Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/9424
Title: High-rise structure damage identification based on pseudo-transfer function
Authors: Li, W
Du, Y
Ni, Y
Li, H
Keywords: ARX model(autoregressive model with exogenous input)
Damage identification
Fit ratio
High-rise structure
Pseudo-transform function
Issue Date: 2015
Publisher: 南京航空航天大學
Source: 振動, 測試與診斷 (Journal of vibration, measurement & diagnosis), 2015, v. 35, no. 1, p. 63-69 How to cite?
Journal: 振動, 測試與診斷 (Journal of vibration, measurement & diagnosis) 
Abstract: A novel damage location method, which is based on the pseudo-transfer function (PTF) established by the ARX model (autoregressive model with eXogenous input), is proposed based on the conception of the transform function reflected the relationship of the input-output (structural characteristics). According to the correlation with the degree of freedom (DOF), the DOF is grouped, the response of one DOF is chosen as a reference channel (which is the ARX model output), and the response of the other DOF correlating with the reference channel is taken as the input of the ARX model. The reference PTF is established using the responses of the health structure. After creating the reference PTF, these models are used to predict the data from the damaged structure. The difference between the fit ratios is used as the damage feature. The methodology is applied to the reduced finite element model of the Canton Tower, and the threshold of damage is established using the change of the fit ratios of the responses with Gaussian white noise of the health structure. The results show that this methodology is successful in damage identification and localization, and can also determine the severity of damage under noise effects.
URI: http://hdl.handle.net/10397/9424
ISSN: 1004-6801
DOI: 10.16450/j.cnki.issn.1004-6801.2015.01.010
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page view(s)

65
Last Week
2
Last month
Checked on Aug 13, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.