CNC machine tool's wear diagnostic and prognostic by using dynamic Bayesian networks
暂无分享,去创建一个
Noureddine Zerhouni | Kamal Medjaher | D. A. Tobon-Mejia | N. Zerhouni | K. Medjaher | D. Tobon-Mejia
[1] Jose Vicente Abellan-Nebot,et al. A review of machining monitoring systems based on artificial intelligence process models , 2010 .
[2] Daming Lin,et al. A review on machinery diagnostics and prognostics implementing condition-based maintenance , 2006 .
[3] Noureddine Zerhouni,et al. A mixture of Gaussians Hidden Markov Model for failure diagnostic and prognostic , 2010, 2010 IEEE International Conference on Automation Science and Engineering.
[4] Balazs Feil,et al. Cluster Analysis for Data Mining and System Identification , 2007 .
[5] George Vachtsevanos,et al. Fault prognosis using dynamic wavelet neural networks , 2001, 2001 IEEE Autotestcon Proceedings. IEEE Systems Readiness Technology Conference. (Cat. No.01CH37237).
[6] Andrew J. Viterbi,et al. Error bounds for convolutional codes and an asymptotically optimum decoding algorithm , 1967, IEEE Trans. Inf. Theory.
[7] George Vachtsevanos,et al. A Particle Filtering Framework for Failure Prognosis , 2005 .
[8] David C. Swanson,et al. PROGNOSTIC MODELLING OF CRACK GROWTH IN A TENSIONED STEEL BAND , 2000 .
[9] B.-H. Juang,et al. Maximum-likelihood estimation for mixture multivariate stochastic observations of Markov chains , 1985, AT&T Technical Journal.
[10] X. Jiang,et al. An Intelligent Damage Detection System for Thermal Protection Panels with Active Sensors , 2008 .
[11] M. Farid Golnaraghi,et al. Prognosis of machine health condition using neuro-fuzzy systems , 2004 .
[12] Noureddine Zerhouni,et al. Failure prognostic by using Dynamic Bayesian Networks , 2009 .
[13] Cuneyt Oysu,et al. Drill wear monitoring using cutting force signals , 2004 .
[14] Joseph Mathew,et al. Rotating machinery prognostics. State of the art, challenges and opportunities , 2009 .
[15] Ratna Babu Chinnam,et al. A neuro-fuzzy approach for estimating mean residual life in condition-based maintenance systems , 2004 .
[16] Colin Bradley,et al. A review of machine vision sensors for tool condition monitoring , 1997 .
[17] M.J. Roemer,et al. Prognostic enhancements to diagnostic systems for improved condition-based maintenance [military aircraft] , 2002, Proceedings, IEEE Aerospace Conference.
[18] Karel D. Vohnout. Curve Fitting and Evaluation , 2003 .
[19] Sankaran Mahadevan,et al. Bayesian Wavelet Methodology for Damage Detection of Thermal Protection System Panels , 2009 .
[20] Krishna R. Pattipati,et al. Model-based prognostic techniques [maintenance applications] , 2003, Proceedings AUTOTESTCON 2003. IEEE Systems Readiness Technology Conference..
[21] A. Z. Keller,et al. Reliability analysis of CNC machine tools , 1982 .
[22] Benoît Iung,et al. Formalisation of a new prognosis model for supporting proactive maintenance implementation on industrial system , 2008, Reliab. Eng. Syst. Saf..
[23] Ioan D. Marinescu,et al. Effect of tool wear on surface finish for a case of continuous and interrupted hard turning , 2005 .
[24] Frank L. Lewis,et al. Intelligent Fault Diagnosis and Prognosis for Engineering Systems , 2006 .
[25] J. Hillhouse,et al. Investigating stress effect patterns in hospital staff nurses: results of a cluster analysis. , 1997, Social science & medicine.
[26] Lawrence R. Rabiner,et al. A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.
[27] Venkat Venkatasubramanian,et al. Prognostic and diagnostic monitoring of complex systems for product lifecycle management: Challenges and opportunities , 2005, Comput. Chem. Eng..
[28] Lifeng Xi,et al. Residual life predictions for ball bearings based on self-organizing map and back propagation neural network methods , 2007 .
[29] D. Eisenberg,et al. Three-dimensional cluster analysis identifies interfaces and functional residue clusters in proteins. , 2001, Journal of molecular biology.
[30] Ming Dong,et al. Dynamic Bayesian network based prognosis in machining processes , 2008 .
[31] Wilson Wang,et al. An adaptive predictor for dynamic system forecasting , 2007 .
[32] Noureddine Zerhouni,et al. The ISO 13381-1 standard's failure prognostics process through an example , 2010, 2010 Prognostics and System Health Management Conference.
[33] K. Loparo,et al. Online tracking of bearing wear using wavelet packet decomposition and probabilistic modeling : A method for bearing prognostics , 2007 .
[34] Stuart J. Russell,et al. Dynamic bayesian networks: representation, inference and learning , 2002 .
[35] Gregory Provan. Prognosis and condition-based monitoring: an open systems architecture , 2003 .
[36] N. Zerhouni,et al. Estimation of the Remaining Useful Life by using Wavelet Packet Decomposition and HMMs , 2011, 2011 Aerospace Conference.
[37] Ratna Babu Chinnam,et al. Autonomous diagnostics and prognostics through competitive learning driven HMM-based clustering , 2003, Proceedings of the International Joint Conference on Neural Networks, 2003..
[38] Xiaomo Jiang,et al. Recent Development in Structural Damage Diagnosis and Prognosis , 2010 .
[39] David He,et al. A segmental hidden semi-Markov model (HSMM)-based diagnostics and prognostics framework and methodology , 2007 .
[40] K.W. Przytula,et al. An Implementation of Prognosis with Dynamic Bayesian Networks , 2008, 2008 IEEE Aerospace Conference.
[41] Joseph P. Cusumano,et al. A Dynamical Systems Approach to Failure Prognosis , 2004 .
[42] Geok Soon Hong,et al. Multi-category micro-milling tool wear monitoring with continuous hidden Markov models , 2009 .
[43] T. I. Liu,et al. Intelligent Classification and Measurement of Drill Wear , 1994 .