Classical Resonance Research Articles

Numerical study of acoustic metamaterial made of Helmholtz resonators with complex necks for low frequencies noise attenuation

In this paper, an acoustic metamaterial consisting of Helmholtz resonators with complex necks is proposed for low frequency noise reduction. The resonators are made of a cavity and a complex neck, which is a periodic succession of necks with small and large diameters. The acoustic attenuation performance of the proposed metamaterial design is demonstrated using finite element method. For such a shaped neck, the sound absorption coefficient presents multiple peaks. With a succession of N small and (N - 1) large neck diameters, N peaks in the sound absorption coefficient are obtained. By increasing the number of successions, the number of peaks increases. At the peaks, the surface acoustic impedance of the metamaterial nearly matches with the characteristic impedance of the air. This makes the sound absorption coefficient being nearly 100%. Keeping the same cavity volume, we increase the number of sound absorption peaks by the complex shape of the neck, while the classic Helmholtz resonator presents only one peak.

Nonlinear coupled asymmetric stochastic resonance for weak signal detection based on intelligent algorithm optimization

Stochastic resonance has been extensively studied for detecting weak signals. To improve the diagnostic ability of weak signals, a novel nonlinear coupled asymmetric stochastic resonance (NCASR) system is investigated in this paper. Firstly, the NCASR system is established by coupling the asymmetric bistable system with the monostable system. Next, the expressions for the steady-state probability density (SPD) function, the mean first passage time (MFPT) and the signal-to-noise ratio (SNR) of the proposed system are derived based on the adiabatic approximation theory. Furthermore, the impact of system parameters on the SPD, the MFPT and the SNR is analyzed. Then, by simulation experiments, we verify the effectiveness of detecting weak signals for the NCASR system with Lévy noise. Finally, the NCASR system optimized by Adaptive Weighted Particle Swarm Optimization (AWPSO) algorithm is applied to detect the bearing fault signal. Compared with the optimized classical bistable stochastic resonance (CBSR) system, it is found that the detection performance of the NCASR system is superior to the CBSR system in detecting bearing fault signals.

Two-dimensional quad-stable Gaussian potential stochastic resonance model for enhanced bearing fault diagnosis

In this study, a two-dimensional quad-stable Gaussian potential stochastic resonance model is explored for the first time. First, the structure of the proposed model is analyzed to have a broader potential field and verified to break through the severe output saturation inherent in the classical two-dimensional quad-stable stochastic resonance model. Then, we analyze the relationship between the structure and parameters of the model and derive the steady-state probability density and the mean first-passage time using adiabatic approximation theory to describe the specific process of the Brownian particle transitions. By combining the adiabatic approximation theory and the probability flow equation, the spectral amplification factor of the model is derived, and the effects of different parameters on the model performance are investigated. Further, a fourth-order Runge-Kutta algorithm was applied to evaluate the model performance in multiple dimensions. Finally, the model parameters were optimized using an adaptive genetic algorithm and applied to complex practical engineering detection. The experimental results show that the proposed model is superior and universal in fault diagnosis. Overall, this study provides important mathematical support for solving various engineering problems and demonstrates a wide range of practical applications.

Research and Application of Two-Dimensional Time-Delayed Tri-Stable Stochastic Resonance System for Bearing Fault Detection

The time-delayed feedback term can improve the output of a system, while the two-dimensional stochastic resonance (SR) system has a stronger signal amplification capability. To improve the output signal-to-noise ratio (SNR) of the system, this paper proposes a two-dimensional time-delayed tri-stable stochastic resonance system (TDTDTSR) based on the advantages of the above two systems. First, the steady-state probability density function (SPD), the mean first-pass time (MFPT), and the output SNR are derived under adiabatic approximation theory, and the effects of different system parameters on them are investigated. Next, TDTDTSR and the classical two-dimensional tri-stable stochastic resonance system (CTDTSR) system are simulated numerically. The results show that the mean signal-to-noise gain (MSNRG) of TDTDTSR system is higher than that of the CTDTSR system. Finally, the system parameters are optimized using a genetic algorithm, and the application of TDTDTSR to bearing fault detection is compared with CTDTSR and the novel piecewise symmetric two-dimensional tri-stable stochastic resonance (NPSTDTSR) systems. The experimental results demonstrate that TDTDTSR system has better performance, providing valuable theoretical support and practical engineering applications for the system in subsequent analyses.

