Components Of Different Frequencies Research Articles

Beneficial effects of antisymmetric nonlinear damping with application to energy harvesting and vibration isolation under general inputs

Beneficial effects of nonlinear damping on energy harvesting and vibration isolation under harmonic inputs have been investigated showing that the introduction of nonlinear damping can increase the harvested energy and reduce the vibration over both the resonant and higher frequency ranges. However, the scenario becomes more complicated when the loading inputs are of more general form such as multi-tone and random inputs, which can produce system responses that are induced by an interaction of system input components of different frequencies. In the present study, by introducing the concept of power transmissibility, the study of the beneficial effects of nonlinear damping is extended to the systems subject to general inputs including both multi-tone and random inputs. A rigorous analysis is conducted based on single degree of freedom systems subject to general inputs. The analysis reveals the conditions under which the antisymmetric nonlinear damping is beneficial for improving energy harvester performance and reducing of the power of system output in vibration isolation. Moreover, the beneficial effects are demonstrated by two case studies.

Effect of helical twist angle on the aerodynamic performance and blade dynamic characteristics of floating vertical axis wind turbines

Due to the low fluctuation of aerodynamic torque, the helical blade floating vertical axis wind turbine (FVAWT) is a promising optimization structure compared with the traditional straight blade FVAWT. The helical twist angle plays a significant role in wind turbine design and operation. In this research, the effect of the helical twist angle on the aerodynamic performance and blade dynamic characteristics are investigated. A slack coupled modeling method is applied to model a 5 MW helical blade FVAWT system. Verification is conducted in comparison with a rigid body code and ANSYS software. Then a comparative study is conducted under seven cases with helical twist angles of 0°, 60°, 90°, 100°, 110°, 120° and 150°. The results show that helical twist angles ranging from 90° to 120° could significantly restrain the fluctuation of aerodynamic torque and suppress blade deformation. The varying regularity of blade deformation under different cases is affected by both aerodynamic force and blade stiffness characteristics. In addition, for blade deformation, 1 P and its frequency multiplication, the sum and difference frequency components of 1 P and wave frequency are observed in the amplitude spectrum. For the design of the FVAWT, the natural frequency of the blade should be far from the above frequencies to avoid resonant vibration. This study could provide a feasible mathematical method for the dynamic modeling of helical blade FVAWTs. Additionally, the range of helical twist angles recommended in this paper can be referred to when designing a helical blade.

Inspection method of combine assembly quality based on optimized VMD

Aiming at the problems of low assembly accuracy and difficult to detect assembly quality of combine, a method of combine assembly quality detection based on sparrow search algorithm (SSA) optimized variational mode decomposition (VMD) and particle swarm optimization (PSO) optimized least squares support vector machine (LSSVM) was proposed, Firstly, the sparrow search algorithm is used to obtain the optimal VMD decomposition modal parameter K and penalty factor α, then the combined vibration signal of combine harvester is decomposed into intrinsic modal components of different center frequencies by using the best parameter combination [K, α]. Finally, the feature vector is used as the input of LSSVM classifier to classify different fault features. The analysis results show that the classification accuracy of SSA-VMD joint feature extraction method is 99.5%, which is 17.5% and 9.5% higher than ensemble empirical mode decomposition (EEMD) and fixed parameter VMD, which verifies the superiority of this method in the detection of combine assembly quality.

Sum-frequency excitation of coherent magnons

Coherent excitation of magnons is conventionally achieved through Raman scattering processes, in which the difference-frequency components of the driving field are resonant with the magnon energy. Here, we describe mechanisms by which the sum-frequency components of the driving field can be used to coherently excite magnons through two-particle absorption processes. We use the Landau-Lifshitz-Gilbert formalism to compare the spin-precession amplitudes that different types of impulsive stimulated and ionic Raman scattering processes and their sum-frequency counterparts induce in an antiferromagnetic model system. We show that sum-frequency mechanisms enabled by linearly polarized driving fields yield excitation efficiencies comparable or larger than established Raman techniques, while elliptical polarizations produce only weak and circularly polarizations no sum-frequency components at all. The mechanisms presented here complete the map for dynamical spin control by the means of Raman-type processes.

