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《Diamond & Abrasives Engineering》 2004-03
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ARTIFICIAL NEURAL NETWORK MODELING FOR EXPERIMENTS OF ELECTRICAL DISCHARGE GRINDING OF POLYCRYSTALLINE DIAMOND

Zhang Qinjian 1 Cao Fengguo 1 Zhai Lijun 1 Wang Xiankui 2(1. Beijing Institute of Electro-Machining,Beijing 100083, China)(2. Tsinghua University,Beijing 100084, China)  
Polycrystalline Diamond (PCD) materials are now widely used in machining various advanced materials in many fields due to their excellent performances such as high hardness, high wear resistance and high erosion resistance. However, the shaping of the PCD materials is challenging due to their inherent properties of high strength and high toughness. The main techniques generally used in PCD machining are mechanical lapping and electrical discharge grinding (EDG). The former is a conventional, slow and costly machining method. The latter offers high productivity and good flatness-controlling. In this paper,the influence of the main parameters of electrical discharge grinding such as workpiece polarity, pulse-on time, pulse-off time, open discharge voltage and peak current on the material removal rate of PCD are investigated. An artificial neural networks (ANN) is developed to describe the relationship between the EDG parameters and the performance characteristics. After training and testing, the maximal predicting error of the ANN model for the unknown technological condition is 14.29%, which can meet the requirment of practical application.
【Fund】: 国家自然科学基金资助项目 (50 0 770 1 );; 北京市科技新星计划 (B类 )项目 (H0 2 0 82 1 31 0 1 30 );; 北京市科学技术研究院萌芽项目 (MY0 2 1 )
【CateGory Index】: TG580.6
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【References】
Chinese Journal Full-text Database 1 Hits
1 Gan Xiao ming Hua HongYan (Nanjing University of Aeronautics and Astrorautics, Nanjing 210016 , China) (Zhengzhou Research Institute for Abrasives and Grinding , Zhengzhou 450007 , China) (Zhengzhou Institute of Aeronautical Industry Management , Zhengzhou 450005 , China);A Summary of Non - Traditional Machining for Polycrystalline Diamond Drawing Die[J];Diamond & Abrasives Engineering;2005-03
【Co-references】
Chinese Journal Full-text Database 10 Hits
1 YU Ai-bing1,2,WANG Min2,TIAN Xin-li3(1.Faculty of Engineering,Ningbo University,Ningbo 315211,Zhejiang,China;2.The State Education Ministry Key Laboratory of Advanced Ceramics and Machining Technology,Tianjin University,Tianjin 300072,China;3.Institute of Armored Force,Beijing 100072,China);Grindability Evaluation of Ceramics via Grey Clustering Approach[J];Acta Armamentarii;2007-02
2 QIN Xu-da~1 ZHAO Jian-bo~1 ZHANG Jian-gang~1 LIU Huan-ling~1 Tom O Muller~2 Ni Wang-yang~2 Liu Yi-xiong~2 1.School of Mechanical Engineering,Tianjin university Tianjin 300072,China; 2.Kennametal Inc.Latrobe,PA 15650,USA;Analysis and Modeling About Milling Force in Plunge Milling for Ti-6AI-4V Based on Regression[J];Journal of Beijing University of Technology;2006-08
3 LI Hong~1, HUANG Lang-huan~1, RAN Jun-guo~2 , GOU Li~2 (1.Department of Chemistry, Jinan University, Guangzhou 510632, P.R.China; 2.Department of Inorganic Materials, Sichuan University, Chengdu 610065, P.R.China);Properties and Microstructure of Machinable Glass-Ceramic in CaO-MgO- Al_2O_3-SiO_2-F System[J];Glass & Enamel;2005-02
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