Research on Structural Dynamic Optimal Design of NC Internal Grinder


Article Preview

Structural dynamics optimal design of key components is basis to reach optimal design of whole machine tool. The method of sensitivity analysis is applied to optimize the arrangement shapes and parameters of the strengthened bars of components. The BP neural networks model of the spindle system is established and corrected based on comparing with the experimental result, and the structure parameters of the spindle are optimized. These technologies will benefit to realize optimal design of whole NC internal grinder and guide dynamic optimal design of other machine tools.



Advanced Materials Research (Volumes 129-131)

Edited by:

Xie Yi and Li Mi




R. F. Hu and X. P. Chen, "Research on Structural Dynamic Optimal Design of NC Internal Grinder", Advanced Materials Research, Vols. 129-131, pp. 814-818, 2010

Online since:

August 2010




[1] Hsieh C C, etc. Design Sensitivity Analysis and Optimization of Dynamic Response. Computer. maths, Applied mechanical . engineer. 1984, 43(2): 24~29.

[2] T. P. Yeh and J.M. Vance. Applying Virtual Reality Techniques to Sensitivity-Based Structural Shape Design . Journal of Mechanical Design , Transaction of the ASME, 1998 , (120): 621~619.


[3] Tang Wencheng, Yi Hong. Relations between the Plate Thickness and Dynamic Characters of Machine Tool Bed. Manufacturing Technology & Machine Tool. 1997(3): 13~14.

[4] Wu Changzhi , et, al. Analysis for the weak links of MG1432B. Journal of Mechanical Strength, 1992, 14(4): 51~56.

[5] Shi Hanmin, Chen Jihong, Yan Pngjiang. Artificial Neural Network and Its Application in the Field of Mechanical Engineering. China Mechanical Engineering. 1997, 8(6): 82~85.

[6] XU YanShen, et al. Research of dynamic design of machine tools bed structures based on optimization unit structures and frames. Journal of Mechanical strength, 2001, 23(1): 1~3.

[7] Huang ShiSen, Tian JiFang. Sensitivity Analysis and Modification of the Dynamic Behavior of Machine Structures, Journal of Tsinghua University, 1986, 26(4): 29~42.

[8] Huang Wenpei, Huang Hongzhong, Wang Jinnuo. Decomposition approach to mechanical structural systems optimization based on networks, 1997, 33(4): p.31~36.

[9] Wu. X etc. Use of neural networks in detection of structural damage. Computers and Structures, 1992, 42(4): 649- 659.


[10] Levin R. I, Lieven A.J. Dynamic Finite Element Model updating using neural networks, J. of Sound & Vibration, 1998, 210(5): 593~607.


[11] CHEN Xiao-ping, YU Xiao-li, JI Bing-wei. Study of Crankshaft Strength based on Isight Platform and DOE Methods. International Conference on Measuring Technology and Mechatronics Automation, 2010, vol. 3, p.548~551.