Identification of nonlinear structures using discrete-time Volterra series

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A Time-domain Harmonic Power-Flow Analysis in Electrical Energy Distribution Networks, Using Norton Models for Non-linear Loading

The purpose of this paper is to present the application of a three-phase harmonic propagation analysis time-domain tool, using the Norton model to approach the modeling of non-linear loads, making the harmonics currents flow more appropriate to the operation analysis and to the influence of mitigation elements analysis. This software makes it possible to obtain results closer to the real distribution network, considering voltages unbalances, currents imbalances and the application of mitigation elements for harmonic distortions. In this scenario, a real case study with network data and equipments connected to the network will be presented, as well as the modeling of non-linear loads based on real data obtained from some PCCs (Points of Common Coupling) of interests for a distribution company.

Fast determination of beef quality parameters with time-domain nuclear magnetic resonance spectroscopy and chemometrics

The noteworthy of this study is to predict seven quality parameters for beef samples using time-domain nuclear magnetic resonance (TD-NMR) relaxometry data and multivariate models. Samples from 61 Bonsmara heifers were separated into five groups based on genetic (breeding composition) and feed system (grain and grass feed). Seven sample parameters were analyzed by reference methods; among them, three sensorial parameters, flavor, juiciness and tenderness and four physicochemical parameters, cooking loss, fat and moisture content and instrumental tenderness using Warner Bratzler shear force (WBSF). The raw beef samples of the same animals were analyzed by TD-NMR relaxometry using Carr-Purcell-Meiboom-Gill (CPMG) and Continuous Wave-Free Precession (CWFP) sequences. Regression models computed by partial least squares (PLS) chemometric technique using CPMG and CWFP data and the results of the classical analysis were constructed. The results allowed for the prediction of aforementioned seven properties. The predictive ability of the method was evaluated using the root mean square error (RMSE) for the calibration (RMSEC) and validation (RMSEP) data sets. The reference and predicted values showed no significant differences at a 95% confidence level.

Classification of intact fresh plums according to sweetness using time-domain nuclear magnetic resonance and chemometrics

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Determination of quality parameters for mustard sauces in sealed packets using time-domain nuclear magnetic resonance spectroscopy and chemometrics

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Discrete-time sliding mode control for uncertain networked system subject to time delay

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Measuring the solubility product constant of paramagnetic cations using time-domain nuclear magnetic resonance relaxometry

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Non-parametric identification of a non-linear buckled beam using discrete-time Volterra Series

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Characterization of the nonlinear behavior of a F-16 aircraft using discrete-time Volterra series

The linearity assumption in the structural dynamics analysis is a severe practical limitation. Further, in the investigation of mechanisms presented in fighter aircrafts, as for instance aeroelastic nonlinearity, friction or gaps in wing-load-payload mounting interfaces, is mandatory to use a nonlinear analysis technique. Among different approaches that can be used to this matter, the Volterra theory is an interesting strategy, since it is a generalization of the linear convolution. It represents the response of a nonlinear system as a sum of linear and nonlinear components. Thus, this paper aims to use the discrete-time version of Volterra series expanded with Kautz filters to characterize the nonlinear dynamics of a F-16 aircraft. To illustrate the approach, it is identified and characterized a non-parametric model using the data obtained during a ground vibration test performed in a F-16 wing-to-payload mounting interfaces. Several amplitude inputs applied in two shakers are used to show softening nonlinearities presented in the acceleration data. The results obtained in the analysis have shown the capability of the Volterra series to give some insight about the nonlinear dynamics of the F-16 mounting interfaces. The biggest advantage of this approach is to separate the linear and nonlinear contributions through the multiple convolutions through the Volterra kernels.

Comparison of frequency and time domain electromyography parameters in women with patellofemoral pain

Despite its high incidence, patellofemoral pain etiology remains unclear. No prior study has compared surface electromyography frequency domain parameters and surface electromyography time domain variables, which have been used as a classic analysis of patellofemoral pain. Thirty one women with patellofemoral pain and twenty eight pain-free women were recruited. Each participant was asked to descend a seven step staircase and data from five successful trials were collected. During the task, the vastus medialis and vastus lateralis muscle activities were monitored by surface electromyography. The data were processed and analyzed in four variables of the frequency domain (median frequency, low, medium and high frequency bands) and three time domain variables (Automatic, Cross-correlation and Visual Onset between the vastus medialis and vastus lateralis muscles). Reliability, Receiver Operating Characteristic curves and regression models were performed. The medium frequency band was the most reliable variable and different between the groups for both muscles, also demonstrated the best values of sensitivity and sensibility, 72% and 69% for the vastus medialis and 68% and 62% for the vastus lateralis, respectively. The frequency variables predicted the pain of individuals with patellofemoral pain, 26% for the vastus medialis and 20% for the vastus lateralis, being better than the time variables, which achieved only 7%. The frequency domain parameters presented greater reliability, diagnostic accuracy and capacity to predict pain than the time domain variables during stair descent and might be a useful tool to diagnose individuals with patellofemoral pain.

In Situ Quantification of Cu(II) during an Electrodeposition Reaction Using Time-Domain NMR Relaxometry

The use of a low-cost benchtop time-domain NMR (TD-NMR) spectrometer to monitor copper electrodeposition in situ is presented. The measurements are based on the strong linear correlation between the concentration of paramagnetic ions and the transverse relaxation rates (R-2) of the solvent protons Two electrochemical NMR (EC-NMR) cells were constructed and applied to monitor the Cu2+ concentration during the electrodeposition reaction. The results show that TD-NMR relaxometry using the Carr-Purcell-Meiboom-Gill pulse sequence can be a very fast, simple, and efficient technique to monitor, in real time, the variation in the Cu2+ concentration during an electrodeposition reaction. This methodology can also be applied to monitor the electrodeposition of other paramagnetic ions, such as Ni2+ and Cr3+, which are commonly used in electroplating.

Optimal mean-variance control for discrete-time linear systems with Markovian jumps and multiplicative noises

In this paper, we consider the stochastic optimal control problem of discrete-time linear systems subject to Markov jumps and multiplicative noises under two criteria. The first one is an unconstrained mean-variance trade-off performance criterion along the time, and the second one is a minimum variance criterion along the time with constraints on the expected output. We present explicit conditions for the existence of an optimal control strategy for the problems, generalizing previous results in the literature. We conclude the paper by presenting a numerical example of a multi-period portfolio selection problem with regime switching in which it is desired to minimize the sum of the variances of the portfolio along the time under the restriction of keeping the expected value of the portfolio greater than some minimum values specified by the investor. (C) 2011 Elsevier Ltd. All rights reserved.

Comparison between frequency domain and time domain riser analysis

In the optimization or parametric analyses of risers, several configurations must be analyzed. It is laborious to perform time domain solutions for the dynamic analysis, since they are time-consuming tasks. So, frequency domain solutions appear to be a possible alternative, mainly in the early stages of a riser design. However, frequency domain analysis is linear and requires that nonlinear effects are treated. The aim of this paper is to present a possible way to treat some of these nonlinearities, using an iterative process together with an analytical correction, and compare the results of a frequency domain analysis with the those of a full nonlinear analysis. [DOI: 10.1115/1.4006149]

Neural coding tools, based on Information Theory, applied to discrete time series: from electrophysiology to neuroethology

This work is supported by Brazilian agencies Fapesp, CAPES and CNPq