High sensitivity low cost capacitive strain gage

This paper describes a high senstivity low cost capacitive strain gage sensor. The theory, design, and sensor construction details are presented. It consists of eight capacitive sensors connected in two full bridges. The capacitive strain gage sensor structure was designed in order to produce high sensitivity and low dependence with temperature. By using a simple signal conditioning circuit constituted by a differential amplifier, a band-pass filter, and a precision rectifier the device can measure forces with resolution of 0.009 N and precision of 98.7%. It is rugged, presents linear response, and good repeatability. It presents sensitivity of 8.7 V/N and fall time of 12 ms.

Effects of the thyristor controlled serie capacitor on the electric power system

This work deals with the effects of the series compensation on the electric power system for small-signal stability studies. Therefore, the system is modeled admitting the existence of the compensation and then, the equations are linearized and a linear model is obtained for a single machine-infinite bus power system with a compensator installed. The resulting model with nine defined constants is very similar to the Heffron & Phillips linear model widely used on the existent literature. Finally, simulations are executed for an example system, to analyze the behavior of these constants when loading the system. © 2004 IEEE.

Precision of yule-walker methods for the arma spectral model

In this work a new method is proposed of separated estimation for the ARMA spectral model based on the modified Yule-Walker equations and on the least squares method. The proposal of the new method consists of performing an AR filtering in the random process generated obtaining a new random estimate, which will reestimate the ARMA model parameters, given a better spectrum estimate. Some numerical examples will be presented in order to ilustrate the performance of the method proposed, which is evaluated by the relative error and the average variation coefficient.

Revisão sobre técnicas de controle em estruturas inteligentes

One of the great challenges of structural dynamics is to ally structures lighther and stronger. The great difficulty is that light systems, in general, have a low inherent damping. Besides, they contain resonance frequencies in the low frequency range. So, any external disturbance can excite the system in some resonance and the resulting effect can be drastic. The methodologies of active damping, with control algorithms and piezoelectric sensors and actuators coupled in a base structure, are attractive in current days, in order to overcome the contradictory features of these requeriments. In this sense, this article contributes with a bibliographical review of the literature on the importance of active noise and vibration control in engineering applications, models of smart structures, techniques of optimal placement of piezoelectric sensors and actuators and methodologies of structural active control. Finally, it is discussed the future perspectives in this area.

Virtual instrumentation applied to the implementation of IEEE STD 1459-2000 power definitions

This paper discusses the utilization of Virtual Instrumentation to the implementation and evaluation of different power definitions, so that classical formulations and new definitions can be compared without the necessity of acquiring different power meters or analyzers. Accordingly, the definitions of IEEE Standard 1459-2000 for the measurement of power quantities under distorted and unbalanced situations, have been digitally implemented. Thus, several power and power factor components related to the decomposition of the measured voltage and current signals have been obtained. The proposed PC-based Virtual Instrument uses a high performance acquisition board and isolated sensors and transducers. All digital algorithms and routines have been implemented by means of a graphical development system. Regarding to the implementation of STD 1459, this paper also proposes several different algorithms to the required decompositions of voltage, current and power components. © 2005 IEEE.

In-process grinding monitoring through acoustic emission

This work aims to investigate the efficiency of digital signal processing tools of acoustic emission signals in order to detect thermal damages in grinding processes. To accomplish such a goal, an experimental work was carried out for 15 runs in a surface grinding machine operating with an aluminum oxide grinding wheel and ABNT 1045 Steel as work material. The acoustic emission signals were acquired from a fixed sensor placed on the workpiece holder. A high sampling rate data acquisition system working at 2.5 MHz was used to collect the raw acoustic emission instead of the root mean square value usually employed. Many statistical analyses have shown to be effective to detect burn, such as the root mean square (RMS), correlation of the AE, constant false alarm rate (CFAR), ratio of power (ROP) and mean-value deviance (MVD). However, the CFAR, ROP, Kurtosis and correlation of the AE have been presented more sensitive than the RMS. Copyright © 2006 by ABCM.

