dc.citation.conferencePlace |
KO |
- |
dc.citation.conferencePlace |
Jeju |
- |
dc.citation.title |
Asia Pacific Conference of the Prognostics and Health Management Society 2021 |
- |
dc.contributor.author |
Kim, Minsun |
- |
dc.contributor.author |
Lee, Jaebeom |
- |
dc.contributor.author |
Lee, Young-Joo |
- |
dc.date.accessioned |
2024-01-31T21:36:51Z |
- |
dc.date.available |
2024-01-31T21:36:51Z |
- |
dc.date.created |
2021-12-29 |
- |
dc.date.issued |
2021-09-09 |
- |
dc.description.abstract |
Structural condition monitoring techniques based on sensor data have been studied, and they have been applied to various civil infrastructures including cable-stayed bridges for assessing their structural safety. However, such a technique typically requires pre-defining a threshold to detect anomalies, which can be heuristic. This study suggests a new probabilistic method for the cable condition monitoring of cable-stayed bridges using Gaussian process regression (GPR). To monitor the condition of multiple cables in parallel, the GPR analysis is conducted based on multi-input multi-output (MIMO), which enables to set the threshold values for anomaly detection in a reasonable manner. To demonstrate the proposed method, it is applied to an actual cable-stayed bridge in the Republic of Korea, and the corresponding analysis results are presented. |
- |
dc.identifier.bibliographicCitation |
Asia Pacific Conference of the Prognostics and Health Management Society 2021 |
- |
dc.identifier.uri |
https://scholarworks.unist.ac.kr/handle/201301/77019 |
- |
dc.language |
영어 |
- |
dc.publisher |
Asia Pacific Conference of the Prognostics and Health Management Society 2021 |
- |
dc.title |
Probabilistic cable condition monitoring for cable-stayed bridges using Gaussian process regression |
- |
dc.type |
Conference Paper |
- |
dc.date.conferenceDate |
2021-09-08 |
- |