基于粒子群算法的在蒸汽水雾中电火花线切割大厚度工件模型优化

Modeling Process Optimization of WEDM Cutting Large Thickness Workpieces in Steam Water Mist Based on Particle Swarm Optimization

本实验利用单因素试验法分析单个因素对大厚度工件表面质量和加工速度的影响,重点进行多因素正交试验,使用Matlab软件建立大厚度工件在蒸汽水雾介质下的第二次电火花线切割的直线度模型、表面粗糙度模型和加工速度模型,通过序关系分析法确定直线度、表面粗糙度和加工速度的权重分别是5/17、6/17和6/17,极差法去量纲化处理后加权出其综合评价模型,检验得出模型显著,拟合度好。基于粒子群算法对模型进行优化,得到在蒸汽水雾介质下的第二次电火花线切割最合适的加工参数。通过实验可得"乳化液-蒸汽水雾"大厚度工件的二次切割工艺与传统二次加工工艺相比,大厚度工件的多介质电火花的加工速度、直线度和表面粗糙度均有较大程度提升,很大的提高了电火花的加工质量和切削效率,满足大厚度工件的精加工要求。

The single factor test method was used in this experiment to analyze the influence of single factors on the surface quality and processing speed of workpieces with large thickness. Through multi-factor orthogonal test, the straightness model, the surface roughness model and the machining speed model of second WEDN of large thickness workpiece under steam water mist medium were established by using Matlab software. The weights of straightness, surface roughness and processing speed determined by order relationship analysis method are 5/17, 6/17 and 6/17, respectively.After de-dimension process by range method, the comprehensive evaluation model is weighted, and the model is found to be remarkable and the fitting degree is good. The model was optimized based on the particle swarm optimization algorithm to obtain the most suitable processing parameters for the second WEDM in steam water mist medium. Compared with the traditional secondary cutting process, the second cutting process with "emulsified liquid-steam mist" can greatly improve the processing speed, straightness and surface roughness of the multi-dielectric EDM of the large thickness workpiece, which greatly improves the processing quality and cutting efficiency of WEDM and meets the finishing requirements of large thickness workpieces.