Importance of T1-Mapping Sequence in Patients with Hypertrophic Cardiomyopathy without Foci of Non-Ischemic Myocardial Injury in Late Gadolinium Enhancement Sequence.

The aim of this study was to assess the importance of T1-mapping sequences in the diagnosis of hypertrophic cardiomyopathy (HCM) in patients without foci of non-ischemic myocardial injury in classic cardiac magnetic resonance (CMR) sequences. Two groups were compared: 28 patients with HCM, without any foci of myocardial injury in the late gadolinium enhancement (LGE) sequence (HCM group), and 28 patients without cardiomyopathy (CON group). Classic CMR sequences and T1-mapping sequences were performed. The following parameters were assessed: T1 time of the whole left ventricular myocardium, T1 time of myocardium in the basal, middle and apical layers of the left ventricle, and T1 time in individual segments of the left ventricular myocardium. Myocardial extracellular volume (ECV) was assessed similarly. ECV was significantly higher in the HCM group than in the CON group, for the whole left ventricular myocardium, for the basal and apical layers of the left ventricle, and for segments 1-3, 8, and 13-16 of the left ventricle. Regression analysis showed that a higher left-ventricular mass index (LVMI), a higher body mass index and older age are factors independently associated with a higher ECV of the whole myocardium but only in the group with LVMI ≥ 131.84 g/m2. In patients with HCM without foci of non-ischemic myocardial injury, higher ECV values of the left ventricular myocardium are observed.

Impact of potential function asymmetry on the performance of a novel stochastic resonance system

Due to output saturation and parameter coupling, the traditional classical bistable stochastic resonance (CBSR) system is often unable to effectively handle the extraction of weak signal features encountered in many engineering applications. To overcome this limitation, an asymmetric decoupled unsaturated bistable stochastic resonance (ADUBSR) system is proposed in this paper. Subsequently, the impact of barrier asymmetry on system output has been analyzed by taking signal-to-noise ratio (SNR), peak signal-to-noise ratio (PSNR), and the optimal noise required for obtaining PSNR as evaluation indicators. The results indicate that: (1) The output SNR is effectively enhanced by barrier-width asymmetry only when the left barrier is narrower than the right. (2) Barrier-height asymmetry fails to effectively improve the output SNR. (3) In the case of barrier-height-width asymmetry, the barrier width asymmetry predominantly enhances the output SNR, resulting in the best performance. (4) For all three asymmetric structures, regardless of noise type, the optimal noise intensity depends greatly on barrier height and width values, and is less influenced by asymmetry. Finally, the proposed system is used for engineering data, and the results show that the signal processed by the ADUBSR system achieves a higher output SNR and the amplitude at the fault frequency is 10 times greater than that of the signal processed by the CBSR system.

Power System Signal-Detection Method Based on the Accelerated Unsaturated Stochastic Resonance Principle

The classical bistable stochastic resonance algorithm has an inherent output saturation defect that restricts the amplitude of the output signal. This paper examines the causes of this phenomenon and its negative impact on the detection of weak signals. Proposing the Unsaturated Bistable Stochastic Resonance (UBSR) detection algorithm involves constructing a segmented potential function using a linear function to eliminate the effect of higher-order terms in the classical stochastic resonance algorithm. A new type of segmented potential function has been created by combining exponential and linear functions. This new function helps to eliminate the impact of higher-order terms in classical algorithms while also improving the noise immunity of the stochastic resonance system. This results in the development of the accelerated stochastic resonance (ASR) detection algorithm. In this paper, the Kramers escape rate and output signal-to-noise ratio of two improved stochastic resonance algorithms are theoretically derived and compared with the classical bistable stochastic resonance algorithms, and the proposed algorithms are able to effectively avoid the output saturation phenomenon and have more excellent detection performance under strong background noise.

