Kinematic error modeling and analysis of the loading device based on multi-body theory and stream of variation theory
Because of some reasons such as machining error and assembly clearance, the loading device will produce kinematic error during movement. While kinematic error will have a great significance on the position accuracy of the loading device. For the above reasons, firstly, the topological structure of the loading device was described based on lower body arrays. The kinematic error matrices of adjacent parts in the loading device were obtained by multi-body system kinematic theory and homogeneous translation matrix (HTM). Then an improved error modeling method was put forward, which combined multi-body system theory with stream of variation theory. And the kinematic error model of the loading device was set up with this method. Numerical results could clearly display the error transformation and propagation among components. Finally, the effect of every kinematic error on final deviation was analyzed, and error sources of a greater effect on the final deviation were obtained. This method can provide a theoretical basis to improve the accuracy of the loading device.
A Geometric Error Modeling Method and Trajectory Optimization Applied in Laser Welding System
In this paper, a geometric error modeling method is carried out on six-axis motion platform (SMP) in laser welding system (LWS), and an optimized algorithm is proposed for the alignment in LWS based on the error model. First, the topological structure of the given SMP is analyzed, and related homogeneous transformation matrices which are used for standing the orientation of SMP are established. By these matrices, the geometric error model is developed mathematically. Then, the error model is used for predicting the alignment deviations. A corresponding series of experiments for calculating the optical power loss in alignment are employed, and the comparison between simulation and experiments results indicate the validation of the error model. Furthermore, an optimized algorithm is applied to search the optimum aligning trajectory. Compared to conventional method, this algorithm has a broader range in searching extreme value, which can reduce the computational volume and improve the efficiency. It is also beneficial for improving the success rate of escaping from the local minimum spot and finding the optimum alignment spot. The error model is helpful to analyze the error propagation process and improve the alignment efficiency in LWS, which can be applied to other similar multi-axis precise system.
Adaptive model estimation of machine-tool thermal errors based on recursive dynamic modeling strategy
A systematic model adaptation methodology is developed in order to continuously update the thermal-error model under varying manufacturing conditions. Process-intermittent probing and adaptive system identification techniques are integrated to monitor and estimate machine-tool thermal errors and recursively modify model coefficients as manufacturing process proceeds. The recursive model adaptation, which is based on the Kalman filter parameter estimation technique and multiple-sampling horizons, minimizes intrusion to production while maintaining good model adaptation capability. The experimental results proved that the proposed methodology has good model accuracy and robustness to frequently changing working conditions.