{"title":"基于数字孪生和深度学习的港口水工结构耐久性寿命预测技术","authors":"Chang Guo","doi":"10.1109/CIPAE53742.2021.00051","DOIUrl":null,"url":null,"abstract":"Digital twin has the characteristics of high- fidelity behavior simulation, and deep learning has powerful data mining capabilities. Our country's port and hydraulic building facilities are now the world's largest, most of which are concrete structures. However, there will be more freeze-thaw damage to concrete structures, and there is less research on the durability test methods of hydraulic structures, especially the life prediction of hydraulic structures after freeze-thaw damage repairs. Based on this, this article has launched a research on the durability life prediction technology of port hydraulic structures driven by the integration of digital twins and deep learning. Aiming at the difficult problem of predicting and maintaining the status of port hydraulic buildings in a harsh working environment, combined with the high-fidelity behavior simulation characteristics of digital twins and the powerful data mining capabilities of deep learning, this paper mainly studies the mutual driving of digital twins and deep learning. In this paper, multiple digital twins of the shearer are constructed based on multiple physical and spatial parameters. Through multiple visual displays and data analysis in the virtual space, the health status is predicted, and a port based on deep machine learning is established. The residual life prediction model of the key parts of hydraulic structures realizes real-time monitoring on the network; integrates the residual life and residual life value of the building parts driven by data, and integrates the status of the digital twin and the residual life of the parts and the port Durability assessment of hydraulic construction buildings. The research results show that although a little steel slag can significantly improve the heat resistance and compressive strength of concrete, when the content of steel slag exceeds a certain meaning, the heat resistance and compressive strength of concrete will change. When the steel slag content reaches 10%, the effect is best. When the steel slag content reaches 20%, the 28d concrete compressive strength and strength will not have a big impact.","PeriodicalId":414529,"journal":{"name":"2021 International Conference on Computers, Information Processing and Advanced Education (CIPAE)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Durability Life Prediction Technology of Port Hydraulic Structure Driven by the Fusion of Digital Twins and Deep Learning\",\"authors\":\"Chang Guo\",\"doi\":\"10.1109/CIPAE53742.2021.00051\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Digital twin has the characteristics of high- fidelity behavior simulation, and deep learning has powerful data mining capabilities. Our country's port and hydraulic building facilities are now the world's largest, most of which are concrete structures. However, there will be more freeze-thaw damage to concrete structures, and there is less research on the durability test methods of hydraulic structures, especially the life prediction of hydraulic structures after freeze-thaw damage repairs. Based on this, this article has launched a research on the durability life prediction technology of port hydraulic structures driven by the integration of digital twins and deep learning. Aiming at the difficult problem of predicting and maintaining the status of port hydraulic buildings in a harsh working environment, combined with the high-fidelity behavior simulation characteristics of digital twins and the powerful data mining capabilities of deep learning, this paper mainly studies the mutual driving of digital twins and deep learning. In this paper, multiple digital twins of the shearer are constructed based on multiple physical and spatial parameters. Through multiple visual displays and data analysis in the virtual space, the health status is predicted, and a port based on deep machine learning is established. The residual life prediction model of the key parts of hydraulic structures realizes real-time monitoring on the network; integrates the residual life and residual life value of the building parts driven by data, and integrates the status of the digital twin and the residual life of the parts and the port Durability assessment of hydraulic construction buildings. The research results show that although a little steel slag can significantly improve the heat resistance and compressive strength of concrete, when the content of steel slag exceeds a certain meaning, the heat resistance and compressive strength of concrete will change. When the steel slag content reaches 10%, the effect is best. When the steel slag content reaches 20%, the 28d concrete compressive strength and strength will not have a big impact.\",\"PeriodicalId\":414529,\"journal\":{\"name\":\"2021 International Conference on Computers, Information Processing and Advanced Education (CIPAE)\",\"volume\":\"87 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 International Conference on Computers, Information Processing and Advanced Education (CIPAE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIPAE53742.2021.00051\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Computers, Information Processing and Advanced Education (CIPAE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIPAE53742.2021.00051","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Durability Life Prediction Technology of Port Hydraulic Structure Driven by the Fusion of Digital Twins and Deep Learning
Digital twin has the characteristics of high- fidelity behavior simulation, and deep learning has powerful data mining capabilities. Our country's port and hydraulic building facilities are now the world's largest, most of which are concrete structures. However, there will be more freeze-thaw damage to concrete structures, and there is less research on the durability test methods of hydraulic structures, especially the life prediction of hydraulic structures after freeze-thaw damage repairs. Based on this, this article has launched a research on the durability life prediction technology of port hydraulic structures driven by the integration of digital twins and deep learning. Aiming at the difficult problem of predicting and maintaining the status of port hydraulic buildings in a harsh working environment, combined with the high-fidelity behavior simulation characteristics of digital twins and the powerful data mining capabilities of deep learning, this paper mainly studies the mutual driving of digital twins and deep learning. In this paper, multiple digital twins of the shearer are constructed based on multiple physical and spatial parameters. Through multiple visual displays and data analysis in the virtual space, the health status is predicted, and a port based on deep machine learning is established. The residual life prediction model of the key parts of hydraulic structures realizes real-time monitoring on the network; integrates the residual life and residual life value of the building parts driven by data, and integrates the status of the digital twin and the residual life of the parts and the port Durability assessment of hydraulic construction buildings. The research results show that although a little steel slag can significantly improve the heat resistance and compressive strength of concrete, when the content of steel slag exceeds a certain meaning, the heat resistance and compressive strength of concrete will change. When the steel slag content reaches 10%, the effect is best. When the steel slag content reaches 20%, the 28d concrete compressive strength and strength will not have a big impact.