Multiscale Entropy Analysis of Instantaneous Frequency Variation to Overcome the Cross-Over Artifact in Rhythmic EEG

Generally, for healthy adults, the entropy of electroencephalogram (EEG) signals gradually decreases from wake to sleep stages N1, N2, to N3, and increases during REM. However, some researchers found that multiscale entropy curves of sleep and wakefulness intercept, a cross-over phenomenon whose origin remains unexplored. The objective of the present work is to trace the origin of the cross-over phenomenon and to propose a workaround strategy. We simulated EEG by generating 1/f broadband signal and chirp signals with continuously varying frequencies. We then retrieved the rhythmic component from simulated EEG and real-world EEG and conducted MSE analysis of the instantaneous frequency variation (IFV) of the rhythmic component. The simulation revealed that this interception was ubiquitous in the MSE analysis of simulated EEG with rhythmic components of different frequencies. The cross-over point moved toward larger scale factors with the increasing sampling rate. We found that the MSE curve of IFV from real-world EEG for the wakefulness group was higher than that for sleep, showing no interception. These results suggest that (1) for a rhythmic signal like EEG, MSE analysis of the raw signal is highly affected by the rhythmic component, presenting artificial cross-over curves in sleep EEG study, (2) frequency variation of rhythmic components are complex signal which differs between wakefulness and sleep, in accordance with the complexity loss theory.

Study for Influence of Harmonic Magnetic Fields on Vibration Properties of Core of Anode Saturable Reactor in HVDC Converter Valve System

The cores of anode saturated reactor (ASR) are the main vibration source of the HVDC converter valve system. The ASR is excited with an impulse voltage, which contains many harmonic components, and the magnetostriction of cores is usually the main reason of the ASR vibration. Therefore it is significant to study the influence of the harmonic on the vibration of core of ASR. In this paper, the magneto-mechanical coupling model is established based on the magnetostriction theory and the expression of vibration acceleration in the presence of third harmonic is derived. The vibration test platform is built to test the core's vibration acceleration. The magnetic and magnetostrictive properties of silicon steel sheet under different working conditions are measured. The three-dimensional simulation model of the core is established, and the vibration acceleration under different magnetic flux density is calculated. The comparison of the experiment and simulation results shows the rationality of the magneto-mechanical coupling model. The influence of third harmonic magnetic flux density on vibration is studied by changing the phase of the third harmonic magnetic flux density and the ratio of the third harmonic magnetic flux density to the fundamental magnetic flux density. Both the calculated and measured results show that the third harmonic magnetic flux density affects the vibration acceleration according to the double-frequency components of the third harmonic, as well the sum-frequency and difference-frequency components of the third harmonic and fundamental frequency.

Numerical Study on Wave Radiation by a Barge with Large Amplitudes and Frequencies

A two-dimensional boundary element method is used to study the hydrodynamics of a single barge with prescribed motions of large amplitudes and high frequencies. The wave radiation problem is solved in the time domain based on the fully nonlinear potential flow theory. For numerical simulations, special treatments like plunging wave cutting and remeshing approaches are presented in detail. The numerical schemes are verified through comparing with analytical results. Both the generated outgoing wave amplitudes and hydrodynamic coefficients can be calculated with sufficient accuracy. Then, we focus on large heave, sway and roll motions to investigate the nonlinear effects on hydrodynamic forces, respectively. In particular, the heave motion with two frequencies is also simulated to study the interactions between results at different frequencies. It is interesting to see the sum and difference frequency components and the envelopes in time histories as a result. For forces caused by forced sway or roll motions, there are only even-order harmonics for vertical forces and only odd-order harmonics for horizontal forces. Finally, a single body with combined sway, heave and roll motion is studied to examine the interactions between motion modes.

Research of vibroacoustic signals in diagnostics of technical condition of engines of beet harvesters combines

The authors of the experimental studies have proved from the possibility of vibration signals to detect the faults and changes in the parameters of the technical condition of engines of beet harvesters combines at the primary stages of their occurrence. Ensuring the predicted reliability of the conclusions, regarding the technical condition of the mechanisms and system of the engine, it can be achieved using the statistical evaluation of the correspondence of the temporal frequency fragments of the vibroacoustic signals and their correspondence to the rotational speed of the crankshaft. The authors investigated the difference between physical models and methods of their mathematical description in different parts of the frequency range and proved the feasibility of dividing it into three frequency subbands: low (0–200 Hz), medium (200–1000 Hz) and high (1 to 10–20 kHz). The authors found out that the series of harmonic signals of engines are characterized by the amplitudes, frequencies and initial phases, whose algebraic sum of ordinates at any given time is equal to the ordinate of the non-sinusoidal signal. Therefore, the Fourier series should be written as the sum of an infinite number of harmonic components of different frequencies. To distinguish the spectrum of the vibroacoustic signal in the diagnosis of the technical condition of engines of beet harvesters combines, it is necessary to use a Fast Fourier Transform. The processing of vibroacoustic signals in the diagnosis of the technical condition parameters of engines of beet harvesters combines is carried out using digital filters, which are implemented by the author’s algorithm.

