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Design and Implementation of Adaptive Protection Strategy for 0.4kV Safety Anti Electric Shock Maintenance Power Box in Smart Grid

Yong Wang

Yong Wang

State Grid Jilin Electric Power Company Limited Extrahigh Voltage CompanyChangchun, China
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Wang, Yong
, 
Bowen Zhang

Bowen Zhang

Northeast Branch of State Grid Corporation of ChinaShenyang, China
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Zhang, Bowen
, 
Songnan Liu

Songnan Liu

Northeast Branch of State Grid Corporation of ChinaShenyang, China
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Liu, Songnan
, 
Chun Liu

Chun Liu

State Grid Jilin Electric Power Company Limited Extrahigh Voltage CompanyChangchun, China
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Liu, Chun
 e 
Weidong Wang

Weidong Wang

State Grid Jilin Electric Power Company Limited Extrahigh Voltage CompanyChangchun, China
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Wang, Weidong
  
17 mar 2025
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Pubblicato online: 17 mar 2025
Ricevuto: 17 ott 2024
Accettato: 06 feb 2025
DOI: https://doi.org/10.2478/amns-2025-0316
Parole chiave
© 2025 Yong Wang et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

Figure 1.

Repair power box security identification framework diagram
Repair power box security identification framework diagram

Figure 2.

The working principle diagram
The working principle diagram

Figure 3.

Safety recognition accuracy of different sample sizes
Safety recognition accuracy of different sample sizes

Figure 4.

Comparison of safety identification methods
Comparison of safety identification methods

Recognition results of inexperienced faces

Methods Accuracy Miss rate Detection rate
Eigenfaces 81.2% 18.8% 95.7%
Fisherfaces 75.8% 24.2% 96.2%
LBPH 82.7% 17.3% 96.5%
Our method 95.3% 4.7% 98.9%

Face recognition results

Face rotation Angle Our model(%) LLR(%) Gaussian regression(%)
25° 99.92 97.36 98.73
40° 97.64 89.83 90.27
55° 93.41 85.25 88.60
70° 90.11 82.53 87.37

The comparison of sample recognition accuracy and time consuming

Subject Method/sample size 1000 2000 3000 4000 5000
Accuracy (%) Code scanning 97.82 98.21 98.11 97.69 97.62
Ours 99.03 99.03 98.88 98.73 98.93
Time (ms) Code scanning 142 655 1132 2077 3352
Ours 38 55 72 80 87

Safety identification results

Sample size/group Accuracy(%)
Our method PCA-SVM LBP PCA-LDA-SVM LBP+MB-LBP LBP+LDRC-Fisher
500 99.23 97.37 96.15 92.53 90.62 88.72
1000 99.03 97.56 97.51 92.38 90.38 88.72
2000 99.03 97.41 96.93 92.87 89.50 89.98
3000 98.88 97.22 96.54 91.79 88.52 88.03
4000 98.73 97.61 97.47 92.09 89.01 89.40
5000 98.93 96.83 96.34 91.79 89.30 87.74
Lingua:
Inglese
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1 volte all'anno
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Scienze biologiche, Scienze della vita, altro, Matematica, Matematica applicata, Matematica generale, Fisica, Fisica, altro
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