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Machine vision method for cable force identification in complex boundary conditions
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Haijian SHI1, Zuocai WANG1, 2, Lingxia WANG3, Yu XIN1, Dayou DUAN4
Journal of Vibration Engineering | 2025, 38(4) : 739 - 749
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Journal of Vibration Engineering | 2025, 38(4): 739-749
Machine vision method for cable force identification in complex boundary conditions
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Haijian SHI1, Zuocai WANG1, 2, Lingxia WANG3, Yu XIN1, Dayou DUAN4
Affiliations
  • 1.College of Civil Engineering,Hefei University of Technology,Hefei 230009,China
  • 2.Anhui Province Road and Bridge Inspection Engineering Research Center,Hefei 230009,China
  • 3.China Railway Major Bridge Engineering Group Co.,Ltd.,Wuhan 430050,China
  • 4.School of Urban Construction and Transportation,Hefei University,Hefei 230601,China
Published: 2025-04-10 doi: 10.16385/j.cnki.issn.1004-4523.2025.04.009
Outline
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In order to accurately identify cable force in complex boundary conditions,a new method of cable force identification using machine vision and generalized regression neural network(GRNN)is proposed. Machine vision technologies,such as the phase-based motion amplification algorithm and sub-pixel edge detection algorithm,are used to extract the vibration displacement time history data and identify the frequency through the cable vibration video to realize multi-point non-contact synchronous measurement of cable vibration deformation. A sample dataset is generated using the finite difference method. The smoothing factor of GRNN is obtained by the sparrow search algorithm(SSA),and a SSA-GRNN cable force prediction model is constructed,establishing the correspondence between frequencies and cable force under complex boundary conditions. The obtained frequency information is input into the model for cable force recognition. Taking a single cable as an example,the numerical simulation of the cable in complex boundary conditions and the cable test under artificial excitation condition are carried out. The results show that the cable force identification using machine vision and GRNN can accurately identify frequencies through vibration video,and improve the recognition accuracy of the cable force in complex boundary conditions.

cable force identification  /  vibration frequency method  /  complex boundary conditions  /  machine vision  /  GRNN
Haijian SHI, Zuocai WANG, Lingxia WANG, Yu XIN, Dayou DUAN. Machine vision method for cable force identification in complex boundary conditions[J]. Journal of Vibration Engineering, 2025 , 38 (4) : 739 -749 . DOI: 10.16385/j.cnki.issn.1004-4523.2025.04.009
Year 2025 volume 38 Issue 4
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Article Info
doi: 10.16385/j.cnki.issn.1004-4523.2025.04.009
  • Receive Date:2024-01-02
  • Online Date:2026-02-12
  • Published:2025-04-10
Article Data
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History
  • Received:2024-01-02
  • Revised:2024-04-02
Funding
Affiliations
    1.College of Civil Engineering,Hefei University of Technology,Hefei 230009,China
    2.Anhui Province Road and Bridge Inspection Engineering Research Center,Hefei 230009,China
    3.China Railway Major Bridge Engineering Group Co.,Ltd.,Wuhan 430050,China
    4.School of Urban Construction and Transportation,Hefei University,Hefei 230601,China
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Number of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
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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