Resonant System Research Articles

Fault feature extraction method of rolling bearings based on coupled resonance system with vibrational resonance-assisted enhanced stochastic resonance

Stochastic resonance (SR), as a signal processing method that is able to use noise to enhance weak periodic signals, provides effective technical support for the detection of weak signals. However, due to the constraints of potential functions or control means, the detection results of a single SR system on weak signals often fails to achieve the desired effect. Through the interaction between different subsystems, SR under the action of multiple systems can obtain rich dynamic response characteristics and improve the detection ability of weak signals. Therefore, this paper proposes a fault feature extraction method of rolling bearings based on a coupled resonance system with vibrational resonance (VR)-assisted enhanced SR. First, a SR system based on a matched steady-state potential model is constructed, which has the ability to alleviate the phenomenon of output saturation to some extent compared with the classical bistable SR. Second, inspired by the synergy of multiple systems, a coupled resonance system with VR-assisted enhanced SR is constructed by combining VR control and SR control, which has the dual advantages of VR and SR and performs well in weak signal detection. Finally, simulation experiment and fault data of rolling bearings are adopted to analyze the suggested method, and the comparison results with other SR methods verify its practicality and superiority.

Recursive Neural Network as a Multiple Input–Multiple Output Speed Controller for Electrical Drive of Three-Mass System

Electrical drive systems are commonly applied for the mechanisms of precise movement, where having a high-quality position and high-quality speed control is especially valuable. Very often, the mechanical part of these systems reveals resonant properties that are related to the limited stiffness of the interconnection between subsequent parts of the mechanism. In most cases, this sort of system may be described as a model of several linked masses. If only the structure of the mechanical part is known and the corresponding parameters are constant and identified, the demanded control quality may be obtained using a properly tuned ADRC or PID controller equipped with appropriate anti-resonance filtration. However, if the parameters of the mechanical part are variant, adaptive control may be considered as a solution. In this paper, artificial neural network (ANN) is considered to be a speed controller and its training method assures adaptation to the unknown mechanical parameters. The paper is particularly focused on a three-mass system, which possesses, due to its structure, two resonant frequencies. The unique property of the analyzed system is the application of drive units at both ends of the system, so that the controller has the ability to influence the resonant system from both sides. The coordination of the drive unit is performed by the aforementioned ANN, from which two outputs affect the drive units independently. The derivation of the mathematical model is followed by its implementation in a computer simulation and finally the evaluation in a dedicated laboratory setup, the construction of which is also presented in the paper.

Research on dual‐coupled wireless power transfer system for cardiac pacemaker based on integrated coils

SummaryIn order to reduce the implantation volume and improve the transmission efficiency of the magnetically coupled resonant wireless power transfer system for cardiac pacemakers, a dual‐coupled wireless power transfer system for cardiac pacemakers that integrates a compensation coil into the main coil was designed. First, the mutual inductance equivalent model of the dual‐coupled wireless power transfer system was established and the impedance matching parameters were solved. The double‐sided inductor–capacitor–inductor (DS‐LCL) circuit simulation model considering the equivalent series resistance was established with MATLAB. The influence of different inductance ratios on the output power and transfer efficiency of the system was analyzed in the range of 200–300 kHz, and the system parameters for optimal transfer efficiency were determined. Second, the compensation coil on the same side was naturally decoupled by changing the aspect ratio of the compensation coil. The magnetic field distribution between the internally integrated dual‐coupled structure proposed in this paper and the conventional integrated structure was compared using COMSOL, and the safety assessment of the system was conducted, considering parameters such as temperature rise and specific absorption rate. Finally, an experimental platform was established to verify the system's output performance and safety. The results showed that compared with conventional integrated structures, the proposed integrated structure increased the output power by 0.229 W and transmission efficiency by 10.08% at a transmission distance of 8 mm. The maximum temperature rise is 1.9°C.

