Stochastic resonance in a fractional oscillator subjected to multiplicative trichotomous noise

Ren, Ruibin; Luo, Maokang; Deng, Ke

doi:10.1007/s11071-017-3669-9

Cited by 21 publications

(6 citation statements)

References 42 publications

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“…Herein, we can analyze the system stationary state response under the framework of the classical method proposed in [24,[29][30][31].…”

Section: Ffamentioning

confidence: 99%

A robust index-guided GSR approach to improve the efficiency of bearing fault diagnosis

Zhang¹,

Chen²,

Wang³

2023

Meas. Sci. Technol.

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Stochastic resonance (SR) has been widely used in bearing fault diagnosis due to the enhancement principle of energy conversion from noise to weak signal. However, the diagnosis efficiency and robustness is still challenging.Under the mechanism of generalized stochastic resonance (GSR), in the paper we propose a scale-transformed linear oscillator (SLO), and obtain the analytical expression of fault feature amplification (FFA) to replace the numerical implementation of output signal-to-noise ratio (SNR) in the multi-parameter optimization.It brings the substantial benefit to the reduction of time complexity in fast fault diagnosis, which is verified in both theory and simulations.In the experimental diagnosis for some typical cases, the results show that the proposed method is valid and exhibits the superiority in diagnosis performance, efficiency, and robustness, which demonstrates that the FFA-guided GSR-SLO method has great potential in the engineering applications, especially the real-time fault diagnosis in complex operating environments.

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“…Herein, we can analyze the system stationary state response under the framework of the classical method proposed in [24,[29][30][31].…”

Section: Ffamentioning

confidence: 99%

A robust index-guided GSR approach to improve the efficiency of bearing fault diagnosis

Zhang¹,

Chen²,

Wang³

2023

Meas. Sci. Technol.

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“…Herein, we can analyze the system stationary state response within the framework of the classical method proposed in [31,[37][38][39]. First, we average equation (11) with respect to the noise term η(t) to obtain…”

Section: System Stationary State Responsementioning

confidence: 99%

The adaptive bearing fault diagnosis based on generalized stochastic resonance in a scale-transformed fractional oscillator driven by unilateral attenuated impulse signal

Zhang

Chen²,

Wang³

2022

Meas. Sci. Technol.

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Bearing fault diagnosis is vital to guarantee the safety operation of rotating machines. Due to the enhancement principle of energy conversion from noise to weak signal, noise-assisted stochastic resonance (SR) methods have been widely applied. In this paper, to utilize the memory-dependent property of mechanical degradation process, we develop a scale-transformed fractional oscillator (SFO) driven by unilateral attenuated impulse signal, and reveal the active effect of generalized stochastic resonance (GSR) on the energy conversion from internal multiplicative noise to signal. By applying quantum particle swarm optimization (QPSO) algorithm in the multi-parameter regulation, we propose the adaptive GSR-SFO diagnosis method to realize the enhancement of weak fault characteristics. The experimental results demonstrate that the proposed method is valid and exhibits the superiority in diagnosis performance, especially in several typical difficult cases, such as smeared bearing fault caused by mechanical looseness, smeared bearing fault disturbed by strong random pulses, and corrupted bearing fault disturbed by patches of electrical noise.

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“…Until now, scholars conduct extensive research on SR due to its unique signal enhancement style in weak signal detection. In early research, a nonlinear system stimulated by periodic signal and additive noise were considered as necessary conditions of SR. Scholars have investigated SR methods for improving the output performance by improving the nonlinear system structure, 5 adjusting the system parameters, 6,7 and applying different noise or multiscale noise as stimulation 8,9 . In recent years, cascaded systems 10 and suprathreshold systems 11 have been proposed for more complex signals.…”

Section: Introductionmentioning

confidence: 99%

An adaptive improved unsaturated bistable stochastic resonance method based on weak signal detection

Cui

Yang

Wang

et al. 2021

Adaptive Control & Signal

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Stochastic resonance can detect weak periodic signals from strong background noise without loss of signal energy. However, the classical bistable stochastic resonance has the inherent output saturation defect, which limits the detection performance of system. And it is more difficult to detect signal with strong background noise. In this article, we constructed improved unsaturated bistable stochastic resonance to overcome this shortcoming. The improved bistable potential function makes the output signal more easily oscillate in two potential wells. To improve the stability and the accuracy of the method, we further propose an adaptive improved unsaturated bistable stochastic resonance (AIUBSR) by constructing a synthetic index (SI). The SI combines zero‐crossing ratio and structural correlation coefficient, which can measure the periodicity of output signal and the accuracy of detective frequency at the same time. Theoretical analysis and numerical simulations show that the proposed AIUBSR can have good weak signal detection capability in strong background noise.

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Stochastic resonance in a fractional oscillator subjected to multiplicative trichotomous noise

Cited by 21 publications

References 42 publications

A robust index-guided GSR approach to improve the efficiency of bearing fault diagnosis

A robust index-guided GSR approach to improve the efficiency of bearing fault diagnosis

The adaptive bearing fault diagnosis based on generalized stochastic resonance in a scale-transformed fractional oscillator driven by unilateral attenuated impulse signal

An adaptive improved unsaturated bistable stochastic resonance method based on weak signal detection

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