dc.contributor |
Ph.D. Program in Earthquake Engineering. |
|
dc.contributor.advisor |
Şafak, Erdal. |
|
dc.contributor.author |
Kaya, Yavuz. |
|
dc.date.accessioned |
2023-03-16T12:56:19Z |
|
dc.date.available |
2023-03-16T12:56:19Z |
|
dc.date.issued |
2009. |
|
dc.identifier.other |
EQE 2009 K38 PhD |
|
dc.identifier.uri |
http://digitalarchive.boun.edu.tr/handle/123456789/18288 |
|
dc.description.abstract |
Framework of the structural health monitoring (SHM) is to detect and locate the damage in the structure. Real-time identification of modal properties of a structure is very important in SHM because the changes in modal properties during its service life may be related to the damage on the structure. Therefore, it is obvious that modal properties should be monitored and identified accurately in real-time in order to have a good estimate in SHM. A new real-time software together with new real-time tools/techniques have been developed in this dissertation to be used in SHM to identify the modal properties of the structure in real-time. In the new proposed tool the real-time modal frequencies are estimated by using basic signal processing tools such as baseline correction, band-pass filtering, windowing, FFT, and smoothing while the real-time damping is estimated with half-power bandwidth technique and/or Logarithmic decrement technique. The developed real-time software, KOERIMIDS, has been tested with the ambient vibration data set recorded from Hagia Sophia Museum. Modal properties of the structure have been identified successfully in real-time. Results of the Hagia Sophia test have been compared with the previous studies conducted by different researchers. Comparison shows that the results of the KOERI-MIDS are in good agreement with that of the previous studies. |
|
dc.format.extent |
30cm. |
|
dc.publisher |
Thesis (Ph.D.)-Bogazici University.Kandilli Observatory and Earthquake Research Institute, 2009. |
|
dc.subject.lcsh |
Structural health monitoring. |
|
dc.subject.lcsh |
Modal analysis. |
|
dc.title |
Tools and techniques for real time modal identification |
|
dc.format.pages |
xvi, 123 leaves; |
|