Stochastic resonance in a single-well potential and its application in rolling bearing fault diagnosis

Cheng, Wei; Xu, Xuemei; Ding, Yipeng; Sun, Kehui

doi:10.1063/1.5143050

Cited by 15 publications

(5 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…where ρ is the probability density function, ∂ ρ/∂t consists of the drag term and the diffusion term on the right. According to the adiabatic approximation theory, SPD [40] is given by…”

Section: Spd Of Qsrmentioning

confidence: 99%

Research and application of stochastic resonance in quad-stable potential system

He¹,

Liu²,

Zhang³

2022

Chinese Phys. B

View full text Add to dashboard Cite

To solve the problem of low weak signal enhancement performance in the quad-stable system, a new Quad-stable potential Stochastic Resonance (QSR) is proposed. Firstly, under the condition of adiabatic approximation theory, the Stationary Probability Distribution (SPD), the Mean First Passage Time (MFPT), the Work (W) and the power Spectrum Amplification Factor (SAF) are derived, and the impacts of system parameters on them are also deeply analyzed. Secondly, numerical simulations are performed to compare QSR with the Classical Tri-stable Stochastic Resonance (CTSR) by using the Genetic Algorithm (GA) and the fourth-order Runge-Kutta algorithm. It shows that the Signal-to-Noise Ratio (SNR) and Mean Signal-to-Noise Increase (MSNRI) of QSR are higher than CTSR, which indicates that QSR has superior noise immunity than CTSR. Finally, the two systems are applied in the detection on real bearing faults. The experimental results show that QSR is superior to CTSR, which provides a better theoretical significance and reference value for practical engineering application.

show abstract

Section: Spd Of Qsrmentioning

confidence: 99%

Research and application of stochastic resonance in quad-stable potential system

He¹,

Liu²,

Zhang³

2022

Chinese Phys. B

View full text Add to dashboard Cite

show abstract

“…Xu et al [40] compared two methods of realizing nonperiodic stochastic resonance by adding noise and adjusting system parameters in real parameter space. Cheng et al [41] proposed a single-well model based on piecewise functions and classical stochastic resonance. Therefore, bistable systems are shown to transform into monostable systems.…”

Section: Introductionmentioning

confidence: 99%

Enhancement of bionic cilia flow rate sensor signals by single-well stochastic resonance

Fu,

Zhang,

et al. 2024

Meas. Sci. Technol.

View full text Add to dashboard Cite

Based on the characteristics of non-periodic signals in bionic cilia flow rate sensors, an investigation on the real-time signal processing methodologies is conducted in single-well stochastic resonance. In this research, we derive a model for an adaptive single-well stochastic resonance system featuring nonlinear recuperation. To assess the scientific robustness and practical viability of the algorithm, a validation experiment was formulated utilizing the single-well stochastic resonance capacitance online detection and processing hardware system. The experimental findings show a notable reduction in noise interference, a marked enhancement in signal quality, and an approximate 0.55 increase in the maximum cross-correlation coefficient among sensor signals. Consequently, the model fulfills the requirements for effectively handling non-periodic signals from sensors.

show abstract

“…To overcome the limitation of conventional SR that it can only process a signal with small parameters (e.g., a signal frequency that is much less than 1 Hz) due to the limitation of the adiabatic approximation theory [18], researchers have proposed many solutions to make SR capable of processing large-parameter signals, such as frequency re-scaling SR (FRSR) [19], frequencyshifted and re-scaling SR (FSRSR) [20], parameter-normalized SR (PNSR) [21], modulated SR (MSR) [22], and scale-transformation SR [23], among others. To appropriately select the system parameters to generate the optimal SR output for given signals, many adaptive parameter-tuning SR methods have been investigated [10,18,24], which are further applied in the fault diagnosis of planetary gearboxes [24], rolling bearing fault diagnosis [25,26], and rotor misalignment fault diagnosis [27].…”

Section: Introductionmentioning

confidence: 99%

High-Performance Adaptive Weak Fault Diagnosis Based on the Global Parameter Optimization Model of a Cascaded Stochastic Resonance System

Lai

Huang

Min

et al. 2023

Sensors

View full text Add to dashboard Cite

Stochastic resonance (SR), as a type of noise-assisted signal processing method, has been widely applied in weak signal detection and mechanical weak fault diagnosis. In order to further improve the weak signal detection performance of SR-based approaches and realize high-performance weak fault diagnosis, a global parameter optimization (GPO) model of a cascaded SR system is proposed in this work. The cascaded SR systems, which involve multiple multi-parameter-adjusting SR systems with both bistable and tri-stable potential functions, are first introduced. The fixed-parameter optimization (FPO) model and the GPO models of the cascaded systems to achieve optimal SR outputs are proposed based on the particle swarm optimization (PSO) algorithm. Simulated results show that the GPO model is capable of achieving a better SR output compared to the FPO model with rather good robustness and stability in detecting low signal-to-noise ratio (SNR) weak signals, and the tri-stable cascaded SR system has a better weak signal detection performance compared to the bistable cascaded SR system. Furthermore, the weak fault diagnosis approach based on the GPO model of the tri-stable cascaded system is proposed, and two rolling bearing weak fault diagnosis experiments are performed, thus verifying the effectiveness of the proposed approach in high-performance adaptive weak fault diagnosis.

show abstract

Stochastic resonance in a single-well potential and its application in rolling bearing fault diagnosis

Cited by 15 publications

References 39 publications

Research and application of stochastic resonance in quad-stable potential system

Research and application of stochastic resonance in quad-stable potential system

Enhancement of bionic cilia flow rate sensor signals by single-well stochastic resonance

High-Performance Adaptive Weak Fault Diagnosis Based on the Global Parameter Optimization Model of a Cascaded Stochastic Resonance System

Contact Info

Product

Resources

About