2,548 research outputs found
Application of physical parameter identification to finite element models
A time domain technique for matching response predictions of a structural dynamic model to test measurements is developed. Significance is attached to prior estimates of physical model parameters and to experimental data. The Bayesian estimation procedure allows confidence levels in predicted physical and modal parameters to be obtained. Structural optimization procedures are employed to minimize an error functional with physical model parameters describing the finite element model as design variables. The number of complete FEM analyses are reduced using approximation concepts, including the recently developed convoluted Taylor series approach. The error function is represented in closed form by converting free decay test data to a time series model using Prony' method. The technique is demonstrated on simulated response of a simple truss structure
Simultaneous Detection of H and D NMR Signals in a micro-Tesla Field
We present NMR spectra of remote-magnetized deuterated water, detected in an
unshielded environment by means of a differential atomic magnetometer. The
measurements are performed in a T field, while pulsed techniques are
applied -following the sample displacement- in a 100~T field, to tip both
D and H nuclei by controllable amounts. The broadband nature of the detection
system enables simultaneous detection of the two signals and accurate
evaluation of their decay times. The outcomes of the experiment demonstrate the
potential of ultra-low-field NMR spectroscopy in important applications where
the correlation between proton and deuteron spin-spin relaxation rates as a
function of external parameters contains significant information.Comment: 7 pages (letter, 4 pages) plus supplemental material as an appendix.
This document is the unedited author's version of a Submitted Work that was
subsequently accepted for publication in Journal of Phys. Chem. Lett.,
copyright American Chemical Society after peer review. To access the final
edited and published work see:
pubs.acs.org/doi/abs/10.1021/acs.jpclett.7b0285
Input design for identification of aircraft stability and control derivatives
An approach for designing inputs to identify stability and control derivatives from flight test data is presented. This approach is based on finding inputs which provide the maximum possible accuracy of derivative estimates. Two techniques of input specification are implemented for this objective - a time domain technique and a frequency domain technique. The time domain technique gives the control input time history and can be used for any allowable duration of test maneuver, including those where data lengths can only be of short duration. The frequency domain technique specifies the input frequency spectrum, and is best applied for tests where extended data lengths, much longer than the time constants of the modes of interest, are possible. These technqiues are used to design inputs to identify parameters in longitudinal and lateral linear models of conventional aircraft. The constraints of aircraft response limits, such as on structural loads, are realized indirectly through a total energy constraint on the input. Tests with simulated data and theoretical predictions show that the new approaches give input signals which can provide more accurate parameter estimates than can conventional inputs of the same total energy. Results obtained indicate that the approach has been brought to the point where it should be used on flight tests for further evaluation
Parameter estimation via differential algebra and operational culculus
Parameter estimation is approached via a new standpoint, based on differential algebra and operational calculus. Some applications such as, the estimation of a noisy damped sinusoid, the analysis of chirp signal, the detection of piecewise polynomial signals and their discontinuities are presented with numerical simulations
Search method for long-duration gravitational-wave transients from neutron stars
We introduce a search method for a new class of gravitational-wave signals,
namely long-duration O(hours - weeks) transients from spinning neutron stars.
We discuss the astrophysical motivation from glitch relaxation models and we
derive a rough estimate for the maximal expected signal strength based on the
superfluid excess rotational energy. The transient signal model considered here
extends the traditional class of infinite-duration continuous-wave signals by a
finite start-time and duration. We derive a multi-detector Bayes factor for
these signals in Gaussian noise using \F-statistic amplitude priors, which
simplifies the detection statistic and allows for an efficient implementation.
We consider both a fully coherent statistic, which is computationally limited
to directed searches for known pulsars, and a cheaper semi-coherent variant,
suitable for wide parameter-space searches for transients from unknown neutron
stars. We have tested our method by Monte-Carlo simulation, and we find that it
outperforms orthodox maximum-likelihood approaches both in sensitivity and in
parameter-estimation quality.Comment: 20 pages, 9 figures; submitted to PR
Bifurcations, Chaos, Controlling and Synchronization of Certain Nonlinear Oscillators
In this set of lectures, we review briefly some of the recent developments in
the study of the chaotic dynamics of nonlinear oscillators, particularly of
damped and driven type. By taking a representative set of examples such as the
Duffing, Bonhoeffer-van der Pol and MLC circuit oscillators, we briefly explain
the various bifurcations and chaos phenomena associated with these systems. We
use numerical and analytical as well as analogue simulation methods to study
these systems. Then we point out how controlling of chaotic motions can be
effected by algorithmic procedures requiring minimal perturbations. Finally we
briefly discuss how synchronization of identically evolving chaotic systems can
be achieved and how they can be used in secure communications.Comment: 31 pages (24 figures) LaTeX. To appear Springer Lecture Notes in
Physics Please Lakshmanan for figures (e-mail: [email protected]
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A sub-Nyquist co-prime sampling music spectral approach for natural frequency identification of white-noise excited structures
Motivated by practical needs to reduce data transmission payloads in wireless sensors for vibration-based monitoring of civil engineering structures, this paper proposes a novel approach for identifying resonant frequencies of white-noise excited structures using acceleration measurements acquired at rates significantly below the Nyquist rate. The approach adopts the deterministic co-prime sub-Nyquist sampling scheme, originally developed to facilitate telecommunication applications, to estimate the autocorrelation function of response acceleration time-histories of low-amplitude white-noise excited structures treated as realizations of a stationary stochastic process. This is achieved without posing any sparsity conditions to the signals. Next, the standard MUSIC algorithm is applied to the estimated autocorrelation function to derive a denoised super-resolution pseudo-spectrum in which natural frequencies are marked by prominent spikes. The accuracy and applicability of the proposed approach is numerically assessed using computer-generated noise-corrupted acceleration time-history data obtained by a simulation-based framework pertaining to a white-noise excited structural system with two closely-spaced modes of vibration carrying the same amount of energy, and a third isolated weakly excited vibrating mode. All three natural frequencies are accurately identified by sampling at as low as 78% below Nyquist rate for signal to noise ratio as low as 0dB (i.e., energy of additive white noise equal to the signal energy), suggesting that the proposed approach is robust and noise-immune while it can reduce data transmission requirements in acceleration wireless sensors for natural frequency identification of engineering structures
Detection of Nonlinear Behavior in Voltage Source Converter Control in Wind Farms Based on Higher-Order Spectral Analysis
In recent years, the sub-synchronous oscillation (SSO) accidents caused by
wind power have received extensive attention. A method is needed to distinguish
if nonlinear behavior exists in the recorded equal-amplitude accident
waveforms, so that different methods can be adopted to analyze the mechanism of
the oscillation. The theory of higher-order statistics (HOS) has become a
powerful tool for detection of nonlinear behavior (DNB) in production quality
control since 1960s. However, HOS analysis has been applied in mechanical
condition monitoring and fault diagnosis, even after being introduced into the
power system and wind farms. This paper focuses on the voltage source converter
(VSC) control systems in wind farms and tries to detect the nonlinear behavior
caused by the bilateral or unilateral saturation hard limits based on HOS
analysis. First, the traditional describing function is extended to obtain more
frequency domain information, and hereby the harmonic characteristics of
bilateral and the unilateral saturation hard limit are studied. Then the
bispectrum and trispectrum are introduced as HOS, which are extended into
bicoherence and tricoherence spectrums to eliminate the effects from linear
parts in the VSC control system. The effectiveness of DNB and classification
based on HOS is strictly proved and its detailed calculation and estimation
process is illustrated. Finally, the proposed method is demonstrated and
further discussed through simulation results
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