基于高质量和低振动的铣削参数优化方法研究

针对数控铣床在切削过程中产生的振动对工件表面质量的影响,提出以低振动和高表面质量为优化目标,对切削参数进行优化。以VDF-850A铣床为研究对象对45号钢进行铣削正交试验,通过建立振动采集系统,采集振动信号提取振动特征值并测量工件表面粗糙度值,应用最小二乘法拟合数据建立了振动和粗糙度数学模型。利用层次分析法确定两目标函数权重,使用平方和加权法对两目标函数加权拟合成综合目标评价函数,运用粒子群算法优化切削参数。试验结果表明:应用粒子群算法优化后的切削参数进行加工可有效的降低振动和提高表面质量。

Research on optimization method of milling parameters based on high quality and low vibration

This paper investigates the influence of the vibration generated by the CNC milling machine during the cutting process on the surface quality of the workpiece. The optimization objectives are to optimize the cutting parameters with low vibration and high surface quality. This paper uses the VDF 850A milling to carry out milling orthogonal test on 45 steel and establishes a vibration acquisition system. Vibration signals were collected to obtain the vibration characteristic value and measure the surface roughness value of the workpiece. In this paper, two mathematical models of vibration and roughness are established by fitting the least-squares method to the data. The weights of the two objective functions are determined by the analytic hierarchy process. Then the two objective functions are weighted and fitted into the comprehensive objective function by the square sum weighting method, and the particle swarm optimization (PSO) algorithm is used to optimize the cutting parameters. The result shows that the machining parameters optimized by particle swarm optimization algorithm can effectively reduce vibration and improve surface quality.