关键词: 人员智能管控, 数字孪生模型, 自适应学习, 视觉增强检测

Abstract: Human is the basic unit of manufacturing resources in the workshops.Due to the high degree of uncertainty in human's autonomous activities,it has always been difficult to obtain the information about the location and quantity of the staffs in the digital twin workshops.Concerning the urgent needs of real productions,an adaptive workshop staff recognition network (namely,Adaptive Rec-network) was proposed,which used the human in the loop approach to enhance the detection in the complex environment in the workshop.Comparing with the our former 3-Stage Cascade Convolutional Neural Network (3-Stage CCNN),the experiments demonstrated that the proposed model was more efficient,accurate and adaptive,and provided stable and accurate data for the digital twin.

Key words: workshop staff management, digital twin model, adaptive learning, visual enhanced detection