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Article
Acoustics
Zong Meng et al.
Summary: This paper proposes a novel coupled array of multi-stable stochastic resonance (NCAMSR) driven by asymmetric trichotomous noise for compound fault diagnosis. The information of different fault features in the compound fault signal is separated using Multipoint Optimal Minimum Entropy Deconvolution Adjusted (MOMEDA), and the outputs of the coupled array system are weighted to find the best effect. The NCAMSR potential model based on the improved Gaussian potential is proposed to alleviate the problem of output saturation, and the superior unsaturation of the NCAMSR potential function model is proven by theoretical analysis and experiments. The excellent performance of NCAMSR in compound fault detection is further verified by using engineering experiments.
Article
Mathematics, Interdisciplinary Applications
Yanfei Jin et al.
Summary: In this paper, the mean first-passage times and stochastic resonance in an asymmetric tri-stable system with time-delayed feedback are studied. Theoretical expressions for small time delay and numerical results for large time delay are provided. The results suggest that the correlation between the noises plays a constructive role on system dynamics, and the phenomenon of noise enhanced stability and stochastic resonance can be optimized by choosing proper time-delayed feedback gain. Additionally, the time delay greatly affects the crossing between left and middle wells, while the feedback gain affects the crossing velocity between right and middle wells.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Mathematics, Interdisciplinary Applications
Hao Ai et al.
Summary: This paper proposes a model of considering the time-delay stochastic resonance from the perspective of engineering applications, using appropriate external noise to enhance the weak signal. The classical bistable symmetric potential is changed into a double-well variable potential well, and a more effective search interval is found through studying the random bifurcation of the system, improving the search efficiency by about 50%. The new model effectively increases the amplitude of the target signal under the condition of restraining interference, verifying the effectiveness and superiority of the proposed method in engineering practice.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Engineering, Mechanical
Bingchang Hou et al.
Summary: This paper proposes a new decomposition approach called difference mode decomposition (DMD) to adaptively decompose a mixed signal into concerned components (CC), reference components, and noise. The proposed DMD relies on convex optimization and Fourier transform, and its decomposition is mathematically justified and composes physical interpretations. Analyses of simulated and real-world bearing and gear vibration signals are used to verify the effectiveness and superiority of the proposed DMD over existing adaptive mode decomposition algorithms.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Engineering, Mechanical
Yanfei Jin et al.
Summary: This paper investigates the stochastic resonance and mean-first passage time of a quad-stable potential in the presence of Gaussian white noise and periodic forcing. The analytical expressions of mean-first passage time and spectral amplification are obtained, respectively. It is found that noise-assisted hopping and accelerated escape process occur in the system under different noise intensities. Moreover, the paper proposes a multi-stable stochastic resonance method for fault diagnosis and demonstrates its superior performance compared to existing methods.
PROBABILISTIC ENGINEERING MECHANICS
(2023)
Article
Acoustics
Jian Suo et al.
Summary: This paper proposes a novel method for direction-of-arrival (DOA) estimation using complex acoustic intensity measurements (CAIM) and unsaturated bistable stochastic resonance (UBSR) to enhance accuracy. The proposed method achieves stable phase shift and linear amplitude response by utilizing the properties of stochastic resonance. Numerical analysis and application verification show that the proposed method outperforms existing methods, particularly in low signal-to-noise ratios (SNRs).
Article
Acoustics
Gang Zhang et al.
Summary: In this paper, the authors propose an innovative method called Adaptive Two-Dimensional Piecewise Tri-Stable Stochastic Resonance (TDPTSR) for extracting weak fault features. They address the saturation issue of the Standard Tri-Stable Stochastic Resonance (STSR) system by constructing a novel piecewise tri-stable potential function. The authors analyze the performance of the TDPTSR system using adiabatic approximation theory and introduce a Modified Kurtosis Index (MKC) for impact signal detection. Simulation analysis demonstrates the effectiveness of MKC as an index and the superior detection capability of the TDPTSR system. The authors also apply TDPTSR to fault diagnosis and optimize system parameters using a genetic algorithm (GA).
Article
Mathematics, Interdisciplinary Applications
Lifang He et al.
Summary: In this paper, a piecewise unsaturated tri-stable stochastic resonance (PUTSR) system is proposed to address the issue of output saturation. The two-dimensional coupled piecewise unsaturated tri-stable stochastic resonance (TCPUTSR) system and cascaded piecewise unsaturated tri-stable stochastic resonance (CPUTSR) system are proposed and their system performance is discussed. The results indicate that the designed cascaded CPUTSR system outperforms the coupled TCPUTSR system in terms of spectral amplification capability and fault signal detection capability.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Mathematics, Interdisciplinary Applications
Jian Suo et al.
