Sinusoidal Components Research Articles

A novel ultrasound based technique for classifying gas bubble sizes in liquids

Characterizing gas bubbles in liquids is crucial to many biomedical, environmental and industrial applications. In this paper a novel method is proposed for the classification of bubble sizes using ultrasound analysis, which is widely acknowledged for being non-invasive, non-contact and inexpensive. This classification is based on 2D templates, i.e. the average spectrum of events representing the trace of bubbles when they cross an ultrasound field. The 2D patterns are obtained by capturing ultrasound signals reflected by bubbles. Frequency-domain based features are analyzed that provide discrimination between bubble sizes. These features are then fed to an artificial neural network, which is designed and trained to classify bubble sizes. The benefits of the proposed method are that it facilitates the processing of multiple bubbles simultaneously, the issues concerning masking interference among bubbles are potentially reduced and using a single sinusoidal component makes the transmitter–receiver electronics relatively simpler. Results from three bubble sizes indicate that the proposed scheme can achieve an accuracy in their classification that is as high as 99%.

The Influence of Time Truncation on Phase Angle Measurement Principle

Real-time accurate voltage phase angle measurement data has a very important significance to monitor and analyze the power system, and phase angle measurement principle of Fourier transform plays an important role in the theoretical calculations and engineering applications. The dynamic sinusoidal voltage signal contains two parts of the sinusoidal steady-state component and decaying DC component, and the decaying DC component having a continuous spectrum, at the frequency corresponding to the sinusoidal steady-state component must have a non-zero value, making dynamic signal phase than steady signal phase has one extra deviation angle. Considering Fourier transform method and theory of engineering application are different, this paper only considered the application conditions of time truncation, analyzes continuous Fourier transform under a real eigenvalue and a pair of conjugate complex roots condition, then compared with the theoretical calculation, for the two case of limited time integration and theoretical calculation condition, the phase angle difference and influencing factors are given.

Prony’s Method with Reduced Sampling - Numerical Aspects

Abstract This paper presents a new modification of the least-squares Prony’s method with reduced sampling, which allows for a significant reduction in the number of the analysed signal samples collected per unit time. The specific combination of non-uniform sampling with Prony’s method enables sampling of the analysed signals at virtually any average frequency, regardless of the Nyquist frequency, maintaining high accuracy in parameter estimation of sinusoidal signal components. This property allows using the method in measuring devices, such as for electric power quality testing equipped with low power signal processors, which in turn contributes to reducing complexity of these devices. This paper presents research on a method for selecting a sampling frequency and an analysis window length for the presented method, which provide maximum estimation accuracy for Prony’s model component parameters. This paper presents simulation tests performed in terms of the proposed method application for analysis of harmonics and interharmonics in electric power signals. Furthermore, the paper provides sensitivity analysis of the method, in terms of common interferences occurring in the actual measurement systems.

Spacing and shape of random peaks in non-parametric spectrum estimates.

In this paper, expressions are derived for the expected number of spurious peaks in a spectrum estimate, that is, crossings above a given significance level per frequency unit, as well as the expected width of these peaks. In numerous scientific applications, spectrum estimates are used for the purpose of identifying sinusoidal or modal components, often thinning large sets of candidate frequencies with coincidence detection. Because one always expects numerous false peaks in a spectrum estimate, knowing the expected rate of false peaks helps to decide whether the number observed is abnormal and hence determine the true nature of the process. An example using solar wind data from the Advanced Composition Explorer is given where spectra display pathological numbers of significant peaks, while temporally permuted versions of the data possess spectra with the number expected for a white, Gaussian process. The permutation test is a valuable diagnostic for processes suspected to contain many line components.

