Structural Health Monitoring - v. 20, n. 4 (April 2021)

Erschienen:	April 2021

Artikel in dieser Ausgabe

Autor(en)	Titel	Seite(n)
Bao, Yuequan / Li, Jian / Nagayama, Tomonori / Xu, Yang / Spencer, Billie F. / Li, Hui	The 1st International Project Competition for Structural Health Monitoring (IPC-SHM, 2020): A summary and benchmark problem	147592172110064
Li, Dan / Wang, Yang / Yan, Wang-Ji / Ren, Wei-Xin	Acoustic emission wave classification for rail crack monitoring based on synchrosqueezed wavelet transform and multi-branch convolutional neural network	147592172092279
Chen, Si-Xin / Zhou, Lu / Ni, Yi-Qing / Liu, Xiao-Zhou	An acoustic-homologous transfer learning approach for acoustic emission–based rail condition evaluation	147592172097694
Xu, Yang / Bao, Yuequan / Zhang, Yufeng / Li, Hui	Attribute-based structural damage identification by few-shot meta learning with inter-class knowledge transfer	147592172092113
Mascareñas, David DL / Ballor, JoAnn P. / McClain, Oscar L. / Mellor, Miranda A. / Shen, Chih-Yu / Bleck, Brian / Morales, John / Yeong, Li-Ming R. / Narushof, Benjamin / Shelton, Philo / Martinez, Eric / Yang, Yongchao / Cattaneo, Alessandro / Harden, Troy A. / Moreu, Fernando	Augmented reality for next generation infrastructure inspections	147592172095384
Jeong, Seunghoo / Kim, Hyunjun / Lee, Junhwa / Sim, Sung-Han	Automated wireless monitoring system for cable tension forces using deep learning	147592172093583
Ni, Yi-Qing / Zhang, Qiu-Hu	A Bayesian machine learning approach for online detection of railway wheel defects using track-side monitoring	147592172092177
Won, Jongbin / Park, Jong-Woong / Shim, Changsu / Park, Man-Woo	Bridge-surface panoramic-image generation for automated bridge-inspection using deepmatching	147592172093038
Nasir, Vahid / Fathi, Hamidreza / Kazemirad, Siavash	Combined machine learning–wave propagation approach for monitoring timber mechanical properties under UV aging	147592172199598
He, Mengyue / Wang, Yishou / Ram Ramakrishnan, Karthik / Zhang, Zhifang	A comparison of machine learning algorithms for assessment of delamination in fiber-reinforced polymer composite beams	147592172096715
He, Hao-Xiang / Zheng, Jia-cheng / Liao, Li-can / Chen, Yan-Jiang	Damage identification based on convolutional neural network and recurrence graph for beam bridge	147592172091692
Wang, Ruhua / An, Senjian / Li, Jun / Li, Ling / Hao, Hong / Liu, Wanquan	Deep residual network framework for structural health monitoring	147592172091837
Bae, Hyunjin / Jang, Keunyoung / An, Yun-Kyu	Deep super resolution crack network (SrcNet) for improving computer vision–based automated crack detectability in in situ bridges	147592172091722
Ma, Meng / Mao, Zhu	Deep wavelet sequence-based gated recurrent units for the prognosis of rotating machinery	147592172093315
Lei, Ying / Zhang, Yixiao / Mi, Jianan / Liu, Weifeng / Liu, Lijun	Detecting structural damage under unknown seismic excitation by deep convolutional neural network with wavelet-based transmissibility data	147592172092308
Fan, Gao / Li, Jun / Hao, Hong	Dynamic response reconstruction for structural health monitoring using densely connected convolutional networks	147592172091688
Narazaki, Yasutaka / Gomez, Fernando / Hoskere, Vedhus / Smith, Matthew D. / Spencer, Billie F.	Efficient development of vision-based dense three-dimensional displacement measurement algorithms using physics-based graphics models	147592172093952
Maharjan, D. / Agüero, M. / Mascarenas, D. / Fierro, R. / Moreu, F.	Enabling human–infrastructure interfaces for inspection using augmented reality	147592172097701
Lee, Kanghyeok / Jeong, Seunghoo / Sim, Sung-Han / Shin, Do Hyoung	Field experiment on a PSC-I bridge for convolutional autoencoder-based damage detection	147592172092626
Dan, Jingpei / Feng, Wending / Huang, Xia / Wang, Yuming	Global bridge damage detection using multi-sensor data based on optimized functional echo state networks	147592172094820
Tang, Zhiyi / Bao, Yuequan / Li, Hui	Group sparsity-aware convolutional neural network for continuous missing data recovery of structural health monitoring	147592172093174
Xu, Fan / Shu, Xin / Li, Xin / Tang, Ruoli	Health indicator construction for roller bearing based on an unsupervised deep belief network with a novel sigmoid zero local minimum point model	147592172096395
Jung, HweeKwon / Green, Andre / Morales, John / Silva, Moisés / Martinez, Bridget / Cattaneo, Alessandro / Yang, Yongchao / Park, Gyuhae / McClean, Jarrod / Mascareñas, David	A holistic cyber-physical security protocol for authenticating the provenance and integrity of structural health monitoring imagery data	147592172092732
Andrade Nunes, Lorena / Piazzaroli Finotti Amaral, Rafaelle / Barbosa, Flávio de Souza / Cury, Alexandre Abrahão	A hybrid learning strategy for structural damage detection	147592172096694
Li, Linchao / Zhou, Haijun / Liu, Hanlin / Zhang, Chaodong / Liu, Junhui	A hybrid method coupling empirical mode decomposition and a long short-term memory network to predict missing measured signal data of SHM systems	147592172093281
Wang, Furui / Mobiny, Aryan / Van Nguyen, Hien / Song, Gangbing	If structure can exclaim: a novel robotic-assisted percussion method for spatial bolt-ball joint looseness detection	147592172092314
