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Research on Reading Recognition Method of Pointer Meters Based on Deep Learning Combined with Rotating Virtual Pointer

机译:基于深度学习的指针仪表阅读识别方法与旋转虚拟指针相结合

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There are still a large number of pointer meters in substations, which mainly rely on manual inspection to detect the readings of pointer meters. In order to solve the above problems, this paper proposes a pointer meter keypoints detection method based on deep learning combined with virtual pointer rotation to determine the meter readings. This method first uses the deep learning algorithm to train data set of pointer meters and obtain the keypoints information of pointer meters. According to the keypoints information, we can further determine the center of rotation and radius of the pointer meter, then the real position of the pointer meter can be determined. Finally, according to the meter range information, as well as the real pointer angle and the meter range angle, we can calculate the readings of the pointer meter. The experiment results show that the proposed method can quickly and accurately obtain the pointer position, and further identify the meter readings. The proposed method can reduce the uncertainty caused by manual inspection and have a great impact on intelligent development of substations.
机译:变电站仍有大量指针仪表,主要依靠手动检查来检测指针仪表的读数。为了解决上述问题,本文提出了一种基于深度学习的指针仪表关键点检测方法,与虚拟指针旋转相结合,以确定仪表读数。该方法首先使用深度学习算法来培训指针计的数据集并获取指针计的关键点信息。根据关键点信息,我们可以进一步确定指针仪的旋转中心和半径,然后可以确定指针计的实际位置。最后,根据仪表范围信息,以及真实指针角度和仪表范围角,我们可以计算指针仪表的读数。实验结果表明,该方法可以快速准确地获得指针位置,进一步识别仪表读数。该方法可以减少手动检查引起的不确定性,对变电站的智能发展产生了很大的影响。

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