2020
DOI: 10.3390/s20185201
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Novel Method for Vibration Sensor-Based Instantaneous Defect Frequency Estimation for Rolling Bearings Under Non-Stationary Conditions

Abstract: It is proposed a novel instantaneous frequency estimation technology, multi-generalized demodulation transform, for non-stationary signals, whose true time variations of instantaneous frequencies are unknown and difficult to extract from the time-frequency representation due to essentially noisy environment. Theoretical bases of the novel instantaneous frequency estimation technology are created. The main innovations are summarized as: (a) novel instantaneous frequency estimation technology, multi-generalized … Show more

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Cited by 13 publications
(8 citation statements)
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“…Spectral entropy can capture the features of the signal's spectrum, including spectral concentration, randomness, regularity, and information content [35]. Instantaneous frequency and spectral entropy have wide applications in signal processing, communication systems, image processing, biomedical engineering, and other fields [36][37][38][39]. This study utilizes non-stationary signals generated by hammer strikes, thus opting to extract the signal's instantaneous frequency and spectral entropy features.…”
Section: Training Lstm Network Using Feature Signalsmentioning
confidence: 99%
“…Spectral entropy can capture the features of the signal's spectrum, including spectral concentration, randomness, regularity, and information content [35]. Instantaneous frequency and spectral entropy have wide applications in signal processing, communication systems, image processing, biomedical engineering, and other fields [36][37][38][39]. This study utilizes non-stationary signals generated by hammer strikes, thus opting to extract the signal's instantaneous frequency and spectral entropy features.…”
Section: Training Lstm Network Using Feature Signalsmentioning
confidence: 99%
“…A particular problem arises when the observed time series have a nonstationary dynamic, which usually affects the greater complexity of their stochastic structure (for more recent studies, see, c.f. [9][10][11][12][13][14]). To solve these and similar problems, Engle and Smith [15] proposed the stochastic permanent breaking (STOPBREAK) process, which was later examined by many authors, especially in the domain of structural and permanent changes in the fluctuations of some real-world data [16][17][18][19][20].…”
Section: Introductionmentioning
confidence: 99%
“…Although our procedure involves minimising the dynamic error for second-order sensors [28], it can easily be extended to the sensors with dynamics of different orders. We chose to focus on second-order sensors in this paper because a significant proportion of real sensors are defined by this dynamic order, such as vibration and pressure sensors [28][29][30][31][32], and the mechanical construction of a wide variety of other measurement instruments [33]. The proposed procedure can be applied in both the time and frequency domains [34][35][36], which are used in practical implementations of procedures intended for sensor modelling.…”
Section: Introductionmentioning
confidence: 99%