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Research on Intelligent Mobile Inspection Technology for Dam Safety Based on Image Recognition Technology and Track Robot
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Qian LI1, Yun JI2, Fu-ting SUN1, Yu-jia LIU1, Jun-jun LI2, Xi-jun LIU2
Water Resources and Power | 2023, 41(4) : 107 - 109
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Water Resources and Power | 2023, 41(4): 107-109
DAM SAFETY AND MONITORING
Research on Intelligent Mobile Inspection Technology for Dam Safety Based on Image Recognition Technology and Track Robot
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Qian LI1, Yun JI2, Fu-ting SUN1, Yu-jia LIU1, Jun-jun LI2, Xi-jun LIU2
Affiliations
  • 1.Large Dam Safety Supervision Center, National Energy Administration, Hangzhou 310000, China
  • 2.PowerChina Huadong Engineering Corporation Limited, Hangzhou 310000, China
Published: 2023-04-25 doi: 10.20040/j.cnki.1000-7709.2023.20221180
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In order to realize the remote mobile monitoring of the dam, the automatic identification of important defects and the measurement of key monitoring equipment, the research on the intelligent mobile inspection technology of dam safety based on image recognition technology and track robot was carried out. Firstly, an intelligent mobile inspection system for dam safety was constructed based on the orbital robot. On this basis, the automatic identification of typical dam defects and the measurement of key monitoring equipment were realized based on image recognition technology. It had been applied in a dam with good results. The remote and large-scale inspection of dam safety was realized, which can significantly reduce the workload of manual inspection, replace manual inspection under extreme natural conditions, and timely grasp the operation of hydraulic structures such as dams. The research results can provide important reference and technical support for the safety monitoring of dams.

intelligent mobile inspection  /  orbital robot  /  image recognition  /  dam safety  /  crack  /  calcium precipitation  /  dial reading
Qian LI, Yun JI, Fu-ting SUN, Yu-jia LIU, Jun-jun LI, Xi-jun LIU. Research on Intelligent Mobile Inspection Technology for Dam Safety Based on Image Recognition Technology and Track Robot[J]. Water Resources and Power, 2023 , 41 (4) : 107 -109 . DOI: 10.20040/j.cnki.1000-7709.2023.20221180
Year 2023 volume 41 Issue 4
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Article Info
doi: 10.20040/j.cnki.1000-7709.2023.20221180
  • Receive Date:2022-06-02
  • Online Date:2026-01-27
  • Published:2023-04-25
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  • Received:2022-06-02
  • Revised:2022-07-06
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Affiliations
    1.Large Dam Safety Supervision Center, National Energy Administration, Hangzhou 310000, China
    2.PowerChina Huadong Engineering Corporation Limited, Hangzhou 310000, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
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Genus
种数
Number of
species
占总种数比例
Percentage of total
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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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