A novel piecewise tri-stable stochastic resonance system with time-delayed feedback and its application

Zhao, Shuaı; Shi, Pengfei; Han, Dongying; Fu, Rongrong

doi:10.1016/j.cjph.2021.06.022

Cited by 9 publications

(3 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In reference [28], it is found, the adjustment of system parameters has a great efect on the shape of the potential function, because the change of the shape of the potential function will greatly change the transition rate of the internal particles. Te study of reference [28] is based on AWGN, and the evaluation standard is the SNR proposed in reference [29], but in this paper, the noise becomes Lévy noise, and the evaluation standard is diferent from that so it is still important to study the efect of parameters on the shape of the potential function. Now, we redraw the potential for the PTSR system and keep the other two parameters constant and only change the size of the other one at a time, as shown in Figure 2.…”

Section: The Ptsr System and Parametersmentioning

confidence: 99%

Feature Extraction and Signal Enhancement Based on Unsaturation Piecewise Tri-Stable Stochastic Resonance Driven by Lévy Noise

Zhao

Shi

2023

Security and Communication Networks

Self Cite

View full text Add to dashboard Cite

As science advances and machines become larger and more sophisticated, it is vital to determine whether there is a mechanical failure without damaging the device. Stochastic resonance (SR), as a widely used method, can effectively extract the periodic signal in the noise and then realize the identification of mechanical faults, which is very important for safety and property protection. Most studies on SR are based on additive white Gaussian noise (AWGN) as the driving source; however, there are many kinds of noise in reality. In this paper, based on the previously proposed piecewise tri-stable SR (PTSR) model, the influence of parameters on the mean of signal-to-noise ratio gain (SNR-GM) of the system driven by Lévy noise is studied. It is also verified by simulation signals and actual signals that PTSR can also achieve feature extraction and signal enhancement with Lévy noise as the driving source, which proves that PTSR can be applied in a wider range of conditions.

show abstract

Section: The Ptsr System and Parametersmentioning

confidence: 99%

Feature Extraction and Signal Enhancement Based on Unsaturation Piecewise Tri-Stable Stochastic Resonance Driven by Lévy Noise

Zhao

Shi

2023

Security and Communication Networks

Self Cite

View full text Add to dashboard Cite

show abstract

“…SPD represents the probability of Brownian particles staying in the potential well. Studying the influence of system parameters on SPD is helpful to further analyze the motion state of particles [32]. Substituting equation (11) into equation (10) so that the amplitude of the input signal A = 0.1 and the frequency f 0 = 0.01Hz, the SPD of the system under the influence of various parameters can be obtained, as shown in figures 8-10 and figure 11.…”

Section: The Spd and Mfpt Of Npuatsr Systemmentioning

confidence: 99%

Research and application of a novel piecewise unsaturated asymmetric tristable stochastic resonance system

Zhang

Zhu

zhang

2022

Meas. Sci. Technol.

View full text Add to dashboard Cite

Early fault diagnosis of rolling bearings is of great significance in the application of mechanical equipment, which makes the extraction of weak fault signals particularly critical by stochastic resonance (SR). Compared with bistable SR, tristable SR has stronger advantages in weak signal extraction, but the classical tristable system (CTSR) was limited by output saturation, which resulted in insufficient signal amplification ability. To solve the above problems, combined with asymmetric system whose output can be improved to a higher degree, a novel piecewise unsaturated asymmetric tristable stochastic resonance (NPUATSR) system is proposed. Through numerical simulation, it is concluded that NPUATSR output amplitude varies proportionally with the amplitude of the input, which overcomes the output saturation of CTSR. Secondly, the stationary probability density and mean first passage time of particles are derived by using adiabatic approximation theory, and the variation law caused by parameters is analyzed in combination with potential function, the internal mechanism of the system is further studied. Through the output signal-to-noise ratio (SNR), it is found that the performance advantage of NPUTASR system is the most obvious, and different parameters affect the output SNR. Finally, the adaptive genetic algorithm is used to optimize the parameters, and the proposed system is applied to early fault diagnosis on different types of bearings. After comparison with different systems, the results show that NPUATSR can effectively detect the fault frequency, and has the most outstanding advantages in spectrum amplification and anti-noise performance, which proves that NPUATSR system has significant value in practical engineering application.

show abstract

“…Shi et al suggested a tri-stable SR system with time-delayed feedback, which showed superior problem-solving ability in practical applications [27]. Zhao et al proposed an asymmetric time-delayed bistable system and found that a higher output SNR could be obtained [28]. Lai and Leng proposed a weak signal detection approach based on bistable Duffing oscillator, and demonstrated the practicable of this approach in the early fault diagnosis [29].…”

Section: Introductionmentioning

confidence: 99%

Weak fault feature extraction of rolling bearing based on multi-system coupled cascaded stochastic resonance system

Li,

Peng,

Zhang

et al. 2023

Meas. Sci. Technol.

View full text Add to dashboard Cite

The accurate extraction of weak signal features under strong noise background plays a crucial role in the fault detection of rolling bearings. In order to promote the ability of stochastic resonance (SR) system to detect weak signals and improve the output performance of the system, a multi-system coupled cascaded SR (MCCSR) system is investigated and applied to the fault detection of rolling bearings. Firstly, a MCCSR system is constructed by exploiting the positive synergistic effect between multiple systems, which consists of a triangular-topology coupled system composed of three SR subsystems and a cascaded SR system with topology output as input. This system makes full use of the advantages of coupled system and cascaded system in weak signal detection. In terms of parameter optimization, a stepwise multi-parameter optimization strategy is proposed, which adopts different optimization methods for different parameters, and avoids the inconsistency between error and step factor by improving the least mean square algorithm. Finally, through the comparative analysis of numerical simulation and experimental signals, it is verified that the proposed method can effectively enhance the weak signal features and improve the system output signal-to-noise ratio, which can better serve for rolling bearing fault detection.

show abstract

A novel piecewise tri-stable stochastic resonance system with time-delayed feedback and its application

Cited by 9 publications

References 33 publications

Feature Extraction and Signal Enhancement Based on Unsaturation Piecewise Tri-Stable Stochastic Resonance Driven by Lévy Noise

Feature Extraction and Signal Enhancement Based on Unsaturation Piecewise Tri-Stable Stochastic Resonance Driven by Lévy Noise

Research and application of a novel piecewise unsaturated asymmetric tristable stochastic resonance system

Weak fault feature extraction of rolling bearing based on multi-system coupled cascaded stochastic resonance system

Contact Info

Product

Resources

About