Multi frequency weak signals detection based on under-sampling bistable stochastic resonance

Signal detection has a wide range of practical applications. Compared with traditional weak signal detection, the nonlinear effect of noise in the bistable system is typical and easy to extend, so bistable stochastic resonance detection technique has a wider applicability. In this paper, the multi-frequency weak signals detection based on under-sampling bistable stochastic resonance is studied. Based on the theory of bistable stochastic resonance, a simulation model is established to simultaneously detect multiple low-frequency weak signals. The spectrum of input and output signals is obtained through numerical simulation calculation, and the system characteristics are analyzed. When the large parameter signal does not meet the adiabatic approximation theory, the appropriate sampling coefficient can be selected to directly under-sample the input signal to make it conform to the conditions, and then the scale inverse transformation can be carried out. Finally, combined with the simulation analysis, the correctness of the under-sampling bistable stochastic resonance system to detect the multi-frequency weak signals is verified, the sampling rate is reduced, and the complexity is effectively decreased.

Statistical complexity and stochastic resonance of an underdamped bistable periodic potential system excited by Lévy noise

This paper focuses on the underdamped bistable potential system's stochastic resonance (SR) phenomenon under Lévy noise excitation. The statistical complexity of the system is analyzed under the changes of damping factor, amplitude and frequency of the periodic signal, stability index and skew parameter of Lévy noise, and the effects of the changes of above parameters on SR are investigated. The results show that the increase of the damping factor hinders the appearance of SR phenomenon; the larger amplitude and lower frequency of the periodic signal are beneficial to the appearance of SR; the larger stability index of the noise parameter, the more likely SR occurs, and the change of the skew parameter has little effect on the SR. Because the Bandt-Pompe (B-P) algorithm is used in the information-theoretic measure to model the statistical complexity of this system, the robustness of the method is analyzed by changing the embedding dimension and the length of residual time interval sequence in the B-P algorithm. Finally, the mean first passage time of the particle is calculated as a function of the noise intensity and the noise-enhanced stability effect is found.

Multiple blast resistance enhancement through negative-mass meta-honeycombs with multi-resonator

Conventional honeycomb materials are difficult to resist multiple blast because the enormous energy generated by the explosion would cause plastic deformation of the material, which weakens the strength of the structure. In this paper, a novel meta-honeycomb is designed by adding local resonance system to hierarchical cells, which is based on the multi-resonator-enhanced bandgap property, to withstand multiple blast. This meta-honeycomb reverses the energy absorption mode of traditional honeycomb materials; that is, the energy absorption by plastic deformation of the material becomes the reflection of the stress wave through the equivalent negative mass property generated by the local resonance system, which significantly reduces the deformation of the material and the reaction force at the support under impact loads. In particular, for the secondary explosion loading, the maximum deformation of the meta-honeycomb is reduced by 74% compared with the traditional hierarchical honeycomb. Furthermore, it is demonstrated that the design of meta-honeycomb can be optimized by coupling the bandgap generated by the negative mass property, thereby improving the energy absorption efficiency. This research result provides a new concept for the design of blast-proof materials, which has a high potential for a wide range of engineering applications.

In situ resistivity measurement of metal surfaces to track down dislocations caused by high field conditioning

AbstractConditioning of a metal surface in a high-voltage system is the progressive development of resistance to vacuum arcing over the operational life of the system. This is relevant for accelerator cavities, where high level of performance is only achievable after a long conditioning period. Beyond the accelerator research field, this is an important topic for any technology where breakdowns can cause device failure, either by directly disrupting device operation or by causing cumulative hardware damage.We are developing a direct method to measure the surface resistivity of a metal surface that is being conditioned with a HV DC system by inducing a high frequency (GHz) radio-frequency current in the parallel-plate electrode system. If the system can function as a resonant cavity, the surface resistivity data would be encoded in its quality factor (Q-factor). The changes in the resistivity measured in cryogenic conditions would indicate a formation of dislocations under the surface, something that has been speculated as an important process behind the conditioning.In this paper, we present two modified designs of the electrode system, which will act as a resonant cavity, the results of 3D EM simulations and experimental results regarding the characterization of this resonant system.

