Stochastic resonance in coupled underdamped bistable systems

Ultrasound generation in water via quasi-periodically snapping polymeric core-shell micro-bead excited with radiowaves

This work reports the results of a theoretical and numerical study showing the occurrence of stochastically resonating bistable dynamic in polymeric micro-bead of sub-micrometric size with stiff core and soft shell. The system, submerged in water, is excited with a pulsed laser working in the Mega-Hertz frequency range and tuned to match both an optical and acoustic resonance of the system. The laser interacts with the carbon nanotubes embedded in the shell of the polymeric micro-bead generating heat. The concurrent action of the generated heat with the standing acoustic oscillations, gives rise to a stochastically resonating bistable system. The system in fact is forced to switch between two states (identifiable with the creation and organized disruption of a quasi-hexagonal tessellation) via a snap-through-buckling mechanism. This phenomenon results in the unprecedented generation of pressure oscillations. These results open the way to develop a new type of core-shell micro-transducers for radioacoustic imaging applications able to work in the Mega-Hertz frequency range. From a more general thermodynamic perspective, the reported mechanism shows a remarkable periodicity and energy conversion efficiency.

Spontaneous Synchronization of Two Bistable Pyridine-Furan Nanosprings Connected by an Oligomeric Bridge

The intensive development of nanodevices acting as two-state systems has motivated the search for nanoscale molecular structures whose long-term conformational dynamics are similar to the dynamics of bistable mechanical systems such as Euler arches and Duffing oscillators. Collective synchrony in bistable dynamics of molecular-sized systems has attracted immense attention as a potential pathway to amplify the output signals of molecular nanodevices. Recently, pyridine-furan oligomers of helical shape that are a few nanometers in size and exhibit bistable dynamics similar to a Duffing oscillator have been identified through molecular dynamics simulations. In this article, we present the case of dynamical synchronization of these bistable systems. We show that two pyridine-furan springs connected by a rigid oligomeric bridge spontaneously synchronize vibrations and stochastic resonance enhances the synchronization effect.

Impact fault detection of gearbox based on variational mode decomposition and coupled underdamped stochastic resonance

In the gear fault diagnosis, the emergence of periodic impulse components in vibration signals is an important symptom of gear failure. However, heavy background noise makes it difficult to extract the weak periodic impulse features. Therefore, the paper presents an impact fault detection method of gearbox by combining variational mode decomposition (VMD) with coupled underdamped stochastic resonance (CUSR) to extract the periodic impulse features. First, the adaptive VMD is presented to decompose the vibration signal into several intrinsic mode functions (IMFs), which can automatically determine the appropriate mode number according to the correlation kurtosis (CK) of decomposition results and extract the sensitive IMF component containing the main fault information. Next, the adaptive CUSR method is developed to analyze the selected sensitive IMF component, and the optimal system parameters are obtained by the genetic algorithm using the CK index as optimization objective function. Finally, the periodic impulse features are extracted by the output signal of CUSR system accurately. Experiments and engineering application verify the effectiveness and superiority of the proposed adaptive VMD-CUSR method for extracting the periodic impulse features in gear fault diagnosis compared to other methods.

Stochastic resonance and bifurcations in a harmonically driven tri-stable potential with colored noise

Stochastic resonance (SR) and stochastic bifurcations are investigated numerically in a nonlinear tri-stable system driven by colored noise and a harmonic excitation. The power spectral density, signal-to-noise ratio, stationary probability density (SPD), and largest Lyapunov exponent (LLE) are calculated to quantify SR, P-bifurcation, and D-bifurcation, respectively. The effects of system parameters, such as noise intensity and correlation time, well-depth ratio, and damping coefficient, on SR and stochastic bifurcations are explored. Numerical results show that both noise-induced suppression and SR can be observed in this system. The SPD changes from bimodal to trimodal and then to the unimodal structure by choosing well-depth ratio, correlation time, and noise intensity as bifurcation parameters, which shows the occurrence of stochastic P-bifurcation. The stochastic D-bifurcation is found through the calculation of LLE. Moreover, the relationship between SR and stochastic bifurcation is explored thoroughly. It indicates that the optimal SR occurs near D-bifurcation and can be realized with weak chaos by adjusting the proper parameters. Finally, the tri-stable energy harvester is chosen as an example to show the improvement of the system performance by exploiting SR and stochastic bifurcations.

RF Spectrum Sensing Based on an Overdamped Nonlinear Oscillator Ring for Cognitive Radios

Existing spectrum-sensing techniques for cognitive radios require an analog-to-digital converter (ADC) to work at high dynamic range and a high sampling rate, resulting in high cost. Therefore, in this paper, a spectrum-sensing method based on a unidirectionally coupled, overdamped nonlinear oscillator ring is proposed. First, the numerical model of such a system is established based on the circuit of the nonlinear oscillator. Through numerical analysis of the model, the critical condition of the system’s starting oscillation is determined, and the simulation results of the system’s response to Gaussian white noise and periodic signal are presented. The results show that once the radio signal is input into the system, it starts oscillating when in the critical region, and the oscillating frequency of each element is f_o/N, where f_o is the frequency of the radio signal and N is the number of elements in the ring. The oscillation indicates that the spectrum resources at f_o are occupied. At the same time, the sampling rate required for an ADC is reduced to the original value, 1/N. A prototypical circuit to verify the functionality of the system is designed, and the sensing bandwidth of the system is measured.

Absolute negative mobility induced by potential phase modulation

We investigate the transport properties of a particle subjected to a deterministic inertial rocking system, under a constant bias, for which the phase of the symmetric spatial potential used is time modulated. We show that this modulated phase, assisted by a periodic driving force, can lead to the occurrence of the so-called absolute negative mobility (ANM), the phenomenon in which the particle surprisingly moves against the bias. Furthermore, we discover that ANM predominantly originates from chaotic-periodic transitions. While a detailed mechanism of ANM remains unclear, we show that one can manipulate the control parameters, i.e., the amplitude and the frequency of the phase, in order to enforce the motion of the particle in a given direction. Finally, for this experimentally realizable system, we devise a two-parameter current plot which may be a good guide for controlling ANM.

Collective dynamics of a network of ratchets coupled via a stochastic dynamical environment

We investigate the collective dynamics of a network of inertia particles diffusing in a ratchet potential and interacting indirectly through their stochastic dynamical environment. We obtain analytically the condition for the existence of a stable collective state, and we show that the number N of particles in the network, and the strength k of their interaction with the environment, play key roles in synchronization and transport processes. Synchronization is preceded by symmetry-breaking associated with double-resonance oscillations and is shown to be strongly dependent on the network size: convergence to the synchronization manifold occurs much faster with a large network. For small networks, increasing the noise level enhances synchronization in the weakly coupled regime, while particles in a large network are weakly synchronized. Similarly, in the strongly coupled regime, particles in a small network are weakly synchronized; whereas the synchronization is strong and robust against noise when the network-size is large. Small and moderate networks maximize and stabilize efficient transport. Although the dynamics for larger networks is highly correlated, the transport current is erratic.