Traditional Time Domain Research Articles

The Transient Stability Preventive Control of Power System Based on RBF Neural Network

The transient stability preventive estimation and control is one of the most important tasks of the power system. The traditional time domain simulation method cannot meet the standard of on-line estimation because of its heavy computation burden. In this paper, we realize the on-line estimation of transient stability limits on critical lines of a power system using the favorable approximation ability of RBF network. We choose right samples by off-line count to train the RBF network in order to make the error satisfy demand. Preventive control direction and amount are determined based on first-order sensitivities of transient stability limits to generator outputs. The sensitivities are derived from partial derivatives of RBF network outputs to inputs. In the end, we take a practical power system for an example to demonstrate the efficiency of RBF network in estimation of the transient stability limit on critical lines and ability to provide preventive control strategy.

Adaptive inverse control of random vibration based on the filtered-X LMS algorithm

Random vibration control is aimed at reproducing the power spectral density (PSD) at specified control points. The classical frequency-spectrum equalization algorithm needs to compute the average of the multiple frequency response functions (FRFs), which lengthens the control loop time in the equalization process. Likewise, the feedback control algorithm has a very slow convergence rate due to the small value of the feedback gain parameter to ensure stability of the system. To overcome these limitations, an adaptive inverse control of random vibrations based on the filtered-X least mean-square (LMS) algorithm is proposed. Furthermore, according to the description and iteration characteristics of random vibration tests in the frequency domain, the frequency domain LMS algorithm is adopted to refine the inverse characteristics of the FRF instead of the traditional time domain LMS algorithm. This inverse characteristic, which is called the impedance function of the system under control, is used to update the drive PSD directly. The test results indicated that in addition to successfully avoiding the instability problem that occurs during the iteration process, the adaptive control strategy minimizes the amount of time needed to obtain a short control loop and achieve equalization.

Heart Rate Nonlinear Dynamics During Sudden Hypoxia at 8230 m Simulated Altitude

Acute hypobaric hypoxia is associated with autonomic changes that bring a global reduction of linear heart rate variability (HRV). Although changes in nonlinear HRV can be associated with physiologic stress and are relevant predictors of fatal arrhythmias in ischemic heart disease, to what extent these components vary in sudden hypobaric hypoxia is not known. Twelve military pilots were supplemented with increasing concentrations of oxygen during decompression to 8230 m in a hypobaric chamber. Linear and nonlinear HRV was evaluated at 8230 m altitude before, during, and after oxygen flow deprivation. Linear HRV was assessed through traditional time-domain and frequency-domain analysis. Nonlinear HRV was quantified through the short-term fractal correlation exponent alpha (alphas) and the Sample Entropy index (SampEn). Hypoxia was related to a decrease in linear HRV indexes at all frequency levels. A non-significant decrease in alphas (basal, 1.39 +/- 0.07; hypoxia, 1.11 +/- 0.13; recovery, 1.41 +/- 0.05; P = .054) and a significant increase in SampEn (basal, 1.07 +/- 0.11; hypoxia, 1.45 +/- 0.12; recovery, 1.43 +/- 0.09; P = .018) were detected. The observed pattern of diminished linear HRV and increased nonlinear HRV is similar to that seen in subjects undergoing heavy exercise or in patients with ischemic heart disease at high risk for ventricular fibrillation.

Analysis of terahertz waveguide modes in continuous wavelet domain

Conventional analytical methods in the wavelet domain are used to present an analysis of terahertz (THz) waveguide modes. To obtain THz radiation pulses passing through a waveguide, we build a simple experimental system with a 5-mm-long, 230-\mum-inner-diameter stainless steel waveguide. The single-mode guided signal from the experiments and the multi-mode signal of a similar THz waveguide reported in the literature are analyzed using the continuous wavelet transform (CWT). The results demonstrate that analyzing THz waveguide modes in the wavelet domain not only possesses all the functionality of the traditional THz time-domain spectroscopy (TDS) data processing but also has the ability to unscramble quantitatively and intuitively detailed information about the target samples, such as mode type, cut-off frequency, amplitude distinction, and group velocity.

