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Base de données et galerie internationale d'ouvrages d'art et du génie civil

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Structural Health Monitoring - v. 13, n. 4 (février 2014)

Publié:	février 2014

Articles dans ce numéro

Auteur(s)	Titre	Page(s)
Ng, Ching-Tai	Bayesian model updating approach for experimental identification of damage in beams using guided waves	359-373
Nguyen, Theanh / Chan, Tommy HT / Thambiratnam, David P.	Controlled Monte Carlo data generation for statistical damage identification employing Mahalanobis squared distance	461-472
Mustapha, Samir / Lu, Ye / Li, Jianchun / Ye, Lin	Damage detection in rebar-reinforced concrete beams based on time reversal of guided waves	347-358
Dackermann, Ulrike / Smith, Wade A. / Randall, Robert B.	Damage identification based on response-only measurements using cepstrum analysis and artificial neural networks	430-444
Nguyen, Theanh / Chan, Tommy HT / Thambiratnam, David P.	Field validation of controlled Monte Carlo data generation for statistical damage identification employing Mahalanobis squared distance	473-488
Dackermann, Ulrike / Skinner, Bradley / Li, Jianchun	Guided wave–based condition assessment of in situ timber utility poles using machine learning algorithms	374-388
Khoa, Nguyen LD / Zhang, Bang / Wang, Yang / Chen, Fang / Mustapha, Samir	Robust dimensionality reduction and damage detection approaches in structural health monitoring	406-417
Bandara, Rupika P. / Chan, Tommy HT / Thambiratnam, David P.	Structural damage detection method using frequency response functions	418-429
Ay, Ali M. / Wang, Ying	Structural damage identification based on self-fitting ARMAX model and multi-sensor data fusion	445-460
Li, Jun / Hao, Hong	Substructure damage identification based on wavelet-domain response reconstruction	389-405

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IssueID
56033
Publié(e) le:
11.02.2021
Modifié(e) le:
11.02.2021

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