Cargando…

Intelligent Tensioning Method for Prestressed Cables Based on Digital Twins and Artificial Intelligence

In this study, to address the problems of multiple dimensions, large scales, complex tension resource scheduling, and strict quality control requirements in the tensioning process of cables in prestressed steel structures, the technical characteristics of digital twins (DTs) and artificial intellige...

Descripción completa

Detalles Bibliográficos
Autores principales: Liu, Zhansheng, Shi, Guoliang, Zhang, Anshan, Huang, Chun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7762533/
https://www.ncbi.nlm.nih.gov/pubmed/33302362
http://dx.doi.org/10.3390/s20247006
_version_ 1783627828624883712
author Liu, Zhansheng
Shi, Guoliang
Zhang, Anshan
Huang, Chun
author_facet Liu, Zhansheng
Shi, Guoliang
Zhang, Anshan
Huang, Chun
author_sort Liu, Zhansheng
collection PubMed
description In this study, to address the problems of multiple dimensions, large scales, complex tension resource scheduling, and strict quality control requirements in the tensioning process of cables in prestressed steel structures, the technical characteristics of digital twins (DTs) and artificial intelligence (AI) are analyzed. An intelligent tensioning of prestressed cables method driven by the integration of DTs and AI is proposed. Based on the current research status of cable tensioning and DTs, combined with the goal of intelligent tensioning, a fusion mechanism for DTs and AI is established and their integration to drive intelligent tensioning of prestressed cables technology is analyzed. In addition, the key issues involved in the construction of an intelligent control center driven by the integration of DTs and AI are discussed. By considering the construction elements of space and time dimensions, the tensioning process is controlled at multiple levels, thereby realizing the intelligent tensioning of prestressed cables. Driven by intelligent tensioning methods, the safety performance evaluation of the intelligent tensioning process is analyzed. Combined with sensing equipment and intelligent algorithms, a high-fidelity twin model and three-dimensional integrated data model are constructed to realize closed-loop control of the intelligent tensioning safety evaluation. Through the study of digital twins and artificial intelligence fusion to drive the intelligent tensioning method for prestressed cables, this study focuses on the analysis of the intelligent evaluation of safety performance. This study provides a reference for fusion applications with DTs and AI in intelligent tensioning of prestressed cables.
format Online
Article
Text
id pubmed-7762533
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-77625332020-12-26 Intelligent Tensioning Method for Prestressed Cables Based on Digital Twins and Artificial Intelligence Liu, Zhansheng Shi, Guoliang Zhang, Anshan Huang, Chun Sensors (Basel) Article In this study, to address the problems of multiple dimensions, large scales, complex tension resource scheduling, and strict quality control requirements in the tensioning process of cables in prestressed steel structures, the technical characteristics of digital twins (DTs) and artificial intelligence (AI) are analyzed. An intelligent tensioning of prestressed cables method driven by the integration of DTs and AI is proposed. Based on the current research status of cable tensioning and DTs, combined with the goal of intelligent tensioning, a fusion mechanism for DTs and AI is established and their integration to drive intelligent tensioning of prestressed cables technology is analyzed. In addition, the key issues involved in the construction of an intelligent control center driven by the integration of DTs and AI are discussed. By considering the construction elements of space and time dimensions, the tensioning process is controlled at multiple levels, thereby realizing the intelligent tensioning of prestressed cables. Driven by intelligent tensioning methods, the safety performance evaluation of the intelligent tensioning process is analyzed. Combined with sensing equipment and intelligent algorithms, a high-fidelity twin model and three-dimensional integrated data model are constructed to realize closed-loop control of the intelligent tensioning safety evaluation. Through the study of digital twins and artificial intelligence fusion to drive the intelligent tensioning method for prestressed cables, this study focuses on the analysis of the intelligent evaluation of safety performance. This study provides a reference for fusion applications with DTs and AI in intelligent tensioning of prestressed cables. MDPI 2020-12-08 /pmc/articles/PMC7762533/ /pubmed/33302362 http://dx.doi.org/10.3390/s20247006 Text en © 2020 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Liu, Zhansheng
Shi, Guoliang
Zhang, Anshan
Huang, Chun
Intelligent Tensioning Method for Prestressed Cables Based on Digital Twins and Artificial Intelligence
title Intelligent Tensioning Method for Prestressed Cables Based on Digital Twins and Artificial Intelligence
title_full Intelligent Tensioning Method for Prestressed Cables Based on Digital Twins and Artificial Intelligence
title_fullStr Intelligent Tensioning Method for Prestressed Cables Based on Digital Twins and Artificial Intelligence
title_full_unstemmed Intelligent Tensioning Method for Prestressed Cables Based on Digital Twins and Artificial Intelligence
title_short Intelligent Tensioning Method for Prestressed Cables Based on Digital Twins and Artificial Intelligence
title_sort intelligent tensioning method for prestressed cables based on digital twins and artificial intelligence
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7762533/
https://www.ncbi.nlm.nih.gov/pubmed/33302362
http://dx.doi.org/10.3390/s20247006
work_keys_str_mv AT liuzhansheng intelligenttensioningmethodforprestressedcablesbasedondigitaltwinsandartificialintelligence
AT shiguoliang intelligenttensioningmethodforprestressedcablesbasedondigitaltwinsandartificialintelligence
AT zhanganshan intelligenttensioningmethodforprestressedcablesbasedondigitaltwinsandartificialintelligence
AT huangchun intelligenttensioningmethodforprestressedcablesbasedondigitaltwinsandartificialintelligence