煤矿安全2024，Vol.55Issue(5)：251-256,6.DOI:10.13347/j.cnki.mkaq.20231389
基于机器视觉的异物识别系统在输送机保护中的应用
Application of foreign object recognition system based on machine vision in conveyor protection
摘要
Abstract
This article designs a foreign object recognition system based on machine vision and applies it to the protection of the main transportation belt conveyor.The study uses YOLOv5s as the deep learning model to deploy the trained model to the edge com-puting module.Real time video is captured by an industrial intrinsic safety camera and transmitted to the edge computing module to identify the foreign matters in the coal flow.Finally,only the recognition results are transmitted externally.When a high level of for-eign object danger is detected,an alarm signal will be sent to the collaborative controller,which will issue a shutdown command to the specific single controller.Simultaneously upload the processed real-time video and alarm information to the control platform for display.This design improves the intelligence,stability,and reliability of the protection of the current main conveyor belt conveyor.关键词
带式输送机保护/异物识别/机器视觉/深度学习/边缘计算Key words
belt conveyor protection/foreign object identification/machine vision/deep learning/edge computing分类
矿业与冶金引用本文复制引用
于志强..基于机器视觉的异物识别系统在输送机保护中的应用[J].煤矿安全,2024,55(5):251-256,6.基金项目
天地(常州)自动化股份有限公司科研资助项目(2022FY0009) （常州）
