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将模糊技术与RBF神经网络相结合并应用于机床热误差建模中,构建了基于模糊RBF神经网络的数控机床热误差模型;以某龙门导轨磨床主轴箱系统为实例,将模糊RBF神经网络建模方法运用到主轴箱系统热误差建模当中。通过与BP神经网络建模方法进行对比,验证了模糊RBF神经网络建模方法无论是在建模效率、建模鲁棒性还是模型的补偿效果方面均优于传统的BP神经网络建模方法,该方法对提高数控机床加工精度具有重要的意义。
Combining fuzzy technology with RBF neural network and applying it to thermal error modeling of machine tools, a thermal error model of CNC machine tool based on fuzzy RBF neural network is constructed. Taking a spindle gantry system as an example, fuzzy RBF neural network The modal approach is used to model the thermal error of the headstock system. By comparing with the BP neural network modeling method, it is verified that the fuzzy RBF neural network modeling method is superior to the traditional BP neural network modeling method both in modeling efficiency, modeling robustness and model compensation effect, The method is of great significance to improve the machining accuracy of CNC machine tools.