Research on Visual Localization Method for Substation Live Working Robot Based on Deep Learning
Author:
Affiliation:
1. State Grid Shanghai Municipal Electric Power Company, China
2. State Grid Shanghai Energy Interconnection Research Institute, China
Funder
science and technology projects of State Grid Corporation of China
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3653081.3653136
Reference17 articles.
1. Infrared Thermal Image Instance Segmentation Method for Power Substation Equipment Based on Visual Feature Reasoning;Zhao Z.;IEEE Transactions on Instrumentation and Measurement,2023
2. D. Lu, X. Liao, F. Xu and J. Bai, “Anomaly Detection Method for Substation Equipment Based on Feature Matching and Multi-Semantic Classification,” 2021 6th Asia Conference on Power and Electrical Engineering (ACPEE), Chongqing, China, pp. 109-113, 2021.
3. L. Yang, C. Yu, W. Li, S. Zhang, Z. Jiang and A. Xiao, “Intelligent Substation Equipment Condition Detection Method Based on Infrared Thermal Imaging Technology and Temperature Probability Density,” 2022 12th International Conference on Power and Energy Systems (ICPES), Guangzhou, China, pp. 383-387, 2022.
4. H. Yu, J. Zhang, J. Li and Y. Liu, “An Comprehensive Detection Method for Fault Location and Fire Risk Judgment of Substation Power Equipment,” 2021 IEEE 4th International Conference on Automation, Electronics and Electrical Engineering (AUTEEE), Shenyang, China, pp. 50-54, 2021.
5. S. Wang, S. Yang, P. Xu, M. Ren and X. Xu, “Substation Equipment Defect Detection based on Temporal-spatial Similarity Calculation,” 2021 3rd International Conference on Electrical Engineering and Control Technologies (CEECT), Macau, Macao, pp. 293-297, 2021.
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