Output Amplitude Research Articles

Weak signal detection method based on novel composite multistable stochastic resonance

The weak signal detection method based on stochastic resonance is usually used to extract and identify the weak characteristic signal submerged in strong noise by using the noise energy transfer mechanism. We propose a novel composite multistable stochastic-resonance (NCMSR) model combining the Gaussian potential model and an improved bistable model. Compared with the traditional multistable stochastic resonance method, all the parameters in the novel model have no symmetry, the output signal-to-noise ratio can be optimized and the output amplitude can be improved by adjusting the system parameters. The model retains the advantages of continuity and constraint of the Gaussian potential model and the advantages of the improved bistable model without output saturation, the NCMSR model has a higher utilization of noise. Taking the output signal-to-noise ratio as the index, weak periodic signal is detected based on the NCMSR model in Gaussian noise and α noise environment respectively, and the detection effect is good. The application of NCMSR to the actual detection of bearing fault signals can realize the fault detection of bearing inner race and outer race. The outstanding advantages of this method in weak signal detection are verified, which provides a theoretical basis for industrial practical applications.

Combined Underdamped Bistatic Stochastic Resonance for Weak Signal Detection and Fault Diagnosis under Wavelet Transform

A novel combined underdamped bistable stochastic resonance (CUBSR) is proposed in this paper. Under the noise-free condition, the output amplitude is used as a measurement index of classical bistable stochastic resonance (CBSR) and CUBSR, which demonstrate CUBSR does not have output saturation characteristics and has a more prominent signal enhancement capability. Then, the expressions of mean first-pass time (MFPT), steady-state probability density (SPD) and signal-to-noise ratio (SNR) are derived. Combined with the fourth-order Runge–Kutta algorithm and genetic algorithm (GA) for numerical simulations, the comparison of the theoretical derivation and numerical simulation of CUBSR can be verified. Then, the two systems are applied to the engineering application of bearing fault diagnosis. Finally, the multi-scale noise-modulated SR method based on wavelet packet transform is studied to overcome the limitation of traditional parameter modulation and to achieve SR detection at multiple frequencies. Simulation analysis and bearing fault diagnosis show that the method can effectively detect the multi-frequency weak signal submerged in noise, resulting in a significant enhancement in signal amplitude.

Frequency matching optimization model of ultrasonic scalpel transducer based on neural network and reinforcement learning

Aiming at the problem that the excitation frequency and resonant frequency of the transducer cannot keep synchronous, the output amplitude decreases and the vibration is unstable. In this study, the working principle of piezoelectric transducers is firstly analyzed by the equivalent circuit method and the instantaneous characteristic variables (installing preload, assembly preload, load, and other factors) that affect the frequency matching obtained to establish the equivalent relationship with the resonant frequency. Secondly, in order to make the synchronization between excitation frequency and resonance frequency, the key instantaneous characteristic variables are extracted based on Pearson correlation coefficient. Thirdly, the mathematical model of the mapping relationships between instantaneous characteristic variables and resonance frequency is established with the radial basis function neural network (RBFNN). Fourthly, for the purpose of the adaptation to the characteristics of dynamic load and real-time frequency modulation in the operation of ultrasonic scalpels, the reinforcement learning (Q-learning algorithm) and the weight vector of RBFNN are used to define the eligibility trace, which is used to dynamically adjust the RBFNN frequency matching optimization model in real time and maintain the “constant” amplitude output and stable harmonic response process. Finally, the experimental results show that, compared with the traditional methods, the frequency matching optimization model of ultrasonic scalpel transducer based on RBF neural network and Q-Learning reinforcement learning is effective, and the vibration amplitude of the transducer is increased by 15.25μm. The amplitude fluctuation is stable at 0.92μm. It can provide decision-making guidance for relevant engineering fields.

