Automatic verification method of relay protection equipment setting value combining cell image gray enhancement and AI recognition

计算机科学 直方图 人工智能 阈值限值 回溯 图像(数学) 粒子群优化 分割 计算机视觉 图像分割 二进制数 模式识别(心理学) 数据挖掘 算法 数学 医学 算术 环境卫生
作者
Xianshan Sun,Yuefeng Sheng,Hongfei Mao,Qingfeng Qian,Qingnan Cai
出处
期刊:Journal of Intelligent and Fuzzy Systems [IOS Press]
卷期号:: 1-13
标识
DOI:10.3233/jifs-234457
摘要

In order to solve the problems of tedious, insufficient manpower, low efficiency, and easy to cause human errors in the verification of relay protection equipment settings with the development of the power grid, an automatic verification method of relay protection equipment settings combining cell image gray enhancement and AI recognition is studied. In this method, Gaussian mixture and particle swarm algorithm are used to enhance the gray level of the original image captured, and the binary method is used to further denoise the image; The histogram is used to segment the cells in the denoised constant value image one by one; The OCR technology in AI technology uses the maximum width backtracking segmentation algorithm to segment a coherent text in a cell into multiple single words, and collects the 13 dimensional characteristics of the text to be detected to compare with the text in the database. The text with the smallest error is the detected text, which completes the text extraction in the cell; Store the extracted text data in the database, check the data in the notification constant value sheet and the device constant value sheet, and give an abnormal prompt of different data. The experimental results show that the image pre processed by this method is clear, the fixed value single cell segmentation is accurate, and the OCR text extraction efficiency is high. Through a large number of data experiments, the final verification accuracy can reach 99.8% .

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