The Irremovable Properties Proof of Decaying DC Component for Dynamic Phasor Measurement

Dynamic voltage can be described by two parts in time domain, sinusoidal steady state component and dynamic state component. The latter reflects the effect of the system’s characteristic root, and is also called decaying DC component. Decaying exponential signal has continuous spectrum, and this characteristic has a bad effect on the accuracy of phase angle’s measurement, therefore the idea of filtering the decaying exponential signal was proposed. To verify the possibility of this proposal, this paper analyzes the frequency formation of dynamic voltage signal mathematically, and points out that at the frequency of the sinusoidal component, measured voltage signal’s time domain description is the superposition of two sinusoidal signals with the same frequency, different phase angles and different amplitudes. This is the reason for the deviation between the measured voltage angle and the theoretical phase angle. The deviation angle not only shows the combined action of steady component and dynamic component, but also illustrates that the decaying exponential signal cannot be filtered out.

Generating controllable velocity fluctuations using twin oscillating hydrofoils: experimental validation

AbstractA method for generating controllable two-dimensional velocity fluctuations using two pitching foils was derived theoretically in a previous companion paper. The present work describes the experimental implementation of the method. The experiments are carried out in a re-circulating water channel optimised to provide low turbulence intensity in the incoming flow. Velocities are measured using an acoustic Doppler velocimeter (ADV). The pitching motions of the foils are position-controlled using a closed-loop control system. Two velocity fluctuation patterns are investigated. They consist of a combination of sinusoidal components. Theoretical predictions and experimental measurements are compared in the time and frequency domain. Although some discrepancies are observed, the agreement is generally good and therefore validates the theoretical method for the conditions investigated.

Comments on "A New Feedforward Hybrid ANC System" - An addendum

The authors of the original article [ibid, vol. 18, no. 10, pp. 591-594, 2011] have submitted the Matlab code they used in their simulations. In their reply they insist that the traditional, broadband ANC system "may become awkward and its performance 'may degrade' seriously when the reference and primary noise signals contain both low-frequency sinusoid and wideband noise component and its convergence is made relatively fast." The "awkwardness" is expressed by the existence of the "firework" noise. In this comment the author does not question the possibility of the "firework" noise to appear in the output signal. He provides a proof that the reason the original authors give for the "fireworks" is wrong, and that the performance degradation was to be expected.

Least-squares fitting of time-domain signals for Fourier transform mass spectrometry.

To advance Fourier transform mass spectrometry (FTMS)-based molecular structure analysis, corresponding development of the FTMS signal processing methods and instrumentation is required. Here, we demonstrate utility of a least-squares fitting (LSF) method for analysis of FTMS time-domain (transient) signals. We evaluate the LSF method in the analysis of single- and multiple-component experimental and simulated ion cyclotron resonance (ICR) and Orbitrap FTMS transient signals. Overall, the LSF method allows one to estimate the analytical limits of the conventional instrumentation and signal processing methods in FTMS. Particularly, LSF provides accurate information on initial phases of sinusoidal components in a given transient. For instance, the phase distribution obtained for a statistical set of experimental transients reveals the effect of the first data-point problem in FT-ICR MS. Additionally, LSF might be useful to improve the implementation of the absorption-mode FT spectral representation for FTMS applications. Finally, LSF can find utility in characterization and development of filter-diagonalization method (FDM) MS.

A Generalized Lattice Filter for Finite Wordlength Implementation With Reduced Number of Multipliers

The excellent finite wordlength (FWL) property of lattice digital filters is well known. The four-multiplier normalized lattice, with signal power at all delay elements normalized to unity, has particular advantage in its overflow property. However, when used to implement an Nth-order digital filter, the normalized lattice implementation requires 5N+1 multipliers. There exists another lattice structure with excellent FWL property called the injected numerator lattice structure. In this paper, we combine the injected numerator lattice and tapped numerator lattice to form a new hybrid lattice structure, which is not only canonic in the number of multipliers resulting in a significant reduction in overall implementation cost but also exhibits much better FWL properties than the normalized lattice structure. An improved “peakedness” measure is also introduced for application where the input signal has a strong time varying sinusoidal component. The new structure requires a few additional adders; it can be used to implement any causal and stable z-transform transfer function. Two numerical examples are presented to demonstrate the performance of the proposed structure.

Beam smoothing characteristics of multi-central frequency and multi-color smoothing by spectral dispersion.