A decouple-decomposition noise analysis model for closed-loop mode-localized tilt sensors

The development of mode-localized sensors based on amplitude output metrics has attracted increasing attention in recent years due to the potential of such sensors for high sensitivity and resolution. Mode-localization phenomena leverage the interaction between multiple coupled resonant modes to achieve enhanced performance, providing a promising solution to overcome the limitations of traditional sensing technologies. Amplitude noise plays a key role in determining the resolution of mode-localized sensors, as the output metric is derived from the measured AR (amplitude ratio) within the weakly coupled resonator system. However, the amplitude noise originating from the weakly coupled resonator’s closed-loop circuit has not yet been fully investigated. This paper presents a decouple-decomposition (DD) noise analysis model, which is applied to achieve high resolution in a mode-localized tilt sensor based on a weakly coupled resonator closed-loop circuit. The DD noise model separates the weakly coupled resonators using the decoupling method considering the nonlinearity of the resonators. By integrating the decoupled weakly coupled resonators, the model decomposes the weakly coupled resonator’s closed-loop circuit into distinct paths for amplitude and phase noise analyses. The DD noise model reveals noise effects at various circuit nodes and models the system noise in the closed-loop circuit of the weakly coupled resonators. MATLAB/Simulink simulations verify the model’s accuracy when compared to theoretical analysis. At the optimal operating point, the mode-localized tilt sensor achieves an input-referred instability of 3.91 × 10-4° and an input-referred AR of PSD of 2.01 × 10-4°⁄√Hz using the closed-loop noise model. This model is also applicable to other varieties of mode-localized sensors.

Philosophy of Body: Embodiment, Perception, and Understanding Other Minds

The lived body, as an embodied self, lives, breathes, perceives, acts and reasons (Drew Leder, 1990, 1-8). The imaginative, with its schematic structures, has a role in thought (Lakoff, 1987, 275; Johnson 1987, 76,) even as we show preference for the biological and psychological turn. The problem of other minds is about how we come by the power to understand other people, comprehend their behaviours, know their intentions, and discern their mental processes. In the Husserlian phenomenology, we come to know and recognize the other through bodily movement. The kinaesthetic experience of having a grip on its surrounding world leads the ego into the knowledge and recognition of the other (Husserl, 1937, 16, § 62). We can take this kinaesthetic experience of knowing the other through motor behaviour farther. Following an empathic understanding that comes from our shared motor resonance system, we understand others when their motor behaviour is put in a narrative framework (Gallagher, 2006). We admit, as Gallagher does, that neither a “cold theoretical logic” (of folk psychology ) nor a “self-controlled simulation” (of simulation theory ) replaces the powers associated with the primary- and secondary inter-subjectivity that attend the way we interact with others, first as babies and later as children (Gallagher, 2006, 12).

Full-scale resonant bending fatigue testing of casing joints under bending moment load

The quality and reliability of oil casings play a pivotal role in the safety and efficiency of offshore oil and gas exploration. This study conducted research on resonant bending fatigue of 9-5/8-inch casing joints and established a systematic theoretical model for resonant bending fatigue based on the Euler–Bernoulli beam equation. The relationships between parameters affected by frequency and mode shape functions were deduced and solved to analyze the influence of wall thicknesses, length and weights at both ends of the specimen on the natural frequency of the resonant bending fatigue system. A full-scale fatigue test was then designed and conducted to investigate the circumferential stress distribution, reveal the stress amplitude–frequency response characteristics of the specimen, and explore resonance response behaviors under different excitation forces. This was done to establish a method for evaluating the oil casing life and obtain fatigue life characteristic curves of the specimen. A finite element model was employed to analyze the internal stress distribution of the coupling under bending moment load, considering the influence of material properties, thread lead angle and non-linear contact on casing joints. Finally, the fatigue life algorithm was summarized and compared by integrating the stress simulation results with the material properties of the specimen, elucidating the fatigue damage evolution process of casing joints. This research provides a significant engineering reference value for structural design optimization, fatigue testing and life analysis of oil casing threaded joints.

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.

