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基于智能技术的电火花加工过程建模和参数优化 被引量:2

The Modeling and Parameter Optimization for Electrical Discharge Machining(EDM)
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摘要 根据电火花加工工艺特点 ,建立基于遗传算法的加工过程人工神经网络模型 ,实现加工结果的预测。根据预测结果 ,在保证表面粗糙度要求的前提下 ,以最大加工速度为目标 ,用遗传算法实现加工参数的优化。实验结果表明以上算法可有效解决电火花加工条件优化的问题 ,自动生成加工参数 ,而且收敛速度较快 ,满足机床控制的要求。 According to EDM processing features, the machining process neural network is built based on genetic algorithm. It realizes the prediction of machining results. According to prediction and aimed at the fastest machining rate, machining parameters are optimized on the condition that parts' surface roughness is ensured. The experiment results show that the algorithm can optimize EDM machining parameters, and its convergence speed is rapid, which can meet machine control requirements.
出处 《机械科学与技术》 CSCD 北大核心 2002年第4期623-624,647,共3页 Mechanical Science and Technology for Aerospace Engineering
关键词 智能技术 建模 遗传算法 人工神经网络 电火花加工 参数优化 Genetic algorithm Neural network Electrical discharge machining(EDM) Parameter optimization
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参考文献2

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  • 1张利彪,周春光,马铭,刘小华.基于粒子群算法求解多目标优化问题[J].计算机研究与发展,2004,41(7):1286-1291. 被引量:225
  • 2黄瑞宁,狄士春,迟关心,赵万生,姜吉涛.基于均匀设计的微细电火花线切割加工工艺规律研究[J].电加工与模具,2005(1):12-15. 被引量:6
  • 3彭泽军,王宝瑞,陈辉.基于神经网络的电火花加工工艺选择模型研究[J].机械科学与技术,2006,25(4):394-397. 被引量:11
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  • 5SunilSheshrao Baraskar,S.S. Banwait,S.C. Laroiya.Multiobjective Optimization of Electrical Discharge Machining Process Using a Hybrid Method[J]. Materials and Manufacturing Processes . 2013 (4)
  • 6S. H. Yang,U. Natarajan.Multi-objective optimization of cutting parameters in turning process using differential evolution and non-dominated sorting genetic algorithm-II approaches[J]. The International Journal of Advanced Manufacturing Technology . 2010 (5-8)
  • 7Mohammad Yeakub Ali,Ammar Sami Mohammad.Effect of Conventional EDM Parameters on the Micromachined Surface Roughness and Fabrication of a Hot Embossing Master Microtool[J]. Materials and Manufacturing Processes . 2009 (4)
  • 8Carlos A. Coello Coello,Ricardo Landa Becerra.Evolutionary Multiobjective Optimization in Materials Science and Engineering[J]. Materials and Manufacturing Processes . 2009 (2)
  • 9Arijit Biswas,N. Chakraborti,P. K. Sen.Multiobjective Optimization of Manganese Recovery from Sea Nodules Using Genetic Algorithms[J]. Materials and Manufacturing Processes . 2009 (1)
  • 10Chorng-Jyh Tzeng,Yung-Kuang Yang.Determination of Optimal Parameters for SKD11 CNC Turning Process[J]. Materials and Manufacturing Processes . 2008 (4)

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