NovelWoods–Saxon stochastic resonance system for weak signal detection*

Zhou, Yonghui; Xu, Xuemei; Liang, Yin; Ding, Yipeng; Ding, Junnan; Sun, Kehui

doi:10.1088/1674-1056/ab75ca

Cited by 10 publications

(5 citation statements)

References 33 publications

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“…( 5) with the fourth-order Runge-Kutta algorithm, the value of x is the output of the NCSR system. [33] 2.4. Detection scheme of NCSR system…”

Section: Ncsr Systemmentioning

confidence: 99%

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Research and application of composite stochastic resonance in enhancement detection

Gao 高,

Jiao 焦,

Xue 薛

2024

Chinese Phys. B

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Aiming at the problem that the intermediate potential part of the traditional bistable stochastic resonance model cannot be adjusted independently, a new composite stochastic resonance (NCSR) model is proposed by combining the Woods Saxon (WS) model and the improved piecewise bistable model. The model retains the characteristics of the independent parameters of WS model and the improved piecewise model has no output saturation， all the parameters in the new model have no coupling characteristics. Under α stable noise environment, the new model is used to detect periodic signal and aperiodic signal, the detection results indicate that the new model has higher noise utilization and better detection effect. Finally, the new model is applied to image denoising, the results showed that under the same conditions, the output peak signal-to-noise ratio (PSNR) and the correlation number of NCSR method is higher than that of other commonly used linear denoising methods and improved piecewise SR methods, the effectiveness of the new model is verified.

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“…( 5) with the fourth-order Runge-Kutta algorithm, the value of x is the output of the NCSR system. [33] 2.4. Detection scheme of NCSR system…”

Section: Ncsr Systemmentioning

confidence: 99%

“…This model success-fully detected the fault frequency of blade cracks. Zhang et al [25] combined the Gaussian potential well model with a single potential well to form a new SR system. These improved models improve the detection ability of SR.…”

Section: Introductionmentioning

confidence: 99%

Research and application of composite stochastic resonance in enhancement detection

Gao 高,

Jiao 焦,

Xue 薛

2024

Chinese Phys. B

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“…The expressions of some key parameters are derived, and the noise reduction effect of nonperiodic image signals is investigated. Zhou et al [10] proposed a joint exponential function and Woods-Saxon stochastic resonance (EWSSR) model that utilizes the effect of different parameters on the shape of the potential function to make the model easier to adjust the shape of the potential function. The model can be adjusted to obtain different widths of potential wells or potential barrier heights by adjusting one of these parameters, thus enabling the system to adaptively match different types of input signals.…”

Section: Introductionmentioning

confidence: 99%

Early Weak Fault Signal Enhancement and Recognition Method of Rudder Paddle Bearings Based on Parameter Adaptive Stochastic Resonance

Yongdong,

Junxian,

Yonggang

2024

IEEE Access

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Aiming at the problem that the characteristic frequency amplitude of early bearing fault signals is weak and difficult to extract under the strong noise, a vibration signal enhancement method based on maximum overlapping wavelet packet transform (MODWPT) and adaptive stochastic resonance (SR) is proposed. Based on multiple single-component signals decomposed by MODWPT, a signal enhancement and reconstruction model of the ordinary variable scale SR system is constructed. At the same time, the whale optimization algorithm (WOA) algorithm is adopted to optimize the parameters of the SR system adaptively with the improved signal noise ratio (ISNR) index as the fitness function. Finally, a feature-enhanced version of the original signal is obtained and transformed into a time-frequency image dataset using a twodimensional wavelet transform, which can be input into the Resnet network for fault identification and classification. Based on a set of early fault data from IMS and marine bearing data, the significant effect of the proposed method on early fault signal feature enhancement is verified. By comparing the fault characteristic frequency and its frequency doubling before and after the enhancement of the envelope spectrum, the component noise component is suppressed, and the fault frequency amplitude is highlighted under the action of SR potential function. This method can effectively improve the fault recognition accuracy, which has a certain application prospect.

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“…Arathi et al studied the SR in a single potential well anharmonic oscillator with coexisting attractors, and conducted a numerical analysis of it [15]. Zhou et al proposed a new type of Woods Saxon SR system, which can switch between bistable system and monostable system [16].…”

Section: Introductionmentioning

confidence: 99%

Mechanism analysis and application of multi-dimensional single potential well stochastic resonance system

Xiao,

Yu,

Liu

2024

J. Phys. A: Math. Theor.

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Currently, the focus of stochastic resonance (SR) research is primarily on bistable systems, and classical bistable SR systems have the problems of low dimension, inconvenient parameter adjustment, and high threshold for SR effects. In this paper, based on the classic bistable system, a class of multi-dimensional single potential well SR systems without transition threshold is proposed and applied to signal processing. Firstly, the mechanism of double potential well SR and single potential well SR is studied. On this basis, a kind of multi-dimensional single potential well SR system is defined and its theoretical conditions are analyzed. Then a specific four-dimensional single potential well SR system is constructed, and the dynamics of the system is analyzed. The gain range and the approximate relationship between the system input and the four-dimensional output are derived. Finally, the four-dimensional single potential well SR system is applied to the processing of various signals. The experimental results show that the constructed system has good noise reduction and feature amplification effects on noisy signals through the advantages of multi-dimensional output, and can be used to highlight the fault feature frequency in bearing fault signals.

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NovelWoods–Saxon stochastic resonance system for weak signal detection*

Cited by 10 publications

References 33 publications

Research and application of composite stochastic resonance in enhancement detection

Research and application of composite stochastic resonance in enhancement detection

Early Weak Fault Signal Enhancement and Recognition Method of Rudder Paddle Bearings Based on Parameter Adaptive Stochastic Resonance

Mechanism analysis and application of multi-dimensional single potential well stochastic resonance system

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