Wideband OFDM receiver using split spectrum processing

A new wideband Orthogonal Frequency Division Multiplexing (OFDM) receiver based on split spectrum processing (SSP) technique is presented. In this receiver, the spectrum of the input signal is first decomposed into a number of sub-bands, and then independently down-converted to baseband for filtering and demodulation. This technique, which is characterized by the number of sub-bands and their bandwidths, reduces the sampling rate of analog-to-digital converter (ADC) by the sub-band bandwidth compared to conventional OFDM system. Analysis and simulation of the phase noise show that the new receiver exhibits the same bit error rate (BER) performance as the conventional OFDM system. Also, the Chebyshev II filter gives rise to superior BER performance compared to Butterworth, Chebyshev I, Elliptic, and Bessel filters. Interestingly, the traditional time domain synchronization algorithms can be employed for the new SSP receiver with only minor modifications.

Surface pressure and wind load characteristics on prisms immersed in a simulated transient gust front flow field

Thunderstorm generated gust fronts are responsible for various degrees of structural damage in many areas of the world. However, the resulting impact of gust front winds is not fully understood to such a level that their flow kinematics, dynamics and impact on structures can be quantified with some certainty. Gust front winds are transient in nature and have a flow profile which differs significantly from a typical boundary layer flow field. This study focuses on investigating the effects of this flow profile and its transient nature on the aerodynamics of bluff, prismatic bodies. A gust front type flow field is generated using a multiple fan wind tunnel and the resulting surface pressures are captured on a suite of prismatic models, which vary in size in relationship to the oncoming wind profile. The temporal variations in surface pressures are analyzed using traditional time, frequency and time-frequency domain schemes. Results indicate the changing nature of the surface pressure field in time, highlighting both qualitative and quantitative differences between local and area-averaged pressures under a host of flow profiles.

Theory and experimental validation of a Class E PA above theoretical maximum frequency

This paper reports an investigation and a proposed solution to design Class E power amplifiers above the theoretical maximum frequency allowed by the adopted active device. Starting from the traditional time domain analysis, a numerical algorithm has been developed and presented in order to extend Class E feasibility through the optimization of the output voltage waveform. A hybrid Class E amplifier in laterally diffused metal oxide semiconductor (LDMOS) technology has been designed and measured. The final amplifier shows an output power of more than 10 W with an associated efficiency of 49% (power added efficiency (PAE) = 45%) over a 100-MHz bandwidth around 2.14 GHz.

Power system transient stability simulation under uncertainty based on Taylor model arithmetic

Abstract The Taylor model arithmetic is introduced to deal with uncertainty. The uncertainty of model parameters is described by Taylor models and each variable in functions is replaced with the Taylor model (TM). Thus, time domain simulation under uncertainty is transformed to the integration of TM-based differential equations. In this paper, the Taylor series method is employed to compute differential equations; moreover, power system time domain simulation under uncertainty based on Taylor model method is presented. This method allows a rigorous estimation of the influence of either form of uncertainty and only needs one simulation. It is computationally fast compared with the Monte Carlo method, which is another technique for uncertainty analysis. The proposed method has been tested on the 39-bus New England system. The test results illustrate the effectiveness and practical value of the approach by comparing with the results of Monte Carlo simulation and traditional time domain simulation.

Frailty and Impaired Cardiac Autonomic Control: New Insights From Principal Components Aggregation of Traditional Heart Rate Variability Indices

