Research on Early Warning and Monitoring Systems for Contact Between Live Equipment and Foreign Objects
ABSTRACT Addressing the safety hazards arising from inadequate clearance between tree growth and power facilities, this paper innovatively proposes an online monitoring and early warning system for distribution networks based on advanced image processing technology. The system integrates three core functions: automatic tree species identification, precise detection of safety distances between tree crowns and live equipment, and real‐time foreign object contact warnings. By deploying maintenance‐free online monitoring terminals, the system can monitor tree growth around the distribution network around the clock, continuously. It utilizes efficient backend algorithms to intelligently analyse the collected image data, promptly detecting and warning of potential tree‐obstacle hazards. Compared to traditional manual inspections and UAV inspections, this system not only significantly improves monitoring accuracy and real‐time performance but also overcomes the limitations of UAV inspections, such as high costs and poor real‐time performance. The solution proposed in this paper is expected to fundamentally enhance the safe operation level of distribution networks and effectively reduce power accidents such as tripping and short circuits caused by tree obstacles. Future plans include further optimizing system functions to promote the wider application and promotion of the technology.
Authors
- Weimin Xia (ORCID: https://orcid.org/0000-0002-8151-9618)
- Kaiyang Liao (ORCID: https://orcid.org/0000-0003-0833-2336)
- Yuan Fang (ORCID: https://orcid.org/0000-0003-0531-6066)
- Boyuan Chen (ORCID: https://orcid.org/0009-0003-4012-1659)
- Yingying Tan
Institutions
- Xi'an University of Technology (CN)
Publication Details
- Journal
- IET Image Processing
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1049/ipr2.70101
- Primary Topic
- Anomaly Detection Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China