Cargando…
Lightweight Hot-Spot Fault Detection Model of Photovoltaic Panels in UAV Remote-Sensing Image
Photovoltaic panels exposed to harsh environments such as mountains and deserts (e.g., the Gobi desert) for a long time are prone to hot-spot failures, which can affect power generation efficiency and even cause fires. The existing hot-spot fault detection methods of photovoltaic panels cannot adequ...
Autores principales: | Zheng, Qiuping, Ma, Jinming, Liu, Minghui, Liu, Yuchen, Li, Yanxiang, Shi, Gang |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9231204/ https://www.ncbi.nlm.nih.gov/pubmed/35746399 http://dx.doi.org/10.3390/s22124617 |
Ejemplares similares
-
Intelligent Scheduling Methodology for UAV Swarm Remote Sensing in Distributed Photovoltaic Array Maintenance
por: An, Qing, et al.
Publicado: (2022) -
LOANet: a lightweight network using object attention for extracting buildings and roads from UAV aerial remote sensing images
por: Han, Xiaoxiang, et al.
Publicado: (2023) -
Fault-Level Grading of Photovoltaic Cells Employing Lightweight Deep Learning Models
por: Khosa, Ikramullah, et al.
Publicado: (2023) -
Diverse Planning for UAV Control and Remote Sensing
por: Tožička, Jan, et al.
Publicado: (2016) -
A Novel Approach for UAV Image Crack Detection
por: Li, Yanxiang, et al.
Publicado: (2022)