Journal ArticleDOI
Stochastic resonance subject to multiplicative and additive noise: The influence of potential asymmetries
TLDR
A double SR phenomenon is observed in certain cases for two correlated noises, whereas it disappears for two independent noises, which are helpful in achieving weak signal detection under heavy background noise.Abstract:
The influence of potential asymmetries on stochastic resonance (SR) subject to both multiplicative and additive noise is studied by using two-state theory, where three types of asymmetries are introduced in double-well potential by varying the depth, the width, and both the depth and the width of the left well alone. The characteristics of SR in the asymmetric cases are different from symmetric ones, where asymmetry has a strong influence on output signal-to-noise ratio (SNR) and optimal noise intensity. Even optimal noise intensity is also associated with the steepness of the potential-barrier wall, which is generally ignored. Moreover, the largest SNR in asymmetric SR is found to be relatively larger than the symmetric one, which also closely depends on noise intensity ratio. In addition, a moderate cross-correlation intensity between two noises is good for improving the output SNR. More interestingly, a double SR phenomenon is observed in certain cases for two correlated noises, whereas it disappears for two independent noises. The above clues are helpful in achieving weak signal detection under heavy background noise.read more
Citations
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Journal ArticleDOI
A review of stochastic resonance in rotating machine fault detection
Siliang Lu,Qingbo He,Jun Wang +2 more
TL;DR: This study is committed to providing a comprehensive review of SR from history to state-of-the-art methods and finally to research prospects, along with the applications in rotating machine fault detection.
Journal ArticleDOI
Applications of stochastic resonance to machinery fault detection: A review and tutorial
TL;DR: This paper attempts to survey and summarize the current progress of SR applied in machinery fault detection, providing comprehensive references for researchers concerning with the subject and further helping them identify future trends for research.
Journal ArticleDOI
An underdamped stochastic resonance method with stable-state matching for incipient fault diagnosis of rolling element bearings
TL;DR: Wang et al. as discussed by the authors proposed an underdamped multistable stochastic resonance (SR) method with stable-state matching for bearing fault diagnosis, which is able to suppress the multiscale noise.
Journal ArticleDOI
Stochastic resonance in a metal-oxide memristive device
Alexey Mikhaylov,Davud V. Guseinov,Alexey Belov,D. S. Korolev,V.A. Shishmakova,M. N. Koryazhkina,Dmitry Filatov,O. N. Gorshkov,D. Maldonado,F. J. Alonso,Juan Bautista Roldán,A. V. Krichigin,N. V. Agudov,Alexander A. Dubkov,Angelo Carollo,Bernardo Spagnolo,Bernardo Spagnolo +16 more
TL;DR: In this article, the effect of white Gaussian noise superimposed on the sub-threshold sinusoidal driving signal is analyzed through the time series statistics of the resistive switching parameters, the spectral response to a periodic perturbation and the signal-to-noise ratio at the output of the nonlinear system.
Journal ArticleDOI
Coupled neurons with multi-objective optimization benefit incipient fault identification of machinery
TL;DR: An adaptive coupled neurons-based method with multi-objective optimization to enhance incipient fault signature identification of machinery for overcoming the drawback that blind noise suppression and cancellation using unwanted noise techniques are prone to remove weak useful signature closely related with health states of machinery.