Age-related deterioration in homeostatic regulatory mechanisms leads to decreased complexity in their output. For example, the degradation of cardiac autonomic control results in loss of complexity in the heart rate signal. Frailty is a state of critically impaired homeostasis that results in heightened vulnerability to stressors. We propose a new measure of heart rate variability (HRV) to capture the impairment in cardiac autonomic control associated with frailty. Traditional time and frequency domain indices of HRV were obtained from 2-hour ambulatory electrocardiograms (ECGs) of 276 women (65-101 years old) in the Women's Health and Aging Study-I. Principal components analysis was conducted on the correlation matrix of HRV indices. Frailty was defined using a validated instrument. Regression models were used to evaluate associations of HRV measures with age, frailty, and 5-year mortality. The first two principal components (PCs), PC1 and PC2, explained 90% of the variance in HRV indices. PC1 is the mean of log-transformed HRV indices. PC2 is a linear combination of log-transformed indices, with positive weights for very low frequency (VLF), low frequency (LF), and standard deviation of N-N intervals (SDNN), and negative weights for high frequency (HF), root-mean-squared differences of successive N-N intervals (RMSSD), and proportion of all N-N intervals that are larger than 50 ms (pNN50). Decreases in SDNN, VLF, LF, and LF/HF were associated with an increased risk of frailty. PC2 was more strongly associated with age (beta = -.23, p < .001) and frailty (beta = -.73, p < 10(-5)) than were the individual HRV indices and LF/HF. PC2 was also the best predictor of 5-year mortality (beta = -.60, p < 10(-6)). Cardiac autonomic control, as reflected by HRV, is impaired in frailty. A new measure derived from PC aggregation of traditional HRV indices provides a compact summary of this impairment.

Detection and Location of Multiple Wiring Faults via Time–Frequency-Domain Reflectometry

In this paper, we propose a high-resolution time-frequency-domain reflectometry technique as a methodology of detection and estimation of faults on a wire. This method adopts the time-frequency cross-correlation characteristics of the observed signal in both the time and frequency domains simultaneously. The accuracy of the proposed method is verified with experiments using a radio-guide-type coaxial cable and comparing it with traditional time-domain as well as frequency-domain reflectometry methods. It is clearly shown here that the proposed algorithm produces excellent results compared to the conventional methods for single as well as multiple fault cables.

Analysis of Dielectric Resonator Antenna Array by Using Unconditionally Stable Pseudospectral Time-Domain Method

To simulate the triangular dielectric resonator antennas (DRAs), an unconditionally stable technique called the alternating direction implicit (ADI) is developed for the pseudospectral time-domain (PSTD) algorithm in this letter. This time-domain method is used for solving Maxwell's equations, which is comparative higher efficiency over the traditional finite-difference time-domain (FDTD) method. Also, the multidomain strategy is employed to allow flexible treatment for internal inhomogeneities. Numerical results are demonstrated with the unconditional stability and the second-order accuracy for the ADI-PSTD algorithm. To verify the DRA array design, reasonable agreement is obtained between theory and experiment.

WAVEGUIDE SIMULATION USING THE HIGH-ORDER SYMPLECTIC FINITE-DIFFERENCE TIME-DOMAIN SCHEME

Abstract—The high-order symplectic finite-difference time-domain scheme is applied to modeling and simulation of waveguide structures. First, the perfect electric conductor boundary is treated by the image theory. Second, to excite all possible modes, an efficient source excitation method is proposed. Third, the modified perfectly matched layer is extended to its high-order form for absorbing the evanescent waves. Finally, a high-order scattering parameter extraction technique is developed. The cases of waveguide resonator, waveguide discontinuities, and periodic waveguide structure demonstrate that the high-order symplectic finite-difference time-domain scheme can obtain better numerical results than the traditional finite-difference timedomain method and save computer resources.

A Comparison of Frequency-Domain Block MIMO Transmission Systems

Block transmission techniques, with appropriate cyclic prefix and frequency-domain processing schemes, have been shown to be excellent candidates for digital transmission over severely time-dispersive channels, allowing good performance with implementation complexity that is much lower than traditional time-domain processing schemes. Orthogonal frequency-division multiplexing (OFDM) modulation is the most popular block transmission technique. Single-carrier (SC) modulation using frequency-domain equalization (FDE) is an attractive alternative approach based on this principle. In this paper, we propose two new receiver structures for multiple-input-multiple-output (MIMO) channels employing SC (MIMO-SC) modulation and FDE schemes. These receivers have a hybrid structure with frequency-domain feedforward and time-domain feedback filters for intersymbol interference (ISI) and interference cancellation. The proposed schemes are compared with different MIMO systems employing OFDM modulation (MIMO-OFDM) receivers in terms of performance [bit error rate (BER) and throughput] and complexity. Our performance results show the superiority of MIMO-SC approaches relative to MIMO-OFDM in terms of the BER performance for the simulated scenarios. Also, the simulation results show that the proposed hybrid MIMO-SC receivers yield a higher throughput than a MIMO-OFDM system.

