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Multi-Object Detection Algorithm in Wind Turbine Nacelles Based on Improved YOLOX-Nano.
- Source :
-
Energies (19961073) . Feb2023, Vol. 16 Issue 3, p1082. 13p. - Publication Year :
- 2023
-
Abstract
- With more and more wind turbines coming into operation, inspecting wind farms has become a challenging task. Currently, the inspection robot has been applied to inspect some essential parts of the wind turbine nacelle. The detection of multiple objects in the wind turbine nacelle is a prerequisite for the condition monitoring of some essential parts of the nacelle by the inspection robot. In this paper, we improve the original YOLOX-Nano model base on the short monitoring time of the inspected object by the inspection robot and the slow inference speed of the original YOLOX-Nano. The accuracy and inference speed of the improved YOLOX-Nano model are enhanced, and especially, the inference speed of the model is improved by 72.8%, and it performs better than other lightweight network models on embedded devices. The improved YOLOX-Nano greatly satisfies the need for a high-precision, low-latency algorithm for multi-object detection in wind turbine nacelle. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 19961073
- Volume :
- 16
- Issue :
- 3
- Database :
- Academic Search Index
- Journal :
- Energies (19961073)
- Publication Type :
- Academic Journal
- Accession number :
- 161820116
- Full Text :
- https://doi.org/10.3390/en16031082