Fault diagnosis and prognosis using wavelet packet decomposition, Fourier transform and artificial neural network

[1]  Zhen He,et al.  Online monitoring and fault identification of mean shifts in bivariate processes using decision tree learning techniques , 2013, J. Intell. Manuf..

[2]  Ruoyu Li,et al.  Fault features extraction for bearing prognostics , 2012, J. Intell. Manuf..

[3]  Zhigang Tian,et al.  An artificial neural network method for remaining useful life prediction of equipment subject to condition monitoring , 2012, J. Intell. Manuf..

[4]  Donghua Zhou,et al.  Remaining useful life estimation - A review on the statistical data driven approaches , 2011, Eur. J. Oper. Res..

[5]  In-Soo Lee,et al.  Fault Diagnosis of Induction Motors Using Discrete Wavelet Transform and Artificial Neural Network , 2011, HCI.

[6]  Ming Guo,et al.  Application to induction motor faults diagnosis of the amplitude recovery method combined with FFT , 2010 .

[7]  Xianli Meng,et al.  Nonlinear System Simulation Based on the BP Neural Network , 2010, 2010 Third International Conference on Intelligent Networks and Intelligent Systems.

[8]  Chang-Hwan Im,et al.  SSVEP-Based Functional Electrical Stimulation System for Motor Control of Patients with Spinal Cord Injury , 2010 .

[9]  K. I. Ramachandran,et al.  Incipient gear box fault diagnosis using discrete wavelet transform (DWT) for feature extraction and classification using artificial neural network (ANN) , 2010, Expert Syst. Appl..

[10]  Chun-Chieh Wang,et al.  Applications of fault diagnosis in rotating machinery by using time series analysis with neural network , 2010, Expert Syst. Appl..

[11]  Jian-Da Wu,et al.  An automotive generator fault diagnosis system using discrete wavelet transform and artificial neural network , 2009, Expert Syst. Appl..

[12]  Jian-Da Wu,et al.  An expert system for fault diagnosis in internal combustion engines using wavelet packet transform and neural network , 2009, Expert Syst. Appl..

[13]  Zhenyuan Zhong,et al.  Fault diagnosis for diesel valve trains based on time–frequency images , 2008 .

[14]  Gang Chen,et al.  Research on intelligent fault diagnosis based on time series analysis algorithm , 2008 .

[15]  R. Peter Jones,et al.  Probability based vehicle fault diagnosis: Bayesian network method , 2008, J. Intell. Manuf..

[16]  V. Rai,et al.  Bearing fault diagnosis using FFT of intrinsic mode functions in Hilbert-Huang transform , 2007 .

[17]  Jay Lee,et al.  Intelligent prognostics tools and e-maintenance , 2006, Comput. Ind..

[18]  Yongyong He,et al.  Hidden Markov model-based fault diagnostics method in speed-up and speed-down process for rotating machinery , 2005 .

[19]  Zhang Yu,et al.  Fault diagnosis for large-scale wind turbine rolling bearing using stress wave and wavelet analysis , 2005, 2005 International Conference on Electrical Machines and Systems.

[20]  P. Tse,et al.  Machine fault diagnosis through an effective exact wavelet analysis , 2004 .

[21]  Hosein Marzi,et al.  Real-time fault detection and isolation in industrial machines using learning vector quantization , 2004 .

[22]  Tommy W. S. Chow,et al.  Induction machine fault detection using SOM-based RBF neural networks , 2004, IEEE Transactions on Industrial Electronics.

[23]  G..  A Theory for Multiresolution Signal Decomposition : The Wavelet Representation , 2004 .

[24]  Sameer Singh,et al.  Novelty detection: a review - part 2: : neural network based approaches , 2003, Signal Process..

[25]  Emine Ayaz,et al.  Feature extraction related to bearing damage in electric motors by wavelet analysis , 2003, J. Frankl. Inst..

[26]  Kesheng Wang,et al.  Intelligent Condition Monitoring and Diagnosis Systems: A Computational Intelligence Approach , 2003 .

[27]  A. Mohanty,et al.  APPLICATION OF DISCRETE WAVELET TRANSFORM FOR DETECTION OF BALL BEARING RACE FAULTS , 2002 .

[28]  Nikola K. Kasabov,et al.  Evolving fuzzy neural networks for supervised/unsupervised online knowledge-based learning , 2001, IEEE Trans. Syst. Man Cybern. Part B.

[29]  R. Duggirala,et al.  Predictive Monitoring and Control of the Cold Extrusion Process , 2000 .

[30]  A. Trotta,et al.  Application of Wigner-Ville distribution to measurements on transient signals , 1993, 1993 IEEE Instrumentation and Measurement Technology Conference.

[31]  W S McCulloch,et al.  A logical calculus of the ideas immanent in nervous activity , 1990, The Philosophy of Artificial Intelligence.

[32]  I. Daubechies.  Orthonormal bases of compactly supported wavelets , 1988 .

[33]  James L. McClelland,et al.  James L. McClelland, David Rumelhart and the PDP Research Group, Parallel distributed processing: explorations in the microstructure of cognition . Vol. 1. Foundations . Vol. 2. Psychological and biological models . Cambridge MA: M.I.T. Press, 1987. , 1989, Journal of Child Language.

[34]  Richard L. Kegg,et al.  One-Line Machine and Process Diagnostics , 1984 .

[35]  M. Portnoff.  Time-frequency representation of digital signals and systems based on short-time Fourier analysis , 1980 .