• Opto-Electronic Engineering
  • Vol. 43, Issue 1, 1 (2016)
MA Lixin*, ZHOU Xiaobo, ZHU Run, and SHAN Yu
Author Affiliations
  • [in Chinese]
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    DOI: 10.3969/j.issn.1003-501x.2016.01.001 Cite this Article
    MA Lixin, ZHOU Xiaobo, ZHU Run, SHAN Yu. The Quantitative Classification of Corona Discharge Intensity of UV Detection[J]. Opto-Electronic Engineering, 2016, 43(1): 1 Copy Citation Text show less

    Abstract

    High voltage equipment that runs for a long time could produce corona discharge phenomenon. The harm of corona discharge is serious, so it’s necessary to detect the corona. As a new technology of detecting high pressure discharge equipment fault, this article used ultraviolet discharge detection that can fuse to corona and visible light images and can locate fault point accurately. The article used the theory of projection pursuit in genetic algorithm, and used the collection of ultraviolet corona figure after processing of the Delphi software as a hierarchical data, and the level model of genetic projection pursuit was set up to study the quantitative classification of corona discharge strength. The experimental results verified the rationality of the model. Test results achieve the desired requirements, and have certain practical significance to discharge fault detection.群体智能与智能电网等。
    MA Lixin, ZHOU Xiaobo, ZHU Run, SHAN Yu. The Quantitative Classification of Corona Discharge Intensity of UV Detection[J]. Opto-Electronic Engineering, 2016, 43(1): 1
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