Rotating machinery fault-induced vibration signal modulation effects: A review with mechanisms, extraction methods and applications for diagnosis
Rotating machinery faults can induce characteristic modulation effects in a vibration signal,
and their diagnosis can thus be conducted by extracting fault-induced modulation features …
and their diagnosis can thus be conducted by extracting fault-induced modulation features …
[HTML][HTML] Linear and synchrosqueezed time–frequency representations revisited: Overview, standards of use, resolution, reconstruction, concentration, and algorithms
D Iatsenko, PVE McClintock, A Stefanovska - Digital Signal Processing, 2015 - Elsevier
Time–frequency representations (TFRs) of signals, such as the windowed Fourier transform
(WFT), wavelet transform (WT) and their synchrosqueezed versions (SWFT, SWT), provide …
(WFT), wavelet transform (WT) and their synchrosqueezed versions (SWFT, SWT), provide …
Improved cellulose X-ray diffraction analysis using Fourier series modeling
W Yao, Y Weng, JM Catchmark - Cellulose, 2020 - Springer
This paper addresses two fundamental issues in the peak deconvolution method of
cellulose XRD data analysis: there is no standard model for amorphous cellulose and …
cellulose XRD data analysis: there is no standard model for amorphous cellulose and …
Detection of non-stationary GW signals in high noise from Cohen's class of time–frequency representations using deep learning
Analysis of non-stationary signals in a noisy environment is a challenging research topic in
many fields often requiring simultaneous signal decomposition in the time and frequency …
many fields often requiring simultaneous signal decomposition in the time and frequency …
Adaptive short-time Fourier transform and synchrosqueezing transform for non-stationary signal separation
The synchrosqueezing transform, a kind of reassignment method, aims to sharpen the time-
frequency representation and to separate the components of a multicomponent non …
frequency representation and to separate the components of a multicomponent non …
Contactless fall detection using time-frequency analysis and convolutional neural networks
Automatic detection of a falling person based on noncontact sensing is a challenging
problem with applications in smart homes for elderly care. In this article, we propose a radar …
problem with applications in smart homes for elderly care. In this article, we propose a radar …
Manufacturing process monitoring using time-frequency representation and transfer learning of deep neural networks
On-line process monitoring increases product quality, improves process stability, and lowers
costs in manufacturing. This paper presents a study of using time-frequency representation …
costs in manufacturing. This paper presents a study of using time-frequency representation …
[HTML][HTML] Development of the method of operational forecasting of fire in the premises of objects under real conditions
B Pospelov, V Andronov, E Rybka… - Восточно …, 2021 - cyberleninka.ru
A method for operational forecasting of fires is proposed that enables the sequential
implementation of five procedures. The method development is necessary to predict early …
implementation of five procedures. The method development is necessary to predict early …
Seismic random noise attenuation using synchrosqueezed wavelet transform and low-rank signal matrix approximation
Random noise elimination acts as an important role in the seismic signal processing.
Generally, noise in seismic data can be divided into two categories of coherent and …
Generally, noise in seismic data can be divided into two categories of coherent and …
Time–frequency features for pattern recognition using high-resolution TFDs: A tutorial review
This paper presents a tutorial review of recent advances in the field of time–frequency (t, f)
signal processing with focus on exploiting (t, f) image feature information using pattern …
signal processing with focus on exploiting (t, f) image feature information using pattern …