Saleem, Muhammad Rakeh / Park, Jong-Woong / Lee, Jin-Hwan / Jung, Hyung-Jo / Sarwar, Muhammad Zohaib	Instant bridge visual inspection using an unmanned aerial vehicle by image capturing and geo-tagging system and deep convolutional neural network	147592172093238
Chen, Honglei / Liu, Zenghua / Wu, Bin / He, Cunfu	An intelligent algorithm based on evolutionary strategy and clustering algorithm for Lamb wave defect location	147592172095959
Tan, Xuyan / Sun, Xuanxuan / Chen, Weizhong / Du, Bowen / Ye, Junchen / Sun, Leilei	Investigation on the data augmentation using machine learning algorithms in structural health monitoring information	147592172199623
Chen, Jingyu / Feng, Xin / Xiao, Shiyun	An iterative method for leakage zone identification in water distribution networks based on machine learning	147592172095047
Lei, Xiaoming / Sun, Limin / Xia, Ye	Lost data reconstruction for structural health monitoring using deep convolutional generative adversarial networks	147592172095922
Bao, Yuequan / Li, Hui	Machine learning paradigm for structural health monitoring	147592172097241
Teng, Jun / Tang, De-Hui / Hu, Wei-Hua / Lu, Wei / Feng, Zhi-Wen / Ao, Chun-Feng / Liao, Ming-Hao	Mechanism of the effect of temperature on frequency based on long-term monitoring of an arch bridge	147592172093137
Liu, Weixu / Tang, Zhifeng / Lv, Fuzai / Chen, Xiangxian	Multi-feature integration and machine learning for guided wave structural health monitoring: Application to switch rail foot	147592172198957
Song, Homin / Yang, Yongchao	Noncontact super-resolution guided wave array imaging of subwavelength defects using a multiscale deep learning approach	147592172094295
Li, Shunlong / Niu, Jin / Li, Zhonglong	Novelty detection of cable-stayed bridges based on cable force correlation exploration using spatiotemporal graph convolutional networks	147592172098866
Champneys, Max David / Green, Andre / Morales, John / Silva, Moisés / Mascareñas, David	On the vulnerability of data-driven structural health monitoring models to adversarial attack	147592172092023
Xu, Jie / Liu, Xuan / Han, Qinghua / Wang, Weixin	A particle swarm optimization–support vector machine hybrid system with acoustic emission on damage degree judgment of carbon fiber reinforced polymer cables	147592172092282
Kuok, Sin-Chi / Yuen, Ka-Veng / Roberts, Stephen / Girolami, Mark A.	Propagative broad learning for nonparametric modeling of ambient effects on structural health indicators	147592172091692
Tsuchimoto, Koji / Narazaki, Yasutaka / Hoskere, Vedhus / Spencer, Billie F.	Rapid postearthquake safety evaluation of buildings using sparse acceleration measurements	147592172093629
Zhang, Lingxin / Shen, Junkai / Zhu, Baijie	A research on an improved Unet-based concrete crack detection algorithm	147592172094006
Yu, Kun / Fu, Qiang / Ma, Hui / Lin, Tian Ran / Li, Xiang	Simulation data driven weakly supervised adversarial domain adaptation approach for intelligent cross-machine fault diagnosis	147592172098071
Zhang, Chaobo / Chang, Chih-Chen / Jamshidi, Maziar	Simultaneous pixel-level concrete defect detection and grouping using a fully convolutional model	147592172098543
Chen, Zhao / Sun, Hao	Sparse representation for damage identification of structural systems	147592172092697
Wang, Xiaoyou / Hou, Rongrong / Xia, Yong / Zhou, Xiaoqing	Structural damage detection based on variational Bayesian inference and delayed rejection adaptive Metropolis algorithm	147592172092125
Zhang, Zhiming / Sun, Chao	Structural damage identification via physics-guided machine learning: a methodology integrating pattern recognition with finite element model updating	147592172092748
Li, Suzhen / Peng, Renzhu / Liu, Zelong	A surveillance system for urban buried pipeline subject to third-party threats based on fiber optic sensing and convolutional neural network	147592172093064
Yoon, Sungsik / Gwon, Gi-Hun / Lee, Jin-Hwan / Jung, Hyung-Jo	Three-dimensional image coordinate-based missing region of interest area detection and damage localization for bridge visual inspection using unmanned aerial vehicles	147592172091867
Mao, Jianxiao / Wang, Hao / Spencer, Billie F.	Toward data anomaly detection for automated structural health monitoring: Exploiting generative adversarial nets and autoencoders	147592172092460
Shang, Zhiqiang / Sun, Limin / Xia, Ye / Zhang, Wei	Vibration-based damage detection for bridges by deep convolutional denoising autoencoder	147592172094283
Rao, Aravinda S. / Nguyen, Tuan / Palaniswami, Marimuthu / Ngo, Tuan	Vision-based automated crack detection using convolutional neural networks for condition assessment of infrastructure	147592172096544

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IssueID
58706
Veröffentlicht am:
29.06.2021
Geändert am:
29.06.2021

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Structural Health Monitoring - v. 20, n. 4 (April 2021)

Artikel in dieser Ausgabe

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Structural Health Monitoring - v. 20, n. 4 (April 2021)

Artikel in dieser Ausgabe

Sie haben Ihr monatliches Download-Limit überschritten! Structurae Plus-Abonnent·innen können 30 Medien bzw. Datensätze pro Monat herunterladen. Structurae Pro-Nutzer·innen sind auf 50 beschränkt.

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