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Sun, Huabin / Guan, Xiaoshu / Bao, Yuequan / Xu, Yang / Li, Hui: Normalising flow-based vehicle load modeling for bridges. Dans: Structure and Infrastructure Engineering.
https://doi.org/10.1080/15732479.2023.2236600
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Liu, Dawei / Bao, Yuequan / Li, Hui (2023): Machine learning-based stochastic subspace identification method for structural modal parameters. Dans: Engineering Structures, v. 274 (janvier 2023).
https://doi.org/10.1016/j.engstruct.2022.115178
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Liu, Dawei / Tang, Zhiyi / Bao, Yuequan / Li, Hui (2021): Machine‐learning‐based methods for output‐only structural modal identification. Dans: Structural Control and Health Monitoring, v. 28, n. 12 (septembre 2021).
https://doi.org/10.1002/stc.2843
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Bao, Yuequan / Li, Jian / Nagayama, Tomonori / Xu, Yang / Spencer, Billie F. / Li, Hui (2021): The 1st International Project Competition for Structural Health Monitoring (IPC-SHM, 2020): A summary and benchmark problem. Dans: Structural Health Monitoring, v. 20, n. 4 (avril 2021).
https://doi.org/10.1177/14759217211006485
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Bao, Yuequan / Li, Hui (2021): Machine learning paradigm for structural health monitoring. Dans: Structural Health Monitoring, v. 20, n. 4 (avril 2021).
https://doi.org/10.1177/1475921720972416
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Tang, Zhiyi / Bao, Yuequan / Li, Hui (2021): Group sparsity-aware convolutional neural network for continuous missing data recovery of structural health monitoring. Dans: Structural Health Monitoring, v. 20, n. 4 (avril 2021).
https://doi.org/10.1177/1475921720931745
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Xu, Yang / Bao, Yuequan / Zhang, Yufeng / Li, Hui (2021): Attribute-based structural damage identification by few-shot meta learning with inter-class knowledge transfer. Dans: Structural Health Monitoring, v. 20, n. 4 (avril 2021).
https://doi.org/10.1177/1475921720921135
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Bao, Yuequan / Beck, James L. / Li, Hui (2010): Compressive sampling for accelerometer signals in structural health monitoring. Dans: Structural Health Monitoring, v. 10, n. 3 (juin 2010).
https://doi.org/10.1177/1475921710373287
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Bao, Yuequan / Li, Hui / An, Yonghui / Ou, Jinping (2011): Dempster–Shafer evidence theory approach to structural damage detection. Dans: Structural Health Monitoring, v. 11, n. 1 (janvier 2011).
https://doi.org/10.1177/1475921710395813
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Bao, Yuequan / Li, Hui / Sun, Xiaodan / Yu, Yan / Ou, Jinping (2012): Compressive sampling–based data loss recovery for wireless sensor networks used in civil structural health monitoring. Dans: Structural Health Monitoring, v. 12, n. 1 (septembre 2012).
https://doi.org/10.1177/1475921712462936
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Bao, Yuequan / Shi, Zuoqiang / Wang, Xiaoyu / Li, Hui (2017): Compressive sensing of wireless sensors based on group sparse optimization for structural health monitoring. Dans: Structural Health Monitoring, v. 17, n. 4 (juillet 2017).
https://doi.org/10.1177/1475921717721457
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Chen, Zhicheng / Bao, Yuequan / Li, Hui / Spencer, Billie F. (2017): A novel distribution regression approach for data loss compensation in structural health monitoring. Dans: Structural Health Monitoring, v. 17, n. 6 (décembre 2017).
https://doi.org/10.1177/1475921717745719
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Bao, Yuequan / Tang, Zhiyi / Li, Hui / Zhang, Yufeng (2018): Computer vision and deep learning–based data anomaly detection method for structural health monitoring. Dans: Structural Health Monitoring, v. 18, n. 2 (janvier 2018).
https://doi.org/10.1177/1475921718757405
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Chen, Zhicheng / Li, Hui / Bao, Yuequan (2018): Analyzing and modeling inter-sensor relationships for strain monitoring data and missing data imputation: a copula and functional data-analytic approach. Dans: Structural Health Monitoring, v. 18, n. 4 (avril 2018).
https://doi.org/10.1177/1475921718788703
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Bao, Yuequan / Tang, Zhiyi / Li, Hui (2018): Compressive-sensing data reconstruction for structural health monitoring: a machine-learning approach. Dans: Structural Health Monitoring, v. 19, n. 1 (octobre 2018).
https://doi.org/10.1177/1475921719844039
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Bao, Yuequan / Guo, Yibing / Li, Hui (2019): A machine learning–based approach for adaptive sparse time–frequency analysis used in structural health monitoring. Dans: Structural Health Monitoring, v. 19, n. 6 (décembre 2019).