Terahertz Biosensor Engineering Based on Quasi-BIC Metasurface with Ultrasensitive Detection.

Terahertz (THz) sensors have attracted great attention in the biological field due to their nondestructive and contact-free biochemical samples. Recently, the concept of a quasi-bound state in the continuum (QBIC) has gained significant attention in designing biosensors with ultrahigh sensitivity. QBIC-based metasurfaces (MSs) achieve excellent performance in various applications, including sensing, optical switching, and laser, providing a reliable platform for biomaterial sensors with terahertz radiation. In this study, a structure-engineered THz MS consisting of a "double C" array has been designed, in which an asymmetry parameter α is introduced into the structure by changing the length of one subunit; the Q-factor of the QBIC device can be optimized by engineering the asymmetry parameter α. Theoretical calculation with coupling equations can well reproduce the THz transmission spectra of the designed THz QBIC MS obtained from the numerical simulation. Experimentally, we adopt an MS with α = 0.44 for testing arginine molecules. The experimental results show that different concentrations of arginine molecules lead to significant transmission changes near QBIC resonant frequencies, and the amplitude change is shown to be 16 times higher than that of the classical dipole resonance. The direct limit of detection for arginine molecules on the QBIC MS reaches 0.36 ng/mL. This work provides a new way to realize rapid, accurate, and nondestructive sensing of trace molecules and has potential application in biomaterial detection.

A terahertz meta-sensor array for 2D strain mapping

Large-scale stretchable strain sensor arrays capable of mapping two-dimensional strain distributions have gained interest for applications as wearable devices and relating to the Internet of Things. However, existing strain sensor arrays are usually unable to achieve accurate directional recognition and experience a trade-off between high sensing resolution and large area detection. Here, based on classical Mie resonance, we report a flexible meta-sensor array that can detect the in-plane direction and magnitude of preloaded strains by referencing a dynamically transmitted terahertz (THz) signal. By building a one-to-one correspondence between the intrinsic electrical/magnetic dipole resonance frequency and the horizontal/perpendicular tension level, arbitrary strain information across the meta-sensor array is accurately detected and quantified using a THz scanning setup. Particularly, with a simple preparation process of micro template-assisted assembly, this meta-sensor array offers ultrahigh sensor density (~11.1 cm−2) and has been seamlessly extended to a record-breaking size (110 × 130 mm2), demonstrating its promise in real-life applications.

Bearing fault feature extraction based on MOMEDA and CS-Wood–Saxon stochastic resonance

Since rolling bearing is of great significance to ensure the safe and stable operation of rotating machinery, bearing fault feature extraction then demonstrates a hot topic of general interest in industry. In this work, we applied Multipoint Optimal Minimum Entroy Deconvolution Adjusted preprocessing algorithm to deal with the large amount of background noise containing in the collected bearing fault original signal. Then, the Wood–Saxon stochastic resonance nonlinear system model is adopted to solve the bearing fault feature extraction problem, which avoids the frequency interval and system parameters disadvantages in bistable stochastic resonance system. Furthermore, the parameter step and scale transform factor in the Wood–Saxon stochastic resonance nonlinear system is optimized adaptively by Cuckoo Search algorithm, in which way the output signal-to-noise of bearing fault signal is improved significantly. Therefore, the bearing fault feature can be extracted more effectively compared with the classical bistable stochastic resonance system model. Simulation and examples demonstrated that the proposed method can effectively reduce the noise in the signal and enhance the weak feature in bearing fault signal, so as to realize the accurate early bearing fault diagnosis.