Power absorption of combined wind turbine and wave energy converter mounted on braceless floating platform

This work investigates the dynamic response and power absorption of a combined wind turbine and wave energy converter (WEC) mounted on a braceless semisubmersible floating platform. The floating platform consists of a Semi-submersible Wind turbine, a Wave energy converter Combination (SWWC) and a NREL 5-MW Current Source Converter (CSC) wind turbine. In this study, ANSYS/AQWA software is used in cooperation with a potential-based boundary element method (BEM) approach. The main targeted results include average power output and response amplitude of surge, heave and pitch motions of the combined concept at various wave and wind directions plus operational conditions. The numerical results are compared with experimental data, suggesting that the current numerical model predicts heave amplitude, average power, power take-off (PTO) damping force and response amplitude operator (RAO) of the platform motions with an acceptable agreement. Meanwhile, six environmental conditions (ECs) and five PTO damping coefficients are considered to optimize energy production. An optimal damping coefficient of 4000 kN s/m was found for the maximum average power generation for all the ECs. In addition, the effect of the wave/wind directions on the response motions and power absorption are obtained and presented.

A wind power curtailment reduction strategy using electric vehicles based on individual differential evolution quantum particle swarm optimization algorithm

A wind power curtailment consumption strategy using electric vehicles (EVs) based on individual differential evolution quantum particle swarm optimization algorithm (IDE-QPSO) is proposed, with the objective of reducing the system’s wind curtailment in order to further improve the wind power consumption rate while effectively reducing wind power output fluctuation and amplitude. EV aggregators act as charging tariff setters, releasing dynamic time-of-use tariffs (DTOU) for EV clusters to respond to based on wind curtailment data accounted for by the dispatch center. This method first establishes an electric vehicle charging load model based on the travel chain theory and residents’ travel rules, then establishes an EV users autonomous response model based on the sensitivity of electric vehicle users to the charging prices. Second, a multi-objective optimization function is established based on the aforementioned model, which integrates wind power curtailment consumption and minimizes wind power output fluctuation and amplitude, and it is solved using an improved quantum particle swarm optimization algorithm. Finally, adequate simulation experiments show that this strategy can effectively smooth out the fluctuation of wind power output and improve the wind power consumption rate.

On radiation dynamics in plasma relativistic microwave amplifier at the edge of electron beam pulse

We consider dynamics of radiation of a plasma microwave amplifier on a surface wave at the leading edge of the relativistic electron beam pulse. It has been shown that depending on the electron density of the plasma, different modes of operation of the amplifier are possible. At low plasma density, there is an early activation of the amplifier with large gain at the leading edge of the electron beam pulse and a significant decrease in the amplification of the signal when the electron energy reaches a plateau. With a higher plasma density, a later activation takes place with an almost constant output amplitude. The effect of ponderomotive force on plasmas was discussed.

Threshold Voltage Cancellation For Low Input Voltage of 65nm CMOS Rectifier of Energy Harvesting For Implantable Medical Devices in Telemedicine Embedded System

Telemedicine applications run at very low voltages, necessitating the use of a Great Precision Rectifier with high sensitivity to function at low input voltages. In this study, we used a 65 nm CMOS rectifier to achieve a 0.2V input voltage for Energy Harvesting Telemedicine application. The suggested rectifier, which has two-stage structure and operates at frequency of 2.4GHz, has been found to perform better in cases where the minimum operating voltage is lower than previously published papers, and the rectifier can operate over a wide range of low input voltage amplitudes. Full-Wave Fully gate cross-coupled Rectifiers (FWFR) CMOS Rectifier Efficiency at Freq of 2.4 GHz: With an input voltage amplitude of 2V, the minimum and maximum output voltages are 0.49V and 1.997V, respectively, with a peak VCE of 99.85 percent and a peak PCE of 46.86 percent. This enables the suggested rectifier to be used in a variety of vibration energy collecting systems, including electrostatic, electromagnetic, and piezoelectric energy harvesters. The proposed rectifier, which is built at 2.4GHz and has a two-stage structure, performs better in the event of low input voltage amplitude and has a lower minimum operation voltage than previously published papers. Full-wave fully gate cross-coupled rectifiers (FWFR) CMOS Rectifier Performance Summary at Freq of 2.4 GHz: With a 2V input voltage amplitude, the minimum and maximum output voltages are 0.49V and 1.997V, respectively, with a maximum VCE of 99.85% and a maximum PCE of 46.86%.

