Abstract
Industrial robots have been proven to be more widely suitable for machining than CNC machines in many applications. However, their lack of rigidity and precision is still a limit for precision tasks. The dynamic behavior of robotic milling system has a significant effect on machining quality. The main difference of dynamic behavior between robot and CNC is that the robot’s modes greatly shift, depending on its varying dynamic parameters and joint configurations. Therefore, it is of great significance to study the dynamic characteristics of the robot to suppress the machining chatter and improve the machining accuracy of the robot. Firstly, a series of modal tests are conducted on a milling robot Considering that the robotic milling system is a time-varying system. The improving accuracy FRFs (frequency response function) are obtained by the low-frequency sensitive accelerometer and high-frequency sensitive accelerometer. The accelerometers are used to conduct corresponding modal tests on robot structure and tool-spindle of the system respectively. Then, in order to smooth the curve and splice the data of the two FRFs, a new method for multi-sensor modal information fusion using moving average method and weighted average method is presented. The experimental support for chatter-free prediction in robot high-speed milling by the regenerative chatter theory. The dynamic behavior for Robotic Milling System is analyzed at last.
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Hao, D., Wang, W., Zhang, G., Wang, Q., Yun, C. (2019). Dynamic Behavior Analysis and Multi-sensor Modal Information Fusion for Robotic Milling System. In: Yu, H., Liu, J., Liu, L., Ju, Z., Liu, Y., Zhou, D. (eds) Intelligent Robotics and Applications. ICIRA 2019. Lecture Notes in Computer Science(), vol 11745. Springer, Cham. https://doi.org/10.1007/978-3-030-27529-7_40
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DOI: https://doi.org/10.1007/978-3-030-27529-7_40
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