基于深度学习与机器视觉的起重机吊装安全监测方法OA

With the rapid development of China's economy,various large-scale projects emerge one after another,and the demand for crane hoisting operation is increasing.However,there are still many safety hidden dangers in the process of hoisting operation,which can easily cause casualties and other safety accidents.Therefore,this paper proposes a crane hoisting safety monitoring method based on deep learning and machine vision.The combination of deep learning and machine vision is used to identify and locate the suspended objects and workers in the surveillance images,and at the same time can independently judge whether workers wear helmets or not.According to the identification and positioning information of the monitoring model,the spatial relationship between the worker and the suspended object is obtained,which provides safety early warning information for the hoisting process of the crane.In order to improve the practicability and portability of the proposed method,an intelligent monitoring system for crane hoisting safety is developed,which can not only display the recognition results of monitoring images in real time,but also output the semantic description of the scene and send out safety early warning signals.