Influence of Power Supply Ripple on Injection Locking of Magnetron with Frequency Pushing Effect

The influence of anode voltage ripple on injection locking of a magnetron with frequency pushing effect has been studied systematically. Theoretical analysis shows that, when power supply ripple and injection ratio are constant, frequency pushing effect will increase the magnetron’s locking bandwidth. Meanwhile, the locking bandwidth decreases with the increase of power supply ripple. Thus, to achieve injection locking, both power supply ripple and frequency pushing effect must be considered. The experiment results show that at injection ratio μ of 0.003, frequency pushing effect at 0.5, and power supply ripple increases from 0% to 1% and 2.5%, the locking bandwidth of magnetron decreases by 0.32 MHz, 2.12 MHz. With the amplitude of ripple increasing, the spectrum after injection locking deteriorates, and output amplitude reduces, which verifies the theoretical analysis. Considering anode voltage ripple and frequency pushing effect, the research results contribute to the realization of high-quality output of injection locked magnetrons.

High Precision Low Input Voltage of 65nm CMOS Rectifier for Energy Harvesting using Threshold Voltage Minimization in Telemedicine Embedded System

Telemedicine applications run at very low input voltages, necessitating the use of Great Precision Rectifier with high sensitivity to function at low input voltages. In this study, we used a 65 nm CMOS rectifier to achieve a 0.2V input voltage for Energy Harvesting Telemedicine application. The suggested rectifier, which has two-stage structure and operates at frequency of 2.4GHz, has been found to perform better in cases where the minimum operating voltage is lower than previously published papers, and the rectifier can operate over a wide range of low input voltage amplitudes. Full-Wave Fully gate cross-coupled Rectifiers (FWFR) CMOS Rectifier Efficiency at Freq of 2.4 GHz: With an input voltage amplitude of 2V, the minimum and maximum output voltages are 0.49V and 1.997V, respectively, with a peak VCE of 99.85 percent and a peak PCE of 46.86 percent. This enables the suggested rectifier to be used in a variety of vibration energy collecting systems, including electrostatic, electromagnetic, and piezoelectric energy harvesters. The proposed rectifier, which is built at 2.4GHz and has a two-stage structure, performs better in the event of low input voltage amplitude and has lower minimum operation voltage than previously published papers. Full-wave fully gate cross-coupled rectifiers (FWFR) CMOS Rectifier Performance Summary at Freq of 2.4 GHz: With a 2V input voltage amplitude, the minimum and maximum output voltages are 0.49V and 1.997V, respectively, with a maximum VCE of 99.85% and a maximum PCE of 46.86%.

NA-CPG: A robust and stable rhythm generator for robot motion control

Central pattern generators (CPGs) have been widely applied in robot motion control for the spontaneous output of coherent periodic rhythms. However, the underlying CPG network exhibits good convergence performance only within a certain range of parameter spaces, and the coupling of oscillators affects the network output accuracy in complex topological relationships. Moreover, CPGs may diverge when parameters change drastically, and the divergence is irreversible, which is catastrophic for the control of robot motion. Therefore, normalized asymmetric CPGs (NA-CPGs) that normalize the amplitude parameters of Hopf-based CPGs and add a constraint function and a frequency regulation mechanism are proposed. NA-CPGs can realize parameter decoupling, precise amplitude output, and stable and rapid convergence, as well as asymmetric output waveforms. Thus, it can effectively cope with large parameter changes to avoid network oscillations and divergence. To optimize the parameters of the NA-CPG model, a reinforcement-learning-based online optimization method is further proposed. Meanwhile, a biomimetic robotic fish is illustrated to realize the whole optimization process. Simulations demonstrated that the designed NA-CPGs exhibit stable, secure, and accurate network outputs, and the proposed optimization method effectively improves the swimming speed and reduces the lateral swing of the multijoint robotic fish by 6.7% and 41.7%, respectively. The proposed approach provides a significant improvement in CPG research and can be widely employed in the field of robot motion control.

