Intrinsic Mode Frequencies Research Articles

Study on flow field characteristics and fluid-induced resonance analysis of swing check valve

The purpose of this study is to investigate the vibration of the valve flap and rocker arm of DN25 swing check valve in piping system caused by fluid under working condition. Computational fluid dynamics (CFD), fluid–solid coupled modal analysis and harmonic response analysis are used to carry out non-constant flow field calculations and structural modal calculations. The flow field characteristics, pressure pulsations, modal frequencies and modal vibration modes of the flap and rocker stem of the rotary check valve at different opening degrees are obtained. The results show that the fluid in front of the valve is relatively stable, while the fluid behind the valve exhibits chaos and vortex. As the valve opening increases, the vortices dissipate and the fluid becomes orderly. The pressure pulsations are mainly concentrated in the high-velocity region downstream of the valve and gradually decrease as the valve opening in the flow direction increases. The peak frequency distribution of pressure pulsations caused by eddy currents and turbulence is in the range of 30 to 1000 Hz in the valve opening range of 0% to 20%. The peak frequencies of pressure pulsations at 5% and 10% opening are 539.56 Hz and 554.24 Hz, respectively, and the intrinsic mode frequencies are 539.44 Hz and 554.1 Hz. These frequencies are similar to those of the medium frequency resonance (FIR). The maximum amplitude of the pressure pulsation in the valve is 0.1763 mm in the Y-axis and 0.10669 mm in the Z-axis.

Automatic wheeze segmentation using harmonic-percussive source separation and empirical mode decomposition.

Wheezes are adventitious respiratory sounds commonly present in patients with respiratory conditions. The presence of wheezes and their time location are relevant for clinical reasons, such as understanding the degree of bronchial obstruction. Conventional auscultation is usually employed to analyze wheezes, but remote monitoring has become a pressing need during recent years. Automatic respiratory sound analysis is required to reliably perform remote auscultation. In this work we propose a method for wheeze segmentation. Our method starts by decomposing a given audio excerpt into intrinsic mode frequencies using empirical mode decomposition. Then, we apply harmonic-percussive source separation to the resulting audio tracks and get harmonic-enhanced spectrograms, which are processed to obtain harmonic masks. Subsequently, a series of empirically derived rules are applied to find wheeze candidates. Finally, the candidates stemming from the different audio tracks are merged and median filtered. In the evaluation stage, we compare our method to three baselines on the ICBHI 2017 Respiratory Sound Database, a challenging dataset containing various noise sources and background sounds. Using the full dataset, our method outperforms the baselines, achieving an F1 of 41.9%. Our method's performance is also better than the baselines across several stratified results focusing on five variables: recording equipment, age, sex, body-mass index, and diagnosis. We conclude that, contrary to what has been reported in the literature, wheeze segmentation has not been solved for real life scenario applications. Adaptation of existing systems to demographic characteristics might be a promising step in the direction of algorithm personalization, which would make automatic wheeze segmentation methods clinically viable.

A Multiscale Approach to Timescale Analysis: Isolating Diel Signals from Solute Concentration Time Series.

Solute concentration time series reflect hydrological and biological drivers through various frequencies, phases, and amplitudes of change. Untangling these signals facilitates the understanding of dynamic ecosystem conditions and transient water quality issues. A case in point is the inference of biogeochemical processes from diel solute concentration variations. This analysis requires approaches capable of isolating subtle diel signals from background variability at other scales. Conventional time series analyses typically assume stationary or deterministic background variability; however, most rivers do not respect such niceties. We developed a time-series filtering method that uses empirical mode decomposition to decompose a measured solute concentration time series into intrinsic mode frequencies. Based on externally supplied mechanistic knowledge, we then filter these modes by periodicity, phase, and coherence with neighboring days. This method is tested on three synthetic series that incorporate environmental variability and sensor noise and on a year of 15 min sampled concentration time series from three hydrologically and ecologically distinct rivers in the eastern United States. The proposed method successfully isolated signals in the measured data sets that corresponded with variability in gross primary productivity. The strength the diel signal isolated through this method was smaller compared to the true signal in the synthetic series; however, uncertainty analysis showed that the process-model-based estimates derived from these signals were similar to other inference methods. This signal decomposition method retains information that can be used for further process modeling while making different assumptions about the data than Fourier and wavelet analyses.

