Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/2813
標題: 利用最小位能原理分析圓環之最小環帶誤差
Minimum zone torisity using minimum potential energy algorithms
作者: 施彥嘉
Shih, Yen-Chia
關鍵字: 最小環帶誤差;minimum zone error;形狀誤差;圓環;最小位能原理;虛功原理;form error;Torus;Torisity;minimum potential energy;principle of virtual work
出版社: 機械工程學系所
引用: [1] Fan, K. C., Lee, J. C., “Analysis of minimum zone sphericity error using minimum potential energy theory,” Precision Engineering, Vol. 23, pp. 65-72, 1999. [2] Huang, P. H., Lee, J. C., “Minimum zone evaluation of conicity error using minimum potential energy algorithms,” Precision Engineering, Vol. 34, pp. 709-717, 2010. [3] ASME standard Y14.5M-1994, “National Standard on Dimensioning and Tolerancing,” The American Society of Mechanical Engineers, New York, 1994. [4] Lai, H. Y., Jywe, W. Y., Chen, C. K., “Precision modeling of form errors for cylindricity evaluation using genetic algorithms,” Precision Engineering, Vol. 24, pp. 310-319, 2000. [5] Zhang Ke, “Minimum Zone Evaluation of Sphericity Error Based on Ant Colony Algorithm,” IEEE International conference on Electronic Measurement and Instruments, pp. 535-538, 2007. [6] Aguirre-Cruz, J. A., and Raman, S., “Torus form inspection using coordinate sampling,” ASME J. Manufacturing Science and Engineering, Vol. 127, pp. 84-95, 2005. [7] Prakasvudhisarn, C., Kunnapapdeelert, S., “Torusity Tolerance Verification Using Swarm Intelligence,” Industrial Engineering and Management Systems, Vol. 6, pp. 94-105, 2007. [8] Yong Wang, Lin Li, Jun Ni, S. h. Huang, “Form Tolerance Evaluation of Toroidal Surfaces Using Particle Swarm Optimization,” ASME J. Manufacturing Science and Engineering, Vol. 131, pp. 1-9, 2009. [9] J. Kennedy, R. Eberhart, “Particle swarm optimization,” IEEE Conference Neural Networks, Vol. 4, pp. 1942-1948, 1995. [10] R. Storn, K. Price, “Differential Evolution - A simple and efficient adaptive scheme for global optimization over continuous spaces,” Technical report, California: International Computer Science Institute, Berkeley, 1995.
摘要: 
本論文利用最小位能原理探討圓環之最小環帶誤差,此最小環帶誤差是以尋找系統最小位能的方式,並形成兩同圓環軸線、中心、圓環半徑之圓環表面虛擬機構系統,而所有之數據資料點必須完全被包圍在此虛擬機構系統內,當系統彈簧在收縮過程中促使兩圓環的逼近,也因此系統朝著最小彈力位能之方向前進,直到最後系統達到一個穩定狀態為止,此時兩圓環所形成之法向距離即為圓環之最小環帶誤差。
本文提出一個調整形狀誤差策略加以改進最小位能演算法,對於求解高維度及大量數據資料點之問題下,能夠在更短的計算時間獲得結果。試驗結果並與粒子群優化和差分進化算法比較後,說明了本方法的有效性。

In this paper, minimum zone evaluation of torus using minimum potential energy algorithms. Minimum zone error based on looking for minimum potential energy of the system. The virtual system consists of two coaxial, same center,and same distance form the center of the tube to the center of the torus. All data points are enclosed within two fictitious torus surface. When the system spring to promote the approximation of two torus surfaces in the process of contraction. Therefore, the virtual system towards the direction of minimum elastic potential energy. Finally, the system reaches stable state with minimum potential energy. Normal deviation between such two torus surfaces becomes minimum zone error.
This paper presented an adjustment form error strategy based on minimum potential energy algorithms. For solving the problem of high dimensions and large number of data points, experimental results will be obtained in a shorter computing time. The control experiment results evaluated by different method such as particle swarm optimization and differential evolution, indicate that effectiveness of proposed method.
URI: http://hdl.handle.net/11455/2813
其他識別: U0005-2607201212493400
Appears in Collections:機械工程學系所

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