A cascaded piecewise unsaturated asymmetric under-damped tri-stable stochastic resonance system and its application in bearing fault diagnosis

A cascaded piecewise unsaturated asymmetric under-damped tri-stable stochastic resonance system and its application in bearing fault diagnosis

On the Fourier Analysis of the Einstein–Klein–Gordon System: Growth and Decay of the Fourier Constants

We consider the (1+3)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$(1+3)$$\\end{document}-dimensional Einstein equations with negative cosmological constant coupled to a spherically symmetric, massless scalar field and study perturbations around the anti-de Sitter spacetime. We derive the resonant systems, pick out vanishing secular terms and discuss issues related to small divisors. Most importantly, we rigorously establish (sharp, in most of the cases) asymptotic behaviour for all the interaction coefficients. The latter is based on uniform estimates for the eigenfunctions associated to the linearized operator as well as on some oscillatory integrals.

Reinforcement learning optimisation for graded metamaterial design using a physical-based constraint on the state representation and action space

The energy harvesting capability of a graded metamaterial is maximised via reinforcement learning (RL) under realistic excitations at the microscale. The metamaterial consists of a waveguide with a set of beam-like resonators of variable length, with piezoelectric patches, attached to it. The piezo-mechanical system is modelled through equivalent lumped parameters determined via a general impedance analysis. Realistic conditions are mimicked by considering either magnetic loading or random excitations, the latter scenario requiring the enhancement of the harvesting capability for a class of forcing terms with similar but different frequency content. The RL-based optimisation is empowered by using the physical understanding of wave propagation in a such local resonance system to constrain the state representation and the action space. The procedure outcomes are compared against grading rules optimised through genetic algorithms. While genetic algorithms are more effective in the deterministic setting featuring the application of magnetic loading, the proposed RL-based proves superior in the inherently stochastic setting of the random excitation scenario.

Weak fault feature extraction of rolling bearing based on multi-system coupled cascaded stochastic resonance system

The accurate extraction of weak signal features under strong noise background plays a crucial role in the fault detection of rolling bearings. In order to promote the ability of stochastic resonance (SR) system to detect weak signals and improve the output performance of the system, a multi-system coupled cascaded SR (MCCSR) system is investigated and applied to the fault detection of rolling bearings. Firstly, a MCCSR system is constructed by exploiting the positive synergistic effect between multiple systems, which consists of a triangular-topology coupled system composed of three SR subsystems and a cascaded SR system with topology output as input. This system makes full use of the advantages of coupled system and cascaded system in weak signal detection. In terms of parameter optimization, a stepwise multi-parameter optimization strategy is proposed, which adopts different optimization methods for different parameters, and avoids the inconsistency between error and step factor by improving the least mean square algorithm. Finally, through the comparative analysis of numerical simulation and experimental signals, it is verified that the proposed method can effectively enhance the weak signal features and improve the system output signal-to-noise ratio, which can better serve for rolling bearing fault detection.

A Novel Two-Dimensional Quad-Stable Stochastic Resonance System for Bearing Fault Detection

A novel two-dimensional Quad-stable stochastic resonance (NTDQSR) system is proposed in this paper to address the poor signal detection capability of the original one-dimensional Quad-stable stochastic resonance (ODQSR) system. Firstly, expressions for the equivalent potential function and the steady-state probability density (SPD) function of the system are derived to study the impact of parameters on it. Secondly, the system is simulated numerically, and the performance of NTDQSR system is evaluated under trichotomous noise in this paper, because trichotomous noise exists widely in practical applications. Finally, the genetic algorithm (GA) is used to optimize the system parameters, and NTDQSR system is applied to bearing fault detection. In LDK UER204 ring fault detection, MSNRG in NTDQSR system is 0.9927 dB and 0.4805 dB higher than ODQSR and under-damped Quad-stable stochastic resonance (UQSR) system. In the outer ring experiment on the experimental bench at CWRU, MSNRG in NTDQSR system is 0.7255dB and 0.0734dB higher than the other two systems, while in the inner ring experiment, MSNRG is 0.6535dB and 0.1943dB higher than the other two systems, respectively. NTDQSR system is compared with ODQSR and UQSR systems to verify the good application value of NTDQSR system in practical engineering.