A multi-central frequency and multi-color smoothing by spectral dispersion (SSD) scheme is presented for better beam smoothing than conventional SSD. One of the difficulties in conventional SSD is the narrow bandwidth limited by efficiency frequency conversion. The new scheme has overcome this problem by using multi-central frequency laser sources and a multi-color beam smoothing system. The multi-central frequency laser sources are incoherent combinations of several pulses in the time domain, each with different central frequencies and independent sinusoidal frequency-modulated components. Then, the laser beams from the multi-central frequency laser sources transmit in the multi-color smoothing system, spatially separated and independently spectrally dispersed by gratings array, independently achieve the third harmonic generation in KDP array with independent phase-matching for efficient conversion. Moreover, by adjusting the dispersion direction of the gratings to be perpendicular to each other, it is an effective way to achieve a 2D beam smoothing effect on the focal plane. Simulation results show that the novel beam smoothing scheme performs better than the conventional SSD.

A HYBRID MODE MODEL OF THE BLAZHKO EFFECT, SHOWN TO ACCURATELY FITKEPLERDATA FOR RR Lyr

The waveform for Blazhko stars can be substantially different during the ascending and descending parts of the Blazhko cycle. A hybrid model, consisting of two component oscillators of the same frequency, is proposed as a means to fit the data over the entire cycle. One component exhibits a sawtooth-like velocity waveform while the other is nearly sinusoidal. One method of generating such a hybrid is presented: a nonlinear model is developed for the first overtone mode, which, if excited to large amplitude, is found to drop strongly in frequency and become highly non-sinusoidal. If the frequency drops sufficiently to become equal to the fundamental frequency, the two can become phase locked and form the desired hybrid. A relationship is assumed between the hybrid mode velocity and the observed light curve, which is approximated as a power series. An accurate fit of the hybrid model is made to actual Kepler data for RR Lyr. The sinusoidal component may tend to stabilize the period of the hybrid which is found in real Blazhko data to be extremely stable. It is proposed that the variations in amplitude and phase might result from a nonlinear interaction with a third mode, possibly a nonradial mode at 3/2 the fundamental frequency. The hybrid model also applies to non-Blazhko RRab stars and provides an explanation for the light curve bump. A method to estimate the surface gravity is also proposed.

Sensory reweighting dynamics in human postural control

Healthy humans control balance during stance by using an active feedback mechanism that generates corrective torque based on a combination of movement and orientation cues from visual, vestibular, and proprioceptive systems. Previous studies found that the contribution of each of these sensory systems changes depending on perturbations applied during stance and on environmental conditions. The process of adjusting the sensory contributions to balance control is referred to as sensory reweighting. To investigate the dynamics of reweighting for the sensory modalities of vision and proprioception, 14 healthy young subjects were exposed to six different combinations of continuous visual scene and platform tilt stimuli while sway responses were recorded. Stimuli consisted of two components: 1) a pseudorandom component whose amplitude periodically switched between low and high amplitudes and 2) a low-amplitude sinusoidal component whose amplitude remained constant throughout a trial. These two stimuli were mathematically independent of one another and, thus, permitted separate analyses of sway responses to the two components. For all six stimulus combinations, the sway responses to the constant-amplitude sine were influenced by the changing amplitude of the pseudorandom component in a manner consistent with sensory reweighting. Results show clear evidence of intra- and intermodality reweighting. Reweighting dynamics were asymmetric, with slower reweighting dynamics following a high-to-low transition in the pseudorandom stimulus amplitude compared with low-to-high amplitude shifts, and were also slower for inter- compared with intramodality reweighting.

Hilbert-Huang processing for single-exposure two-dimensional grating interferometry

Single-shot crossed-type fringe pattern processing and analysis method called Hilbert-Huang grating interferometry (HHGI) is proposed. It consist of three main procedures: (1) crossed pattern is resolved into two fringe families using novel orthogonal empirical mode decomposition approach, (2) separated fringe sets are filtered using modified automatic selective reconstruction aided by enhanced fast empirical mode decomposition and mutual information detrending, and (3) Hilbert spiral transform is employed for fringe phase demodulation. Numerical and experimental studies corroborate the validity, versatility and robustness of the proposed HHGI technique. It can be successfully applied to multiplicative and additive type crossed patterns with sinusoidal and binary orthogonal component structures. Efficient adaptive filtering enables successful fast processing and analysis of complex and defected patterns.

