Adaptive detection of impact signals with two-dimensional piecewise tri-stable stochastic resonance and its application in bearing fault diagnosis

Zhang, Gang; Huang, Xiaoxiao; Xu, Jiaqi; Li, Zhaorui

doi:10.1016/j.apacoust.2023.109702

Cited by 12 publications

(1 citation statement)

References 36 publications

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“…The original signal is injected into the model, the SNR of the signal is calculated using equation (32), where S f ( ) is the power spectral density at signal frequency f , 0 and then the model output SNR is used as the objective function, using quantum genetic algorithm [41,42] to optimize one-stage model adjustment parameters k, integral step h and damping ratio , g the evolution algebra G G 1 = + and satisfy G G , max  then bring the optimal model parameter k , opt h opt and opt g under SNR max conditions back to the model to solve the output. that the sinusoidal signal is overwhelmed by strong noise and the characteristic frequency 20 Hz cannot be recognized.…”

Section: Sr In An Underdamped Nonlinear System With a Fourth-stable P...mentioning

confidence: 99%

Fourth-stable stochastic resonance and its application to weak fault signal detection of rotating machinery

Yun,

Zhang,

Shang

et al. 2024

Phys. Scr.

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Weak characteristic extraction is vital for weak fault signal detection of machinery. Stochastic resonance (SR) is able to transfer noise energy into weak fault characteristic frequency excited by a defect of machines. However, the potential function in SR is vital to enhance weak fault characteristic frequency and determines the capability of SR to improve the signal-to-noise ratio (SNR) of a noisy signal. Now, common potential functions include monostable, bistable and even tri-stable potentials but fourth-stable SR has not been studied and applied to detect early fault characteristic frequency. In this paper, thus, we would investigate the behaviors of SR with a fourth-stable potential subject to additive noise, in which the approximate theoretical expression of the power done by SR is derived to demonstrate the fourth-stable SR. Then, a SR method with the fourth-stable potential is proposed to enhance weak fault characteristic frequency, in which these system parameters are adjusted by using SNR as the objective function and using genetic algorithms adaptively. In this paper, thus, Finally, the proposed method is verified by using a simulated signal with noise and two early fault experiment of rolling element bearings with different levels of defects on the outer and inner races. Moreover, the proposed method is compared with wavelet denoising and fast kurtogram methods. The comparisons indicate that the proposed method has the better performance for enhancing weak fault characteristic frequency or weak useful signals than other two methods and is available to weak fault signal detection of machinery.

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Section: Sr In An Underdamped Nonlinear System With a Fourth-stable P...mentioning

confidence: 99%

Fourth-stable stochastic resonance and its application to weak fault signal detection of rotating machinery

Yun,

Zhang,

Shang

et al. 2024

Phys. Scr.

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Adaptive Optimal Resonance Fault Feature Enhancement for Wind Turbine Based on Frequency Search and Uncertainty Analysis

Dang,

Wang,

Yin

et al. 2024

IEEJ Transactions Elec Engng

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The wind turbine fault feature has strong uncertainty due to various factors such as wind speed and equipment parameters. Based on the analysis of the vibration characteristics of wind turbines with unknown prior conditions, this paper conducts research on the enhancement method of fault features. First, analyzing the change in fault features caused by the change in operating conditions to lay the foundation for subsequent research; Second, for the uncertainty of wind turbine fault feature frequency, searching for fault features by constructing the energy in each spectral interval, then use signal noise optimal resonance to transfer noise energy to low frequency fault features to achieve the purpose of adaptive optimal resonance enhancement of fault feature; Finally, validation of the proposed method by simulation experiments and fault signals of actual wind turbine rolling bearings. The case shows that the proposed algorithm can effectively realize the uncertain fault feature of wind turbines search and enhancement. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

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Rolling Bearing Fault Diagnosis Based on Multi-source Information Fusion

Zhu,

Deng,

Xing

et al. 2024

J Fail. Anal. and Preven.

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Adaptive detection of impact signals with two-dimensional piecewise tri-stable stochastic resonance and its application in bearing fault diagnosis

Cited by 12 publications

References 36 publications

Fourth-stable stochastic resonance and its application to weak fault signal detection of rotating machinery

Fourth-stable stochastic resonance and its application to weak fault signal detection of rotating machinery

Adaptive Optimal Resonance Fault Feature Enhancement for Wind Turbine Based on Frequency Search and Uncertainty Analysis

Rolling Bearing Fault Diagnosis Based on Multi-source Information Fusion

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