基于机器视觉的指针式压力表智能检定系统研究

doi:10.3969/j.issn.1000-1158.2022.11.10

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摘要针对传统的指针式压力表检定装置工作效率低、数据无法保存追溯等问题, 设计了一种基于机器视觉技术的指针式压力表智能化检定系统。首先介绍了系统的硬件架构与软件设计, 然后对其图像解析的技术原理与解决方案进行了阐述,同时提出了系统的智能控制流程与检定数据的追溯复核方法, 实现了2~10块相同检定点的压力表同时进行计量检定的技术方案。实测结果表明, 系统图像解析平均速度为467ms/帧, 检定效率较人工检定可提升2倍以上; 对于量程2.5MPa的0.4级精密压力表和1.6级一般压力表, 系统读数相对误差分别为0.08%、0.2%。

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	伍开宇
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关键词 ：计量学, 指针式压力表, 检定系统, 机器视觉, 智能化, 追溯复核法

Abstract：In order to solve the problems of low efficiency of traditional calibration device of pointer pressure meter, data can not be kept and traced, an intelligent detection system of pointer pressure meter based on machine vision technology is designed. Firstly, the hardware architecture and software design of the system are introduced, and then the technical principle and solution of image analysis are expounded. At the same time, the intelligent control process of the system and the retrospective review method of verification data are put forward, and the technical scheme of simultaneous verification of 2~10 pieces of pressure meters with the same inspection point is realized. The experimental results show that the average speed of image analysis is 467ms per frame, and the verification efficiency can be increased by more than 2 times compared with manual verification. The relative error of the system reading is 0.08% and 0.2% respectively for the class 0.4 precision pressure meter and class 1.6 general pressure meter with a range of 2.5MPa range.

Key words： metrology pointer pressure meter verification system machine vision intelligentize;retrospective review method

收稿日期: 2021-06-23 发布日期: 2022-11-14

PACS:

TB937

通讯作者: 朱海清(1965-), 男, 江西丰城人, 江南大学副教授, 硕士生导师, 主要从事过程装备与控制工程领域的研究。Email:809075521@qq.com E-mail: 1790083082@qq.com

作者简介: 伍开宇(1998-), 男, 湖南娄底人, 江南大学在读研究生,主要研究方向为机械仪表(压力表)智能化检测。Email:1273124525@qq.com

引用本文:

伍开宇,朱海清,沈晓东,沈伟,方明. 基于机器视觉的指针式压力表智能检定系统研究[J]. 计量学报, 2022, 43(11): 1450-1455.
WU Kai-yu,ZHU Hai-qing,SHEN Xiao-dong,SHEN Wei,FANG Ming. Research on Intelligent Verification System of Pointer Pressure Meter Based on Machine Vision. Acta Metrologica Sinica, 2022, 43(11): 1450-1455.

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