Unveiling the principles of stochastic resonance and complex potential functions for bearing fault diagnosis

This paper introduces a novel and complex Unsaturated Piecewise Linear Quad-Stable Stochastic Resonance System (UPLQSR) to address the issue of output saturation in the Classical Quad-Stable Stochastic Resonance (CQSR) system. By linearizing the structure of the potential function, the constraints imposed by high-order terms are effectively eliminated, allowing Brownian particles to move more freely. Numerical simulations demonstrate that UPLQSR achieves significantly higher output signal amplitudes compared to CQSR, highlighting its remarkable signal amplification capability. By analyzing the structure of the potential function, the relationship between the height of the potential barrier and the aggressiveness of the particles jumping is determined. Utilizing adiabatic approximation theory, the paper derives the Steady-state Probability Density (SPD), Mean First Passage Time (MFPT), and Spectral Amplification (SA), revealing the specific process of the particle jumping, as well as the influence of the parameters on the performance of the UPLQSR. After optimizing parameters using the Adaptive Genetic Algorithm (GA), UPLQSR is applied to the early fault diagnosis of various bearing models under Gaussian white noise, demonstrating superior fault detection capabilities. In summary, this study pioneered the theory of non-saturation of quad-stable systems, optimized the weak signal detection technique, and provided a more accurate means of signal identification and analysis, highlighting its great value of application in engineering.

Mode-entangled resonance for lamb waves in a plate

We report a novel resonance phenomenon called the mode-entangled resonance. It can occur at a specific frequency in a plate carrying both symmetric and antisymmetric Lamb wave modes. We show that at this resonance, a symmetric or antisymmetric Lamb wave can be fully transmitted with its mode preserved from one plate to another through a matching plate geometrically misaligned with the two base plates. This phenomenon appears to be counter-intuitive because both symmetric and antisymmetric waves are generally formed in the reflected and transmitted wave fields when the misaligned plate is used as a matching plate. Our analysis shows that if both symmetric and antisymmetric Lamb wave modes at the resonance are entangled in the misaligned matching plate to satisfy the established phase matching condition, the matching plate fully transmits any wave mode across the two base plates. The discovered phenomenon is related to the classical Fabry-Perot resonance (FPR), but FPR is only applicable for single-mode transmission through a matching plate aligned with two base plates. Numerical and experimental results were presented to validate the discovered mode-entangled resonance phenomenon. Furthermore, we show that the discovered phenomenon can be used for super-amplification of the amplitude of the antisymmetric Lamb wave when it is excited by plate-surface-mounted patch transducers.

A pulser R&D for the HEPS booster bumper magnet

The High Energy Photon Source (HEPS) is a fourth generation photon source, including a storage ring, a booster ring and a Linac. Due to the small dynamic aperture of the storage ring, a novel on-axis swap-out injection scheme was chosen. Here, the 6GeV booster acts as an accumulating ring during that injection process. To extract 6 GeV beam from the booster before injection into the storage ring, four slow bumper magnets are applied to assist the extraction kicker to accomplish. The bumper pulse magnetic field waveform is a half-sine wave with 1ms pulse bottom width. Depending on the simulation and test, a classic LC resonance circuit topology with IGBT switching in series with fast recovery diodes is adopted. In addition, an energy recycle circuit and capacitor charging circuit are designed, to decrease power loss and reduce the influence on the output pulse current waveform during the capacitor re-charge process. A pulsed power supply prototype has been completed, and the testing results show that the bumper pulser can fully meet the all requirements of HEPS booster high energy extraction system.

Enhanced fault diagnosis via stochastic resonance in a piecewise asymmetric bistable system.

Weak fault signals are often overwhelmed by strong noise or interference. The key issue in fault diagnosis is to accurately extract useful fault characteristics. Stochastic resonance is an important signal processing method that utilizes noise to enhance weak signals. In this paper, to address the issues of output saturation and imperfect optimization of potential structure models in classical bistable stochastic resonance (CBSR), we propose a piecewise asymmetric stochastic resonance system. A two-state model is used to theoretically derive the output signal-to-noise ratio (SNR) of the bistable system under harmonic excitations, which is compared with the SNR of CBSR to demonstrate the superiority of the method. The method is then applied to fault data. The results indicate that it can achieve a higher output SNR and higher spectral peaks at fault characteristic frequencies/orders, regardless of whether the system operates under fixed or time-varying speed conditions. This study provides new ideas and theoretical guidance for improving the accuracy and reliability of fault diagnosis technology.

