A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Novelty detection: a review—part 2: neural network based approaches
Signal Processing
Intelligent prognostics tools and e-maintenance
Computers in Industry - Special issue: E-maintenance
A Fast Fourier Transform for High-Speed Signal Processing
IEEE Transactions on Computers
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Nonlinear System Simulation Based on the BP Neural Network
ICINIS '10 Proceedings of the 2010 Third International Conference on Intelligent Networks and Intelligent Systems
Journal of Intelligent Manufacturing
Fault features extraction for bearing prognostics
Journal of Intelligent Manufacturing
Evolving fuzzy neural networks for supervised/unsupervised onlineknowledge-based learning
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Journal of Intelligent Manufacturing
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This paper proposes a method for classification of fault and prediction of degradation of components and machines in manufacturing system. The analysis is focused on the vibration signals collected from the sensors mounted on the machines for critical components monitoring. The pre-processed signals were decomposed into several signals containing one approximation and some details using Wavelet Packet Decomposition and, then these signals are transformed to frequency domain using Fast Fourier Transform. The features extracted from frequency domain could be used to train Artificial Neural Network (ANN). Trained ANN could predict the degradation (Remaining Useful Life) and identify the fault of the components and machines. A case study is used to illustrate the proposed method and the result indicates its higher efficiency and effectiveness comparing to traditional methods.