Coupling of Acoustic and Intrinsic Modes in 1D Combustor Models

ABSTRACT The work is concerned with the theoretical examination of a new type of thermo-acoustic instability in combustors not reported in the literature. The instability results from linear coupling between the conventional acoustic mode and the recently discovered “flame intrinsic modes.” Within the framework of a 1D model of a quarter wave resonator with the standard model of flame heat release, intrinsic-acoustic mode coupling occurs when the real parts of the frequencies of neighboring acoustic and flame-intrinsic modes at small interaction index are close. While at small the Eigen-functions of close acoustic and flame intrinsic modes clearly exhibit their distinctive identities, with increase of the mode identities become blurred and the Eigen-functions of acoustic modes resemble more and more those of flame intrinsic modes and at a certain become indistinguishable. We refer them as coupled intrinsic-acoustic modes or coupled modes. When the “Rayleigh index” for a coupled mode behaving as an acoustic mode at small is negative, at a larger such a mode can nevertheless become unstable at one of the nearby intrinsic mode frequencies. We find analytically the instability domain due to coupling in the parameter space. Near the instability boundary, we reduce the transcendental dispersion relation to a quadratic or, if higher accuracy is desired, to a quartic equation. These models capture well all four possible coupling scenarios.

Analytic description of flame intrinsic instability in one-dimensional model of open–open combustors with ideal and non-ideal end boundaries

This paper is concerned with the theoretical study of thermo-acoustic instabilities in combustors and focuses upon recently discovered flame intrinsic modes. Here, a complete analytical description of the salient properties of intrinsic modes is provided for a linearized one-dimensional model of open–open combustors with temperature and cross-section jump across the flame taken into account. The standard [Formula: see text] model of heat release is adopted, where n is the interaction index and τ is the time lag. We build upon the recent key finding that for a closed–lopen combustor, on the neutral curve, the intrinsic mode frequencies become completely decoupled from the combustor parameters like cross-section jump, temperature jump and flame location. Here, we show that this remarkable decoupling phenomenon holds not only for closed–open combustors but also for all combustors with the ideal boundary conditions (i.e. closed–open, open–open and closed–closed). Making use of this decoupling phenomenon for the open–open combustors, we derive explicit analytic expressions for the neutral curve of intrinsic mode instability on the [Formula: see text] plane as well as for the linear growth/decay rate near the neutral curve taking into account temperature and cross-section jumps. The instability domain on the [Formula: see text] plane is shown to be qualitatively different from that of the closed–open combustor; in open–open combustors it is not confined for large τ. To find the instability domain and growth rate characteristics for non-ideal open–open boundaries the combustor end boundaries are perturbed and explicit analytical formulae derived and verified by numerics.

Identification of spin maneuver aerodynamic nonlinear model by applying ensemble empirical mode decomposition and extended multipoint modeling

Identification of the “aircraft aerodynamic model” in some unusual flight conditions such as spin maneuver provides critical information to the flight controller to retake the “dynamic stability” after it has been disturbed by the systematic, natural or environmental oscillations. Hence, a method for identifying the appropriate aerodynamic model in spin maneuvers is presented in this paper. We present an innovative systematic method for aerodynamic modeling of spin maneuvers, which combines the ensemble empirical mode decomposition technique and extended multipoint modeling approach, using flight data. In ensemble empirical mode decomposition, in addition to having all the empirical mode decomposition features, the original signal is collected with the white noise, and by using its statistical characteristics, the ensemble empirical mode decomposition solves the mode mixing problem. By applying the ensemble empirical mode decomposition to the flight parameter data, their intrinsic mode frequencies are extracted and are used as inputs to the extended multipoint modeling model. The extended multipoint modeling structure includes some parameters describing the distribution of aerodynamic forces and moments along each of the aircraft components. Moreover, this method allows coupling between the forces and moments. Unlike conventional methods, which consider the average forces obtained by plane surfaces relative to the center of mass, in the extended multipoint modeling technique, the force generated by each plane of the aircraft is allowed to appear independently in the motion equations. For identifying the aerodynamic model with extended multipoint modeling structure, the equation error method is used with a maximum likelihood optimizer inside. The obtained algorithm has been applied to two sets of spin maneuver flight data which were recorded in actual spin flight. The results demonstrate that the proposed method is able to reproduce the aerodynamic forces and moments for the second spin flight inputs with high accuracy by using a model which is derived from the first spin data identification.

Ion gyroscale fluctuation measurement with microwave imaging reflectometer on KSTAR.

Ion gyroscale turbulent fluctuations with the poloidal wavenumber kθ ∼ 3 cm-1 have been measured in the core region of the neutral beam (NB) injected low confinement (L-mode) plasmas on Korea superconducting tokamak advanced research. The turbulence poloidal wavenumbers are deduced from the frequencies and poloidal rotation velocities in the laboratory frame, measured by the multichannel microwave imaging reflectometer. Linear and nonlinear gyrokinetic simulations also predict the unstable modes with the normalized wavenumber kθρs ∼ 0.4, consistent with the measurement. Comparison of the measured frequencies with the intrinsic mode frequencies from the linear simulations indicates that the measured ones are primarily due to the E × B flow velocity in the NB-injected fast rotating plasmas.