Stochastic resonance in Hindmarsh-Rose neural model driven by multiplicative and additive Gaussian noise

This paper investigates the occurrence of stochastic resonance in the three-dimensional Hindmarsh-Rose (HR) neural model driven by both multiplicative and additive Gaussian noise. Firstly, the three-dimensional HR neural model is transformed into the one-dimensional Langevin equation of the HR neural model using the adiabatic elimination method, and the effects of HR neural model parameters on the potential function are analyzed. Secondly the Steady-state Probability Density (SPD), the Mean First-Passage Time (MFPT), and the Signal-to-Noise Ratio (SNR) of the HR neural model are derived, based on two-state theory. Then, the effects of different parameters (a, b, c, s), noise intensity, and the signal amplitude on these metrics are analyzed through theoretical simulations, and the behavior of particles in a potential well is used to analyze how to choose the right parameters to achieve high-performance stochastic resonance. Finally, numerical simulations conducted with the fourth-order Runge–Kutta algorithm demonstrate the superiority of the HR neural model over the classical bistable stochastic resonance (CBSR) in terms of performance. The peak SNR of the HR neural model is 0.63 dB higher than that of the CBSR system. Simulation results indicate that the occurrence of stochastic resonance occur happens in HR neural model under different values of parameters. Furthermore, under certain conditions, there is a ‘suppress’ phenomenon that can be produced by changes in noise, which provides great feasibilities and practical value for engineering application.

Design and analysis of an electromagnetic energy conversion device

In this study,we introduces an innovative device designed for wave-heat-electricity conversion, incorporating a classical split-ring resonator (SRR) and a Bi2Te3 semiconductor strip. This configuration is adept at absorbing electromagnetic energy, transforming it into thermal energy, and facilitating an electrical response. The paper delves into the detailed physical modeling and operational principles of the device. We begin by employing an equivalent circuit model to analyze the SRR's transmission characteristics and its temperature response under specific conditions. The investigation further extends to examining how structural dimensions and material properties affect the development of a local hotspot, leading to the refinement of the SRR resonant unit. We then integrate a Bi2Te3 semiconductor strip beneath this hotspot, enhancing the device's conversion capabilities. Our findings indicate an absorption efficiency of 0.085 at 2.45 GHz, a remarkable thermal conversion efficiency of 172.8 °C/W, and an electrical conversion efficiency of 0.195 mV/°C, all measured at an input power of 7 W. This research not only demonstrates the efficacy of the proposed device in wave-heat-electricity conversion but also provides a comprehensive reference for future advancements in this field.

Effects of time delay on the collective behavior of globally coupled harmonic oscillators with fluctuating frequency

In the viscoelastic environment, coupling forces between particles often play an essential role. Due to the time delay in the transmission of coupling forces, this paper focuses on investigating the effects of time delay on the collective behaviors of coupled harmonic oscillators, including synchronization, stability, and stochastic resonance. Firstly, we establish a time delay decoupling formula that can complete the accurate solution of the model under a large delay, thus breaking the limitation of previous small delay approximation methods. Secondly, the statistical synchronization between particles is derived, which means the mean-field behavior of the system can be studied through single-particle behavior. Thirdly, the system’s stability condition is given, demonstrating that the stability region expands with increasing time delay. Finally, the output response amplitude gain of the system is obtained, and then the stochastic resonance behavior of the system is studied. In the small delay region, noise competes with the ordered driving force, resulting in the classical stochastic resonance (CSR) behavior consistent with previous research findings. In the large delay region, periodic matching between the time delay and driving frequency gives rise to parameter-induced stochastic resonance (PSR) behavior, which has not been observed in previous studies.

