Instantaneous Signal Research Articles

Synchro-Reassigning Transform for Instantaneous Frequency Estimation and Signal Reconstruction

Traditional signal postprocessing methods suffer from the repeated assignment problem (RAP), which can result in inaccurate instantaneous frequency (IF) estimation and signal recovery. In this article, to solve this problem, a novel time-frequency (TF) analysis (TFA) method called the synchro-reassigning transform (SRT) is proposed. This method aims to obtain the ideal TF representation (TFR) by utilizing derivatives of the constructed amplitude function and a three-step selection rule to adaptively extract the TF coefficients on the IF trajectories in the TF plane, and reassigning these TF coefficients into a new TFR. In this way, SRT can eliminate the RAP, thus obtaining an approximately ideal TFR that helps to realize more accurate IF estimation and signal reconstruction. Furthermore, SRT shows satisfactory performance on signals with high nonlinear IFs or relatively close IFs, even under strong noise conditions. Two simulated signal and three real-life signals were used to demonstrate the performance of SRT.

Parameter Identification With Synchrophasor Trajectory Fitting Technique for Sub-/Super-Synchronous Oscillations

To enhance the real-time monitoring of sub-/super-synchronous oscillation dynamics by utilizing the advantages of wide-area time-synchronization and dynamic measurement of synchrophasor measurement data, the idea of a parameter identification algorithm with synchrophasor trajectory fitting (PTF) is proposed in this letter to identify the parameters of each component of the instantaneous signal during sub-/super-synchronous oscillations. Simulated PMU data are used to demonstrate the proposed idea and verify the performance of PTF compared with the interpolated DFT algorithm. Discussions are also provided for further improvements.

Tongue and Lip Acceleration as a Measure of Speech Decline in Amyotrophic Lateral Sclerosis

Purpose: The goal of this study was to examine the efficacy of acceleration-based articulatory measures in characterizing the decline in speech motor control due to amyotrophic lateral sclerosis (ALS). Method: Electromagnetic articulography was used to record tongue and lip movements during the production of 20 phrases. Data were collected from 50 individuals diagnosed with ALS. Articulatory kinematic variability was measured using the spatiotemporal index of both instantaneous acceleration and speed signals. Linear regression models were used to analyze the relationship between variability measures and intelligible speaking rate (a clinical measure of disease progression). A machine learning algorithm (support vector regression, SVR) was used to assess whether acceleration or speed features (e.g., mean, median, maximum) showed better performance at predicting speech severity in patients with ALS. Results: As intelligible speaking rate declined, the variability of acceleration of tongue and lip movement patterns significantly increased (p < 0.001). The variability of speed and vertical displacement did not significantly predict speech performance measures. Additionally, based on R² and root mean square error (RMSE) values, the SVR model was able to predict speech severity more accurately from acceleration features (R² = 0.601, RMSE = 38.453) and displacement features (R² = 0.218, RMSE = 52.700) than from speed features (R² = 0.554, RMSE = 40.772). Conclusion: Results from these models highlight differences in speech motor control in participants with ALS. The variability in acceleration of tongue and lip movements increases as speech performance declines, potentially reflecting physiological deviations due to the progression of ALS. Our findings suggest that acceleration is a more sensitive indicator of speech deterioration due to ALS than displacement and speed and may contribute to improved algorithm designs for monitoring disease progression from speech signals.

Comparison of flow dynamics and reactor performance in gas-solids circulating turbulent fluidized bed with other fluidized beds across regimes

The hydrodynamics and the reactor performance in the recently proposed gas-solids circulating turbulent fluidized bed (CTFB) were compared with that in the low-velocity conventional fluidized beds and the high-density circulating fluidized bed (HDCFB) riser. The average solids holdup distributions, fluctuations, and probability density distributions of the instantaneous solids holdup signals indicate that the CTFB either more resembles a TFB if the Gs/Ug ratio is large or more resembles an HDCFB if the Gs/Ug ratio is small. The distributions of the bubble occurrence, equivalent bubble size, and bubble phase fraction were extracted from the optical fiber signals of the local solids holdup using the wavelet analysis method. The CTFB was found to have a greater number of smaller bubbles than the bubbling and turbulent fluidized beds and relatively fewer and larger bubbles than that in an HDCFB. The effect of flow dynamics and bubble behaviors on the reaction performance in different types of fluidized beds are compared by analytical calculation based on the K-L reactor model. A superior reactor performance can be achieved using the CTFB reactor for a higher effective reaction rate, higher mass transfer rates, and a lower degree of solids backmixing.

