【摘要】 目前高速液压驱动主轴头在现场摩擦叠焊中,低速钻孔效率较低。通过分析,提出全液压驱动主轴水下钻孔特性建模方法和离线优化方案。根据数次试验获取钻孔数据参数,采用BP神经网络对数据进行拟合研究,获得水下钻孔时扭矩特性,经遗传算法寻优,得出优化切削参数,并将此作为在线优化初始输入值。该方法可获得全液压驱动主轴水下钻孔特性及最优切削参数,减少了现场钻孔在线优化时间,在较大程度上提高了加工效率。更多还原

【Abstract】 At present, the high speed hydraulic drive spindle head has low efficiency in low speed drilling in spot friction welding. Through analysis, the modeling method and off-line optimization of full hydraulic drive spindle underwater drilling characteristics were put forward. According to several tests to obtain drilling data parameters, BP neural network was used to fit the data, and torque characteristics of underwater drilling were obtained. Optimized cu tting parameters were obtained by genetic algorithm optimization, and this was used as the initial input value of online optimization. This method could obtain the underwater drilling characteristics and the optimal cutting parameters of the full hydraulic drive spindle, reduced the on-line drilling optimization time and greatly improve the machining efficiency.更多还原