCA has been performed. The results demonstrate that the proposed methodology accurately identifies debonding in composite panels.

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Section: Principal Component Analysismentioning

confidence: 99%

“…The principal advantage is that new data can be easily incorporated into the training database with no need to re-train the algorithm as in the case of ANNs. The LME algorithm was first developed for damage assessment [21,22], and Sanchez et al [23] and Meruane et al [24] employed it in impact identification.…”

Section: Introductionmentioning

confidence: 99%

Modal Strain Energy-Based Debonding Assessment of Sandwich Panels Using a Linear Approximation with Maximum Entropy

Meruane

Lasen

Droguett

et al. 2017

Entropy

Self Cite

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“…Acoustic emission has the characteristics of real-time, online, mature technology, low resource occupancy, relatively simple system and strong environmental adaptability, which is a very effective impact sensing and localization method. In this regard, some scholars have also conducted related research [36][37][38][39][40]. Through the maximum entropy linear approximation method, the four sensors were used to sense and locate the hammer impact on the aluminum plate, and compared with the artificial neural network and the support vector machine, it is found that it has better locating results and requires fewer parameters to be determined [37].…”

Section: Introductionmentioning

confidence: 99%

“…Through the maximum entropy linear approximation method, the four sensors were used to sense and locate the hammer impact on the aluminum plate, and compared with the artificial neural network and the support vector machine, it is found that it has better locating results and requires fewer parameters to be determined [37]. An impact recognition algorithm-based on principal component analysis and maximum entropy linear approximation was proposed to locate and quantify impact in aluminum and aluminum sandwich panels [39].…”

Section: Introductionmentioning

confidence: 99%

Impact Location on a Fan-Ring Shaped High-Stiffened Panel Using Adaptive Energy Compensation Threshold Filtering Method

Wang

Rui

et al. 2019

Applied Sciences

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The increase in the number of space debris is a serious threat to the safe operation of in-orbit spacecraft. The propagation law of the impact signal in the stiffened panel of the spacecraft’s sealed bulkhead is very complicated, and there is less research on the impact source location in the high-stiffened panel. In this paper, an adaptive energy compensation threshold filtering (AECTF) method based on acoustic emission is proposed, which can realize large-scale, fast and accurate locating of the impact source on the stiffened panel with less resource consumption. The influence law of the stiffeners on the lamb wave is analyzed by finite element simulation, and the Lamb wave energy factor curve is obtained. The correctness of the simulation is verified by the locating experiment on the impact point. The results show that the proposed AECTF method has better adaptability and can correctly locate the impact points in complicated locations. By selecting the appropriate frequency band to filter the signal, the locating accuracy and stability can be improved. When the frequency band is 100–200 kHz, the locating result is optimal, the average absolute error is 7.0 mm, the average relative error is 0.86%, and the error standard deviation is 3.5 mm. This study will generate fresh insight into the impact location technology of high-stiffened panel and provide a reference for the in-orbit spacecraft health monitoring system.

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“…For the sake of debonding detection, the linear dynamic FEA has been carried out in [49] to highlight the relative changes of dynamic response between a healthy sandwich plate and a debonded one. More advanced techniques using modal dataset to detect debonding in sandwich structures can be found in some recent works, for example, [50][51][52].…”

Section: Introductionmentioning

confidence: 99%

Linear and Nonlinear Dynamic Analyses of Sandwich Panels with Face Sheet‐to‐Core Debonding

Burlayenko

2018

Shock and Vibration

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A survey of recent developments in the dynamic analysis of sandwich panels with face sheet-to-core debonding is presented. The finite element method within the ABAQUS6 code is utilized. The emphasis is directed to the procedures used to elaborate linear and nonlinear models and to predict dynamic response of the sandwich panels. Recently developed models are presented, which can be applied for structural health monitoring algorithms of real-scale sandwich panels. First, various popular theories of intact sandwich panels are briefly mentioned and a model is proposed to effectively analyse the modal dynamics of debonded and damaged (due to impact) sandwich panels. The influences of debonding size, form, and location and number of such damage incidents on the modal characteristics of sandwich panels are shown. For nonlinear analysis, models based on implicit and explicit time integration schemes are presented and dynamic responses gained with those models are discussed. Finally, questions related to debonding progression at the face sheet-core interface when dynamic loading continues with time are briefly highlighted.

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

Cited by 6 publications

References 29 publications

Modal Strain Energy-Based Debonding Assessment of Sandwich Panels Using a Linear Approximation with Maximum Entropy

Modal Strain Energy-Based Debonding Assessment of Sandwich Panels Using a Linear Approximation with Maximum Entropy

Impact Location on a Fan-Ring Shaped High-Stiffened Panel Using Adaptive Energy Compensation Threshold Filtering Method

Linear and Nonlinear Dynamic Analyses of Sandwich Panels with Face Sheet‐to‐Core Debonding

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