ALGORITHMIC PROVISION OF MONITORING OF IDENTITY OF CYLINDER POWERS OF POWER UNITS ON THE BASIS OF PROCESSING OF DIRECT INDIRECT DATA

A frequency-modulated instantaneous crankshaft speed signal is proposed as input information for monitoring the identity of the cylinder power of an internal combustion engine. Algorithmic software is based on solving a predefined system of linear algebraic equations with optimization of the solution based on the least-squares method. Frequency and time methods of signal measurement research are investigated. In the temporal representation, the system of algebraic equations is the balance between the values of the fluctuation signal of the first mass at specific points in time and the sum of the calculated contributions of the cylinders. The addition to the sum is determined by the product of the weights for the corresponding function of the contribution of the cylinder to the fluctuation signal. This function is calculated as the convolution interval between the torque of an individual cylinder and its transfer function. As a result of solving the system of equations, we obtain the weights of the cylinders, which are used to determine the distribution of cylinder power of the power unit. When comparing the methods, it was found that the time method of presentation provides better performance. A mathematical apparatus for estimating the maximum plausibility of the parameters of the determined components of the contributions of individual cylinders in the signal of fluctuations in the speed of rotation of the first mass of the crankshaft has been developed. An algorithm for estimating the weights of cylinders, which implements the correlation method of analysis, is also proposed. This provides a significant improvement in the signal-to-noise ratio in the measurement implementation of the signal of fluctuations in the speed of the crankshaft. An analytical expression for the cross-correlation function between the time realization of the fluctuation signal and the torque of the first cylinder is obtained. The scheme of the algorithm for monitoring of identity of cylindrical powers of the power unit is developed. The uncertainty of information technology for processing indirect measurement data is investigated and the requirements for metrological characteristics of hardware for measuring the signal of the instantaneous crankshaft speed signal are established.

Single-Channel Blind Separation Using Adaptive Mode Separation- Based Wavelet Transform and ICA Single-Channel Separation of the

In this paper, a new method to solve the signal-channel blind source separation (SCBSS) problem has been proposed. The method is based on combining the Adaptive Mode Separation-Based Wavelet Transform (AMSWT) and the ICA-based single channel separation. First, the amplitude spectrum of the instantaneous mixture signal is obtained via the Fourier transform. Then, the AMSWT is introduced to adaptively extract spectral intrinsic components (SIC) by applying the variational scaling and wavelet functions. The AMSWT is applied to every mode to obtain the time-frequency distribution. Then the timefrequency distribution of the mixed signal is exploited. The ICA-based single-channel separation has been applied on spectral rows corresponding to different time intervals. Finally, these components are grouped using the β-distance of Gaussian distribution Dβ. Objective measure of separation quality has been performed using the scale-invariant (SI) parameters and compared with the existing method to solve SCBSS problem. Experimental results show that the proposed method has better separation performance than the existed methods, and the proposed method present a powerful method to solve de SCBSS problem. Keywords: Signal-channel blind source separation. Adaptive Mode Separation-Based Wavelet Transform. Spectral decomposition-based method. β-distance of Gaussian distribution

Instantaneous Current Signal Analysis Based on Z-Transform to Detect Oscillation Modes

In power systems, phasor measurement units of current, voltage, power, and frequency have traditionally allowed the capture of electromechanical oscillations and inspired the development of data analysis tools. These oscillations can be described by oscillatory modes, which provide security and stability. In this study, a technique is proposed to detect and identify oscillation modes quickly from instantaneous current signals. The proposed method is based on the Z-transform of the analyzed signal. Simulated data resulting from power systems previously used to analyze the generated oscillations between buses were obtained to demonstrate the effectiveness of the proposed technique. The accuracy of this methodology was compared with that of Prony analysis and the eigensystem realization algorithm. The results show that the oscillatory modes are characterized more rapidly; therefore, the proposed method is a promising tool for oscillation monitoring.

Real-Time Fault Location Using the Retardation Method

A new method for short-circuit fault location is proposed. The method is based on instantaneous signal measurement and its first and second derivatives, which are the novel elements of the current approach. The derivatives allow associating a precise time stamp to the occurrence of the fault. Due to retardation phenomena, the difference between the times in which a signal is registered in two detectors can be used to locate the fault. We offer several mathematical models to describe the fault. Although a description of faults in terms of a lumped circuit is useful for elucidating the methods for detecting the fault, this description will not suffice to describe the fault signal propagation; hence, a distributed models is needed, which is given in terms of the telegraph equations. Those equations were used to derive a transmission line transfer function, and an exact analytical description of the fault signal propagating in the transmission line was obtained. The analytical solution was verified both by numerical simulations and experimentally.

