발간년도 : [2023]
| 논문정보 |
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| 논문명(한글) |
[Vol.18, No.2] Artificial Intelligence-based Structural Safety Management Prediction System |
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| 논문투고자 |
Jungjip Kim, Jaeyoon Lim, Sunghwan Kim, Hoekyung Jung |
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| 논문내용 |
A sensor and detector that can monitor the safety status in real time has been installed in the structure to determine an emergency situation. Systems have been developed that analyze the data coming from the sensor and the detector and compare it with the safety diagnosis standard method and manage it. With the developed system, it is possible to understand the state of the structure in real time to some extent, and it is contributing to the safety of the structure. However, these existing systems can determine the current safety state of a structure, but cannot predict the state of the structure in the future. Therefore, in this paper, by applying artificial intelligence to the existing structural safety
management system, it is possible to not only understand the current safety status of structures, but also to predict the safety status of structures from the near future to the distant future to prevent safety accidents in advance. Predicting the instability of a structure in the future makes it easier to maintain, repair, and manage the structure through safety diagnosis instructions, repairs, and reinforcement work. The system of this paper will be able to minimize damage to public property and contribute to national safety policy by producing and sharing safety and security information through the status information of public and private facilities. |
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