Papers by Author: Xiu Shan Wang

Abstract: The thermal error model of the ucp710 5-axis machine tool was acquired by the homogeneous coordinate transformation, and includes 17 thermal error components. The thermal behavior of the ucp710 machine tool has been tested and the temperature fields were recorded by the compensation control and temperature sensing systems. The developed compensation system has been applied to the ucp710 5-axis machine tool, and the accuracy has been improved about 1 times after compensation, demonstrating a very high potential for the error compensation of CNC machine tools.

Abstract: The thermal error model of the 5-axis grinding machine tool was acquired by the homogeneous coordinate transformation, including 17 thermal error components. The thermal volumetric error real time compensation model was built by using the multiple regression analysis. The thermal error compensation control system and the temperature sensing system were developed and used as real-time compensation for the 5-axis grinding machine tool.

Abstract: Based on the synthetic analysis of thermal error sources, ICA (Independent component analysis) method is proposed to reduce the number of temperature sensor, and the selected temperature variables is used for thermal error modeling of gear hobbing machine. Finally, the hardware system of thermal error compensation is presented based on SCM (Single chip microcomputer) technique, and which is tested on Y3150K hobbing machine then. The results show that cumulative pitch error is reduced from 80μmto 20μm, and the machining accuracy is improved more than 2 grades.

Abstract: Thermal errors and force-induced errors are two most significant sources of the NC grinding machine inaccuracy. And error compensation technique is an effective way to improve the manufacturing accuracy of the NC machine tools. Effective compensation relies on an accurate error model that can predict the errors exactly during machining. In this paper, a PSO–BP neural network modeling technique has been developed to build the model of the dynamic and highly nonlinear thermal errors and grinding force induced errors. The PSO–BP neural network modeling technique not only enhances the prediction accuracy of the model but also reduces the training time of the neural networks. The radial error of a grinding machine has been reduced from 27 to 8μmafter compensating its thermal error and force-induced error in this paper.

Abstract: Aimed at the requirement of a project, a man-machine cooperation(MMC) manipulator was designed based on its system structure and man-machine function analysis. Meanwhile, the system functions were allocated between man and manipulator, and in order to realize information integration in MMC material handling system, a application method of mechatronics was discussed. Then an example is given to express one of the realization methods of information communication between man and manipulator.

Abstract: The synthesis error model of UCP710 five-axis machining center is divided into two parts: the position and orientation error models, and the article gets their models which are used as real-time compensation. One data collector system of thermal displacement and temperature is developed and used as real-time compensation for UCP710. The results of thermal error compensation have proved that the error model is correct and collector system works well.