Wind turbine pitch bearing fault detection with Bayesian augmented temporal convolutional networks (English)
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- New search for: Zhang, Chao
- New search for: Zhang, Long
- Further information on Zhang, Long:
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https://orcid.org/0000-0001-7877-7993
- New search for: Zhang, Chao
- New search for: Zhang, Long
- Further information on Zhang, Long:
-
https://orcid.org/0000-0001-7877-7993
In:
Structural Health Monitoring
;
23
, 2
;
1089-1106
;
2024
- Article (Journal) / Electronic Resource
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Title:Wind turbine pitch bearing fault detection with Bayesian augmented temporal convolutional networks
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Contributors:Zhang, Chao ( author ) / Zhang, Long ( author )
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Published in:Structural Health Monitoring ; 23, 2 ; 1089-1106
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Publisher:
- New search for: SAGE Publications
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Place of publication:Sage UK: London, England
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Publication date:2024-03-01
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ISSN:
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DOI:
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Type of media:Article (Journal)
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Type of material:Electronic Resource
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Language:English
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Keywords:
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Licence:
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Source:
Table of contents – Volume 23, Issue 2
The tables of contents are generated automatically and are based on the data records of the individual contributions available in the index of the TIB portal. The display of the Tables of Contents may therefore be incomplete.
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- 701
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- 714
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Deep learning-based bridge damage identification approach inspired by internal force redistribution effectsYang, Kang / Ding, Youliang / Jiang, Huachen / Zhang, Yun / Zou, Zhengbo et al. | 2024
- 733
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- 750
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- 796
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CrackDenseLinkNet: a deep convolutional neural network for semantic segmentation of cracks on concrete surface imagesManjunatha, Preetham / Masri, Sami F / Nakano, Aiichiro / Wellford, Landon Carter et al. | 2024
- 818
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Multi-source information fusion meta-learning network with convolutional block attention module for bearing fault diagnosis under limited datasetSong, Shanshan / Zhang, Shuqing / Dong, Wei / Li, Gaochen / Pan, Chengyu et al. | 2024
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- 856
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Structural nonlinear damage identification based on the information distance of GNPAX/GARCH model and its experimental studyZuo, Heng / Guo, Huiyong et al. | 2024
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- 1025
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- 1037
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- 1089
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Wind turbine pitch bearing fault detection with Bayesian augmented temporal convolutional networksZhang, Chao / Zhang, Long et al. | 2024
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- 1123
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Dynamic characteristics analysis and the identification signal of the horizontal tail drive shaft system with the ballistic impact damage of a helicopterZhang, Chao / Zhu, Rupeng / Wang, Dan / Cao, Peng / Li, Jian / Li, Peng et al. | 2024
- 1148
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A novel Lamb wave-based multi-damage dataset construction and quantification algorithm under the framework of multi-task deep learningShao, Weihan / Sun, Hu / Zhou, Qifeng / Wang, Yishou / Qing, Xinlin et al. | 2024
- 1170
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A novel transformer-based semantic segmentation framework for structural condition assessmentWang, Ruhua / Shao, Yanda / Li, Qilin / Li, Ling / Li, Jun / Hao, Hong et al. | 2024
- 1184
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An active learning method for crack detection based on subset searching and weighted samplingXiang, Zhengliang / He, Xuhui / Zou, Yunfeng / Jing, Haiquan et al. | 2024
- 1201
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- 1217
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Geometry-informed phase space warping for reliable fatigue damage monitoringLi, He-Wen-Xuan / Chelidze, David et al. | 2024
- 1245
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Harmonic spectral correlated kurtosis and an adaptive matching extraction strategy of multi-fault features for rotating machineryYi, Cai / Ran, Le / Tang, Jiayin / Zhou, Qiuyang / Zhou, Lu et al. | 2024
- 1263
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Pixel-level detection of multiple pavement distresses and surface design features with ShuttleNetV2Zhang, Hang / Zhang, Allen A. / He, Anzheng / Dong, Zishuo / Liu, Yang et al. | 2024
- 1280
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Probabilistic outlier detection for robust regression modeling of structural response for high-speed railway track monitoringLi, Qi / Gao, Jingze / Beck, James L. / Lin, Chao / Huang, Yong / Li, Hui et al. | 2024