Machined Surface Quality Monitoring Using a Wireless Sensory Tool Holder in the Machining Process
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Meiqing Wang | Zhiyuan Lu | Wei Dai | W. Dai | Meiqing Wang | Zhiyuan Lu
[1] Steven Y. Liang,et al. Machining Process Monitoring and Control: The State-of-the-Art , 2004 .
[2] E. García Plaza,et al. Surface roughness monitoring by singular spectrum analysis of vibration signals , 2017 .
[3] Kate Fox,et al. Process monitoring to assist the workpiece surface quality in machining , 2004 .
[4] Concha Bielza,et al. Comparison of Bayesian networks and artificial neural networks for quality detection in a machining process , 2009, Expert Syst. Appl..
[5] Mohammad Reza Soleymani Yazdi,et al. Development of a dynamic surface roughness monitoring system based on artificial neural networks (ANN) in milling operation , 2015, The International Journal of Advanced Manufacturing Technology.
[6] F. Ferraz Jr,et al. Data acquisition and monitoring in machine tools with CNC of open architecture using internet , 2005 .
[7] Martin Eckstein,et al. Monitoring of Drilling Process for Highly Stressed Aeroengine Components , 2012 .
[8] Yalcin M. Ertekin,et al. Identification of common sensory features for the control of CNC milling operations under varying cutting conditions , 2003 .
[9] Joaquim Ciurana,et al. Surface roughness monitoring application based on artificial neural networks for ball-end milling operations , 2011, J. Intell. Manuf..
[10] Prasan Kumar Sahoo,et al. Efficient Security Mechanisms for mHealth Applications Using Wireless Body Sensor Networks , 2012, Sensors.
[11] Shinn-Ying Ho,et al. Accurate estimation of surface roughness from texture features of the surface image using an adaptive neuro-fuzzy inference system , 2005 .
[12] Joseph C. Chen,et al. The development of an in-process surface roughness adaptive control system in turning operations , 2007, J. Intell. Manuf..
[13] Alessandro Mecocci,et al. Monitoring Architectural Heritage by Wireless Sensors Networks: San Gimignano — A Case Study , 2014, Sensors.
[14] B. Nowicki,et al. The in-process surface roughness measurement using fringe field capacitive (FFC) method , 1998 .
[15] Joseph C. Chen,et al. An in-process surface recognition system based on neural networks in end milling cutting operations , 1999 .
[16] Meng Joo Er,et al. Wireless Sensor Networks for Industrial Environments , 2005, International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC'06).
[17] B. Samanta,et al. Prediction of workpiece surface roughness using soft computing , 2008 .
[18] Tegoeh Tjahjowidodo,et al. Fuzzy inference system based intelligent sensor fusion for estimation of surface roughness in machining process , 2015, 2015 9th International Conference on Sensing Technology (ICST).
[19] Roberto Teti,et al. Signal processing and pattern recognition for surface roughness assessment in multiple sensor monitoring of robot-assisted polishing , 2017 .
[20] Christian Brecher,et al. Using kernel data in machine tools for the indirect evaluation of surface roughness in vertical milling operations , 2011 .
[21] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[22] Ji Feng,et al. Deep Forest: Towards An Alternative to Deep Neural Networks , 2017, IJCAI.
[23] I. Choudhury,et al. Monitoring the tool wear, surface roughness and chip formation occurrences using multiple sensors in turning , 2014 .
[24] Hun-Keun Chang,et al. In-process surface roughness prediction using displacement signals from spindle motion , 2007 .
[25] Martin Eckstein,et al. Comparison of Sensors Signal Quality when Drilling Inconel 718 , 2015 .
[26] Roberto Teti,et al. Surface Roughness Evaluation Based on Acoustic Emission Signals in Robot Assisted Polishing , 2014, Sensors.
[27] D. Osypiw,et al. Surface quality monitoring for process control by on-line vibration analysis using an adaptive spline wavelet algorithm , 2003 .
[28] Xifan Yao,et al. Tool Condition Monitoring and Remaining Useful Life Prognostic Based on a Wireless Sensor in Dry Milling Operations , 2016, Sensors.
[29] Christian Brecher,et al. Use of NC kernel data for surface roughness monitoring in milling operations , 2011 .
[30] E. García Plaza,et al. Application of the wavelet packet transform to vibration signals for surface roughness monitoring in CNC turning operations , 2018 .
[31] Potsang B. Huang. An intelligent neural-fuzzy model for an in-process surface roughness monitoring system in end milling operations , 2014, Journal of Intelligent Manufacturing.
[32] George-Christopher Vosniakos,et al. Predicting surface roughness in machining: a review , 2003 .
[33] Marc Thomas,et al. Effect of tool vibrations on surface roughness during lathe dry turning process , 1996 .