Real-time structural health monitoring using statistical methods
dc.contributor | Ph.D. Program in Earthquake Engineering. | |
dc.contributor.advisor | Çaktı, Eser. | |
dc.contributor.author | Dar, Emrullah. | |
dc.date.accessioned | 2025-04-14T16:45:23Z | |
dc.date.available | 2025-04-14T16:45:23Z | |
dc.date.issued | 2023 | |
dc.description.abstract | The detection of structural damage relies on understanding the long-term variation of modal parameters and their relationship to changes in atmospheric conditions. This thesis aims to address this challenge by developing a real-time algorithm for structural health monitoring systems, which are becoming increasingly important. The algorithm uses statistical models developed by analyzing four years of modal frequencies, damping ratios, and mode shapes of Hagia Sophia, a UNESCO World Heritage structure, and their correlation with atmospheric parameters such as temperature, humidity, and wind speed. The algorithm uses four different regression models to predict the modal frequency as a function of the atmospheric conditions and selects the most suitable one. It then compares the predicted and measured frequencies to identify structural anomalies. The algorithm also employs the Modal Assurance Criterion (MAC), Coordinate Modal Assurance Criterion (COMAC), and Enhanced Coordinate Modal Assurance Criterion (ECOMAC) methods to examine the long-term variation of mode shapes. The algorithm is implemented in a user interface software called “AISHM,” which displays the modal parameters and the 3-D animation of the structure in real-time. The software also has the capability to track earthquakes and analyze the structural response in real-time. In summary, this thesis presents a comprehensive approach to real-time structural health monitoring using statistical models and advanced analysis techniques, which can have significant implications for maintaining and preserving historical structures. | |
dc.format.pages | xvi, 112 leaves | |
dc.identifier.other | Ph.D. Program in Earthquake Engineering. HTR 2023 S33 (Thes CMPE 2023 B37 PhD | |
dc.identifier.uri | https://digitalarchive.library.bogazici.edu.tr/handle/123456789/21820 | |
dc.publisher | Thesis (Ph.D.)-Bogazici University.Kandilli Observatory and Earthquake Research Institute, 2023. | |
dc.subject.lcsh | Structural health monitoring. | |
dc.subject.lcsh | Structural control (Engineering) | |
dc.title | Real-time structural health monitoring using statistical methods |
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