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Browsing byAuthorDackermann, U
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Showing results 47 to 58 of 58
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Issue Date
Title
Author(s)
2010
Quantification of notch-type damage in a two-storey framed structure utilising frequency response functions and artificial neural networks'
Dackermann, U
;
Li, JL
;
Samali, BS
2012
R&D of NDTs for Timber Utility Poles in Service - Challenges and Applications (Extension for Bridge Sub-Structures and Wharf Structures)
Dackermann, U
;
Li, JL
;
Subhani, MMS
2013
Separation of bi-directional stress waves for the non-destructive condition assessment of in-service timber utility
Jozi, BJ
;
Dackermann, U
;
Braun, RB
;
Li, JL
;
Samali, BS
2017-01-01
Simulation of various damage scenarios using finite element modelling for structural health monitoring systems
Nguyen, VV
;
Li, J
;
Yu, Y
;
Dackermann, U
;
Alamdari, MM
2008-12-01
Structural damage identification utilising PCA-compressed frequency response functions and neural network ensembles
Dackermann, U
;
Li, J
;
Samali, B
2014-10-22
Structural health monitoring in civil structures based on the time series analysis
Mustapha, S
;
Nguyen, K
;
Runcie, P
;
Hu, Y
;
Dackermann, U
;
Nguyen, VV
;
Li, J
;
Ye, L
;
Kotze, RK
2013-08-12
Transmissibility function analysis for boundary damage identification of a two-storey framed structure using artificial neural networks
Dackermann, U
;
Li, J
;
Samali, B
2019-10-01
Vibration behaviour of steel-timber composite floors, part (1): Experimental & numerical investigation
A. Chiniforush, A
;
Makki Alamdari, M
;
Dackermann, U
;
Valipour, HR
;
Akbarnezhad, A
2013-10-30
A vibration-based approach for the estimation of the loss of composite action in timber composite systems
Dackermann, U
;
Li, JC
;
Rijal, R
;
Samali, B
2014-01-01
Vibration-based damage detection for timber structures in Australia
Samali, B
;
Li, J
;
Dackermann, U
;
Choi, FC
2009
Vibration-based damage identification methods for civil engineering structures using artificial neural networks
Dackermann, U
2019-01-01
Wavelet packet energy–based damage identification of wood utility poles using support vector machine multi-classifier and evidence theory
Yu, Y
;
Dackermann, U
;
Li, J
;
Niederleithinger, E