Sparse processing with range migration compensation capability for a frequency agile orthogonal frequency division multiplexing waveform

Digital-to-analogue and analogue-to-digital in a digital array radar limits the transmission and reception of instantaneous broadband signals (IBSs), which makes it a technical bottleneck for digital array radar to obtain an instantaneous broadband high-resolution range profile (HRRP). A frequency-agile orthogonal frequency division multiplexing (OFDM) waveform with a high repetition frequency pulse train is proposed, which uses multiple narrowband OFDM to realise large bandwidth so that the digital array radar can easily realise the broadband working mode. This frequency hopping signal makes the digital array radar have the characteristics of broadband HRRP formation and low interception simultaneously. To solve the problem of range migration caused by high-speed moving targets, a two-stage sparse processing algorithm with range migration compensation capability (FS-RMCSP) in slow time and fast time domains is proposed. By constructing a sparse processing dictionary matrix with range compensation operator according to the phase offset of the moving target echo, the proposed algorithm can complete the compensation of target range migration with high resolution, accurately recover the range-Doppler parameters of target, and realise the coherent accumulation of target echo. The simulation results show that this waveform can obtain the range-Doppler high-resolution characteristics equivalent to the IBS in the radar tracking working mode. Compared with the conventional sparse signal processing algorithm, the FS-RMCSP algorithm significantly improves the performance of target reconstruction in the scene of high-speed moving targets.

English

Comparative Study of Synchronous Reference Frame and Instantaneous Active Reactive Power Reference Current Signal Generation Technique-Based Shunt Active Power Filter in Solar Photovoltaic Microgrid System

Broadband Millimeter-Wave 5G Power Amplifier Design in 22 nm CMOS FD-SOI and 40 nm GaN HEMT

Three millimeter-wave (mm-Wave) power amplifiers (PAs) that cover the key 5G FR2 band of 24.25 to 43.5 GHz are designed in two different state-of-the-art device technologies and are presented in this work. First, a single-ended broadband PA that employs a third-order input matching network is designed in a 40 nm GaN/SiC HEMT (High Electron Mobility Transistor) technology. Good agreement between the measurement and post-layout parasitic extracted (PEX) electromagnetic (EM) simulation data is observed, and it achieves a measured 3-dB BW (bandwidth) of 18.0–40.3 GHz and &gt;20% maximum PAE (power-added-efficiency) across the entire 20–44 GHz band. Expanding upon this measured design, a differential broadband GaN PA that utilizes neutralization capacitors is designed, laid out, and EM simulated. Simulation results indicate that this PA achieves 3-dB BW 20.1–44.3 GHz and maximum PAE &gt; 23% across this range. Finally, a broadband mm-Wave differential CMOS PA using a cascode topology with RC feedback and neutralization capacitors is designed in a 22 nm FD-SOI (fully depleted silicon-on-insulator) CMOS technology. This PA achieves an outstanding measured 3-dB BW of 19.1–46.5 GHz and &gt;12.5% maximum PAE across the entire frequency band. This CMOS PA as well as the single-ended GaN PA are tested with 256-QAM-modulated 5G NR signals with an instantaneous signal BW of 50/100/400/9 × 100 MHz at a PAPR (peak-to-average-power ratio) of 8 dB. The data exhibit impressive linearity vs. POUT trade-off and useful insights on CMOS vs. GaN PA linearity degradation against an increasing BW for potential mm-Wave 5G applications.

A unified non-linear system model view of hyperelasticity, viscoelasticity and hysteresis exhibited by rubber

Rubber modeling is an old subject and so many models exist that it is difficult to have a clear vision of what exists and is more appropriate. Rather than attempting a standard review, this paper proposes classification using the traditional system modeling strategy, where raw measurements are either processed to obtain non-parametric models, or used to identify parametric models, whose accuracy can be controlled by order selection or by numerical implementation considerations. A full test campaign, including multi-step relaxation, low speed triangular and sine tests, on a large deformation compression sample is used to illustrate the need to model and combine the base behaviors known as hyperelasticity, viscoelasticity, and rate independent hysteresis. The equivalence between linear viscoelasticity and linear time invariant systems is used to clarify the link between order selection and accuracy of a generalized Maxwell model. Rate independent hysteresis is analyzed using a convolution product like the one used for viscoelastic transients by introducing a relaxation modulus. Measurements of the hysteretic relaxation modulus are used to propose strategies to measure the asymptotic hyperelastic modulus and discriminate between different hysteretic model forms. A parallel between Iwan and Maxwell models is detailed, and non-parametric models are used to show that the two overlap in the low frequency small deformation regime. Regularized rate independent hysteresis and non-linear viscoelasticity are finally shown to lead to a similar view allowing a transition between the rate independent and linear relaxation models. The instantaneous ratio analytic force and displacement signals, or instant complex modulus, is introduced as novel non-parametric estimation of sine measurements and shown to be a powerful tool to analyze and validate the fact that a force rate relaxation with non-linear relaxation frequencies is most appropriate to represent the non-linear coupling of all three effects.

