Journal ArticleDOI
Time–energy density analysis based on wavelet transform
Cheng Junsheng,Yu Dejie,Yang Yu +2 more
TLDR
Simulation and practical application of the proposed time–energy density analysis approach based on wavelet transform to roller bearing with faults show that the method can extract the fault characteristics from vibration signal efficiently.Abstract:
Energy is an important physical variable in signal analysis. The distribution of energy with the change of time and frequency can show the characteristics of a signal. A time–energy density analysis approach based on wavelet transform is proposed in this paper. This method can analyze the energy distribution of signal with the change of time in different frequency bands. Simulation and practical application of the proposed method to roller bearing with faults show that the time–energy density analysis approach can extract the fault characteristics from vibration signal efficiently.read more
Citations
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Journal ArticleDOI
Bearing fault diagnosis using FFT of intrinsic mode functions in Hilbert-Huang transform
V.K. Rai,Amiya R Mohanty +1 more
TL;DR: In this paper, a Hilbert-Huang Transform (HHT) based time domain approach for bearing vibration signature analysis is proposed for bearing bearing vibration analysis and its efficiency is evaluated.
Journal ArticleDOI
Wind turbine fault diagnosis based on Morlet wavelet transformation and Wigner-Ville distribution
Baoping Tang,Wenyi Liu,Tao Song +2 more
TL;DR: In this paper, the authors used the continuous wavelet transformation (CWT) to filter useless noise in raw vibration signals, and auto terms window (ATW) function is used to suppress the cross terms in WVD, which can not only remove cross terms faraway from the auto terms, but also keep high energy close to every instantaneous frequency.
Journal ArticleDOI
Feature extraction method of wind turbine based on adaptive Morlet wavelet and SVD
TL;DR: In this article, a new denoising method based on adaptive Morlet wavelet and singular value decomposition (SVD) is applied to feature extraction for wind turbine vibration signals.
Journal ArticleDOI
Semisupervised Distance-Preserving Self-Organizing Map for Machine-Defect Detection and Classification
TL;DR: A semisupervised diagnosis method based on a distance-preserving SOM for machine-fault detection and classification, which can also be used to visualize the SOM learning results directly is presented.
Journal ArticleDOI
An Extended Wavelet Spectrum for Bearing Fault Diagnostics
TL;DR: An extended wavelet spectrum analysis technique is proposed for a more positive assessment of bearing health conditions and two strategies have been suggested for different wavelet function implementation.
References
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TL;DR: In this paper, it is shown that the difference of information between the approximation of a signal at the resolutions 2/sup j+1/ and 2 /sup j/ (where j is an integer) can be extracted by decomposing this signal on a wavelet orthonormal basis of L/sup 2/(R/sup n/), the vector space of measurable, square-integrable n-dimensional functions.
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Orthonormal bases of compactly supported wavelets
TL;DR: This work construct orthonormal bases of compactly supported wavelets, with arbitrarily high regularity, by reviewing the concept of multiresolution analysis as well as several algorithms in vision decomposition and reconstruction.
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Journal ArticleDOI
Singularity detection and processing with wavelets
Stéphane Mallat,Wen-Liang Hwang +1 more
TL;DR: It is proven that the local maxima of the wavelet transform modulus detect the locations of irregular structures and provide numerical procedures to compute their Lipschitz exponents.
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