Adaptive stochastic resonance in bistable system driven by noisy NLFM signal: phenomenon and application

The stochastic resonance (SR) in a bistable system driven by nonlinear frequency modulation (NLFM) signal and strong noise is studied. Combined with empirical mode decomposition (EMD) and piecewise idea, an adaptive piecewise re-scaled SR method based on the optimal intrinsic mode function (IMF), is proposed to enhance the weak NLFM signal. At first, considering the advantages of EMD for dealing with non-stationary signals, the segmented NLFM signal is processed by EMD. Meanwhile, the cross-correlation coefficient is used as the measure to select the optimal IMF that contains the NLFM signal feature. Then, the spectral amplification gain indicator is proposed to realize the adaptive SR of the optimal IMF of each sub-segment signal and reconstruct the enhanced NLFM signal. Finally, the effectiveness of the proposed method is highlighted with the analysis of the short-time Fourier transform spectrum of the simulation results. As an application example, the proposed method is verified adaptability in bearing fault diagnosis under the speed-varying condition that represents a typical and complicated NLFM signal in mechanical engineering. The research provides a new way for the enhancement of weak non-stationary signals. This article is part of the theme issue ‘Vibrational and stochastic resonance in driven nonlinear systems (part 1)’.

Download Full-text

Realizing the empirical mode decomposition by the adaptive stochastic resonance in a new periodical model and its application in bearing fault diagnosis

Journal of Mechanical Science and Technology ◽

10.1007/s12206-017-0906-6 ◽

2017 ◽

Vol 31 (10) ◽

pp. 4599-4610 ◽

Cited By ~ 12

Author(s):

Jingling Zhang ◽

Dawen Huang ◽

Jianhua Yang ◽

Houguang Liu ◽

Xiaole Liu

Keyword(s):

Fault Diagnosis ◽

Stochastic Resonance ◽

Empirical Mode Decomposition ◽

Bearing Fault ◽

Bearing Fault Diagnosis ◽

Mode Decomposition

Download Full-text

Stochastic Resonance in Unsaturated Piecewise Nonlinear Bistable System Under Multiplicative and Additive Noise for Bearing Fault Diagnosis

IEEE Access ◽

10.1109/access.2019.2914138 ◽

2019 ◽

Vol 7 ◽

pp. 58435-58448 ◽

Cited By ~ 8

Author(s):

Gang Zhang ◽

Dayun Hu ◽

Tianqi Zhang

Keyword(s):

Fault Diagnosis ◽

Stochastic Resonance ◽

Additive Noise ◽

Bistable System ◽

Bearing Fault ◽

Bearing Fault Diagnosis

Download Full-text

Bearing fault diagnosis based on variational mode decomposition and stochastic resonance

2018 IEEE International Conference on Prognostics and Health Management (ICPHM) ◽

10.1109/icphm.2018.8448480 ◽

2018 ◽

Cited By ~ 1

Author(s):

Xin Zhang ◽

Huiyu Liu ◽

Heng Zhang ◽

Qiang Miao

Keyword(s):

Fault Diagnosis ◽

Stochastic Resonance ◽

Variational Mode Decomposition ◽

Bearing Fault ◽

Bearing Fault Diagnosis ◽

Mode Decomposition

Download Full-text

Adaptive Modulation Stochastic Resonance of Two-Dimensional Asymmetric Bistable System and its Application in Bearing Fault Diagnosis

IEEE Access ◽

10.1109/access.2021.3100112 ◽

2021 ◽

pp. 1-1

Author(s):

Gang Zhang ◽

Yichen Shu ◽

Tianqi Zhang

Keyword(s):

Fault Diagnosis ◽

Stochastic Resonance ◽

Adaptive Modulation ◽

Bistable System ◽

Two Dimensional ◽

Bearing Fault ◽

Bearing Fault Diagnosis

Download Full-text

EMD Analysis of Power Harmonics

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.706-708.1331 ◽

2013 ◽

Vol 706-708 ◽

pp. 1331-1334

Author(s):

Kai Tuo Zhang ◽

Ming Li

Keyword(s):

Power System ◽

Harmonic Analysis ◽

Empirical Mode Decomposition ◽

Single Phase ◽

Signal Wave ◽

Harmonic Frequency ◽

Mode Function ◽

Mode Decomposition ◽

Stationary Signals ◽

Power Harmonics

It can obtain intrinsic mode function (IMF) of signal wave with empirical mode decomposition (EMD) in harmonic analysis of power system. Harmonic frequency, amplitude and duration can be obtained through analysis of IMFs. Through EMD analysis on distortion waveform of single-phase AC inverter output as an example, combined with applied scene of distorted voltage, cause of distortion waveform can be deduced. The result shows that EMD analysis on non-stationary signals is of good performance, and a new substitute method of FFT transform in harmonic analysis.

Download Full-text

Application of Generalized Stochastic Resonance to the Vibration Test

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.141.21 ◽

2011 ◽

Vol 141 ◽

pp. 21-25

Author(s):

Ying Zhang ◽

Shu Ming Li

Keyword(s):

Stochastic Resonance ◽

Input Signal ◽

Parameter Tuning ◽

Sampling Frequency ◽

Bistable System ◽

Vibration Test ◽

System Behavior ◽

System Parameters ◽

Sr Method ◽

Large Frequency

Noise, bistable system and input signal are the three essential factors in stochastic resonance (SR). The noise-induced SR method, the parameter-tuning SR method, and the twice sampling SR method change the characteristics of the noise, the bistable system and the input signal, respectively. With the new cooperation, they can all produce the SR phenomena when the system exceeds the small-parameter area. If treating the strong noise and the input signal with large frequency, the actions of the system parameters can build the system behavior in an orderly way, associated with the twice sampling frequency. The united parameter-tuning SR method adjusts the system parameters to fit the normalized frequency after the twice sampling SR, in order to make the optimal noise intensity. The application to the flow meter vibration test has presented the practicability and effectiveness of the united parameter-tuning SR method.

Download Full-text

Stochastic Resonance and Self-Induced Stochastic Resonance in Bearing Fault Diagnosis

Fluctuation and Noise Letters ◽

10.1142/s0219477521500474 ◽

2021 ◽

pp. 2150047

Author(s):

Shuai Zhang ◽

Jianhua Yang ◽

Canjun Wang ◽

Houguang Liu ◽

Chen Yang

Keyword(s):

Nonlinear System ◽

Stochastic Resonance ◽

Evolutionary Process ◽

Vibration Signal ◽

Bearing Failure ◽

Bearing Fault ◽

Bearing Fault Diagnosis ◽

Fault Features ◽

Characteristic Signal ◽

Sr Method

Stochastic resonance (SR) and self-induced stochastic resonance (SISR) are two kinds of important dynamical phenomena in the nonlinear system. SR occurs at the frequency of the characteristic signal. However, SISR can occur at a frequency that is included in the excitation. In present, there are volumes of literatures focusing on extracting the bearing fault characteristics from the vibration signal by SR method. However, the occurrence of SISR may result in the fault features misjudgment in SR processing. Through experimental verifications, we find that the interference of SISR is illustrated strongly in the fault characteristics identification. More importantly, the transition from SISR to SR corresponds to the evolution process of bearing state from normal to damage. Therefore, this evolutionary process can not only judge the state of bearing, but also describe the severity of bearing failure. The result is verified by processing the signals of bearing fault with different severity in noise background. They are the most important findings in this work.

Download Full-text