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Research and Application of Key Technology of Safety Situational Awareness for the Whole Process of Grid Infrastructure Construction Based on Edge-Side Scene Recognition and Knowledge Fusion

Bo Chen

Bo Chen

  • State Grid Beijing Electric Power CompanyBeijing, China
  • Beijing Electric Power Economic Research Institute Co., LtdBeijing, China
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Chen, Bo
, 
Hongyu Zhang

Hongyu Zhang

  • State Grid Beijing Electric Power CompanyBeijing, China
  • Beijing Electric Power Economic Research Institute Co., LtdBeijing, China
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Zhang, Hongyu
, 
Runxi Yang

Runxi Yang

  • State Grid Beijing Electric Power CompanyBeijing, China
  • Beijing Electric Power Economic Research Institute Co., LtdBeijing, China
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Yang, Runxi
, 
Hongyu Du

Hongyu Du

  • State Grid Beijing Electric Power CompanyBeijing, China
  • Beijing Electric Power Economic Research Institute Co., LtdBeijing, China
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Du, Hongyu
 et 
Mengzhu Xu

Mengzhu Xu

Nanjing Artificial Intelligence Research of IANanjing, China
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Xu, Mengzhu
  
03 févr. 2025
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Publié en ligne: 03 févr. 2025
Reçu: 06 sept. 2024
Accepté: 18 déc. 2024
DOI: https://doi.org/10.2478/amns-2025-0004
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© 2025 Bo Chen et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

Figure 1.

Point cloud characterization
Point cloud characterization

Figure 2.

Personnel spatial positioning effect
Personnel spatial positioning effect

Figure 3.

Point cloud ground extraction
Point cloud ground extraction

Figure 4.

Ground fitting effect (blue dots are fitted ground points)
Ground fitting effect (blue dots are fitted ground points)

Figure 5.

Fitted boom line in point cloud (red points are boom points)
Fitted boom line in point cloud (red points are boom points)

Figure 6.

Point cloud segmentation results
Point cloud segmentation results

Figure 7.

Digging arm rotating frame
Digging arm rotating frame

Figure 8.

Digging arm radius
Digging arm radius

Figure 9.

Personnel spatial positioning
Personnel spatial positioning

Figure 10.

The comparison of RMSE
The comparison of RMSE

The accuracy of the basic action

Action Recognition accuracy(%)
Bow down 71.36
Stooping 74.82
Pendulum 71.53
Stride 74.13
Reach out 73.93
Average 73.154
Langue:
Anglais
Périodicité:
1 fois par an
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