Effects of asset frequency components on value-at-risk in emerging and developed markets

Value-at-Risk was estimated using the technique of wavelet decomposition with goal to analyze the frequency components' impacts on variances of daily stock returns, and on forecasts. Daily returns of twenty-one shares of the Ibovespa and daily returns of twenty-two shares of the DJIA were used. The model was applied to the reconstructed returns to model and establish the prediction of conditional variance, applying the rolling window technique. The Value-at-Risk was then estimated, and the results showed that the DJIA shares showed more efficient market behavior than those of Ibovespa. The differences in behavior induces to affirm that VaRs, used in the analysis of financial assets from different markets with different governance premises, should be estimated by series of returns reconstructed by aggregations of components of different frequencies. A set of back-testing was applied to confront the estimated , which demonstrated that the estimation of models are consistent.

Dynamic acoustic tractor beams II: Oscillatory powers, cross sections, and energy efficiencies of a spherical non-viscous liquid droplet

A previous work on dynamic acoustic tractor beams [Mitri, J. Appl. Phys. 117, 094903 (2015)] demonstrated the feasibility of pulling a liquid sphere toward a finite circular piezo-disk transducer and vibrating it around an equilibrium position at the beat frequency of two interfering waves driven at slightly different frequencies. The analysis is extended here to investigate the oscillatory phenomenon from the standpoint of energy conservation applied to scattering. Expressions for dynamic scattering, extinction and absorption powers, and their related cross sections and energy efficiencies are formally defined and derived based on the partial-wave series expansion method in spherical coordinates and the short-term time averaging (STTA) procedure. A circular flat piston transducer insonifying a spherical liquid hexane droplet (with arbitrary radius) centered on the axis of wave propagation is considered. Numerical predictions for dynamic extinction and scattering energy efficiencies illustrate the theory. A percentage error criterion related to extinction and scattering energy efficiencies is defined. Computations are also performed to quantify the numerical inaccuracy introduced by the difference-frequency component of the STTA. This criterion must be always utilized as a benchmark tool to validate dynamic radiation force computations. The results show that the percent error (induced by the difference-frequency component of the STTA process) increases as the dimensionless difference-frequency Δka increases. The present analysis is of some importance to validate dynamic radiation force numerical computations from the standpoint of energy conservation, used in the design and optimization of dynamic/oscillatory acoustic tractor beams and single-beam tweezers.

Nonlinear Maximization of the Sum-Frequency Component from Two Ultrasonic Signals in a Bubbly Liquid.

Techniques based on ultrasound in nondestructive testing and medical imaging analyze the response of the source frequencies (linear theory) or the second-order frequencies such as higher harmonics, difference and sum frequencies (nonlinear theory). The low attenuation and high directivity of the difference-frequency component generated nonlinearly by parametric arrays are useful. Higher harmonics created directly from a single-frequency source and the sum-frequency component generated nonlinearly by parametric arrays are attractive because of their high spatial resolution and accuracy. The nonlinear response of bubbly liquids can be strong even at relatively low acoustic pressure amplitudes. Thus, these nonlinear frequencies can be generated easily in these media. Since the experimental study of such nonlinear waves in stable bubbly liquids is a very difficult task, in this work we use a numerical model developed previously to describe the nonlinear propagation of ultrasound interacting with nonlinearly oscillating bubbles in a liquid. This numerical model solves a differential system coupling a Rayleigh–Plesset equation and the wave equation. This paper performs an analysis of the generation of the sum-frequency component by nonlinear mixing of two signals of lower frequencies. It shows that the amplitude of this component can be maximized by taking into account the nonlinear resonance of the system. This effect is due to the softening of the medium when pressure amplitudes rise.

Nonlinear dynamics of coupled transverse-rotational waves in granular chains.

The nonlinear dynamics of coupled waves in one-dimensional granular chains with and without a substrate is theoretically studied accounting for quadratic nonlinearity. The multiple time scale method is used to derive the nonlinear dispersion relations for infinite granular chains and to obtain the wave solutions for semi-infinite systems. It is shown that the sum frequency and difference frequency components of the coupled transverse-rotational waves are generated due to their nonlinear interactions with the longitudinal wave. Nonlinear resonances are not present in the chain with no substrate where these frequency components have low amplitudes and exhibit beating oscillations. In the chain positioned on a substrate two types of nonlinear resonances are predicted. At resonance, the fundamental frequency wave amplitudes decrease and the generated frequency component amplitudes increase along the chain, accompanied by the oscillations due to the wave number asynchronism. The results confirm the possibility of a highly efficient energy transfer between the waves of different frequencies, which could find applications in the design of acoustic devices for energy transfer and energy rectification.