Design and numerical simulation of a piezoelectric harvester using PVDF polymer for keyboard application

Finding new energy sources has received in recent years a particular interest among scientists. Our research focuses on the generation of micro-renewable energy. This energy is used to power various wireless devices, such as sensors, actuators and micro-electromechanical systems (MEMS). In this work, a new innovative form of piezoelectric harvester, using PVDF polymer, has been proposed, “piezo-spring”. Their time deformation gives a time signal, useful for applications that need an instantaneous electrical signal. Materials and geometry were chosen such as to increase the stiffness of the spring and by this the piezoelectric conversion. A numerical simulation of the use of this device in a keyboard application was carried out using finite element calculation software. A power value in the range of 0.625 µW was obtained at a 10 Hz frequency.

Arm-Current-Sensorless Circulating Current Control of MMC

The circulating current and the large energy storage requirement are the two major limitations of the modular multilevel converter (MMC). The circulating current in MMC is majorly, in addition to the dc current, second harmonic in nature. If not controlled properly, it results in reduced efficiency and/or increased energy storage requirement (ESR). To enhance the efficiency, the second and the higher-order harmonic components in the circulating current of MMC are required to be suppressed. On the other hand, controlling the circulating current to have predefined magnitude and phase-angle can reduce the ESR. There are many control methods available in literature to suppress and also, to control the second harmonic circulating current (SHCC). These methods are mainly based on sensing the arm current and calculating the SHCC and then suppressing or controlling it based on the set objectives. In this paper, two control schemes are proposed to suppress the SHCC and to reduce the ESR. The proposed schemes are based on utilizing the instantaneous voltage signals of the sub-module capacitors in MMC. Hence, the sensing and communicating the sensed signal of arm currents can be avoided using the proposed schemes, which increases the reliability and leads to reduced cost and complexity. The efficacy of the proposed control schemes is verified using the simulation studies and also by using the scaled-down lab prototype of a 3-phase 7-level MMC.

Neurophysiology, pathology and models of rapid eye movements.

This chapter discusses the premotor neural mechanisms that control horizontal saccadic eye movements. Oculomotoneurons carry a pulse-step signal that underlies the pulse-step force driving the overdamped plant. The pulse and step are both generated by a common signal, arising from medium-lead burst neurons in the pons. Their burst signal encodes saccadic eye velocity, while the number of spikes in the burst relates to the saccade amplitude. The step component, which encodes the eye position, is obtained by neural integration of the burst. Several oculomotor neural disorders can be explained by impairments in the binocular push-pull organization of this pulse-step mechanism. Plasticity of the pulse-step control, e.g., in response to muscle weakening, is mediated by cerebellar vermis and flocculus. Saccadic offset may be controlled, either by active braking, or by an exponential slide signal. The neurophysiology is summarized by a quantitative model, in which the firing rate of burst neurons is controlled by a dynamic negative feedback loop that carries the instantaneous eye position signal from the neural integrator. This signal is compared with a desired eye-position command in the head from higher centers, and the resulting dynamic motor error drives the high-gain burst cells. Instability of the system is prevented by the mutual inhibitory interaction between burst cells and omnipause neurons. The model explains many features of normal saccades, but also accounts for pathologies and abnormalities like dynamic overshoots and saccade oscillations.

Measurement of Turbulent Temperature Fluctuations by Fine-Wire Temperature Sensors with Various Shapes

In a turbulent thermal boundary layer, to accurately measure the temperature fluctuation near the wall, a thin-wire temperature sensor with high spatial resolution is indispensable for capturing small-scale temperature fluctuations in the immediate vicinity of the wall. On the other hand, in order to minimize the deterioration in the dynamic response of the thin-wire sensor, its length-to-diameter ratio need generally exceed 1000. To meet these conflicting requirements, the wire diameter of the sensor must be extremely thin. In this study, as a novel approach, we proposed a new temperature probe consisting a V-shaped thin tungsten wire, and verified its measurement accuracy by using a standard cold-wire probe as a reference. As a result, the turbulence characteristics measured in a fully-developed thermal boundary layer—r.m.s. values, power spectra, instantaneous signal traces of temperature fluctuations, etc.—show that the V-shaped thin-wire temperature sensor can improve the spatial resolution of the sensor while enabling us to take full advantage of the response compensation technique developed for the standard cold-wire probe.

