基于机器视觉的压力表全自动化检定系统

Automatic Verification System of Pressure Meter Based on Machine Vision

针对人工检定压力表时存在的效率低下且目视读数易引入误差等问题,设计一套基于机器视觉的压力表全自动化检定系统,并开发配套的控制软件和识别算法。控制软件面向自动化过程设计,引入多线程、容器化和监听事件技术,协调控制PLC、机械臂、工业摄像头、标准压力发生器等硬件,实现检定过程全自动化,且支持多块压力表同时检定。考虑到工控机配置低的情况,结合深度学习模型Paddle和OpenCV库设计一种轻量化的识别算法,该算法不仅占用内存少、运算速度快,而且识别信息更加丰富、识别准确率更高。实验结果表明:该系统能够有效提升检定效率,减少人为误差,具有应用和推广价值。

Aiming at the problems of low efficiency and easy introduction of errors in visual readings when manually verification pressure meter,an automatic verification system of pressure meter based on machine vision was designed,and the control software and recognition method were developed.The control software was designed for automation processes,introducing multi-threading,containerization,and monitoring event technology.It controlled hardware such as PLC,robotic arm,industrial camera,and standard pressure generator in the system to achieve automation of the calibration process,and supported simultaneous verification of multiple pressure meter.Considering the low configuration of industrial computers,a lightweight recognition method was designed based on the deep learning model Paddle and the OpenCV library.This method not only takes up less memory and has fast operation speed,but also has richer recognition information and higher recognition accuracy.The experimental results show that the system can effectively improve verification,reduce human error,and has application and promotion value.