Particle image velocimetry for estimating shear wave elasticity imaging (SWEI) in the esophagus dysplasia

In this study, a 128-channel high-frequency pulse generator/receiver system was used to emit multi-angle wave propagation, and the generator plane excitation was used to generate a focused beam, which induced the phenomenon of particle displacement in the esophagus phantom recorded. Shear wave electrography is generated by using a micro-ultrasound probe (ARFI), which excites the shear waves with the output acoustic energy. In addition, we perform the method of PIV proper orthogonal decomposition to better qualify and quantify the differences between the PIV and Doppler, especially for analysis block into PIV for particle tracking, in which the external environment, with a Doppler similarity index of 82%, and PIV mainly uses the Doppler algorithm for analysis and obtains 97 frames, and fixed 0.33 ms time difference to output pictures. Each pass interrogation area is set to 128 in sequence, the distance is defined in calibration, in which the low filter contrast of image-based validation is set to 0.004, and the bright filter objects are set to 0.5. Through the analysis results of PIV, each particle's speed and movement are critical for the hospital to think. The relative position of the lesion and the effect of ARFI on the lesion are to be understood by understanding the direction of movement of the contrast agent. Overall, the shear wave and Doppler output amplitudes provided the best image quality and PIV results for esophagus dysplasia.

Self-compression of stimulated Raman backscattering by a flying focus.

The regime of self-compression has been proposed for plasma-based backward Raman amplification upon a flying focus. By using a pumping focus moving with a speed equal to the group velocity of stimulated Raman backscattering (SRBS), only a short part of SRBS which always synchronizes with the flying focus can be amplified. Therefore, instead of a short pulse, plasma noise or a long pulse can seed the BRA amplifiers. Here we demonstrate the regime by 2D particle-in-cell simulations, showing that the pump pulse is compressed from 26 ps to 116 fs, with an output amplitude comparable with the case of a well-synchronized short seed. As only one laser pulse is used in the simulation, the results present a significant path to simplify the Raman amplifiers.

Stochastic resonance of double fractional-order coupled oscillator with mass and damping fluctuations

In this study, the stochastic resonance phenomenon of a coupled double fractional-order harmonic oscillator with mass and damping fluctuation is investigated. Firstly, the Shapiro-Loginov formula and Laplace transform are used to obtain the analytical expression of the output amplitude gain of the system output. On this basis, aiming at the key factors involved in the model, including the coupling structure, fractional system, random fluctuation and external periodic force, the influence of coupling coefficient, double fractional order and driving frequency on the output amplitude gain (OAG) is analyzed, and reasonable physical explanations are provided. Secondly, numerical simulations are carried out to verify the accuracy of the theoretical solutions. The simulation results show that under certain conditions, the OAG of the system can appear stochastic resonance phenomenon with the above parameters, especially: (1) The OAG with the change of external drive frequency appears double peak, single peak and single valley stochastic resonance phenomenon, which does not appear under the same external disturbance with integer order and uncoupled conditions; (2) The order of double fractional derivative significantly affects the variation trend of OAG; (3) The coupling coefficient is not sensitive to the OAG.

