DPIM algorithm for hoisting operation scene based on inspection robot
In order to improve the high-precision detection and early warning of crane safety operation and enhance the safety management ability of enterprises,focusing on the needs of unmanned industrial safety incident analysis and monitoring and early warning,an inspection robot that combines ground and air flight in hoisting scene was customized to intelligentize hoisting safety monitoring,pop-up image recording and safety alarm.A lifting dataset Cranes-Dataset(CRN-Dataset)containing 3 120 images was made,and DPIM algorithm was proposed to enhance the rapid detection ability of multi-scale objects.Based on corner detection and density-based spatial clustering of applications with noise and considering the safety attributes of the space distance between cranes and workers,the process of triggering alarms based on safety rules was developed to record real-time illegal operation image and popup alarm.The results show that,after actual deployment and verification,the DPIM algorithm significantly improves target identification ability compared with other traditional algorithms,and it is suitable for real-time calculation and data transmission of embedded edge intelligent analysis nodes to complete field deployment.
万方数据
维普
