Remaining Useful Life Prediction of Bearing Based on Deep Perceptron Neural Networks
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[1] Daming Lin,et al. A review on machinery diagnostics and prognostics implementing condition-based maintenance , 2006 .
[2] Jian Sun,et al. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[3] Enrico Zio,et al. Condition assessment for the performance degradation of bearing based on a combinatorial feature extraction method , 2014, Digit. Signal Process..
[4] Lifeng Xi,et al. Residual life predictions for ball bearings based on self-organizing map and back propagation neural network methods , 2007 .
[5] Lidia A. Braunstein,et al. Cascading failure and recovery of spatially interdependent networks , 2017 .
[6] Derek C. Rose,et al. Deep Machine Learning - A New Frontier in Artificial Intelligence Research [Research Frontier] , 2010, IEEE Computational Intelligence Magazine.
[7] Sheng Hong,et al. Epidemic spreading model of complex dynamical network with the heterogeneity of nodes , 2016, Int. J. Syst. Sci..
[8] Sheng Hong,et al. Performance Degradation Assessment for Bearing Based on Ensemble Empirical Mode Decomposition and Gaussian Mixture Model , 2014 .
[9] Elif Derya Übeyli. Combined neural network model employing wavelet coefficients for EEG signals classification , 2009, Digit. Signal Process..
[10] Sheng Hong,et al. Failure cascade in interdependent network with traffic loads , 2015 .
[11] Y Shao,et al. Prognosis of remaining bearing life using neural networks , 2000 .
[12] Geoffrey E. Hinton,et al. Deep Learning , 2015, Nature.
[13] Meng Joo Er,et al. Bearing Condition Prediction Using Enhanced Online Learning Fuzzy Neural Networks , 2013 .
[14] Chen Lu,et al. Bearing remaining life prediction using Gaussian process regression with composite kernel functions , 2015 .
[15] Stéphane Mallat,et al. A Wavelet Tour of Signal Processing - The Sparse Way, 3rd Edition , 2008 .
[16] Enrico Zio,et al. A novel dynamics model of fault propagation and equilibrium analysis in complex dynamical communication network , 2014, Appl. Math. Comput..
[17] Simon Haykin,et al. Neural Networks and Learning Machines , 2010 .
[18] Mahmut Ozer,et al. EEG signals classification using the K-means clustering and a multilayer perceptron neural network model , 2011, Expert Syst. Appl..
[19] Takashi Hiyama,et al. Predicting remaining useful life of rotating machinery based artificial neural network , 2010, Comput. Math. Appl..
[20] Dong Yu,et al. Error back propagation for sequence training of Context-Dependent Deep NetworkS for conversational speech transcription , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[21] Daren Yu,et al. Mechanical equipment fault diagnosis based on redundant second generation wavelet packet transform , 2010, Digit. Signal Process..
[22] Stphane Mallat,et al. A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way , 2008 .
[23] Shen Zhenzhong,et al. Prediction of the strength of concrete radiation shielding based on LS-SVM , 2015 .
[24] Cenk Sahin,et al. Neural Network-Based Computer-Aided Diagnosis in Classification of Primary Generalized Epilepsy by EEG Signals , 2009, Journal of Medical Systems.
[25] Sheng Hong,et al. Suppressing failure cascades in interconnected networks: Considering capacity allocation pattern and load redistribution , 2016 .
[26] Abdulhamit Subasi,et al. EEG signal classification using wavelet feature extraction and a mixture of expert model , 2007, Expert Syst. Appl..
[27] Mallat Stéphane. CHAPTER 6 – Wavelet Zoom , 2009 .
[28] Enrico Zio,et al. An adaptive method for health trend prediction of rotating bearings , 2014, Digit. Signal Process..
[29] Kishor S. Trivedi,et al. Analysis of propagation dynamics in complex dynamical network based on disturbance propagation model , 2014 .
[30] Venizelos Efthymiou,et al. Feature extraction of partial discharge signals using the wavelet packet transform and classification with a probabilistic neural network , 2010 .
[31] Yaguo Lei,et al. A review on empirical mode decomposition in fault diagnosis of rotating machinery , 2013 .