A review of recent trends in machine diagnosis and prognosis algorithms
暂无分享,去创建一个
[1] A Yoshida,et al. Application of the wavelet transform to health monitoring and evaluation of dynamic characteristics in gear sets , 2004 .
[2] Bo-Suk Yang,et al. Machine condition prognosis based on regression trees and one-step-ahead prediction , 2008 .
[3] Zhao Hong. Reliability-modeling for the repairable system based on Markov process , 2007 .
[4] Viliam Makis,et al. Multivariate Bayesian process control for a finite production run , 2009, Eur. J. Oper. Res..
[5] Claudine Badue,et al. Multi-Label Text Categorization with a Data Correlated VG-RAM Weightless Neural Network , 2009 .
[6] Dilli,et al. Time-series analysis with a hybrid Box-Jenkins ARIMA and neural network model , 2004 .
[7] Jay Lee,et al. Robust performance degradation assessment methods for enhanced rolling element bearing prognostics , 2003, Adv. Eng. Informatics.
[8] Elijah Kannatey-Asibu,et al. Hidden Markov model-based tool wear monitoring in turning , 2002 .
[9] Jun Ni,et al. Maintenance scheduling in manufacturing systems based on predicted machine degradation , 2008, J. Intell. Manuf..
[10] Diego J. Pedregal,et al. State space models for condition monitoring: a case study , 2006, Reliab. Eng. Syst. Saf..
[11] John Yen,et al. Using Q-Learning and Genetic Algorithms to Improve the Efficiency of Weight Adjustments for Optimal Control and Design Problems , 2007, J. Comput. Inf. Sci. Eng..
[12] T.M. Welte. Using State Diagrams for Modeling Maintenance of Deteriorating Systems , 2009, IEEE Transactions on Power Systems.
[13] W. E. Tobler,et al. Steady State Hydraulic Valve Fluid Field Estimator Based on Non-Dimensional Artificial Neural Network (NDANN) , 2004, J. Comput. Inf. Sci. Eng..
[14] Dong Ming. Equipment Fault Diagnosis Using Auto-regressive Hidden Markov Models , 2008 .
[15] Yuo-Tern Tsai,et al. Optimizing preventive maintenance for mechanical components using genetic algorithms , 2001, Reliab. Eng. Syst. Saf..
[16] John Bowles,et al. An assessment of RPN prioritization in a failure modes effects and criticality analysis , 2003, Annual Reliability and Maintainability Symposium, 2003..
[17] Hsiao-Chun Wu,et al. Novel Fast Computation Algorithm of the Second-Order Statistics for Autoregressive Moving-Average Processes , 2009, IEEE Trans. Signal Process..
[18] Samy E. Oraby,et al. A Diagnostic Approach for Turning Tool Based on the Dynamic Force Signals , 2005 .
[19] D. Dane Quinn,et al. Structural Health Monitoring of Rotordynamic Systems by Wavelet Analysis , 2006 .
[20] Gregory Levitin,et al. Optimal load distribution in series-parallel systems , 2009, Reliab. Eng. Syst. Saf..
[21] M. Farid Golnaraghi,et al. Prognosis of machine health condition using neuro-fuzzy systems , 2004 .
[22] P. Baruah,et al. HMMs for diagnostics and prognostics in machining processes , 2005 .
[23] Hu Niao-qing. Study on Fault Diagnosis and Prognosis Methods Based on Hidden Semi-Markov Model , 2009 .
[24] Li Xiaobai,et al. Forecasting method for aeroengine performance parameters , 2008 .
[25] Yang Xianhui. Quantitative reliability assessment for safety related systems using Markov models , 2008 .
[26] World Congress on Nature & Biologically Inspired Computing, NaBIC 2009, 9-11 December 2009, Coimbatore, India , 2009, NaBIC.
[27] Yang Liu,et al. Process Mean Shift Detection Using Prediction Error Analysis , 1998 .
[28] Yong Lei,et al. System level optimization of preventive maintenance in industrial automation systems , 2006 .
[29] R. Ghazal,et al. Forecasting the UK/EU and JP/UK trading signals using Polynomial Neural Networks , 2009 .
[30] Puteh Saad,et al. Combination of Forecasting Using Modified GMDH and Genetic Algorithm , 2009 .
[31] E. G. Kyriakidis,et al. Markov decision models for the optimal maintenance of a production unit with an upstream buffer , 2009, Comput. Oper. Res..
[32] D. C. Swanson,et al. A general prognostic tracking algorithm for predictive maintenance , 2001, 2001 IEEE Aerospace Conference Proceedings (Cat. No.01TH8542).
[33] Geok Soon Hong,et al. Multi-category micro-milling tool wear monitoring with continuous hidden Markov models , 2009 .
[34] Argon Chen,et al. Real-time health prognosis and dynamic preventive maintenance policy for equipment under aging Markovian deterioration , 2007 .
[35] Sunil Menon,et al. Neural Network Models for Usage Based Remaining Life Computation , 2006 .
[36] Zhe George Zhang,et al. A discrete semi-Markov decision model to determine the optimal repair/replacement policy under general repairs , 2000, Eur. J. Oper. Res..
[37] Cheng-Hwai Liou,et al. Machine Repair Problem in Production Systems with Spares and Server Vacations , 2009, RAIRO Oper. Res..
[38] Joseph H. Saleh,et al. Beyond its cost, the value of maintenance: An analytical framework for capturing its net present value , 2009, Reliab. Eng. Syst. Saf..
[39] Elias Oliveira,et al. Multi-Label Text Categorization Using a Probabilistic Neural Network , 2009 .
[40] Spilios D. Fassois,et al. Pseudolinear estimation of fractionally integrated ARMA (ARFIMA) models with automotive application , 1999, IEEE Trans. Signal Process..
[41] Andrew Hess,et al. SH-60 helicopter integrated diagnostic system (HIDS) program-diagnostic and prognostic development experience , 1999, 1999 IEEE Aerospace Conference. Proceedings (Cat. No.99TH8403).
[42] Carey Bunks,et al. CONDITION-BASED MAINTENANCE OF MACHINES USING HIDDEN MARKOV MODELS , 2000 .
[43] Irem Y. Tumer,et al. Mapping function to failure mode during component development , 2003 .
[44] L. S. Qu,et al. Defect Detection for Bearings Using Envelope Spectra of Wavelet Transform , 2004 .
[45] Tep Sastri,et al. MARKOV CHAIN APPROACH TO FAILURE COST ESTIMATION IN BATCH MANUFACTURING , 2001 .
[46] Kenneth A. Loparo,et al. Tool wear condition monitoring in drilling operations using hidden Markov models (HMMs) , 2001 .
[47] Lei Guo,et al. Robust bearing performance degradation assessment method based on improved wavelet packet–support vector data description , 2009 .