Turbocharger surge behavior for sudden valve closing downstream the compressor and effect of actuating variable nozzle turbine

Surge is an unstable phenomenon appearing when a valve closing reduces the compressor flow rate. This phenomenon is avoided for automotive turbochargers by defining a surge margin during powertrain system design. This surge margin established with measurements in steady state testing regime limits the maximal engine torque at low levels of output. An active control of the compressor could reduce the surge margin and facilitate a transient compressor operation for a short time in surge zone. In this paper, an experimental study of the transient operation of a turbocharger compressor entering the surge zone is performed. Control of the turbocharger speed is sought to avoid unsteady operation using the variable geometry turbine (VGT) nozzle actuator. From a given stable operating point, surge is induced by reducing the opening of a valve located downstream of the compressor air circuit. The effect of reducing the speed of rotation by controlling the VGT valve is investigated, as this should lead to more stable compressor operation. The rotation speed of the turbocharger is controlled to avoid an unstable operating point using servo-actuator of variable geometry turbine. From a stable operating point, the surge appearance is caused by closing a butterfly valve downstream the air circuit of the compressor. The effect on the compressor rotation speed when the opening of variable geometry turbocharger valve is modified is studied. Measurements have been conducted for different control profiles of the VGT valve placed downstream the compressor. This article presents the means used to carry out these tests as well as the results of the measurements of the instantaneous signals of pressure, temperature, flow rate and rotation speed, allowing the analysis of the surge phenomenon.

Multi-Frequency Instantaneous Signal Detection Scheme Based on Non-Uniform Optical Frequency Comb

Multi-Frequency Instantaneous Signal Detection Scheme Based on Non-Uniform Optical Frequency Comb

A robust computational approach for jaw movement detection and classification in grazing cattle using acoustic signals

Monitoring behaviour of the grazing livestock is a difficult task because of its demanding requirements (continuous operation, large amount of information, computational efficiency, device portability, precision and accuracy) under harsh environmental conditions. Detection and classification of jaw movements (JM) events are essential for estimating information related with foraging behaviour. Acoustic monitoring is the best way to classify and quantify ruminant events related with its foraging behaviour. Although existing acoustic methods are computationally efficient, a common failure for broad applications is the deal with interference associated with environmental noises. In this work, the acoustic method, called Chew-Bite Energy Based Algorithm (CBEBA), is proposed to automatically detect and classify masticatory events of grazing cattle. The system incorporates computations of instantaneous power signal for JM-events classification associated with chews, bites and composite chew-bites, and additionally between two classes of chew events: i) low energy chews that are associated with rumination and ii) high energy chews that are associated with grazing. The results demonstrate that CBEBA achieve a recognition rate of 91.9% and 91.6% in noiseless and noisy conditions, respectively, with a high classification precision and a marginal increment of computational cost compared to previous algorithms, suggesting feasibility for implementation in low-cost embedded systems.

Surf Zone Turbulence and Suspended Sediment Dynamics—A Review

The existence of sandy beaches relies on the onshore transport of sand by waves during post-storm conditions. Most operational sediment transport models employ wave-averaged terms, and/or the instantaneous cross-shore velocity signal, but the models often fail in predictions of the onshore-directed transport rates. An important reason is that they rarely consider the phase relationships between wave orbital velocity and the suspended sediment concentration. This relationship depends on the intra-wave structure of the bed shear stress and hence on the timing and magnitude of turbulence production in the water column. This paper provides an up-to-date review of recent experimental advances on intra-wave turbulence characteristics, sediment mobilization, and suspended sediment transport in laboratory and natural surf zones. Experimental results generally show that peaks in the suspended sediment concentration are shifted forward on the wave phase with increasing turbulence levels and instantaneous near-bed sediment concentration scales with instantaneous turbulent kinetic energy. The magnitude and intra-wave phase of turbulence production and sediment concentration are shown to depend on wave (breaker) type, seabed configuration, and relative wave height, which opens up the possibility of more robust predictions of transport rates for different wave and beach conditions.