Structural Health Monitoring - v. 21, n. 5 (mars 2022)

Publié:	mars 2022

Articles dans ce numéro

Auteur(s)	Titre	Page(s)
Zhang, Xin / Wang, Hui / Hou, Borui / Xu, Jiawen / Yan, Ruqiang	1D-CNN-based damage identification method based on piezoelectric impedance using adjustable inductive shunt circuitry for data enrichment	147592172110497
Qu, Jinxiu / Shi, Changquan / Guo, Jinzhu / Shi, Xiaowei / Huang, Jiaqi / Cao, Wei / Sun, Jinjuan	Aging state detection of viscoelastic sandwich structure using redundant second generation wavelet packet transform and fuzzy support vector data description	147592172110575
Esu, Obukho E. / Wang, Ying / Chryssanthopoulos, Marios K.	A baseline-free method for damage identification in pipes from local vibration mode pair frequencies	147592172110523
Zhang, Yi-Ming / Wang, Hao / Bai, Yu / Mao, Jian-Xiao / Xu, Yi-Chao	Bayesian dynamic regression for reconstructing missing data in structural health monitoring	147592172110537
Xue, Songtao / Li, Xianzhi / Xie, Liyu / Yi, Zhuoran / Wan, Guochun	A bolt loosening detection method based on patch antenna with overlapping sub-patch	147592172110556
Ghorbani, Esmaeil / Svecova, Dagmar / Thomson, Douglas J. / Cha, Young-Jin	Bridge pier scour level quantification based on output-only Kalman filtering	147592172110537
Yaghoubi, Vahid / Cheng, Liangliang / Van Paepegem, Wim / Kersemans, Mathias	CNN-DST: Ensemble deep learning based on Dempster–Shafer theory for vibration-based fault recognition	147592172110500
Omar, Intisar / Khan, Muhammad / Starr, Andrew	Compatibility and challenges in machine learning approach for structural crack assessment	147592172110613
Yu, Yang / Rashidi, Maria / Samali, Bijan / Mohammadi, Masoud / Nguyen, Thuc N. / Zhou, Xinxiu	Crack detection of concrete structures using deep convolutional neural networks optimized by enhanced chicken swarm algorithm	147592172110535
Zhou, Xiaoyong / Wang, Jiahui / Tu, Fubin / Bhat, Prakash	Damage detection in cementitious materials with optimized absolute electrical resistance tomography	147592172110590
Giordano, PF / Turksezer, ZI / Previtali, M. / Limongelli, MP	Damage detection on a historic iron bridge using satellite DInSAR data	147592172110543
Bao, Yanqing / Mahadevan, Sankaran	Diagnosis of interior damage with a convolutional neural network using simulation and measurement data	147592172110565
Miele, Sarah / Karve, Pranav M. / Mahadevan, Sankaran / Agarwal, Vivek	Diagnosis of internal cracks in concrete using vibro-acoustic modulation and machine learning	147592172110479
Hussain, Zahoor / Pu, Zhang / Hussain, Abasal / Ahmed, Shakeel / Shah, Atta Ullah / Ali, Aitzaz / Ali, Azhar	Effect of fiber dosage on water permeability using a newly designed apparatus and crack monitoring of steel fiber–reinforced concrete under direct tensile loading	147592172110528
Kang, Dong H. / Cha, Young-Jin	Efficient attention-based deep encoder and decoder for automatic crack segmentation	147592172110537
Essassi, Khawla / Rebiere, Jean-Luc / El Mahi, Abderrahim / Amine Ben souf, Mohamed / Bouguecha, Anas / Haddar, Mohamed	Health monitoring of sandwich composites with auxetic core subjected to indentation tests using acoustic emission	147592172110539
Chen, Dongdong / Huo, Linsheng / Song, Gangbing	High resolution bolt pre-load looseness monitoring using coda wave interferometry	147592172110634
Wen, Fuzhen / Shan, Shengbo / Cheng, Li	Immunity of the second harmonic shear horizontal waves to adhesive nonlinearity for breathing crack detection	147592172110571
Seventekidis, Panagiotis / Giagopoulos, Dimitrios	Model-based damage identification with simulated transmittance deviations and deep learning classification	147592172110543
Xu, Dong / Liu, Pengfei / Chen, Zhiping / Wu, Tao	A new quantitative acoustic emission model for damage characterization of composite laminates using original waveforms	147592172110565
Wang, Furui	A novel autonomous strategy for multi-bolt looseness detection using smart glove and Siamese double-path CapsNet	147592172110545
Kim, Chungeon / Oh, Hyunseok / Chang Jung, Byung / Moon, Seok Jun	Optimal sensor placement to detect ruptures in pipeline systems subject to uncertainty using an Adam-mutated genetic algorithm	147592172110565
Gu, Jun / Peng, Yuxing / Lu, Hao / Chang, Xiangdong / Cao, Shuang / Chen, Guoan / Cao, Bobo	An optimized variational mode decomposition method and its application in vibration signal analysis of bearings	147592172110574
Miguel, Luccas P. / Teloli, Rafael de O. / da Silva, Samuel / Chevallier, Gaël	Probabilistic machine learning for detection of tightening torque in bolted joints	147592172110541
Wang, Yu / Hu, Shuguang / Xiong, Tao / Huang, Yongan / Qiu, Lei	Recent progress in aircraft smart skin for structural health monitoring	147592172110568
Niu, Jin / Li, Shunlong / Li, Zhonglong	Restoration of missing structural health monitoring data using spatiotemporal graph attention networks	147592172110568
Silionis, Nicholas E. / Anyfantis, Konstantinos N.	Static strain-based identification of extensive damages in thin-walled structures	147592172110506
Zhou, Xiaoyong / Tu, Fubin / Wang, Jiahui / Li, Qinggang	Subdomain integration method of electrical resistance tomography for multiple flaws detection in cementitious materials	147592172110602
Qi, Yanzhi / Li, Peizhen / Xiong, Bing / Wang, Shuyin / Yuan, Cheng / Kong, Qingzhao	A two-step computer vision-based framework for bolt loosening detection and its implementation on a smartphone application	147592172110499
Han, Fei / Dan, Danhui / Xu, Zhaoyuan / Deng, Zichen	A vibration-based approach for damage identification and monitoring of prefabricated beam bridges	147592172110478

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sur cette fiche
IssueID
66651
Publié(e) le:
23.09.2022
Modifié(e) le:
23.09.2022

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International Association for Bridge and Structural Engineering (IABSE)

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Structural Health Monitoring - v. 21, n. 5 (mars 2022)

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Structural Health Monitoring - v. 21, n. 5 (mars 2022)

Articles dans ce numéro

Vous avez dépassé votre limite de téléchargement mensuelle ! Les abonné·es à Structurae Plus peuvent télécharger 30 images ou ensembles de données par mois. Les utilisateurs·rices de Structurae Pro sont limités à 50.

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