Multi-dimensional hybrid potential stochastic resonance and application of bearing fault diagnosis

Stochastic resonance is a method to enhance weak signal by using noise, which has a wide range of applications in weak signal detection. In order to further investigate the application of multi-dimensional coupling stochastic resonance in practical engineering, a Multi-dimensional Double connection coupling Hybrid Potential Stochastic Resonance (MDHPSR) system is proposed in this paper. Firstly, the potential functions of bi-stable and tri-stable are briefly described, and the tri-stable system having a higher output amplitude. Secondly, the effect of different coupling methods on the output of the central and adjacent coupling ends are studied, and the output amplitude of double connection coupling is higher. Then, the double connection coupling of different potential functions is studied, and MDHPSR system effect is the best. Compared with Multi-dimensional Double connection Classical Bi-stable Stochastic Resonance (MDCBSR) system, MDHPSR system has better anti-noise performance. Finally, applying the two multi-dimensional coupling systems to bearing fault diagnosis, MDHPSR system output amplitude is higher and the Signal-to-Noise Ratio (SNR) is improved by more than 3 dB. This demonstrates the superior performance of MDHPSR system for weak signal detection and the value of the multi-dimensional coupling system for practical engineering applications.

Investigation of the orifice flow of over-the-rotor liner and its interaction with the rotor flow field

The emergence of ultra-high bypass ratio engines calls for advanced noise control technology. A promising technology is installing the acoustic liner at the casing over the rotor (OTR), forming the so-called OTR liner. Experiments have shown that this treatment could compensate for the reduced noise absorption due to the shortened intake length. Compared with the conventional liner receiving a pure acoustic pressure excitation, the OTR liner is exposed to the combined aerodynamic pressure perturbance and high acoustic pressure excitation, leading to complex flow mechanisms in the liner orifices. In this work, the large-eddy simulation method is used to investigate the flow phenomenon of OTR liner where each liner orifice is explicitly modeled to capture the flow behaviors at the blade tip proximity. Interesting findings are as follows: first, OTR liner orifices have an asynchronous dynamic response with a phase lag corresponding to the blade traversing speed; second, oscillating flow, resembling that in a classical Helmholtz resonator, is formed in the upstream liner orifices, while a bias flow appears in the downstream liner orifices. The dramatically different flow behaviors lead to non-uniform energy dissipation among orifices, implying the uniform impedance assumption in conventional acoustic liner definition fails when installing the liner near the rotor blade. Results also show that the orifice flow interacts with the blade tip leakage flow, affecting the development of the tip leakage vortex that may impact the rotor–stator interaction noise.

Piecewise time-delay tri-stable stochastic resonance system and its application in bearing fault diagnosis

Current studies of time-delay based systems are compared to classical tri-stable stochastic resonance (CTSR) system and do not reflect the effect of adding a delay term on unsaturated systems. In this paper, a piecewise delayed tri-stable stochastic resonance (PTTSR) system is proposed. Firstly, the equivalent Langevin for PTTSR system is derived and compared with the output of CTSR and piecewise tri-stable stochastic resonance (PTSR) systems, where the addition of the time-delay term can further improve the output amplitude. Secondly, mean first pass time (MFPT) and output signal-to-noise ratio (SNR) are derived, and the effects of different parameters on MFPT and SNR are investigated. increasing the feedback intensity and time-delay length improved the output SNR. Then, the input period signal is then numerically simulated using the signal-to-noise ratio gain (SNRG) as a measurement, which increases by 2.75 dB for PTTSR system compared to PTSR system. Finally, the three systems are used for bearing fault detection and the system parameters are optimized by genetic algorithm. The results showed that the output amplitude of PTTSR system is more than 12 times that of PTSR system and the SNRG increased by more than 2 dB. This demonstrates the superior performance of PTTSR system in detecting weak signals and provides good feasibility in engineering applications.