基于灵敏度分析的角向磨光机散热性能优化

Optimizing Performance of Heat Dissipation in Angle Grinder with Sensitivity Analysis

现代机械加工中,对于角向磨光机的散热性能要求越来越高,因此针对角磨散热性能进行了形状优化设计。首先对角磨进行三维参数化建模,考查其内部热流动情况。选定设计变量,构造目标函数,通过对角向磨光机参数样本点及角磨内部温度分布进行灵敏度分析,运用样条曲线与神经网络算法两种方式拟合目标函数,建立优化模型以找出降低角磨内部最高温度和电机两端温差的最优解。最后模拟最优解时的角磨内部温度分布情况,结果证明,本方法确能改善角磨散热效能。

There are increasing requirements for the thermal performance of an angle grinder in the machining industry, so the shape of the angle grinder in terms of its heat dissipation optimizes. It establishes the three-dimen- sional parametric modeling of the angle grinder to examine its internal thermal flow. Then it develops an objective function and conducts the sensitivity analysis of the sample points of the parameters of the angle grinder. The spline curve fitting and neural network algorithms are used to model the shape of the angle grinder and to seek the optimal solutions for reducing its maximum temperature and the temperature difference between the two ends of its motor. The internal temperature distribution during the optimal solution is simulated in the paper. The simulation results show that the method can enhance the heat dissipation in the angle grinder.