Abstract
The industrial robot machining performance is highly dependent on dynamic behavior of the robot, especially the natural frequency. This paper aims at introducing a method to predict the natural frequency of a 6R industrial robot at random configuration, for improving dynamic performance during robot machining. A prediction model of natural frequency which expresses the mathematical relation between natural frequency and configuration is constructed for a 6R robot. Joint angles are used as input variables to represent the configurations in the model. The quantity and range of variables are limited for efficiency and practicability. Then sample configurations are selected by central composite design method due to its capacity of disposing nonlinear effects, and natural frequency data is acquired through experimental modal test. The model, which is in form of regression equation, is fitted and optimized with sample data through partial least square (PLS) method. The proposed model is verified with random configurations and compared with the original model and a model fitted by least square method. Prediction results indicate that the model fitted and optimized by PLS method has the best prediction ability. The universality of the proposed method is validated through implementation onto a similar 6R robot.
Highlights
Common industrial robot is of open-loop articulated serial structure with six revolute joints (6R); the stiffness and dynamic performance are much inferior to machine tool, which results in vibration issues and poor surface quality in machining process [13]
The two models constructed for two different robots through the method proposed in this paper models constructed two robots through the method proposed in this paper both The owntwo good prediction ability.for
Once the prediction model of natural frequency is constructed and verified, the prediction result can be used as optimization parameter to improve the machining performance
Summary
In the whole workspace, the stiffness and dynamic behavior nearly remain steady, so machining stability and chatter suppression, which are concerned with multiple factors, are research emphasis [10,11,12]. Common industrial robot is of open-loop articulated serial structure with six revolute joints (6R); the stiffness and dynamic performance are much inferior to machine tool, which results in vibration issues and poor surface quality in machining process [13]. Dynamic behavior of robot is studied to evaluate the capacity of dealing with time-variant load in machining process, which may help to suppress vibration [18,19]. As 6R robot realizes movement through adjusting joint angles, dynamic behavior keeps varying with configurations during motion process. Bisu et al [20] selected
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