Summary: Extracting ship-radiated line signatures from intense background noise is a challenging task in remote passive sonar detection and identification. In this study, we propose a feed-forward cascaded stochastic resonance (FCSR) method that leverages complete target signal information and gradually improves the signal-to-noise ratio (SNR) with high robustness. Theoretical analysis and simulation results demonstrate the effectiveness of the FCSR method, which outperforms the cascaded stochastic resonance (CSR) method in filtering performance, anti-noise ability, and robustness.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Acoustics
Peiming Shi et al.
Summary: This paper proposes a novel adaptive multi-parameter unsaturation bistable stochastic resonance (AMUBSR) system based on piecewise linearization of potential function, and adopts the beetle antennae search (BAS) algorithm to optimize the system parameters. The simulation results demonstrate the effectiveness and superiority of the proposed method in parameter matching, as well as the further improvement of the output SNR, higher spectrum peak value at characteristic frequency, and larger recognition quantity in fault diagnosis.
Article
Engineering, Mechanical
Tao Gong et al.
Summary: In this paper, an adaptive cascaded stochastic resonance method is proposed to extract and enhance non-stationary weak feature information. The non-stationary feature information is transformed into stationary feature information using preprocessing and computed order analysis method. Filtering and enhancement methods are applied to highlight the characteristic signal and reduce noise interference. Experimental results show that the proposed method significantly improves the output characteristic amplitude and signal-to-noise ratio.
NONLINEAR DYNAMICS
(2022)
Article
Physics, Multidisciplinary
Gang Zhang et al.
Summary: This study proposes a two-dimensional tri-stable stochastic resonance (TDTSR) system with adjustable parameters to address the problem of difficult parameter tuning in one-dimensional stochastic resonance systems. Numerical analysis and simulation show that the TDTSR system has a higher mean signal-to-noise ratio gain compared to the one-dimensional tri-stable stochastic resonance (ODTSR) system. The systems are further applied in bearing faults detection, and the TDTSR system shows superior performance. This research provides significant theoretical and practical value for engineering applications.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
Article
Mathematics, Interdisciplinary Applications
Jimeng Li et al.
Summary: This paper combines vibrational resonance and stochastic resonance to construct a cascaded feedback model, forming a parallel resonance system to improve the detection performance of weak signals. A multi-parameter optimization strategy based on the improved whale optimization algorithm is proposed for parameter selection of the parallel resonance system, achieving automatic adjustment of multiple parameters and obtaining the final output through weighted summation of optimal results obtained by multiple iterations.
CHAOS SOLITONS & FRACTALS
(2022)
Article
Mathematics, Interdisciplinary Applications
Lingling Duan et al.
Summary: This paper explores the adaptive stochastic resonance effect in convolutional neural networks and applies it to enable back-propagation gradient computation. The research shows that this method can use noise to improve network performance and the network has hardware-friendly features.
CHAOS SOLITONS & FRACTALS
(2022)
Article
Physics, Multidisciplinary
Elso Drigo Filho et al.
Summary: The purpose of this work is to explore the kinetics of the transition probability distribution obtained as a solution to the Fokker-Planck equation for a system with a tristable potential. The Fokker-Planck equation is rewritten as a Schrodinger equation, allowing the use of the Supersymmetric Quantum Mechanics formalism to obtain the analytical approximated spectrum. The characteristic passage time between the potential minima is determined by evaluating the probability distribution obtained from the solutions.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
Article
Engineering, Mechanical
Gang Zhang et al.
Summary: The TDTS method proposed in this study effectively detects weak periodic signals and inner and outer ring faults of bearings. The potential field structure and spectral power amplification of the TDTS were discussed and analyzed, showing that stochastic resonance phenomena occur in the system. Comparisons with the ODATS method demonstrated the effectiveness and advancement of the TDTS method in detecting weak signals from intense noise.
JOURNAL OF VIBRATION ENGINEERING & TECHNOLOGIES
(2021)
Article
Mathematics, Interdisciplinary Applications
Mengdi Li et al.
Summary: This study proposes an under damped continuous unsaturation bistable stochastic resonance (UCUBSR) system to address the saturation issue in classical bistable stochastic resonance (CBSR) system. The introduction of amplitude gain as a modified unsaturation index is effective in quantifying stochastic resonance and analyzing system performance. The simulation and experimental results demonstrate that a larger amplitude gain indicates better performance in weak fault detection and parameter adjustment, enhancing fault signature identification.
CHAOS SOLITONS & FRACTALS
(2021)
Article
Mathematics, Interdisciplinary Applications
Zhiqiang Liao et al.
Summary: Stochastic resonance (SR) is a phenomenon where information-carrying signals are enhanced by noise in nonlinear systems. The proposed bistable SR activation function for Echo State Networks (ESN) improves noise adaptability and provides short-term memory capability, demonstrating potential for physical reservoir computing.
CHAOS SOLITONS & FRACTALS
(2021)
Article
Physics, Multidisciplinary
Shuai Zhao et al.
