Application of Subspace Identification Technique to Long Term Seismic Response Monitoring of Structures
Date Issued
2014
Date
2014
Author(s)
Lin, Pei-Chuan
Abstract
This study applies the subspace identification to system identification. Base on the Central Weather Bureau Taiwan Strong Motion Instrumentation Program (TSMIP) seven instrumented buildings and one 1/4 scale-down nuclear plant containment structure as the target structures for the analysis. Based on the collected seismic response data during the past, each event data will be analyzed to identify the dynamic characteristics of the structure during earthquake excitation. The result of analyses are in order to develop the proper earthquake-proof design norms for architectural structures in Taiwan. First, according to the use of the collection data two theoretical derivations are introduced：(1)the stochastic subspace identification(SSI) using output-only data, or the ambient vibration data for continuous monitoring；and (2)the subspace identification (SI) using input/output data, or the seismic responses. In this study, there are six normal steel or reinforced concrete buildings with different height, one mid-story isolation building, and a 1/4 scale-down nuclear plant containment structure are analyzed by using Subspace Identification. In order to study the parameters used in the analyses and discuss the change of structural properties during earthquake excitation. In the end, comparing the first natural frequencies from the system identification with the values which are suggested in internal earthquake-proof design norms. Hope to propose a new regression line that can have the best estimation between the height and the first natural frequencies. Furthermore, the effect of the isolation system and the dynamic characteristics will also be discussed in this study.
Subjects
隨機子空間識別
子空間識別
系統識別
中央氣象局結構物強震監測網
中間層隔震系統
Type
thesis
File(s)![Thumbnail Image]()
Loading...
Name
ntu-103-R99521223-1.pdf
Size
23.32 KB
Format
Adobe PDF
Checksum
(MD5):cdb927b8254891ceab467da8303410f1