scholarly journals Feature Extraction Method for Weak Faults Based on Time-Delayed Feedback Mixed Potential Stochastic Resonance

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Jiachen Tang ◽  
Boqiang Shi ◽  
Zhixing Li
Keyword(s):  
Feature Extraction ◽  
Stochastic Resonance ◽  
Ant Colony Algorithm ◽  
Delayed Feedback ◽  
Mixed Potential ◽  
Feature Extraction Method ◽  
Delay Term ◽  
Short Memory ◽  
Weak Fault ◽  
Time Delayed Feedback

To extract weak faults under strong noise, a method for feature extraction of weak faults with time-delayed feedback mixed potential stochastic resonance (TFMSR) is proposed. This method not only overcomes the saturation characteristics of classical bistable stochastic resonance (CBSR), but also verifies a new potential function model. Based on this model, considering the short memory characteristics of the CBSR method, a method is proposed that can add historical information to the negative feedback process of the stochastic resonance (SR). Through the combination of the above two methods, the weak fault extraction under strong background noise is realized. The article analyzes the effects of the delay term, feedback term, and system parameter on the effect of SR and uses the ant colony algorithm (ACA) to optimize the above parameters. Finally, through simulated and engineering experimental results, it is proved that the proposed method has more advantages than the CBSR method in weak fault feature extraction.

Stochastic resonance in asymmetric time-delayed bistable system under multiplicative and additive noise and its applications in bearing fault detection

2019 ◽  
Vol 33 (28) ◽  
pp. 1950341 ◽  
Author(s):  
Lifang He ◽  
Dayun Hu ◽  
Gang Zhang ◽  
Siliang Lu
Keyword(s):  
Time Delay ◽  
Stochastic Resonance ◽  
Additive Noise ◽  
Random Force ◽  
Small Time ◽  
Delayed Feedback ◽  
Bistable System ◽  
Bearing Fault ◽  
Strength Formula ◽  
Time Delayed Feedback

The asymmetric bistable system with time delays in the feedback force and random force under multiplicative and additive Gaussian noise is studied. Using the small time delay approximation approach and time-delayed Fokker–Planck equations (FPE), the signal-to-noise ratio (SNR) of the proposed stochastic system is obtained. The stochastic resonance (SR) phenomena influenced by parameters — including system parameters [Formula: see text], [Formula: see text], asymmetry parameter [Formula: see text], time delay [Formula: see text], strength [Formula: see text] of the time-delayed feedback, noise intensities [Formula: see text] and [Formula: see text] of multiplicative and additive noise, and correlation strength [Formula: see text] between two noises, are also analyzed by numerical simulations. Results demonstrate that the SR performance of the asymmetric bistable system is superior to one symmetric bistable system. Besides, both time delay and strength of time-delayed feedback could enhance the SR to some extent. Then, the asymmetric time-delayed bistable SR (ATDBSR) method is used to the bearing fault diagnosis. The engineering applications of the ATDBSR method are realized and the value of the method is verified by effective experimental results.

Enhanced Rotating Machine Fault Diagnosis Based on Time-Delayed Feedback Stochastic Resonance

2015 ◽  
Vol 137 (5) ◽  
Author(s):  
Siliang Lu ◽  
Qingbo He ◽  
Haibin Zhang ◽  
Fanrang Kong
Keyword(s):  
Fault Diagnosis ◽  
Signal Detection ◽  
Stochastic Resonance ◽  
Delayed Feedback ◽  
Weak Signal ◽  
Noise Interference ◽  
Rotating Machine ◽  
Machine Fault Diagnosis ◽  
Machine Fault ◽  
Time Delayed Feedback

The fault-induced impulses with uneven amplitudes and durations are always accompanied with amplitude modulation and (or) frequency modulation, which leads to that the acquired vibration/acoustic signals for rotating machine fault diagnosis always present nonlinear and nonstationary properties. Such an effect affects precise fault detection, especially when the impulses are submerged in heavy background noise. To address this issue, a nonstationary weak signal detection strategy is proposed based on a time-delayed feedback stochastic resonance (TFSR) model. The TFSR is a long-memory system that can utilize historical information to enhance the signal periodicity in the feedback process, and such an effect is beneficial to periodic signal detection. By selecting the proper parameters including time delay, feedback intensity, and calculation step in the regime of TFSR, the weak signal, the noise, and the potential can be matched with each other to an extreme, and consequently a regular output waveform with low-noise interference can be obtained with the assistant of the distinct band-pass filtering effect. Simulation study and experimental verification are performed to evaluate the effectiveness and superiority of the proposed TFSR method in comparison with a traditional stochastic resonance (SR) method. The proposed method is suitable for detecting signals with strong nonlinear and nonstationary properties and (or) being subjected to heavy multiscale noise interference.

Asymmetric stochastic resonance under non-Gaussian colored noise and time-delayed feedback

2020 ◽  
Vol 29 (5) ◽  
pp. 050501 ◽  
Author(s):  
Ting-Ting Shi ◽  
Xue-Mei Xu ◽  
Ke-Hui Sun ◽  
Yi-Peng Ding ◽  
Guo-Wei Huang
Keyword(s):  
Stochastic Resonance ◽  
Colored Noise ◽  
Delayed Feedback ◽  
Gaussian Colored Noise ◽  
Non Gaussian ◽  
Time Delayed Feedback
Sign in / Sign up

Export Citation Format

Share Document