Robust Wavelet-Domain Estimation of the Fractional Difference Parameter in Heavy-Tailed Time Series: An Empirical Study

We investigate the performance of several wavelet-based estimators of the fractional difference parameter. We consider situations where, in addition to long-range dependence, the time series exhibit heavy tails and are perturbed by polynomial and change-point trends. We make detailed study of a wavelet-domain pseudo Maximum Likelihood Estimator (MLE), for which we provide an asymptotic and finite-sample justification. Using numerical experiments, we show that unlike the traditional time-domain estimators, estimators based on the wavelet transform are robust to additive trends and change points in mean, and produce accurate estimates even under significant departures from normality. The Wavelet-domain MLE appears to dominate a regression-based wavelet estimator in terms of smaller root mean squared error. These findings are derived from a simulation study and application to computer traffic traces.

The Lobatto Cell: Robust, Explicit, Higher Order FDTD That Handles Inhomogeneous Media

To improve numerical dispersion and second-order convergence behavior of the traditional Yee finite-difference time-domain (FDTD) algorithm, various higher order finite difference implementations have been proposed. Many have difficulty handling interfaces between distinct dielectric media or metallic sheets, because the high-order Taylor expansions on which these codes are based are invalidated by field or derivative discontinuities. One-sided extensions/extrapolations are a common approach to remedy interface discontinuities. Here, another approach based upon Whitney form, mass lumped finite elements is pursued to develop the ldquoLobatto Cell,rdquo a high-order replacement for the Yee cell with appropriate continuity behavior at contrasting media interfaces. The Lobatto Cell retains many robust features of the Yee method (discrete conservation laws, a guarantee of conditional stability and straightforward explicit updating), but provides higher order interpolation and dispersion error convergence. A notable drawback of the method is larger modeling granularity (staircasing), which is managed here by combining the Lobatto Cell method with preexisting, robust subgridding techniques.

Coherent-subspace array processing based on wavelet covariance: an application to broad-band, seismo-volcanic signals

SUMMARY Long-Period (LP) and Very-Long-Period (VLP) signals are the most characteristic seismic signature of volcano dynamics, and provide important information about the physical processes occurring in magmatic and hydrothermal systems. These events are usually characterized by sharp spectral peaks, which may span several frequency decades, by emergent onsets, and by a lack of clear S-wave arrivals. These two latter features make both signal detection and location a challenging task. In this paper, we propose a processing procedure based on Continuous Wavelet Transform of multichannel, broad-band data to simultaneously solve the signal detection and location problems. Our method consists of two steps. First, we apply a frequency-dependent threshold to the estimates of the array-averaged WCO in order to locate the time-frequency regions spanned by coherent arrivals. For these data, we then use the time-series of the complex wavelet coefficients for deriving the elements of the spatial Cross-Spectral Matrix. From the eigenstructure of this matrix, we eventually estimate the kinematic signals' parameters using the MUltiple SIgnal Characterization (MUSIC) algorithm. The whole procedure greatly facilitates the detection and location of weak, broad-band signals, in turn avoiding the time-frequency resolution trade-off and frequency leakage effects which affect conventional covariance estimates based upon Windowed Fourier Transform. The method is applied to explosion signals recorded at Stromboli volcano by either a short-period, small aperture antenna, or a large-aperture, broad-band network. The LP (0.2 2 s) of the explosion recordings from the broad-band network. Source locations obtained this way are fully compatible with those retrieved from application of more traditional (and computationally expensive) time-domain techniques, such as the Radial Semblance method.

Time–Frequency Signal Analysis for Nondestructive Evaluation of Pile with Cap

As stress waves decay as they pass through the pile foundation system, it is extremely challenging for all nondestructive testing methods to evaluate the pile integrity of a shaft underneath a structure. In this study, time–frequency signal analysis (TFSA) is used for signal processing and adopted to interpret the pile integrity testing signal. An experimental case with pile lengths of 58m with caps, were tested by the low strain sonic echo method. Traditional time domain analyses can not identify the pile tip response signals 58m lengths. After time-history curves are transformed into a time–frequency domain distribution, the results indicate the pile tip can be located more easily and clearly than the traditional time-domain analyses of pile integrity testing allowed for.