The role of artificial intelligence in the modeling, analysis and inspection of ultrasonic welding processes — A review

Ultrasonic Welding is a popular welding procedure that uses high-frequency energy to heat joints. It is a complicated process involving a number of variable parameters that can each greatly modify the final weld product. A number of Artificial Intelligence (AI) technologies have thus been employed to regress and classify results such as weld parameters such as failure load, weld quality and joint strength on the basis of different parameters including power output, annealing temperature and vibration amplitude. Artificial neural network models are the most popular and adept at weld modeling on varying materials and composites. This paper reviews and compares the materials, feature extraction techniques and AI architectures and their performances on predicting a host of welding objectives.

Effect of acetylcholine deficiency on neural oscillation in a brainstem-thalamus-cortex neurocomputational model related with Alzheimer’s disease

Previous works imply that involving brainstem in neuropathological studies of Alzheimer’s disease (AD) is of clinically significant. This work constructs a comprehensive neural mass model for cholinergic neuropathogenesis that involves brainstem, thalamus and cortex, wherein how acetylcholine deficiency in AD affects neural oscillation of the model output is systematically explored from the perspective of neurocomputation. By decreasing synapse connectivity parameters in direct cholinergic pathway from brainstem to thalamus or in indirect glutamatergic synapse pathway from cortex to brainstem to mimic the pathological condition of reduced acetylcholine release in patients with AD, the property of neural oscillation in this model is numerically investigated by means of power spectrum in frequency domain and amplitude distribution in time domain. Simulated results demonstrate that decreasing synapse connectivity whether in the direct cholinergic pathway or in the indirect glutamatergic synapse pathway can alter the neural oscillation significantly in three aspects: it induces an obvious decrease of dominant frequency; it leads to a degraded rhythmic activity in the alpha frequency band as well as an enhanced rhythmic activity in the theta frequency band; it results in reduced oscillation amplitude of the model output. These results are agreement with the characteristic of electrophysiological EEG measurement recorded in AD, especially support the hypothesis that cholinergic deficiency is a promising pathophysiological origin of EEG slowing in AD. Our analysis indicates that targeting the cholinergic system may have potential prospects in early diagnosis and treatment of AD.

SIMULATION CHAOTIC DYNAMICS OF RELATIVISTIC BACKWARD-WAVE OSCILLATOR WITH USING CHAOS THEORY AND QUANTUM NEURAL NETWORKS

Nonlinear simulation and forecasting chaotic evolutionary dynamics of such complex system as relativistic backward-wave oscillator is treated using the new combined method, based on the chaos theory algorithms, concept of geometric attractors, and algorithms for quantum neural network simulation. It has been performed modelling the dynamics of multilayer photon echo neural network for the case of noisy input sequence. It has been performed analysis, modelling and processing the temporal dependence of the output amplitude for the backward-wave oscillator, described by system of the nonstationary nonlinear theory equations for the amplitude of electromagnetic field and motion of a beam. The data on the Lyapunov’s exponents, Kolmogorov entropy, correlation coefficient between the actual and neural networks prognostic rows, referred to a temporal dependence of the output signal amplitude of the nonrelativistic (relativistic) backward-wave oscillator are listed. The combining the advanced algorithms of the modern chaos theory, concept of a compact geometric attractors and one of the effective neural network algorithms, or, in a more general using an effective model of artificial intelligence etc, could provide very adequate and quantitatively correct description of temporal evolutionary dynamics of most complicated systems, in particular, in the field of modern ultrahigh-frequency electronics

Analysis and design of ultra-wideband PRGW hybrid coupler using PEC/PMC waveguide model

