Valve Internal Leakage Signal Enhancement Method Based on the Search and Rescue Team–Coupled Multi-Stable Stochastic Resonance Algorithm
Source abstract
Abstract
The leakage signal of the hydraulic valve is a weak, nonlinear, and non-periodic signal that is easily overpowered by background noise from the surroundings. To address this issue, the Search and Rescue Team (SaRT) algorithm was introduced to adaptive coupled stochastic resonance, and a new signal-enhancement method based on SaRT for coupled multi-stable stochastic resonance (CMSR) was proposed for enhancing valve-leakage vibration signals. Initially, the method employs the rescaling technique to preprocess the signal, thereby transforming the fault signal into a small-parameter signal. Subsequently, the mutual correlation gain is utilized as an adaptive measure function of the SaRT algorithm to optimize the parameters of the coupled multi-stable stochastic resonance system. Ultimately, the output signal is solved by the fourth-order Runge–Kutta method. This study validated the method using sinusoidal signals and leakage signals of the check valve. The results demonstrate that all CMSR parameters require optimization. Furthermore, the noise reduction was effective for three different leakage signals of faulty check valves, in which the highest in the number of interrelationships increased by 6.9569 times and the highest amplitude ratio of the peak frequency increased by 11.7004 times. The data quality was significantly improved.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Control Systems and Identification · stochastic dynamics and bifurcation · Fault Detection and Control Systems
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
College of Mechanical and Electrical Engineering, Hunan Agricultural University, Changsha 410125, China
Intelligent Agricultural Machinery Equipment Hunan Key Laboratory, Changsha 410125, China
Funding
Natural Science Foundation of Hunan Province · Scientific Research Foundation of Hunan Provincial Education Department · China Scholarship Council (CSC)
References (30)
Show source-provided references
1. Multi-leakage source localization of safety valve based on improved KDE algorithm10.1016/j.psep.2023.01.027 ↗
2. Shen, K., and Zhao, D. (2023). An EMD-LSTM Deep Learning Method for Aircraft Hydraulic System Fault Diagnosis under Different Environmental Noises. Aerospace, 10.10.3390/aerospace10010055 ↗
3. Vibration based fault diagnosis of a hydraulic brake system using Variational Mode Decomposition (VMD)
4. The mechanism of stochastic resonance10.1088/0305-4470/14/11/006 ↗
5. Stochastic resonance10.1103/RevModPhys.70.223 ↗
6. Structural damage detection of adaptive tangent-based unsaturated bistable stochastic resonance10.1177/09544062221124719 ↗
7. A second-order stochastic resonance method enhanced by fractional-order derivative for mechanical fault detection10.1007/s11071-021-06857-7 ↗
8. Image denoising using adaptive bi-dimensional stochastic resonance system10.1080/00150193.2023.2198947 ↗
9. A high dimensional stochastic resonance system and its application in signal processing10.1016/j.chaos.2021.111642 ↗
10. The novel method of magnetic anomaly recognition based on the fourth order aperiodic stochastic resonance10.1109/JSEN.2022.3192668 ↗
11. Huang, J., Zheng, Z., Zhou, Y., Tan, Y., Wang, C., Xu, G., and Zha, B. (2023). Magnetic Anomaly Detection Based on a Compound Tri-Stable Stochastic Resonance System. Sensors, 23.10.3390/s23229293 ↗
12. Predictive coding and stochastic resonance as fundamental principles of auditory phantom perception10.1093/brain/awad255 ↗
13. Shi, P., Li, J., Zhang, W., Li, M., and Han, D. (2023). Characteristic frequency detection of steady-state visual evoked potentials based on filter bank second-order underdamped tristable stochastic resonance. Biomed. Signal Process. Control, 84.10.1016/j.bspc.2023.104817 ↗
14. An adaptive stochastic resonance detection method based on a fast artificial fish swarm algorithm10.1088/1742-6596/2517/1/012013 ↗
15. An adaptive stochastic resonance detection method with a knowledge-based improved artificial fish swarm algorithm10.1007/s11042-022-12076-y ↗
16. A new method for rubbing fault identification based on the combination of improved particle swarm optimization with self-adaptive stochastic resonance10.1007/s11668-022-01365-1 ↗
17. Huang, W., and Zhang, G. (2023). Bearing fault-detection method based on improved grey wolf algorithm to optimize parameters of multistable stochastic resonance. Sensors, 23.10.3390/s23146529 ↗
18. A Novel Adaptive Stochastic Resonance Method Based on Tristable System and its Applications10.1142/S0219477521500048 ↗
19. Adaptive detection of impact signals with two-dimensional piecewise tri-stable stochastic resonance and its application in bearing fault diagnosis10.1016/j.apacoust.2023.109702 ↗
20. Mutual information-assisted feed-forward cascaded stochastic resonance for large parameter10.1007/s11071-023-08873-1 ↗
21. Detection of bearing fault signals based on coupled Bistable system stochastic resonance10.1007/s11802-014-1939-4 ↗
22. Stochastic resonance in a high-dimensional space coupled bistable system and its application10.1016/j.apm.2022.08.023 ↗
23. Unveiling the principles of stochastic resonance and complex potential functions for bearing fault diagnosis10.1016/j.chaos.2024.114484 ↗
24. Cui, H., Guan, Y., Chen, H., and Deng, W. (2021). A novel advancing signal processing method based on coupled multi-stable stochastic resonance for fault detection. Appl. Sci., 11.10.3390/app11125385 ↗
25. Fault diagnosis of rolling bearing based on the three-dimensional coupled periodic potential-induced stochastic resonance10.1088/1361-6501/ad191a ↗
26. A novel coupled array of multi-stable stochastic resonance under asymmetric trichotomous noise and its application in rolling bearing compound fault diagnosis10.1016/j.apacoust.2023.109405 ↗
27. A fast search method for optimal parameters of stochastic resonance based on stochastic bifurcation and its application in fault diagnosis of rolling bearings10.1016/j.chaos.2023.113211 ↗
28. Stochastic resonance in a bistable system10.1016/0375-9601(83)90086-5 ↗
29. Coupled neurons with multi-objective optimization benefit incipient fault identification of machinery10.1016/j.chaos.2021.110813 ↗
30. Principle and performance validation of search and rescue team algorithm10.1007/s12206-024-1125-6 ↗