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Smart Detection of Connection Loosening of Frame Supported Glass Curtain Walls Based on Coupled Structural Response Vector and Support Vector Machine Approach
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Qiang ZHANG, Jian YANG, Xing'er WANG, Han XU, Yanran MENG
Journal of the Chinese Ceramic Society | 2020, 48(10) : 1682 - 1688
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Journal of the Chinese Ceramic Society | 2020, 48(10): 1682-1688
Smart Detection of Connection Loosening of Frame Supported Glass Curtain Walls Based on Coupled Structural Response Vector and Support Vector Machine Approach
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Qiang ZHANG, Jian YANG, Xing'er WANG, Han XU, Yanran MENG
Affiliations
  • State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, Shanghai 200240, China School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China Shanghai Key Laboratory for Digital Maintenance of Buildings and Infrastructure, Shanghai 200240, China

    • ZHANG Qiang (1995-), male, Master candidate. E-mail:

About Author:

ZHANG Qiang (1995-), male, Master candidate. E-mail:

Published: 2020-10-20 doi: 10.14062/j.issn.0454-5648.20200178
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A coupled structural response vector (SRV) and support vector machine (SVM) approach was developed for the connection loosening detection of frame supported glass curtain walls. Firstly, a structural simulation model was established, which considered both static and dynamic characteristics for the connection damage due to the loosening effect of frame supported glass walls. Secondly, the structural response vector was then used for damage pattern identification and quantification, which validated the effectiveness and applicability of SRV as damage indicators. Finally, a damage identification sample database containing different SRVs with the first four frequencies of glass panels and the inclination angles at nine points was established. Three SVMs with different kernels functions were used for the sample training and damaged identification. Particle swarm optimization was also utilized to optimize the parameters of radial basis function kernel. The results show that the effectiveness of coupled SRV-SVM approach for the identification and quantification of connection loosening of frame supported glass curtain walls is satisfactory.

frame supported glass walls  /  connection loosening detection  /  support vector machine  /  structural response vector  /  particle swarm optimization
张强, 杨健, 王星尔, 徐涵, 孟嫣然. 基于结构响应向量和支持向量机的框支承玻璃幕墙连接松弛状态智能识别. 硅酸盐学报, 2020 , 48 (10) : 1682 -1688 . DOI: 10.14062/j.issn.0454-5648.20200178
Qiang ZHANG, Jian YANG, Xing'er WANG, Han XU, Yanran MENG. Smart Detection of Connection Loosening of Frame Supported Glass Curtain Walls Based on Coupled Structural Response Vector and Support Vector Machine Approach[J]. Journal of the Chinese Ceramic Society, 2020 , 48 (10) : 1682 -1688 . DOI: 10.14062/j.issn.0454-5648.20200178
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Year 2020 volume 48 Issue 10
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Article Info
doi: 10.14062/j.issn.0454-5648.20200178
  • Receive Date：2020-03-18
  • Online Date：2026-10-29
  • Published：2020-10-20
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History
  • Received：2020-03-18
  • Revised：2020-04-14
Funding
Affiliations
    State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, Shanghai 200240, China School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China Shanghai Key Laboratory for Digital Maintenance of Buildings and Infrastructure, Shanghai 200240, China

Corresponding:

YANG Jian (1974-), male, Ph.D., Professor. E-mail:
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光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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