Detecting multiple periodicities in observational data with the multifrequency periodogram—II. Frequency Decomposer, a parallelized time-series analysis algorithm

This is a parallelized algorithm performing a decomposition of a noisy time series into a number of sinusoidal components. The algorithm analyses all suspicious periodicities that can be revealed, including the ones that look like an alias or noise at a glance, but later may prove to be a real variation. After selection of the initial candidates, the algorithm performs a complete pass through all their possible combinations and computes the rigorous multifrequency statistical significance for each such frequency tuple. The largest combinations that still survived this thresholding procedure represent the outcome of the analysis. The parallel computing on a graphics processing unit (GPU) is implemented through CUDA and brings a significant performance increase. It is still possible to run FREDEC solely on CPU in the traditional single-threaded mode, when no suitable GPU device is available. To verify the practical applicability of our algorithm, we apply it to an artificial time series as well as to some real-life exoplanetary radial-velocity data. We demonstrate that FREDEC can successfully reveal several known exoplanets. Moreover, it detected a new $9.8$-day variation in the Lick data for the five-planet system of 55 Cnc. It might indicate the existence of a small sixth planet in the 3:2 commensurability with the planet 55 Cnc b, although this detection is model-dependent and still needs a detailed verification.

The Two Approaches of Surface-Texture Optimization in Thin-Film Silicon Solar Cells

Textured interfaces in thin-film silicon solar cells can increase the photocurrent of the devices. However, the challenge is how to design textures (periodic or random) that could outperform the state-of-the-art random ones. Moreover, the textures should enable defect-less semiconductor layer growth, which has often been neglected in the past, resulting in the low open-circuit voltage and fill factor of the devices. In this paper, we present two approaches for the systematic optimization of surface-textures: bottom-up and top-down. Fully 3-D optical simulations, including calibrated nonconformal layer growth model were employed to predict gains in short-circuit current densities in a micromorph solar cell (bottom-up approach) and a single-junction amorphous silicon solar cell (top-down approach). In the bottom-up approach, we start with a simple sinusoidal component and change its shape systematically in the direction of broader valleys, also resulting in better conditions for the layer growth. In the top-down approach, we start from a random texture (morphology fingerprint taken from Asahi U type substrate) and modify it in a spatial frequency domain. We show the role of the presence/absence of different frequency regions as well as the important role of the phase spectrum on the optical characteristics of the device. In both approaches, improved textures have the potential to outperform state-of-the-art random ones, not only from optical point of view but in terms of conversion efficiency as well.

Modified shuffled frog leaping algorithm with genetic algorithm crossover for solving economic load dispatch problem with valve-point effect

This paper addresses a hybrid solution methodology involving modified shuffled frog leaping algorithm (MSFLA) with genetic algorithm (GA) crossover for the economic load dispatch problem of generating units considering the valve-point effects. The MSFLA uses a more dynamic and less stochastic approach to problem solving than classical non-traditional algorithms, such as genetic algorithm, and evolutionary programming. The potentiality of MSFLA includes its simple structure, ease of use, convergence property, quality of solution, and robustness. In order to overcome the defects of shuffled frog leaping algorithm (SFLA), such as slow searching speed in the late evolution and getting trapped easily into local iteration, MSFLA with GA cross-over is put forward in this paper. MSFLA with GA cross-over produces better possibilities of getting the best result in much less global as well as local iteration as one has strong local search capability while the other is good at global search. This paper proposes a new approach for solving economic load dispatch problems with valve-point effect where the cost function of the generating units exhibits non-convex characteristics, as the valve-point effects are modeled and imposed as rectified sinusoid components. The combined methodology and its variants are validated for the following four test systems: IEEE standard 30 bus test system, a practical Eastern Indian power grid system of 203 buses, 264 lines, and 23 generators, and 13 and 40 thermal units systems whose incremental fuel cost function take into account the valve-point loading effects. The results are quite promising and effective compared with several benchmark methods.

