Uma nova proposta de antena planar multibanda para comunicações móveis

The great interest observed in wireless communication systems has required the development of new configurations of microstrip antennas, because they are easily built and integrated to other microwave circuit components, which is suitable for the construction and development of planar antenna arrays and microwave integrated circuits. This work presents a new configuration of tapered microstrip antenna, which is obtained by impressing U-slots on the conducting patch combined with a transmission line matching circuit that uses an inset length. It is shown that the use of U-slots in the microstrip antenna conducting patch excites new resonating modes, that gives a multiband characteristic for the slotted microstrip antenna, that is suitable for applications in communication systems that operates several frequencies simultaneously. Up to this date, the works reported in the literature deals with the use of Uslotted microstrip rectangular antennas fed by a coaxial probe. The properties of a linear array of microstrip patch tapered antennas are also investigated. The main parameters of the U slotted tapered microstrip antennas are investigated for different sizes and locations of the slots impressed on the conducting patch. The analysis of the proposed antenna is performed by using the resonant cavity and equivalent transmission line methods, in combination with a parametric study, that is conducted by the use of the Ansoft Designer, a commercial computer aided microwave software well known by its accuracy and efficiency. The mentioned methods are used to evaluate the effect in the antennas parameters, like resonant frequency and return loss, produced by variations of the antenna structural parameters, accomplished separately or simultaneously. An experimental investigation is also developed, that consists of the design, construction and measurement of several U slotted microstrip antenna prototypes. Finally, theoretical and simulated results are presented that are in agreement with the measured ones. These results are related to the resonating modes identification and to the determination of the main characteristics of the investigated antennas, such as resonant frequency, return loss, and radiation pattern

Métodos estatísticos recursivos aplicados ao problema de estimação de vazão de gás em plantas de Plunger-lift

This work has as main objective to find mathematical models based on linear parametric estimation techniques applied to the problem of calculating the grow of gas in oil wells. In particular we focus on achieving grow models applied to the case of wells that produce by plunger-lift technique on oil rigs, in which case, there are high peaks in the grow values that hinder their direct measurement by instruments. For this, we have developed estimators based on recursive least squares and make an analysis of statistical measures such as autocorrelation, cross-correlation, variogram and the cumulative periodogram, which are calculated recursively as data are obtained in real time from the plant in operation; the values obtained for these measures tell us how accurate the used model is and how it can be changed to better fit the measured values. The models have been tested in a pilot plant which emulates the process gas production in oil wells

Detecção e diagnóstico de falhas não-supervisionados baseados em estimativa de densidade recursiva e classificador fuzzy auto-evolutivo

In this work, we propose a two-stage algorithm for real-time fault detection and identification of industrial plants. Our proposal is based on the analysis of selected features using recursive density estimation and a new evolving classifier algorithm. More specifically, the proposed approach for the detection stage is based on the concept of density in the data space, which is not the same as probability density function, but is a very useful measure for abnormality/outliers detection. This density can be expressed by a Cauchy function and can be calculated recursively, which makes it memory and computational power efficient and, therefore, suitable for on-line applications. The identification/diagnosis stage is based on a self-developing (evolving) fuzzy rule-based classifier system proposed in this work, called AutoClass. An important property of AutoClass is that it can start learning from scratch". Not only do the fuzzy rules not need to be prespecified, but neither do the number of classes for AutoClass (the number may grow, with new class labels being added by the on-line learning process), in a fully unsupervised manner. In the event that an initial rule base exists, AutoClass can evolve/develop it further based on the newly arrived faulty state data. In order to validate our proposal, we present experimental results from a level control didactic process, where control and error signals are used as features for the fault detection and identification systems, but the approach is generic and the number of features can be significant due to the computationally lean methodology, since covariance or more complex calculations, as well as storage of old data, are not required. The obtained results are significantly better than the traditional approaches used for comparison