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基于灰色预测模型电火花线切割工艺参数优化
引用本文:陈志,李贺,张臻,明五一.基于灰色预测模型电火花线切割工艺参数优化[J].机床与液压,2014,42(23):5-8.
作者姓名:陈志  李贺  张臻  明五一
作者单位:1. 华中科技大学机械科学与工程学院,湖北武汉,430074
2. 东莞华中科技大学制造工程研究院,广东省制造装备数字化重点实验室,广东东莞523808
基金项目:国家自然科学基金资助项目(51175207);国家科技支撑计划项目(2012BAF13B07);广东省数控一代示范工程项目
摘    要:针对电火花线切割加工机制的不确定性,工艺参数与工艺指标具有高度非线性关系;设计正交实验,分析脉宽、占空比、加工电流、丝速和跟踪系数对SKD?11材料去除率( MRR)的影响;分别建立逐次广义回归模型( GRM)和灰色预测模型( GFM),并对两个模型进行实验验证和比较,寻求出最佳的工艺参数。验证实验表明,所建立的灰色预测模型( GFM)能够对实际加工的材料去除率( MRR)进行精确的预测。

关 键 词:线切割  工艺参数优化  广义回归  灰色预测模型

Process Parameters Optimization in WEDM Based on GFM
CHEN Zhi,LI He,ZHANG Zhen,MING Wuyi.Process Parameters Optimization in WEDM Based on GFM[J].Machine Tool & Hydraulics,2014,42(23):5-8.
Authors:CHEN Zhi  LI He  ZHANG Zhen  MING Wuyi
Abstract:Aimed at uncertainty of the machining mechanism of wire electrical discharge machining (WEDM), the relationship between process parameters and process indexes is highly nonlinear. Taguchi experiment was designed to analyze the impact of pulse on time, pulse off time, pulse current, wire speed and tracking coefficient on the material removal rate (MRR) of during machining SKD 11. Generalized regression model (GRM) and Grey forecasting model (GFM) were respectively designed, and the two models were proved by validation experiments and compared to seek the optimal process parameters. Validation experiments result shows that GFM which is built can accurately predict the MRR in actual machining.
Keywords:WEDM  Process parameters optimization  Generalized regression model  Grey forecasting model
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