An Integrated Pulsed Interference Mitigation for GNSS Receivers

The E5/L5 frequency band for the new Global Navigation Satellite System (GNSS) signals is crowded with aeronautical pulsed emitters. This results in severe degradation of the performance of GNSS receivers. This paper describes a novel technique for estimating and suppressing time-varying pulsed interference signals such as the Distance Measuring Equipment (DME)/Tactical Air Navigation (TACAN) signals generated by these pulsed emitters. The proposed technique involves the integration of the time-based pulse blanker and the wavelet-based interference mitigation technique. Aviation is the key application considered although many other applications such as transport management and navigation, environmental monitoring, and telecommunications would benefit. A performance assessment of the new technique is carried out by determining the degradation of the carrier-to-noise ratio (CNR) at the output of the correlator. The performance of the new technique is compared with the traditional time domain pulse blanking approach. The results show that the proposed technique performs better than both the time domain pulse blanker and the wavelet-based interference mitigation algorithm. Hence, the integrated pulse mitigation approach can be employed to provide an enhanced degree of interference detection and suppression.

Multiscale Analysis of Heart Rate Dynamics: Entropy and Time Irreversibility Measures

Cardiovascular signals are largely analyzed using traditional time and frequency domain measures. However, such measures fail to account for important properties related to multiscale organization and non-equilibrium dynamics. The complementary role of conventional signal analysis methods and emerging multiscale techniques, is, therefore, an important frontier area of investigation. The key finding of this presentation is that two recently developed multiscale computational tools--multiscale entropy and multiscale time irreversibility--are able to extract information from cardiac interbeat interval time series not contained in traditional methods based on mean, variance or Fourier spectrum (two-point correlation) techniques. These new methods, with careful attention to their limitations, may be useful in diagnostics, risk stratification and detection of toxicity of cardiac drugs.

Spectral Domain Optical Coherence Tomography and Glaucoma

Glaucoma may be the second leading cause of blindness in the world, affecting about 60 million people globally.1,2 The true prevalence may be underestimated as up to half of patients with glaucoma are undiagnosed, and a large proportion of glaucoma patients who are eligible for registration as legally blind remain unregistered.3–7 Glaucoma is a characteristic optic neuropathy characterized by retinal ganglion cell death, which then leads to retinal nerve fiber layer (RNFL) thinning and optic nerve head (ONH) cupping. The most important risk factor is elevated intraocular pressure. Since these structural changes in the RNFL and ONH may result in irreversible visual field (VF) loss,8,9 the early diagnosis of glaucoma is vital for the early initiation of treatment that may stop or slow down further permanent vision loss. One reason why early diagnosis often does not occur is that patients are usually asymptomatic early in their disease. Another problem preventing early diagnosis is that the standard clinical methods for diagnosing glaucoma (ie, VF testing) can only diagnose glaucomatous vision loss after up to 40% of the nerve tissue is lost irreversibly.10–13 VF testing is also not an ideal method to diagnose glaucoma because these tests rely on not only the subjective test response of the patient but also the subjective interpretation of the physician. Because of the need to diagnose glaucoma not only earlier but also in a more objective manner, various imaging technologies have been developed over the past decade in an attempt to quantitatively analyze progressive glaucomatous structural changes, such as RNFL thinning and/or ONH cupping, both of which are known to precede clinically detectable VF defects. So far, there are 3 main commercially available imaging technologies that are used to image glaucomatous structural changes: confocal scanning laser ophthalmoscopy (CSLO) (Heidelberg Retina Tomograph—HRTII and III, Heidelberg Engineering, Germany), scanning laser polarimetry (SLP) (GDxVCC, Carl Zeiss Meditec Inc, Dublin, CA), and optical coherence tomography (OCT). We feel that spectral domain optical coherence tomography (SDOCT), also called Fourier domain OCT, has the greatest potential for imaging glaucomatous structural changes. Before describing SDOCT in more detail, we will describe the science as to why CSLO, SLP, and traditional time domain optical coherence tomography (TDOCT) have not been proven to be better than a complete eye examination (which includes VF testing and stereo disc photography).14,15