In this paper, a new method to facilitate the design of Printed Ridge Gap Waveguide (PRGW) structures is introduced. One of the main difficulties in designing such structures is related to their simulation process which is really time and energy-consuming. Therefore, a suitable boundary condition is considered to bring about the primary structure without involving the bed of nails or mushroom unit cells. Using this technique, a wideband PRGW 3 dB hybrid double-box coupler is designed to serve in mm-wave frequencies at a center frequency of 30 GHz, which can be deployed for the next generation of mobile communication. The designed coupler provides a wide matching and isolation bandwidth with low output amplitude imbalance, which is unique in comparison with current couplers. The prototype of the proposed coupler is fabricated and measured where the simulation and measurement results show a good agreement indicating the strength of the proposed method in PRGW structure design as well. The measured results show the couplers achieve better than 10-dB return loss and isolation over the frequency range from 25 to 40 GHz (46% BW) with the power-split unbalance and phase error within ± 1 dB and ± 5°, respectively. In addition, square mushrooms are chosen here to satisfy the high impedance surface. Not only do they bring about larger stop bandwidth, but also their configuration facilitates the arrangement of them around the coupler. The proposed design has superb characteristics such as low profile, low loss, and easy integration with microwave circuits and systems that can be suitable for designing mm-wave beamforming networks.

Collective dynamic behaviors of a general adjacent coupled chain in both unconfined and confined spaces

This paper studies the collective dynamic behaviors of a general adjacent coupled chain under a periodic driving force and dichotomous noise in both unconfined and confined spaces. The precise conditions for the stability, synchronization, and stochastic resonance (SR) of the system in an unconfined space were analytically derived and verified by numerical algorithms. The stability and synchronization of the adjacent coupled chain in the unconfined space were found to be related to the system and noise parameters. The collective dynamic behaviors of the adjacent coupled chain in the confined space were also analyzed through numerical simulations, and it was found that due to boundary constraints, the adjacent coupled chain consistently achieves stability and synchronization in the confined space. Moreover, when compared with the unconfined system, the output amplitude of the confined system exhibits more complex SR phenomena, such as double-peak SR, multi-peak SR, superharmonic SR and so on.

AC Power Flow Analysis for Inverters in Microgrid Application

In a microgrid system, proper current distribution and load sharing strategies are essential to achieve reliable parallel operation. Line impedance is an important factor when implementing a control technique for an inverter for microgrid operation, whether it is operating in grid connected or island mode. It is sometime difficult to visualize the impact of different line impedance to the power flow in AC microgrid. In this paper, AC power flow of an inverter-based system connected to a common ac bus through purely resistive, inductive or complex line impedances is investigated. For each line impedance case, the effect of an inverter’s output voltage power angle and amplitude on the active and reactive power flow are studied. Several active and reactive powers plots are generated in 3D surf plots to visualize the impact of line impedance on the power flow in an AC system.

Performances of resonant frequency tracking methods and compensation strategies for rotary ultrasonic machining device with contactless energy transfer

As the core component of rotary ultrasonic machining (RUM) device, the ultrasonic transducer is subjected to mechanical loads during processing, leading to variations in its equivalent electrical parameters. For RUM device with contactless energy transfer (CET) system, this phenomenon can cause the mismatch between the compensation parameters and the transient electrical parameters of the transducer, which will further degrade the resonant frequency tracking (RFT) accuracy and the output performance. In this study, bilateral compensation parameters and coil turns of the CET were first calculated for no-load RUM device to gain optimal transfer efficiency and achieve tuning matching and impedance matching. After that, the drift of the transducer electrical parameters under load conditions was quantified by loading experiments. Based on electrical model, the influences of mechanical loads on the impedance characteristics of RUM equipment were revealed. For the four compensation topologies, different RFT methods were employed according to the above analysis. Finally, theoretical analyses and verification experiments were conducted to investigate the performances of various driving configurations for the transducer considering the load effects. The results demonstrate that inappropriate selection of RFT method and compensation strategy can introduce considerable error between the tracking frequency and the resonant frequency of the transducer, causing poor output performance of RUM device. The Series-Series (SS) topology combined with the phase-locked method can gain stable transfer efficiency and high power factor with excellent RFT accuracy. Furthermore, this configuration has load adaptive capability, meaning that the power obtained by the transducer increases as the load increases, which is beneficial to suppress the output amplitude decay during machining. The conclusions presented in this research can provide references for the design of RUM device.