【摘要】 随着人工智能技术的迅猛发展,工业生产中的缺陷检测正逐渐从传统的人工目视方法转向计算机视觉技术,如何将机器视觉技术实际应用已成为工业生产中的重要任务。设计了一种基于数据驱动的冷轧板表面质量检测系统,以提升自动化专业学生在工业自动化领域应用人工智能的能力。该系统涵盖了从工业大数据处理、机器视觉模型训练到工业部署和人机界面设计的完整流程,为学生提供了真实的工业应用背景和切实可行的实验设计方案。该教学实验系统具有较强的实用性和跨学科特点,适用于广泛的实际工业应用场景。更多还原

【Abstract】 With the rapid development of artificial intelligence technology,defect detection in industrial production is gradually transitioning from visual inspection methods to computer vision technology.Effectively applying machine vision technology has become an important task in industrial production.This paper designs a data-driven surface quality detection system for cold-rolled plates to enhance students’ ability to apply artificial intelligence in industrial automation.The system covers the complete process from industrial big data processing and machine vision model training to industrial deployment and human-machine interface design,providing students with a real industrial application background and feasible experimental design solutions.This teaching and experimental system is highly practical and interdisciplinary,making it suitable for a wide range of real industrial application scenarios.更多还原