contributor author | Xiao-Mei Yang; Ting-Hua Yi; Chun-Xu Qu; Hong-Nan Li; Hua Liu | |
date accessioned | 2019-03-10T12:12:08Z | |
date available | 2019-03-10T12:12:08Z | |
date issued | 2019 | |
identifier other | %28ASCE%29AS.1943-5525.0000984.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4255083 | |
description abstract | The subject of vibration-based structural health monitoring (SHM) has attracted increasing attention, especially in the field of civil engineering. However, the development of these monitoring processes is not a simple task, with user interaction playing a significant role in the extraction of modal characteristics. In this paper, an automated operational modal analysis methodology based on an eigensystem realization algorithm (ERA) and a two-stage clustering strategy is proposed. Three crucial steps are addressed in this study. In the first phase, ERA is adopted to calculate modes from state-space models of different orders. Subsequently, the dissimilarity of modal parameters is employed as the features of fuzzy C-means (FCM) clustering to separate stable modes from unstable ones. The final step consists of grouping stable modes with similar structural properties to select physical modes. No user-specified parameter is required in the clustering procedure to single out physical modes. A practical bridge example is used to verify that the proposed method can estimate modal parameters effectively in real time. | |
publisher | American Society of Civil Engineers | |
title | Automated Eigensystem Realization Algorithm for Operational Modal Identification of Bridge Structures | |
type | Journal Paper | |
journal volume | 32 | |
journal issue | 2 | |
journal title | Journal of Aerospace Engineering | |
identifier doi | 10.1061/(ASCE)AS.1943-5525.0000984 | |
page | 04018148 | |
tree | Journal of Aerospace Engineering:;2019:;Volume ( 032 ):;issue: 002 | |
contenttype | Fulltext | |