Research on UV image processing technology for high voltage line inspection
In order to cope with the gradual increase in social electricity consumption, people have invested a lot of resources to expand high-voltage transmission lines, and high-voltage line inspection is a key link to maintain its stable operation. High-voltage equipment discharge produces weak ultraviolet light, part of the wavelength is located in the day-blind region (240nm to 280nm), which can avoid the interference of sunlight on the ultraviolet. Therefore, the use of day-blind UV detectors can accurately identify high-voltage corona discharges, avoiding problems such as energy waste and line short circuits. The efficiency of the photocathode is an important factor in photon detection technology and affects the detection performance of the UV image intensifier. In this paper, we analyze the light absorption characteristics of AlGaN crystals under the conditions of different Al fractions and the effect of Al fractions on the quantum efficiency of AlGaN photocathode in combination with the characteristics of AlGaN crystals. The aim of this study is to reveal the main factors affecting the cathode photoemission performance and to explore the optimization method for the preparation of AlGaN photocathodes. The application of AlGaN photocathode in UV image processing is studied in depth, and the imaging characteristics in the UV band and its noise characteristics and models are analyzed. Matlab is utilized for video image processing. After obtaining the comparison graph of the effect of different algorithms, the effect of different algorithms is compared with the peak signal-to-noise ratio of the image to obtain the best algorithm. The results show that the UV image intensifier based on reflective AlGaN photocathode has high quantum efficiency and stability. In UV imaging, the effect of using time-domain median filtering processing is better than other processing algorithms, and the noise is greatly reduced, which makes it easy to observe the corona discharge position and thus obtain high-quality images.
Authors
- Boran Ma (ORCID: https://orcid.org/0009-0003-6543-3130)
- Xingjie Li (ORCID: https://orcid.org/0000-0002-5623-9681)
- Richard Fu
- Yafeng Qiu (ORCID: https://orcid.org/0009-0002-0282-8875)
Institutions
- Nanjing University of Science and Technology (CN)
Publication Details
- Published
- 2025-05-23
- DOI
- https://doi.org/10.1117/12.3055153
- Primary Topic
- Advanced Measurement and Detection Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00