Abstract
This paper analyzes the inspection error of the traditional electric energy meter constant inspection method. It is believed that the inspection error of the electric energy meter constant is mainly caused by the manual control pulse when the inspector carries out the last digit of the liquid crystal meter of the electric energy meter during the constant inspection. The time difference between the start and stop of the counter is not synchronized and the truncation error of the pulse counter recorded pulse. Based on the establishment of a smart energy meter image detection system with C# and Halcon as the software platform, the Blob analysis algorithm is used to extract the ROI (region of interest) from the image, and the histogram equalization is used to process the extracted image to enhance the contrast between the background and the target area can obtain a high-quality electric energy meter picture, and the Canny edge detection algorithm is improved by the OTSU algorithm to improve the adaptability of the image threshold range to obtain a more complete image appearance outline. Character segmentation processing to obtain the rated parameter information of the electric energy meter. According to the regulations of OIML and NE standards, through analysis and demonstration, an optimized solution for fast inspection of electric energy meter constants that not only meets the inspection error requirements specified in the standard but also shortens the test time is proposed.
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