Research And Implementation Of Fault Diagnosis System For Robotic Arm Based On Digital Twin

Robotic arms are automatic control equipment that imitate the functions of human arms and can complete various tasks.They have been widely used in many fields such as industrial production,medical and health care,military and aerospace.When the robotic arm is running,failure to promptly judge its health status and handle it will lead to serious consequences.However,existing fault diagnosis methods require a large number of damage experiments to obtain fault characteristic data,which have long cycle times,high costs,and low safety.Therefore,this paper proposes a fault data generation and fault diagnosis method based on digital twins.The main contents are as follows:This study explores the construction method of a robotic arm digital twin model,building a digital twin body of the robotic arm from multiple dimensions,including visual models,kinematic models,and dynamic models.We also design a model accuracy validation method and update mechanism to achieve high fidelity and consistency of the digital twin model.Additionally,we realize the functions of virtual-to-real and virtualto-control of the digital twin body and entity.We design a fault diagnosis scheme based on digital twin technology.By constructing a high-fidelity digital twin body using digital twin technology,we can obtain fault data from different operating conditions and devices for training.Then,we use transfer learning to transfer the fault diagnosis model trained on the digital twin device to the actual device,thereby solving the problem of scarce fault samples.We conduct experiments on fault diagnosis of robotic arms based on digital twins,and after comparison with other algorithm models,the transferred fault diagnosis model achieves the best results.We establish a digital twin monitoring system to collect and process data from robotic arms.Finally,we conduct data insertion tests,equipment simulation tests,and fault diagnosis tests on the system.The results show that the system can achieve real-time monitoring and control of robotic arms,and the delay and deviation of the digital twin body and entity movement meet the requirements,supporting data writing of about 50,000 QPS.