Mechanism and data combined burr prediction method for robot drilling

Due to its advantages of high spatial accessibility and flexibility, the robot hole-making system is widely used in parts processing scenes with large size and complex structure and technology. However, due to the poor rigidity of the system, it will chatter and burr easily during hole-making. According to the above problem, a prediction method of mechanism and data fusion was proposed to predict the burr height at the exit of robot hole making. A static physical model for the prediction of drilling burr height based on drilling force and flutter model was constructed, and the preliminary prediction of burr height was carried out. And based on it, the data dynamic update model was used to revise and update it. The model was verified by the robot drilling experiment, and the experimental results show that the accuracy of the method for the classification of the burr height reaches 94.74%.This prediction method lays a foundation for active control of hole burr and improvement of machining quality of hole making system. © 2022, Editorial Board of Journal of Huazhong University of Science and Technology. All right reserved.