Optimization of Feedforward Neural Networks Using an Improved Flower Pollination Algorithm for Short-Term Wind Speed Prediction

It is well known that the inherent instability of wind speed may jeopardize the safety and operation of wind power generation, consequently affecting the power dispatch efficiency in power systems. Therefore, accurate short-term wind speed prediction can provide valuable information to solve the wind power grid connection problem. For this reason, the optimization of feedforward (FF) neural networks using an improved flower pollination algorithm is proposed. First of all, the empirical mode decomposition method is devoted to decompose the wind speed sequence into components of different frequencies for decreasing the volatility of the wind speed sequence. Secondly, a back propagation neural network is integrated with the improved flower pollination algorithm to predict the changing trend of each decomposed component. Finally, the predicted values of each component can get into an overlay combination process and achieve the purpose of accurate prediction of wind speed. Compared with major existing neural network models, the performance tests confirm that the average absolute error using the proposed algorithm can be reduced up to 3.67%.

Nuovi scenari sulle tecniche PMRI: il compressed sense

This Project Work intends to illustrate the technique of Compressed Sense (CS), innovative method introduced in thefield of signal processing, which allows you to capture signals and images with far fewer samplings than “needed”,reducing scan times up to 50% and offering accurate and high resolution images.The Compressed Sense technique can be successfully applied for Imaging in Magnetic Resonance as it satisfies theproperties of sparsity and incoherent. One of the primary requirements of the CS is based on the use of particularmathematical bases, whose function will be to represent the sampled functions. Between these, the Wavelet basesare of considerable importance as they subdivide the data in question into components of different frequencies, andtherefore allow to study every component of the frequency spectrum with a resolution matched to its scale, such as,for example, those that are used in the encoding of images with the JPEG-2000. The Compressed Sense technique hasallowed us to overcome the intrinsic physical limits inherent in the matter, developing a technique that continues toevolve and expand, improving and refining.

Nuovi scenari sulle tecniche PMRI: il compressed sense

This Project Work intends to illustrate the technique of Compressed Sense (CS), innovative method introduced in the field of signal processing, which allows you to capture signals and images with far fewer samplings than "needed", reducing scan times up to 50% and offering accurate and high resolution images. The Compressed Sense technique can be successfully applied for Imaging in Magnetic Resonance as it satisfies the properties of sparsity and incoherent. One of the primary requirements of the CS is based on the use of particular mathematical bases, whose function will be to represent the sampled functions. Between these, the Wavelet bases are of considerable importance as they subdivide the data in question into components of different frequencies, and therefore allow to study every component of the frequency spectrum with a resolution matched to its scale, such as, for example, those that are used in the encoding of images with the JPEG-2000. The Compressed Sense technique has allowed us to overcome the intrinsic physical limits inherent in the matter, developing a technique that continues to evolve and expand, improving and refining.

Análisis de la serie de captura de sardina Monterrey, Sardinops sagax en el Golfo de California, México

Background: The Pacific sardine is a small pelagic fish which supports the most important fishery at national scale. Goals: This paper analyzes the catch information generated by the commercial fleet operating in the Gulf of California from 1969 to 2016 in order to identify the catch trends and the presence of the harmonic components that is related to environmental variability. Methods: Fast Fourier Transformation (FFT) was applied to the time series in order to establish the dominant frequencies. The Singular Spectrum Analysis (SSA) method was used to separate the trend and harmonic components. Each harmonic component was correlated to the Southern Oscillation Index (SOI), the Pacific Decadal Oscillation (PDO) and the Solar Activity data. Results: The FFT showed dominant frequencies at 7 and 11 years. An increasing linear trend was identified from 1969 to 2008 with a decreasing linear segment from 2009 to 2016, as well as two harmonic components of different frequencies (7 and 11 years respectively). The trend and the two harmonic components explain 87.49% of the total variance of the capture. The first and second harmonic components correlated positively with SOI (r= 0.2921, r= 0.3870 respectively), while the second harmonic component correlated negatively with solar activity (r= -0.5313). There were no correlations with the PDO. Conclusions: The fluctuations of Pacific sardine in the Gulf of California are mainly due to three factors: increased catch, the influence of the El Niño events and the influence of the solar activity cycle.  

