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《China Mechanical Engineering(中国机械工程)》 2012-01
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Forming Quality Forecast for Internal Threads Formed by Cold Extrusion Based on Principal Component Analysis and Neural Networks

Zhang Min Li Xiangfeng Zuo Dunwen Miao Hong Nanjing University of Aeronautics and Astronautics,Nanjing,210016  
Forming quality grade of internal threads formed by cold extrusion was rated synthetically by BP neural network based on pitch diameter,thread pitch,half of thread angle and threads height ratio.For eliminating linear relevance in inter-influencing factors while the data pre-processing,major factors that affected the forming quality of internal threads formed by cold extrusion were extracted by principal component analysis.The experimental results show that the neural networks input by the processed data by this method become simple,with improved convergence rate and forecast accuracy.This method realizes the forecast for quality grade of internal threads formed by cold extrusion precisely.Also it provides a new solution for detection of internal thread quality.
【Fund】: 空军装备部“十一五”预研项目
【CateGory Index】: TG376.3;TG62
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