https://doi.org/10.1177/1475921720909440
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Li, Hui / Huang, Yong / Ou, Jinping / Bao, Yuequan (2011): Fractal Dimension-Based Damage Detection Method for Beams with a Uniform Cross-Section. FD-based damage detection method for beams. Dans: Computer-Aided Civil and Infrastructure Engineering, v. 26, n. 3 ( 2011).
https://doi.org/10.1111/j.1467-8667.2010.00686.x
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Bao, Yuequan / Xia, Yong / Li, Hui / Xu, You-Lin / Zhang, Peng (2012): Data Fusion-based Structural Damage Detection Under Varying Temperature Conditions. Dans: International Journal of Structural Stability and Dynamics, v. 12, n. 6 (décembre 2012).
https://doi.org/10.1142/s0219455412500526
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Chen, Zhicheng / Bao, Yuequan / Chen, Jiahui / Li, Hui (2019): Modelling the spatial distribution of heavy vehicle loads on long-span bridges based on undirected graphical model. Dans: Structure and Infrastructure Engineering, v. 15, n. 11 (juin 2019).
https://doi.org/10.1080/15732479.2019.1639774
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Xu, Yang / Wei, Shiyin / Bao, Yuequan / Li, Hui (2019): Automatic seismic damage identification of reinforced concrete columns from images by a region-based deep convolutional neural network. Dans: Structural Control and Health Monitoring, v. 26, n. 3 (février 2019).
https://doi.org/10.1002/stc.2313
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Tang, Zhiyi / Chen, Zhicheng / Bao, Yuequan / Li, Hui (2019): Convolutional neural network-based data anomaly detection method using multiple information for structural health monitoring. Dans: Structural Control and Health Monitoring, v. 26, n. 1 (janvier 2019).
https://doi.org/10.1002/stc.2296
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Li, Hui / Tao, Dongwang / Huang, Yong / Bao, Yuequan (2013): A data-driven approach for seismic damage detection of shear-type building structures using the fractal dimension of time-frequency features. Dans: Structural Control and Health Monitoring, v. 20, n. 9 (septembre 2013).
https://doi.org/10.1002/stc.1528
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Bao, Yuequan / Yu, Yan / Li, Hui / Mao, Xingquan / Jiao, Wenfeng / Zou, Zilong / Ou, Jinping (2015): Compressive sensing-based lost data recovery of fast-moving wireless sensing for structural health monitoring. Dans: Structural Control and Health Monitoring, v. 22, n. 3 (mars 2015).
https://doi.org/10.1002/stc.1681
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Chen, Zhicheng / Li, Hui / Bao, Yuequan / Li, Na / Jin, Yao (2016): Identification of spatio-temporal distribution of vehicle loads on long-span bridges using computer vision technology. Dans: Structural Control and Health Monitoring, v. 23, n. 3 (mars 2016).
https://doi.org/10.1002/stc.1780
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Bao, Yuequan / Shi, Zuoqiang / Beck, James L. / Li, Hui / Hou, Thomas Y. (2017): Identification of time-varying cable tension forces based on adaptive sparse time-frequency analysis of cable vibrations. Dans: Structural Control and Health Monitoring, v. 24, n. 3 (mars 2017).
https://doi.org/10.1002/stc.1889
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Wang, Peng / Zhou, Wensong / Bao, Yuequan / Li, Hui (2018): Ice monitoring of a full-scale wind turbine blade using ultrasonic guided waves under varying temperature conditions. Dans: Structural Control and Health Monitoring, v. 25, n. 4 (avril 2018).
https://doi.org/10.1002/stc.2138
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Zhang, Deyi / Bao, Yuequan / Li, Hui / Ou, Jinping (2012): Investigation of Temperature Effects on Modal Parameters of the China National Aquatics Center. Dans: Advances in Structural Engineering, v. 15, n. 7 (juillet 2012).
https://doi.org/10.1260/1369-4332.15.7.1139
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Li, Shunlong / Wei, Shiyin / Bao, Yuequan / Li, Hui (2018): Condition assessment of cables by pattern recognition of vehicle-induced cable tension ratio. Dans: Engineering Structures, v. 155 (janvier 2018).
https://doi.org/10.1016/j.engstruct.2017.09.063
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Bao, Yuequan / Feng, Dongyang / Ma, Nan / Zhu, Hehua / Rabczuk, Timon (2018): Experimental and numerical study on structural performance of reinforced concrete box sewer with localized extreme defect. Dans: Underground Space, v. 3, n. 2 (juin 2018).
https://doi.org/10.1016/j.undsp.2018.04.001
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Bao, Yuequan / Li, Hui / Ou, Jinping (2014): Emerging data technology in structural health monitoring: compressive sensing technology. Dans: Journal of Civil Structural Health Monitoring, v. 4, n. 2 (janvier 2014).
https://doi.org/10.1007/s13349-013-0064-1