Application of machine learning-base k-means clustering for feature recognition of fibre bragg grating acoustic signal from different delamination sizes

Application of machine learning-base k-means clustering for feature recognition of fibre bragg grating acoustic signal from different delamination sizes

Continuous monitoring of composite structures is crucial to preserve their integrity over their entire service life, particularly when it comes to detecting subtle interior degradation like delamination. Extensive research has been dedicated to examining the utilisation of conventional electrical se...

書誌詳細
主要な著者:	Ihsan Naiman, Ibrahim, Mohd Hafizi, Zohari, Mohd Fadhlan, Mohd Yusof
フォーマット:	Conference or Workshop Item
言語:	English English
出版事項:	IEEE 2024
主題:	T Technology (General) TJ Mechanical engineering and machinery
オンライン･アクセス:	http://umpir.ump.edu.my/id/eprint/42621/1/Application_of_Machine_Learning-Base_K-Means_Clustering_for_Feature_Recognition_of_Fibre_Bragg_Grating_Acoustic_Signal.pdf http://umpir.ump.edu.my/id/eprint/42621/2/Application_of_Machine_Learning-Base_K-Means_Clustering_for_Feature_Recognition_of_Fibre_Bragg_Grating_Acoustic_Signal_from_Different_Delamination_Sizes.pdf

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