Journal ArticleDOI
Wavelet filter-based weak signature detection method and its application on rolling element bearing prognostics
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In this paper, the performance of wavelet decomposition-based de-noising and wavelet filter based denoising methods are compared based on signals from mechanical defects, and the comparison result reveals that wavelet filters are more suitable and reliable to detect a weak signature of mechanical impulse-like defect signals, whereas the wavelet transform has a better performance on smooth signal detection.About:
This article is published in Journal of Sound and Vibration.The article was published on 2006-02-07. It has received 1104 citations till now. The article focuses on the topics: Wavelet packet decomposition & Stationary wavelet transform.read more
Citations
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Journal ArticleDOI
Remaining useful life estimation - A review on the statistical data driven approaches
TL;DR: This paper systematically reviews the recent modeling developments for estimating the RUL and focuses on statistical data driven approaches which rely only on available past observed data and statistical models.
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Prognostics and health management design for rotary machinery systems—Reviews, methodology and applications
TL;DR: A comprehensive review of the PHM field is provided, followed by an introduction of a systematic PHM design methodology, 5S methodology, for converting data to prognostics information, to enable rapid customization and integration of PHM systems for diverse applications.
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Machinery health prognostics: A systematic review from data acquisition to RUL prediction
TL;DR: A review on machinery prognostics following its whole program, i.e., from data acquisition to RUL prediction, which provides discussions on current situation, upcoming challenges as well as possible future trends for researchers in this field.
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Wavelets for fault diagnosis of rotary machines: A review with applications
TL;DR: Current applications of wavelets in rotary machine fault diagnosis are summarized and some new research trends, including wavelet finite element method, dual-tree complex wavelet transform, wavelet function selection, newWavelet function design, and multi-wavelets that advance the development of wavelet-based fault diagnosed are discussed.
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Deep Convolutional Transfer Learning Network: A New Method for Intelligent Fault Diagnosis of Machines With Unlabeled Data
TL;DR: A new intelligent method named deep convolutional transfer learning network (DCTLN) is proposed, which facilitates the 1-D CNN to learn domain-invariant features by maximizing domain recognition errors and minimizing the probability distribution distance.
References
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A mathematical theory of communication
TL;DR: This final installment of the paper considers the case where the signals or the messages or both are continuously variable, in contrast with the discrete nature assumed until now.
Journal Article
The mathematical theory of communication
Claude E. Shannon,Warren Weaver +1 more
TL;DR: The Mathematical Theory of Communication (MTOC) as discussed by the authors was originally published as a paper on communication theory more than fifty years ago and has since gone through four hardcover and sixteen paperback printings.
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The Mathematical Theory of Communication
TL;DR: The theory of communication is extended to include a number of new factors, in particular the effect of noise in the channel, and the savings possible due to the statistical structure of the original message anddue to the nature of the final destination of the information.
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De-noising by soft-thresholding
TL;DR: The authors prove two results about this type of estimator that are unprecedented in several ways: with high probability f/spl circ/*/sub n/ is at least as smooth as f, in any of a wide variety of smoothness measures.