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Integrated Video and Acoustic Emission Data Fusion for Intelligent Decision Making in Material Surface Inspection System

In the field of intelligent surface inspection systems, particular attention is paid to decision making problems, based on data from different sensors. The combination of such data helps to make an intelligent decision. In this research, an approach to intelligent decision making based on a data int...

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Autores principales: Chernov, Andrey V., Savvas, Ilias K., Alexandrov, Alexander A., Kartashov, Oleg O., Polyanichenko, Dmitry S., Butakova, Maria A., Soldatov, Alexander V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9656752/
https://www.ncbi.nlm.nih.gov/pubmed/36366252
http://dx.doi.org/10.3390/s22218554
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author Chernov, Andrey V.
Savvas, Ilias K.
Alexandrov, Alexander A.
Kartashov, Oleg O.
Polyanichenko, Dmitry S.
Butakova, Maria A.
Soldatov, Alexander V.
author_facet Chernov, Andrey V.
Savvas, Ilias K.
Alexandrov, Alexander A.
Kartashov, Oleg O.
Polyanichenko, Dmitry S.
Butakova, Maria A.
Soldatov, Alexander V.
author_sort Chernov, Andrey V.
collection PubMed
description In the field of intelligent surface inspection systems, particular attention is paid to decision making problems, based on data from different sensors. The combination of such data helps to make an intelligent decision. In this research, an approach to intelligent decision making based on a data integration strategy to raise awareness of a controlled object is used. In the following article, this approach is considered in the context of reasonable decisions when detecting defects on the surface of welds that arise after the metal pipe welding processes. The main data types were RGB, RGB-D images, and acoustic emission signals. The fusion of such multimodality data, which mimics the eyes and ears of an experienced person through computer vision and digital signal processing, provides more concrete and meaningful information for intelligent decision making. The main results of this study include an overview of the architecture of the system with a detailed description of its parts, methods for acquiring data from various sensors, pseudocodes for data processing algorithms, and an approach to data fusion meant to improve the efficiency of decision making in detecting defects on the surface of various materials.
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spelling pubmed-96567522022-11-15 Integrated Video and Acoustic Emission Data Fusion for Intelligent Decision Making in Material Surface Inspection System Chernov, Andrey V. Savvas, Ilias K. Alexandrov, Alexander A. Kartashov, Oleg O. Polyanichenko, Dmitry S. Butakova, Maria A. Soldatov, Alexander V. Sensors (Basel) Article In the field of intelligent surface inspection systems, particular attention is paid to decision making problems, based on data from different sensors. The combination of such data helps to make an intelligent decision. In this research, an approach to intelligent decision making based on a data integration strategy to raise awareness of a controlled object is used. In the following article, this approach is considered in the context of reasonable decisions when detecting defects on the surface of welds that arise after the metal pipe welding processes. The main data types were RGB, RGB-D images, and acoustic emission signals. The fusion of such multimodality data, which mimics the eyes and ears of an experienced person through computer vision and digital signal processing, provides more concrete and meaningful information for intelligent decision making. The main results of this study include an overview of the architecture of the system with a detailed description of its parts, methods for acquiring data from various sensors, pseudocodes for data processing algorithms, and an approach to data fusion meant to improve the efficiency of decision making in detecting defects on the surface of various materials. MDPI 2022-11-06 /pmc/articles/PMC9656752/ /pubmed/36366252 http://dx.doi.org/10.3390/s22218554 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Chernov, Andrey V.
Savvas, Ilias K.
Alexandrov, Alexander A.
Kartashov, Oleg O.
Polyanichenko, Dmitry S.
Butakova, Maria A.
Soldatov, Alexander V.
Integrated Video and Acoustic Emission Data Fusion for Intelligent Decision Making in Material Surface Inspection System
title Integrated Video and Acoustic Emission Data Fusion for Intelligent Decision Making in Material Surface Inspection System
title_full Integrated Video and Acoustic Emission Data Fusion for Intelligent Decision Making in Material Surface Inspection System
title_fullStr Integrated Video and Acoustic Emission Data Fusion for Intelligent Decision Making in Material Surface Inspection System
title_full_unstemmed Integrated Video and Acoustic Emission Data Fusion for Intelligent Decision Making in Material Surface Inspection System
title_short Integrated Video and Acoustic Emission Data Fusion for Intelligent Decision Making in Material Surface Inspection System
title_sort integrated video and acoustic emission data fusion for intelligent decision making in material surface inspection system
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9656752/
https://www.ncbi.nlm.nih.gov/pubmed/36366252
http://dx.doi.org/10.3390/s22218554
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