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Assessment of ultrasonic data of signals backscattered by mortar using the principal component analysis

In this paper, we present the assessment of ultrasonic parameters of signals backscattered by mortar using the Principal Component Method. The measurement has been performed by the ultrasonic reflection technique using a transducer with a central frequency 0.5 MHz. The samples examined consist of sp...

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Autores principales: Lotfi, Hicham, Izbaim, Driss, Bita, Hassan, Mesbah, H., Banouni, H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7820378/
https://www.ncbi.nlm.nih.gov/pubmed/33521181
http://dx.doi.org/10.1016/j.dib.2021.106741
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author Lotfi, Hicham
Izbaim, Driss
Bita, Hassan
Mesbah, H.
Banouni, H.
author_facet Lotfi, Hicham
Izbaim, Driss
Bita, Hassan
Mesbah, H.
Banouni, H.
author_sort Lotfi, Hicham
collection PubMed
description In this paper, we present the assessment of ultrasonic parameters of signals backscattered by mortar using the Principal Component Method. The measurement has been performed by the ultrasonic reflection technique using a transducer with a central frequency 0.5 MHz. The samples examined consist of specimen mortar mixtures prepared with ratio cement/sand (c/s = 0.5) and water/cement (w/c = 0.65) and studied at three temperatures 25 °C, 32 °C and 42 °C. The projection of the data showed that more than 93% of the information is retained and presented in 2D space. The correlation between Acoustic Impedance and Ultrasonic Velocity at 25 °C, 32 °C and 42 °C are 96.95%, 99.98%, and 99.98% respectively. The data are associated with the research article “Ultrasonic Characterization and Hardening of Mortar Using the Reflection Technique” (H.LOTFI and al.).
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spelling pubmed-78203782021-01-29 Assessment of ultrasonic data of signals backscattered by mortar using the principal component analysis Lotfi, Hicham Izbaim, Driss Bita, Hassan Mesbah, H. Banouni, H. Data Brief Data Article In this paper, we present the assessment of ultrasonic parameters of signals backscattered by mortar using the Principal Component Method. The measurement has been performed by the ultrasonic reflection technique using a transducer with a central frequency 0.5 MHz. The samples examined consist of specimen mortar mixtures prepared with ratio cement/sand (c/s = 0.5) and water/cement (w/c = 0.65) and studied at three temperatures 25 °C, 32 °C and 42 °C. The projection of the data showed that more than 93% of the information is retained and presented in 2D space. The correlation between Acoustic Impedance and Ultrasonic Velocity at 25 °C, 32 °C and 42 °C are 96.95%, 99.98%, and 99.98% respectively. The data are associated with the research article “Ultrasonic Characterization and Hardening of Mortar Using the Reflection Technique” (H.LOTFI and al.). Elsevier 2021-01-14 /pmc/articles/PMC7820378/ /pubmed/33521181 http://dx.doi.org/10.1016/j.dib.2021.106741 Text en © 2021 The Authors. Published by Elsevier Inc. http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Lotfi, Hicham
Izbaim, Driss
Bita, Hassan
Mesbah, H.
Banouni, H.
Assessment of ultrasonic data of signals backscattered by mortar using the principal component analysis
title Assessment of ultrasonic data of signals backscattered by mortar using the principal component analysis
title_full Assessment of ultrasonic data of signals backscattered by mortar using the principal component analysis
title_fullStr Assessment of ultrasonic data of signals backscattered by mortar using the principal component analysis
title_full_unstemmed Assessment of ultrasonic data of signals backscattered by mortar using the principal component analysis
title_short Assessment of ultrasonic data of signals backscattered by mortar using the principal component analysis
title_sort assessment of ultrasonic data of signals backscattered by mortar using the principal component analysis
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7820378/
https://www.ncbi.nlm.nih.gov/pubmed/33521181
http://dx.doi.org/10.1016/j.dib.2021.106741
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