2022
DOI: 10.1177/14759217211073335
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Statistics-based baseline-free approach for rapid inspection of delamination in composite structures using ultrasonic guided waves

Abstract: Delamination in composite structures is characterized by a resonant cavity wherein a fraction of an ultrasonic guided wave may be trapped. Based on this wave trapping phenomenon, we propose a baseline-free statistical approach for the identification and localization of delamination using sparse sampling and density-based spatial clustering of applications with noise (DBSCAN) technique. The proposed technique can be deployed for rapid inspection with minimal human intervention. The Performance of the proposed t… Show more

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Cited by 59 publications
(13 citation statements)
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“…Moreover, HHO 42 algorithm utilizes a randomly selected hawk from the current population for updating the exploration phase. In contrast, this OE‐HHO algorithm is introduced by adopting the best and worst fitness solutions to select the hawk from the current population for updating the exploration phase of HHO 43 , 44 . Thus, the exploration phase considers the best and worst fitness solutions to increase the “convergence rate of the algorithm.”…”
Section: Channel Estimation In Millimeter Wave Massive Mimo System Us...mentioning
confidence: 99%
“…Moreover, HHO 42 algorithm utilizes a randomly selected hawk from the current population for updating the exploration phase. In contrast, this OE‐HHO algorithm is introduced by adopting the best and worst fitness solutions to select the hawk from the current population for updating the exploration phase of HHO 43 , 44 . Thus, the exploration phase considers the best and worst fitness solutions to increase the “convergence rate of the algorithm.”…”
Section: Channel Estimation In Millimeter Wave Massive Mimo System Us...mentioning
confidence: 99%
“…The conventional DHOA 32 algorithm has the benefit of providing the optimum results by exploring and exploiting the optimization. Nevertheless, the downside of the DHOA algorithm 33 is attaining premature convergence and quickly getting trapped into local optima problems. To alleviate the remarkable limitations, a novel algorithm is introduced, termed ADHOA.…”
Section: Target Generation With Heuristic‐based Sequence Decompositio...mentioning
confidence: 99%
“…The suggested plant disease classification model utilizes the PCA 40 for selecting the essential features from the extracted features FTdext$$ {FT}_d^{\mathrm{ext}} $$ of the leaf disease. PCA is the feature selection method in broad areas like data compression, computer vision, machine learning, 41 image processing, and pattern compression. Feature selection using PCA is more significant for reducing the data dimensionality while processing the high‐dimensional patterns.…”
Section: Tuned Long Short‐term Memory With Recurrent Neural Network F...mentioning
confidence: 99%