Summary: The study focuses on the stochastic resonance system with time-delay feedback terms, which shows potential in improving output performance. Through calculation comparisons, it is found that the TFPTSR method can achieve better output signal-to-noise ratio in processing the same signal as the PTSR method.
CHINESE JOURNAL OF PHYSICS
(2021)
Article
Engineering, Multidisciplinary
Shuai Zhao et al.
Summary: The PTSR method, by utilizing a piecewise approach, effectively avoids output saturation phenomenon present in the STSR method, resulting in higher signal-to-noise ratio and signal amplitude in the output signal.
Article
Acoustics
Yinwen Qiu et al.
Summary: The study analyzed parameters influencing the stochastic resonance system in underwater acoustic communication and proposed an adaptive method called RLGA for parameter adjustment. By combining reinforcement learning with genetic algorithm, the method improved the local search ability and accelerated convergence speed, making it more suitable for signal detection.
Article
Mathematics, Interdisciplinary Applications
Zijian Qiao et al.
Summary: Organisms can amplify subtle changes in the environment using noise through interconnected neurons, which inspired the development of a method using coupled neurons and multi-objective optimization to enhance machinery fault signature identification. This approach outperformed traditional filter-based methods in experimental tests.
CHAOS SOLITONS & FRACTALS
(2021)
Article
Engineering, Mechanical
Jimeng Li et al.
Summary: This study introduces a double-feedback cascaded monostable SR system, which significantly improves system performance by incorporating feedback control and serial structure. The system can exhibit low-pass filtering or band-pass filtering behavior through different combinations of feedback coefficients, better matching the frequency characteristics of the target signal.
NONLINEAR DYNAMICS
(2021)
Article
Engineering, Mechanical
Gang Zhang et al.
Summary: This study introduces a novel PUUTSR system that overcomes the output saturation issue of the CTSR system, demonstrating superior signal amplification and fault diagnosis capabilities in numerical simulations and experiments.
JOURNAL OF VIBRATION ENGINEERING & TECHNOLOGIES
(2021)
Review
Geochemistry & Geophysics
Zefeng Li
Summary: Seismic data processing techniques have significantly improved earthquake monitoring capabilities in the past two decades, thanks to advancements in computational power, signal processing, and machine learning. Techniques such as template matching and deep learning have enhanced the ability to extract small earthquake signals from noisy data. Future research needs to focus on developing highly generalizable detection algorithms and real-time monitoring technologies for ongoing seismic sequences.
EARTHQUAKE SCIENCE
(2021)
Review
Geochemistry & Geophysics
Zefeng Li
Summary: This paper reviews the advancements in earthquake monitoring capability achieved through improvements in seismic data processing techniques over the past two decades, particularly the widespread use of template matching and deep learning. Relative location techniques provide critical tools for analyzing fault geometries and seismicity migration patterns at unprecedented resolution levels. The development of intelligent software systems and high-resolution processing could potentially revolutionize traditional earthquake monitoring workflows and free seismologists from laborious catalog construction tasks.
EARTHQUAKE SCIENCE
(2021)
Article
Engineering, Multidisciplinary
Pengfei Xu et al.
APPLIED MATHEMATICAL MODELLING
(2020)
Article
Mathematics, Interdisciplinary Applications
Mengdi Li et al.
CHAOS SOLITONS & FRACTALS
(2020)
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Mathematics, Interdisciplinary Applications
Pengfei Xu et al.
CHAOS SOLITONS & FRACTALS
(2020)
Review
Engineering, Mechanical
Siliang Lu et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2019)
Review
Engineering, Mechanical
Zijian Qiao et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2019)
Article
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Z. H. Lai et al.
NONLINEAR DYNAMICS
(2019)
Article
Acoustics
Haitao Dong et al.
JOURNAL OF SOUND AND VIBRATION
(2019)
Article
Physics, Multidisciplinary
Lifang He et al.
Article
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MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2017)
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Mathematics, Interdisciplinary Applications
Yanfei Jin et al.
CHAOS SOLITONS & FRACTALS
(2017)
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Biology
Chaitra Sridhar et al.
COMPUTERS IN BIOLOGY AND MEDICINE
(2017)
Article
Physics, Multidisciplinary
Yulei Liu et al.
CHINESE JOURNAL OF PHYSICS
(2017)
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Engineering, Mechanical
Zhi-hui Lai et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2016)
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Mathematics, Interdisciplinary Applications
A. Soleimani et al.
CHAOS SOLITONS & FRACTALS
(2015)
Article
Engineering, Electrical & Electronic
Siliang Lu et al.
DIGITAL SIGNAL PROCESSING
(2015)
Article
Acoustics
Jimeng Li et al.
JOURNAL OF SOUND AND VIBRATION
(2013)
Article
Physics, Multidisciplinary
Kaihe Liu et al.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2013)
