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Mechanics of Advanced Materials and Structures Volume 27, 2020 - Issue 21
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Original Articles

Machine-learning-based damage identification methods with features derived from moving principal component analysis

Ge ZhangSchool of Civil Engineering and Transportation, State Key Laboratory of Subtropical Building Science, South China University of Technology, Guangzhou, ChinaView further author information
,
Liqun TangSchool of Civil Engineering and Transportation, State Key Laboratory of Subtropical Building Science, South China University of Technology, Guangzhou, ChinaORCID Iconhttp://orcid.org/0000-0001-6037-1733View further author information
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Zejia LiuSchool of Civil Engineering and Transportation, State Key Laboratory of Subtropical Building Science, South China University of Technology, Guangzhou, ChinaORCID Iconhttp://orcid.org/0000-0001-9420-4896View further author information
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Licheng ZhouSchool of Civil Engineering and Transportation, State Key Laboratory of Subtropical Building Science, South China University of Technology, Guangzhou, ChinaCorrespondence[email protected]
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,
Yiping LiuSchool of Civil Engineering and Transportation, State Key Laboratory of Subtropical Building Science, South China University of Technology, Guangzhou, ChinaCorrespondence[email protected]
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&
Zhenyu JiangSchool of Civil Engineering and Transportation, State Key Laboratory of Subtropical Building Science, South China University of Technology, Guangzhou, ChinaORCID Iconhttp://orcid.org/0000-0001-8497-3405View further author information
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Pages 1789-1802 | Received 16 Jul 2019, Accepted 26 Dec 2019, Published online: 06 Jan 2020

Citations (11)

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Eugenio Brusa, Cristiana Delprete & Luigi Gianpio Di Maggio. (2023) Eigen-spectrograms: An interpretable feature space for bearing fault diagnosis based on artificial intelligence and image processing. Mechanics of Advanced Materials and Structures 30:22, pages 4639-4651.
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Qingkai Xiao, Liu Yiping, Chengbin Chen, Licheng Zhou, Liu Zejia, Zhenyu Jiang, Bao Yang & Liqun Tang. (2023) Data-driven time-variant reliability assessment of bridge girders based on deep learning. Mechanics of Advanced Materials and Structures 0:0, pages 1-13.
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Kleison A. Possenti, Vanessa G. S. de Menezes, Dirk Vandepitte, Volnei Tita & Ricardo de Medeiros. (2023) Detection of changes in dynamic characteristics of composite structures using Kriging metamodeling procedure: Experimental and computational analysis. Mechanics of Advanced Materials and Structures 0:0, pages 1-18.
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Thanh Q. Nguyen, Tuan Anh Nguyen, Thuy T. Nguyen & Duong N. Nguyen. (2023) Damage identification technique for short-span bridges using representative power spectral density (RPSD) and static moment area (SSM): a case study of the random vibration signals of 38 bridges under random load. Mechanics of Advanced Materials and Structures 0:0, pages 1-19.
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Ali Maghami & Seyed Mahmoud Hosseini. (2022) Intelligent step-length adjustment for adaptive path-following in nonlinear structural mechanics based on group method of data handling neural network. Mechanics of Advanced Materials and Structures 29:20, pages 2895-2912.
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Articles from other publishers (6)

Minguo Lin, Ruobin Su, Geng Chen, Yonghui Chen, Zi Ye & Nan Hu. (2023) Compressive strength prediction of hydrothermally solidified clay with different machine learning techniques. Journal of Cleaner Production 413, pages 137541.
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Chengbin Chen, Liqun Tang, Qingkai Xiao, Licheng Zhou, Hao Wang, Zejia Liu, Chenxi Xing, Yiping Liu, Jinming Chen, Zhenyu Jiang & Bao Yang. (2023) Unsupervised anomaly detection for long-span bridges combining response forecasting by deep learning with Td-MPCA. Structures 54, pages 1815-1830.
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Chengbin Chen, Liqun Tang, Yonghui Lu, Yong Wang, Zejia Liu, Yiping Liu, Licheng Zhou, Zhenyu Jiang & Bao Yang. (2023) Reconstruction of long-term strain data for structural health monitoring with a hybrid deep-learning and autoregressive model considering thermal effects. Engineering Structures 285, pages 116063.
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Yubo LiuChunlai Wang, Changfeng LiZhian BaiLin HuangKang PengXuhui XuePeng Cao. (2023) Robustness of Rock Damage Regions Induced by Crack Nucleation. International Journal of Geomechanics 23:5.
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Siyang Zhou, Shanglin Liu, Yilan Kang, Jie Cai, Haimei Xie & Qian Zhang. (2022) Physics-based machine learning method and the application to energy consumption prediction in tunneling construction. Advanced Engineering Informatics 53, pages 101642.
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Jongbin Won, Jong-Woong Park, Soojin Jang, Kyohoon Jin & Youngbin Kim. (2021) Automated Structural Damage Identification Using Data Normalization and 1-Dimensional Convolutional Neural Network. Applied Sciences 11:6, pages 2610.
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