Parametric Audio Coding With Exponentially Damped Sinusoids

Sinusoidal modeling is one of the most popular techniques for low bitrate audio coding. Usually, the sinusoidal parameters (amplitude, pulsation and phase of each sinusoidal component) are kept constant within a time segment. An alternative model, the so-called Exponentially-Damped Sinusoidal (EDS) model, includes an additional damping parameter for each sinusoidal component to better represent the signal characteristics. It was however never shown that the EDS model could be efficient for perceptual audio coding. To that aim, we propose in this paper an efficient analysis/synthesis framework with dynamic time-segmentation on transients and psychoacoustic modeling, and an asymptotically optimal entropy-constrained quantization method for the four sinusoid parameters (e.g., including damping). We then apply this coding technique to real audio excerpts for a given entropy target corresponding to a low bitrate (20 kbits/s), and compare this method with a classical sinusoidal coding scheme using a constant-amplitude sinusoidal model and the perceptually weighted Matching Pursuit algorithm. Subjective listening tests show that the EDS model is more efficient on audio samples with fast transient content, and similar to the classical model for more stationary audio samples.

Stochastic-Deterministic MMSE STFT Speech Enhancement With General A Priori Information

A wide range of Bayesian short-time spectral amplitude (STSA) speech enhancement algorithms exist, varying in both the statistical model used for speech and the cost functions considered. Current algorithms of this class consistently assume that the distribution of clean speech short time Fourier transform (STFT) samples are either randomly distributed with zero mean or deterministic. No single distribution function has been considered that captures both deterministic and random signal components. In this paper a Bayesian STSA algorithm is proposed under a stochastic-deterministic (SD) speech model that makes provision for the inclusion of a priori information by considering a non-zero mean. Analytical expressions are derived for the speech STFT magnitude in the MMSE sense, and phase in the maximum-likelihood sense. Furthermore, a practical method of estimating the a priori SD speech model parameters is described based on explicit consideration of harmonically related sinusoidal components in each STFT frame, and variations in both the magnitude and phase of these components between successive STFT frames. Objective tests using the PESQ measure indicate that the proposed algorithm results in superior speech quality when compared to several other speech enhancement algorithms. In particular it is clear that the proposed algorithm has an improved capability to retain low amplitude voiced speech components in low SNR conditions.

Approach to direct coning/sculling error compensation based on the sinusoidal modelling of IMU signal

A direct coning mitigation algorithm based on the detection of a sinusoidal component in the gyro measurements is proposed. The coning error, which is one of dominant error sources affecting the accuracy of attitude computation in the inertial navigation system (INS), is induced by the sinusoidal motion such as a manoeuvre of vehicle or the vibration of a dithering of ring laser gyro. However, many researchers have developed coning error mitigation algorithms based on the higher-order polynomial model and its correction terms are extracted from the gyro output without faithful consideration of the periodicity of motion. Hence, the authors first detect and estimate the sinusoidal components from gyro measurements, and then find the higherorder correction terms from the estimated sinusoidal parameters. The authors also show that this algorithm can be applied to the mitigation of sculling error because of its duality to the coning motion. Simulation results show that the direct compensation algorithm works effectively for the navigation of vehicles with continuous and steady oscillations. Also, the rate table test with HG1700 inertial measurement unit (IMU) is conducted to show the effectiveness of proposed algorithm on real INS signal.

Tracking and removing modulated sinusoidal components: A solution based on the kurtosis and the Extended Kalman Filter

This work describes an automatic method for removing modulated sinusoidal components in signals. The method consists in using the Optimized Spectral Kurtosis for initializing Series of Extended Kalman Filters.The first section is an introduction to vibration applications with Kalman Filters and modulated sinusoids. The detection process with OSK is described in the second section. The third section concerns the tracking algorithm with SEKF for amplitude and frequency modulated sinusoidal components. The last section deals with the complete process illustrated with an experimental application on a rotating machine.