Weak-fault diagnosis using state-transition-algorithm-based adaptive stochastic-resonance method

Vibration signals are used to diagnosis faults of the rolling bearing which is symmetric structure. Stochastic resonance (SR) has been widely applied in weak signal feature extraction in recent years. It can utilize noise and enhance weak signals. However, the traditional SR method has poor performance, and it is difficult to determine parameters of SR. Therefore, a new second-order tristable SR method (STSR) based on a new potential combining the classical bistable potential with Woods-Saxon potential is proposed in this paper. Firstly, the envelope signal of rolling bearings is the input signal of STSR. Then, the output of signal-to-noise ratio (SNR) is used as the fitness function of the Seeker Optimization Algorithm (SOA) in order to optimize the parameters of SR. Finally, the optimal parameters are used to set the STSR system in order to enhance and extract weak signals of rolling bearings. Simulated and experimental signals are used to demonstrate the effectiveness of STSR. The diagnosis results show that the proposed STSR method can obtain higher output SNR and better filtering performance than the traditional SR methods. It provides a new idea for fault diagnosis of rotating machinery.

Download Full-text

Actuator Weak Fault Diagnosis in Autonomous Underwater Vehicle Based on Tri-Stable Stochastic Resonance

Applied Sciences ◽

10.3390/app10062048 ◽

2020 ◽

Vol 10 (6) ◽

pp. 2048 ◽

Cited By ~ 1

Author(s):

Yang Jiang ◽

Bo He ◽

Jia Guo ◽

Pengfei Lv ◽

Xiaokai Mu ◽

...

Keyword(s):

Fault Diagnosis ◽

Stochastic Resonance ◽

Autonomous Underwater Vehicle ◽

Underwater Vehicle ◽

Ant Colony ◽

Resonance System ◽

Resonance Model ◽

Weak Fault

The autonomous underwater vehicle (AUV) is mainly used in the development and exploration of the ocean. As an important module of the AUV, the actuator plays an important role in the normal execution of the AUV. Therefore, the fault diagnosis of the actuator is particularly important. At present, the research on the strong faults, such as the winding of the actuator, has achieved good results, but the research on the weak fault diagnosis is relatively rare. In this paper, the tri-stable stochastic resonance model is analyzed, and the ant colony tri-stable stochastic resonance model is used to diagnose the weak fault. The system accurately diagnoses the fault of the actuator collision and verifies the adaptive tri-stable stochastic resonance system. This model has better diagnostic results than the bi-stable stochastic resonance system.

Download Full-text

A weak fault diagnosis method for rotating machinery based on compressed sensing and stochastic resonance

Journal of Vibroengineering ◽

10.21595/jve.2018.20140 ◽

2019 ◽

Vol 21 (3) ◽

pp. 654-664 ◽

Cited By ~ 1

Author(s):

Peiming Shi ◽

Xiaojie Ma ◽

Dongying Han

Keyword(s):

Fault Diagnosis ◽

Compressed Sensing ◽

Stochastic Resonance ◽

Rotating Machinery ◽

Diagnosis Method ◽

Weak Fault

Download Full-text

Application of continuous potential function stochastic resonance in early fault diagnosis of rolling bearings

Measurement and Control ◽

10.1177/0020294019890633 ◽

2020 ◽

Vol 53 (5-6) ◽

pp. 767-777

Author(s):

Xueping Ren ◽

Jian Kang ◽

Zhixing Li ◽

Jianguo Wang

Keyword(s):

Fault Diagnosis ◽

Stochastic Resonance ◽

Potential Function ◽

Output Signal ◽

Signal To Noise Ratio ◽

Resonance Method ◽

Signal To Noise ◽

Rolling Bearings ◽

Continuous Potential ◽

Potential Parameters

The early fault signal of rolling bearings is very weak, and when analyzed under strong background noise, the traditional signal processing method is not ideal. To extract fault characteristic information more clearly, the second-order UCPSR method is applied to the early fault diagnosis of rolling bearings. The continuous potential function itself is a continuous sinusoidal function. The particle transition is smooth and the output is better. Because of its three parameters, the potential structure is more comprehensive and has more abundant characteristics. When the periodic signal, noise and potential function are the best match, the system exhibits better denoise compared to that of other methods. This paper discusses the influence of potential parameters on the motion state of particles between potential wells in combination with the potential parameter variation diagrams discussed. Then, the formula of output signal-to-noise ratio is derived to further study the relationships among potential parameters, and then the ant colony algorithm is used to optimize potential parameters in order to obtain the optimal output signal-to-noise ratio. Finally, an early weak fault diagnosis method for bearings based on the underdamped continuous potential stochastic resonance model is proposed. Through simulation and experimental verification, the underdamped continuous potential stochastic resonance results are compared with those of the time-delayed feedback stochastic resonance method, which proves the validity of the underdamped continuous potential stochastic resonance method.

Download Full-text