Research of SF6 Pressure Gauge Automatic Reading Methods Based on Machine Vision

Abstract : With the rapid development of artificial intelligence and pattern recognition, digital image processing and recognition technologies become a popular research direction, especially, the using of it is quite extensive in power industry. Among various using, dashboard automatic reading is an important part of routing inspection of substation system by using robot. Automatic reading of SF6 pressure gauge pointer is based on image processing and automatic reading techniques, avoiding the influence of subjective factors of naked eye judgment. Designing and analyzing of identification algorithm ofSF6 meter pointer are shown in this paper. First, pre-processing operations were operated on the instrument image by using gray level transformation equalization and binarization to improve image quality, by using Hough line detection to realize pointer line extraction; determining the number by using the straight-line in mathematics. This traditional method of using morphological and Hough line detection method to determine reading have certain bias, so the using of Hough circle detection methods and centroid detection methods were proposed. The results showed that the improved method has greatly improved the accuracy of the readings, the method has better accuracy than traditional standard line Hough detection method.
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Communication dans un congrès
Daoliang Li; Yingyi Chen. 8th International Conference on Computer and Computing Technologies in Agriculture (CCTA), Sep 2014, Beijing, China. IFIP Advances in Information and Communication Technology, AICT-452, pp.534-545, 2015, Computer and Computing Technologies in Agriculture VIII. 〈10.1007/978-3-319-19620-6_60〉
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Song Yao, Liu Chunhong, Deng Qiao, Wang Yixuan. Research of SF6 Pressure Gauge Automatic Reading Methods Based on Machine Vision. Daoliang Li; Yingyi Chen. 8th International Conference on Computer and Computing Technologies in Agriculture (CCTA), Sep 2014, Beijing, China. IFIP Advances in Information and Communication Technology, AICT-452, pp.534-545, 2015, Computer and Computing Technologies in Agriculture VIII. 〈10.1007/978-3-319-19620-6_60〉. 〈hal-01420269〉

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