4FSK signal processing based on adaptive tristable stochastic resonance under levy noise

Aiming at the problem of low quality of coherent demodulation transmission signal of digital signal in the background of Levy noise, this paper proposes a new method of 4FSK signal reception based on adaptive tristable stochastic resonance (SR) system. The bit error rate (BER) of output signals of adaptive tristable SR system model and the traditional modulation model are compared by simulation. The numerical simulation results show that compared with the traditional model, the output BER of the 4FSK signal after demodulation of the adaptive tristable SR system model is reduced by 4% compared with the traditional model. The time domain image of 4FSK signal is clearer, the burrs are significantly reduced and the spectral amplitude of 4FSK signal is greatly improved. The success of this experiment suggests a strong promise of SR systems for digital signal detection in impact noise.

MEMS Electrostatically Driven Coupled Beam Filter Banks.

MEMS bandpass filters based on electrostatically driven, mechanically coupled beams with in-plane motion have been demonstrated up to the VHF band. Filters higher than second order with parallel plate drives have inherent tuning difficulties, which may be resolved by adding mass-loaded beams to the ends of the array. These beams deflect for DC voltages, and thus allow synchronized electrostatic tuning, but do not respond to in-band AC voltages and hence do not interfere with dynamic synchronization. Additional out-of-band responses may be damped, leaving the desired response. The principle is extended here to close-packed banks of filters, with adjacent arrays sharing mass-loaded beams that localize modes to sub-arrays. The operating principles are explained using a lumped element model (LEM) of the equations of motion in terms of resonant modes and the reflection of acoustic waves at discontinuities. Performance is simulated using the LEM and verified using the more realistic stiffness matrix method (SMM) for banks of up to eight filters. Similar or dissimilar filters may be combined in a compact arrangement, and the method may be extended to higher order resonances and alternative coupled resonator systems.

Dual-channel two-dimensional stochastic resonance and its application in bearing fault detection under alpha-stable noise

Coupled two-dimensional stochastic resonance (CTDSR) systems exhibit a higher quantity of steady-states and hold significant theoretical and practical value. However, the coupling between nonlinear systems generates multiplicative noise, which impairs signal transmission. In this paper, a novel dual-channel two-dimensional stochastic resonance (DCTDSR) model is proposed to harness multiplicative noise for enhancing system output. It is evident from the potential well analysis that multiplicative noise causes variations in the properties and amounts (from 2 to 4) of resonance peaks in the DCTDSR system. The steady-state probability density (SPD) of the novel system is derived by implementing the adiabatic approximation theory. In the background of alpha-stable noise, simulation results indicate that the DCTDSR system exhibits heightened detection capabilities for weak signals that are immersed in severe impulsive and heavy-tailed noise. Based on the stability of alpha-stable noise, an adaptive stochastic resonance fault diagnosis method that adjusts both parameters and multiplicative noise is designed to overcome the issue of insufficient single energy regulation. Experimental results have demonstrated that the DCTDSR system boosts noise energy transmission and offers improved bearing fault detection accuracy. Thus, effectively utilizing multiplicative alpha-stable noise can further enhance the practical applicability of stochastic resonance theory in engineering.

A Measurement Method of Power Transferred to an Electric Vehicle Using Wireless Charging.

The increasing number of zero-emission vehicles on the roads demands novel vehicle charging solutions that ensure convenience, safety, increased charging infrastructure availability, and aesthetics. Wireless charging technology is seen as the one that could assure these desirable properties and could be applied not just in conventional implementations but also in off-grid solutions together with roadway energy harvesting systems. Both approaches require proper transfer of energy metering methods. In this paper, a method for measuring the power transferred to the load in a wireless charging system is presented, and its systematic error is assessed in the relevant range of influencing factors. The novelty of the method is that it does not require any metrologically certified measurement instrumentation on the receiver side of the wireless charging system. The error analysis is performed using a numerical simulation. Considered error-influencing factors included secondary side electrical load, coils' coupling coefficient and quality factor, current and voltage quantization resolution, and compensation topology type (serial-serial (SS) and serial-parallel (SP)). It was determined that the systematic error of the power assessment does not exceed 0.7% for SS and 1.1% for SP topologies when the coupling coefficient is in the range of 0.05 to 0.4 and the quality factor of the resonant system is in the range of 100 to 800.