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1 March 2023 Measurement error detection method of electric energy meter based on machine vision
Zhen Gu, Daihu Chen, Jin Wang, Chen Dai, Gewei Zhuang
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Proceedings Volume 12588, International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2022); 1258816 (2023) https://doi.org/10.1117/12.2667641
Event: International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2022), 2022, Chongqing, China
Abstract
Due to the slow response and poor accuracy of traditional measurement error detection of the electric energy meter, the measurement error detection method of electric energy meter based on machine vision is studied. The minimum error method is used to segment the image threshold to form a binary image. The morphological refinement method is used to extract the image edge contour, combined with machine vision to refine the edge pixels, to achieve the measurement error detection of the instrument. The experimental results show that using the error detection method of machine vision, the detection results are consistent with the error detection results set by the system and the trend is the same. The accuracy also meets the requirements of relevant regulations, which improves the accuracy of electric energy meter measurement.
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Zhen Gu, Daihu Chen, Jin Wang, Chen Dai, and Gewei Zhuang "Measurement error detection method of electric energy meter based on machine vision", Proc. SPIE 12588, International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2022), 1258816 (1 March 2023); https://doi.org/10.1117/12.2667641
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KEYWORDS
Error analysis
Image segmentation
Machine vision
Image processing
Technology
Environmental sensing
Image filtering
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