【摘要】 热误差对于主轴的回转精度至关重要，而对流换热系数的精确计算是有限元稳态热分析获得精确结果的前提。通过利用狮群优化（Lion Swarm Optimization, LSO）算法对主轴的对流换热系数进行优化，LSO相对于遗传算法等其他优化算法有更快的收敛速度、更高的精度、更能较好地获得全局最优解。首先，通过使用Lion的热分析模块测量主轴系统的关键点温度和主轴的热伸长。其次，通过经验公式计算主轴不准确但接近真实的对流换热系数值，不准确的对流换热系数会导致不准确的有限元仿真温度结果，因此使用LSO对对流换热系数寻优，将对流换热系数被视为感兴趣的目标值，实验温度值与模拟温度值之间的均方根误差被视为适应度函数。在150代之后，搜索了误差最小的最佳对流换热系数。最后，通过对搜索到的最优对流换热系数进行主轴系统的有限元稳态热分析，并与实验结果进行比较，证明了所提方法的有效性。更多还原

【Abstract】 Heat is very important to the rotation accuracy of the spindle, and the accurate calculation of the convection heat transfer coefficient is the premise of obtaining accurate results from the finite element steady-state thermal analysis. In this paper, the convective heat transfer coefficient of the main shaft was optimized by using the lion swarm optimization(LSO) algorithm. Compared with other optimization algorithms such as genetic algorithm, the LSO algorithm has faster convergence speed, higher accuracy, and better global optimal solution. Firstly, the critical point temperature of the spindle system and the thermal elongation of the spindle were measured by using Lion′s thermal analysis module. Secondly, the inaccurate but close to real convective heat transfer coefficient value of the main shaft was calculated by empirical formula. Inaccurate convective heat transfer coefficient was led to inaccurate finite element simulation temperature results, so used the lion optimization algorithm to optimize the convective heat transfer coefficient, the convection heat transfer coefficient was regarded as the target value of interest, and the root mean square error between the experimental temperature value and the simulated temperature value was regarded as the fitness function. After 150 generations, the optimal convective heat transfer coefficient with the smallest error was searched. Finally, the finite element steady-state thermal analysis of the spindle system was carried out on the searched optimal convective heat transfer coefficient, and the comparison with the experimental results proved the effectiveness of the proposed method.更多还原