指针式仪表读数识别的研究现状与发展  

Research status and development of pointer meter reading recognition

作　　者：钱玉宝[1] 王紫涵 邱腾煌 Qian Yubao;Wang Zihan;Qiu Tenghuang(College of Mechanical Engineering,Yangtze University,Jingzhou 434023,China)

机构地区：[1]长江大学机械工程学院,荆州434023

出　　处：《电子测量技术》2024年第8期110-119,共10页Electronic Measurement Technology

基　　金：国家采油装备工程技术研究中心项目(ZBKJ2021-A-03);长江大学研究生院项目(YJY202336)资助。

摘　　要：在高温高压强磁场等恶劣环境下,指针式仪表有着优于数显式仪表的良好性能表现,对指针式仪表读数识别进行研究具有重要的现实意义。近年来,深度学习与计算机视觉紧密结合,基于深度学习的指针式仪表读数识别技术是前沿研究的重点方向。文中首先概述指针式仪表读数识别的过程,然后从3个方面论述指针式仪表读数识别技术的研究现状与进展:仪表图像的预处理、仪表表盘区域的检测和仪表的读数识别,论述过程中分别阐述基于传统机器学习的方法和基于深度学习的方法。最后介绍公开的仪表数据集和应用场景,并从深度学习算法、巡检机器人工作特点和公共数据集的建立3个方面对未来的研究进行展望与建议。In harsh environments such as high temperature,high pressure,and strong magnetic fields,pointer instruments have shown superior performance compared to digital instruments.Therefore,the research on pointer instrument reading recognition has significant practical significance.In recent years,the combination of deep learning and computer vision has become a key focus in the research of pointer instrument reading recognition technology.This paper first outlines the process of pointer instrument reading recognition,and then discusses the research status and progress of pointer instrument reading recognition technology from 3 aspects:image preprocessing,dial region detection,and reading recognition.The paper elaborates on both traditional machine learning methods and deep learning methods.Finally,it introduces publicly available pointer instrument datasets and application scenarios,and provides prospects and suggestions for future research from the aspects of deep learning algorithms,inspection robot characteristics,and the establishment of public datasets.

关 键 词：指针式仪表 读数识别 深度学习 图像处理 视觉技术 

分 类 号：TP216.1[自动化与计算机技术—检测技术与自动化装置] TN802[自动化与计算机技术—控制科学与工程]