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Vision tracking multi-rotor displacement measurement
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Rong-liang YANG1, Sen WANG1, Xing WU2, Xiao-qin LIU1, Tao LIU1
Journal of Vibration Engineering | 2024, 37(1) : 113 - 125
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Journal of Vibration Engineering | 2024, 37(1): 113-125
Vision tracking multi-rotor displacement measurement
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Rong-liang YANG1, Sen WANG1, Xing WU2, Xiao-qin LIU1, Tao LIU1
Affiliations
  • 1School of Mechanical and Electrical Engineering,Kunming University of Science and Technology,Kunming 650500,China
  • 2Yunnan Mechanical and Electrical Vocational and Technical College,Kunming 650023,China
Published: 2024-01-28 doi: 10.16385/j.cnki.issn.1004-4523.2024.01.012
Outline
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Aiming at the problem that the current traditional vibration sensor is limited by the installation and the number of measuring points when measuring the displacement of the rotating body,this paper uses a high-speed industrial camera as the acquisition medium,and collects the rotor vibration video on the rotor vibration test bench. The visual vibration measurement method tracks the full-field vibration displacement of multiple rotor targets. The feature pyramid network structure is introduced into the residual neural network,and the improved feature extraction backbone network is established by combining the attention mechanism. The identity re-identification method is used to strengthen the correlation of target displacement between adjacent frames,and to track the full-field vibration displacement signals of the rotator. Qualitative and quantitative comparisons of different network models on the rotor vibration displacement measurement dataset show that the network model proposed in this paper can obtain a tighter fit when the bounding box is regressed. The collected eddy current displacement signal is used as the standard value to compare the two rotor displacement signals,and the experimental results show that the waveform and spectral noise fitted by the multi-target tracking algorithm in this paper is the smallest and can match the eddy current signal. The experiments also prove the generalization performance of the algorithm in this paper,which reflects the engineering application value of visual measurement in the field of vibration displacement tracking of rotating bodies.

visual vibration measurement  /  deep learning  /  multi-target  /  visual tracking  /  blurred image  /  rotational body displacement measurement
Rong-liang YANG, Sen WANG, Xing WU, Xiao-qin LIU, Tao LIU. Vision tracking multi-rotor displacement measurement[J]. Journal of Vibration Engineering, 2024 , 37 (1) : 113 -125 . DOI: 10.16385/j.cnki.issn.1004-4523.2024.01.012
Year 2024 volume 37 Issue 1
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Article Info
doi: 10.16385/j.cnki.issn.1004-4523.2024.01.012
  • Receive Date:2022-04-06
  • Online Date:2026-02-10
  • Published:2024-01-28
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  • Received:2022-04-06
  • Revised:2022-07-24
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Affiliations
    1School of Mechanical and Electrical Engineering,Kunming University of Science and Technology,Kunming 650500,China
    2Yunnan Mechanical and Electrical Vocational and Technical College,Kunming 650023,China
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表12种不同金属材料的力学参数

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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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