System load trend prediction method based on IF-EMD-LSTM

Accurately predicting the load change of the information system during operation has important guiding significance for ensuring that the system operation is not interrupted and resource scheduling is carried out in advance. For the information system monitoring time series data, this article proposes a load trend prediction method based on isolated forests-empirical modal decomposition-long-term (IF-EMD-LSTM). First, considering the problem of noise and abnormal points in the original data, the isolated forest algorithm is used to eliminate the abnormal points in the data. Second, in order to further improve the prediction accuracy, the empirical modal decomposition algorithm is used to decompose the input data into intrinsic mode function (IMF) components of different frequencies. Each intrinsic mode function (IMF) and residual is predicted using a separate long-term and short-term memory neural network, and the predicted values are reconstructed from each long-term and short-term memory model. Finally, experimental verification was carried out on Amazon’s public data set and compared with autoregressive integrated moving average and Prophet models. The experimental results show the superior performance of the proposed IF-EMD-LSTM prediction model in information system load trend prediction.

Análisis de la serie de captura de sardina Monterrey, Sardinops sagax en el Golfo de California, México

Background: The Pacific sardine is a small pelagic fish which supports the most important fishery at national scale. Goals: This paper analyzes the catch information generated by the commercial fleet operating in the Gulf of California from 1969 to 2016 in order to identify the catch trends and the presence of the harmonic components that is related to environmental variability. Methods: Fast Fourier Transformation (FFT) was applied to the time series in order to establish the dominant frequencies. The Singular Spectrum Analysis (SSA) method was used to separate the trend and harmonic components. Each harmonic component was correlated to the Southern Oscillation Index (SOI), the Pacific Decadal Oscillation (PDO) and the Solar Activity data. Results: The FFT showed dominant frequencies at 7 and 11 years. An increasing linear trend was identified from 1969 to 2008 with a decreasing linear segment from 2009 to 2016, as well as two harmonic components of different frequencies (7 and 11 years respectively). The trend and the two harmonic components explain 87.49% of the total variance of the capture. The first and second harmonic components correlated positively with SOI (r= 0.2921, r= 0.3870 respectively), while the second harmonic component correlated negatively with solar activity (r= -0.5313). There were no correlations with the PDO. Conclusions: The fluctuations of Pacific sardine in the Gulf of California are mainly due to three factors: increased catch, the influence of the El Niño events and the influence of the solar activity cycle.  

Analysis of shares frequency components on daily value-at-risk in emerging and developed markets

Value-at-Risk was estimated using the technique of wavelet decomposition with the goal to analyze the frequency components’ impacts on variances of daily stock returns, and VaR forecasts. Daily returns of twenty-one shares of the Ibovespa and daily returns of twenty-two shares of the DJIA were used. The FIGARCH(1,d,1) model was applied to the reconstructed returns to model and establish the prediction of conditional variance, applying the rolling window technique. The Value-at-Risk was then estimated, and the results showed that the DJIA shares showed more efficient market behavior than those of Ibovespa. The differences in behavior induce to affirm that VaRs, used in the analysis of financial assets from different markets with different governance premises, should be estimated by series of returns reconstructed by aggregations of components of different frequencies. A set of back-testing was applied to confront the estimated VaRs, which demonstrated that the estimations of VaRs models are consistent.

Stochastic analysis of the non-Gaussian airgap response of a semi-submersible using frequency domain analysis

Airgap is a crucial design parameter for semi-submersibles. The analysis of the extreme airgap statistics is challenging due to nonlinearities in the wave elevation and platform motions, as well as their interactions and phase relationships. In this paper, an efficient frequency domain approach is developed for airgap analysis, using second-order diffraction analysis to model the wave loads. The wave amplification effect is predicted using second-order random wave theory together with linear diffraction/radiation analysis, and the drag forces are linearized. The linear and quadratic transfer functions (sum- and difference frequencies) of the airgap response are derived, preserving all the phase relationships. The crossing rate is a key quantity for characterizing the extreme of a stochastic process. Using the transfer functions, the crossing rate of the non-Gaussian airgap process is derived via a statistical method that preserves the statistical dependency between the linear, sum- and difference-frequency components. In the case studies, the spectral density of the airgap obtained from frequency domain analysis are compared to time domain simulations (which are performed as a benchmark), and the results are found to be in excellent agreement. Moreover, the proposed approach generally provides good estimation of the crossing rate. The results also reveal insights into the airgap behavior; for example, the airgap at the platform center is nearly Gaussian, whereas the off-center locations are significantly non-Gaussian. Finally, the influence of various nonlinearities on the airgap statistics are systematically investigated.