金属切削表面粗糙度在线监测研究现状

[1] 基于遗传神经网络的表面粗糙度预测模型 [J]. 制造业自动化, 2011, 33 (24) : 10 - 12

[2] Neural networks and physical systems with emergent collective computational abilities. Hopfield J.J. Proc.Natl.Acad Scien, USA . 1982

[3] 基于BP神经网络的高效深磨工程陶瓷工件表面粗糙度的声发射预测附视频 [J]. 湖南文理学院学报(自然科学版), 2008, (03) : 62 - 67

[4] 表面粗糙度的光学在线检测 [J]. 哈尔滨工程大学学报, 2003, (05) : 560 - 562

[5] Bayesian-inference-based neural networks for tool wear estimation[J] . Jianfei Dong,K. V. R. Subrahmanyam,Yoke San Wong,Geok Soon Hong,A. R. Mohanty. &nbspThe International Journal of Advanced Manufacturing Technology . 2006 (9)

[6] The correlation of vibration signal features to cutting tool wear in a metal turning operation [J]. International Journal of Advanced Manufacturing Technology, 2002, 19 (10) : 705 - 713

[7] Machining process monitoring and control: the state-of-the-art. Liang,SY,Hecker,RL,Landers,RG. J Manuf Sci Eng—Trans ASME . 2004

[8] Identification of common sensory features for the control of CNC milling operations under varying cutting conditions. YM Ertekin,Y Kwon,TL Tseng. International Journal of Machine Tools and Manufacture . 2003

[9] Sensors for intelligent machi-ning:a research and application survey. Zhou Y,Orban P,Nikumb S. IEEE internationalconference on intelligent systems for the 21st century.Systems,Man and Cybernetics . 1995

[10] 基于BP神经网络的表面粗糙度声发射预测 [J]. 精密制造与自动化, 2009, (01) : 10 - 14+5

[1] 基于遗传神经网络的表面粗糙度预测模型 [J]. 制造业自动化, 2011, 33 (24) : 10 - 12

[2] Neural networks and physical systems with emergent collective computational abilities. Hopfield J.J. Proc.Natl.Acad Scien, USA . 1982

[3] 基于BP神经网络的高效深磨工程陶瓷工件表面粗糙度的声发射预测附视频 [J]. 湖南文理学院学报(自然科学版), 2008, (03) : 62 - 67

[4] 表面粗糙度的光学在线检测 [J]. 哈尔滨工程大学学报, 2003, (05) : 560 - 562

[5] Bayesian-inference-based neural networks for tool wear estimation[J] . Jianfei Dong,K. V. R. Subrahmanyam,Yoke San Wong,Geok Soon Hong,A. R. Mohanty. &nbspThe International Journal of Advanced Manufacturing Technology . 2006 (9)

[6] The correlation of vibration signal features to cutting tool wear in a metal turning operation [J]. International Journal of Advanced Manufacturing Technology, 2002, 19 (10) : 705 - 713

[7] Machining process monitoring and control: the state-of-the-art. Liang,SY,Hecker,RL,Landers,RG. J Manuf Sci Eng—Trans ASME . 2004

[8] Identification of common sensory features for the control of CNC milling operations under varying cutting conditions. YM Ertekin,Y Kwon,TL Tseng. International Journal of Machine Tools and Manufacture . 2003

[9] Sensors for intelligent machi-ning:a research and application survey. Zhou Y,Orban P,Nikumb S. IEEE internationalconference on intelligent systems for the 21st century.Systems,Man and Cybernetics . 1995

[10] 基于BP神经网络的表面粗糙度声发射预测 [J]. 精密制造与自动化, 2009, (01) : 10 - 14+5