Application of Probabilistic Neural Network in Fault Diagnosis of Wind Turbine Using FAST, TurbSim and Simulink

This paper presents an intelligent diagnosis technique for wind turbine imbalance fault identification based on generator current signals. For this aim, Probabilistic Neural Network (PNN), which is powerful algorithm for classification problems that needs small training time in solving nonlinear problems and applicable to high dimension applications, is employed. The complete dynamics of a permanent magnet synchronous generator (PMSG) based wind-turbine (WTG) model are imitated in an amalgamated domain of Simulink, FAST and TurbSim under six distinct conditions, i.e., aerodynamic asymmetry, rotor furl imbalance, tail furl imbalance, blade imbalance, nacelle-yaw imbalance and normal operating scenarios. The simulation results in time domain of the PMSG stator current are decomposed into the Intrinsic Mode Frequency (IMF) using EMD method, which are utilized as input variable in PNN. The analyzed results proclaim the effectiveness of the proposed approach to identify the healthy condition from imbalance faults in WTG. The presented work renders initial results that are helpful for online condition monitoring and health assessment of WTG.

Order parameter for the transition from strong to weak generalized synchrony from empirical mode decomposition analysis

We examine driven nonlinear dynamical systems that are known to be in a state of generalized synchronization with an external drive. The chaotic time series of the response system are subject to empirical mode decomposition analysis. The instantaneous intrinsic mode frequencies (and their variance) present in these signals provide suitable order parameters for detecting the transition between the regimes of strong and weak generalized synchrony. Application is made to a variety of chaotically driven flows as well as maps.

Analytical signal analysis of strange nonchaotic dynamics

We apply an analytical signal analysis to strange nonchaotic dynamics. Through this technique it is possible to obtain the spectrum of instantaneous intrinsic mode frequencies that are present in a given signal. We find that the second-mode frequency and its variance are good order parameters for dynamical transitions from quasiperiodic tori to strange nonchaotic attractors (SNAs) and from SNAs to chaotic attractors. Phase fluctuation analysis shows that SNAs and chaotic attractors behave identically within short time windows as a consequence of local instabilities in the dynamics. In longer time windows, however, the globally stable character of SNAs becomes apparent. This methodology can be of great utility in the analysis of experimental time series, and representative applications are made to signals obtained from Rössler and Duffing oscillators.

The pulsatingλ Bootis star 15 Andromedae: results from a three-site photometry campaign

Context. The A Bootis stars are a chemically peculiar subgroup of main sequence A/F stars. Several of these fall into the instability strip of the δ Scuti stars and the whole spectroscopic group shows a high incidence of pulsational variability. Aims. We investigated the pulsational behaviour of the A Bootis star 15 And (HD 221756) to determine as many intrinsic mode frequencies as possible for asteroseismic applications. Methods. The star was included as a secondary target for three telescopes during a campaign devoted to the β Cep stars 12 and 16 Lac, due to its proximity to these targets. 302.8 h of time-resolved photometry spanning 161.2 d were acquired and analyzed. Results. Our frequency analysis revealed f 1 = 24.7887(2) c/d as the main pulsation frequency, with an amplitude of only 1.9(1) mmag. The residual periodogram suggests the presence of additional frequencies in an interval from 20 to 25 c/d, with very low amplitudes. We succeeded in detecting a second frequency f2 = 22.2580(9) with an amplitude of 0.6(1) mmag. Low-frequency light variations of the comparison star HD 220575 were revealed as well. Conclusions. The pulsational behaviour of 15 And as a typical A Boo-type star is compared with that of δ Scuti stars with normal abundances and with metallic-line 6 Scuti stars. We discuss the value of A Boo stars in understanding accretion and mixing in pulsating stars. The difficulties in the selection of reliable comparison stars for such high-precision research are pointed out.

Hopping transport in two-dimensional systems with spin-orbit interaction in external magnetic field

The theory of spin rotation waves (SRWs), representing excitations of a new type arising in twodimensional systems with spin-orbit interaction in an external electric field, has been developed. These intrinsic modes correspond to rotation of the magnetic moment vector in the plane formed by the electric field vector and the normal to the sample plate surface. An experimental method is proposed for detecting SRWs by measuring the frequency dependence of the magnetic susceptibility, which exhibits a resonance at the intrinsic mode frequency. A particular calculation is performed for a hopping conductivity model (for small-size polarons), but it is likely that intrinsic oscillations of the SRW type also take place for the band transport, since their appearance is related to the symmetry of the system.

Resonance properties of domain walls in ferromagnets with a weak exchange interaction

The spin dynamics of a domain wall is studied in an infinite ferromagnetic chain with an easy-axis anisotropy as well as in a chain of finite size. The dependence of the intrinsic mode frequency of the domain wall on the exchange interaction is studied for all admissible values of the latter. It is shown that this dependence is considerably modified in the region of transition of the domain wall from collinear structure to canted form.