Electromyographic analysis of the pectoralis major and deltoideus anterior in the inclined flying exercise with loads

Due to a shortage of textbooks with specific data on muscular activity concerning physical conditioning and sports, we analysed electromyographically the muscles pectoralis major and deltoideus anterior, bilaterally, in inclined flying exercises, during the concentric and eccentric phases, with external loads of 25, 50, 75 and 100% of the maximum load. The electromyographic analysis was performed in eleven male volunteers with MEDITRACE-200 surface electrodes connected to a six-channel biologic signal acquisition module coupled to a PC/AT computer. The electromyographic signals were processed and the obtained effective values were normalized through maximum voluntary isometric contraction. Statistically, the results showed that all the muscles studied presented significant differences between the concentric and the eccentric phases, with higher electromyographic activity during the concentric phase. By analysing the different loads for each muscle in both phases, significant electromyographic activity was observed for all muscles. When the effect of each load on each muscle during the concentric phase was analysed, it was noticed that the muscles on the left were more active than those on the right side, while in the eccentric phase the muscles had different behavior.

Pitch detection algorithms based on zero-cross rate and autocorrelation function for musical notes

This paper discusses two pitch detection algorithms (PDA) for simple audio signals which are based on zero-cross rate (ZCR) and autocorrelation function (ACF). As it is well known, pitch detection methods based on ZCR and ACF are widely used in signal processing. This work shows some features and problems in using these methods, as well as some improvements developed to increase their performance. © 2008 IEEE.

Video target tracking by using competitive neural networks

A target tracking algorithm able to identify the position and to pursuit moving targets in video digital sequences is proposed in this paper. The proposed approach aims to track moving targets inside the vision field of a digital camera. The position and trajectory of the target are identified by using a neural network presenting competitive learning technique. The winning neuron is trained to approximate to the target and, then, pursuit it. A digital camera provides a sequence of images and the algorithm process those frames in real time tracking the moving target. The algorithm is performed both with black and white and multi-colored images to simulate real world situations. Results show the effectiveness of the proposed algorithm, since the neurons tracked the moving targets even if there is no pre-processing image analysis. Single and multiple moving targets are followed in real time.

Robust and fast vowel recognition using optimum-path forest

The applications of Automatic Vowel Recognition (AVR), which is a sub-part of fundamental importance in most of the speech processing systems, vary from automatic interpretation of spoken language to biometrics. State-of-the-art systems for AVR are based on traditional machine learning models such as Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs), however, such classifiers can not deal with efficiency and effectiveness at the same time, existing a gap to be explored when real-time processing is required. In this work, we present an algorithm for AVR based on the Optimum-Path Forest (OPF), which is an emergent pattern recognition technique recently introduced in literature. Adopting a supervised training procedure and using speech tags from two public datasets, we observed that OPF has outperformed ANNs, SVMs, plus other classifiers, in terms of training time and accuracy. ©2010 IEEE.

Methodology proposal for acquisition of biotelemetric data in a real time

This work presents a methodological proposal for acquisition of biometric data through telemetry basing its development on a research-action and a case study. Nowadays, the qualified professionals of physical evaluation have to use specific devices to obtain biometric signals and data. These devices in the most of the time are high cost and difficult to use and handling. Therefore, the methodological proposal was elaborate in order to develop, conceptually, a bio telemetric device which could acquire the desirable biometric signals: oxymetry, biometrics, corporal temperature and pedometry which are essential for the area of physical evaluation. It was researched the existent biometrics sensors, the possible ways for the remote transmission of signals and the computer systems available so that the acquisition of data could be possible. This methodological proposal of remote acquisition of biometrical signals is structured in four modules: Acquisitor of biometrics data; Converser and transmitter of biometric signals; Receiver and Processor of biometrics signals and Generator of Interpretative Graphs. The modules aim the obtention of interpretative graphics of human biometric signals. In order to validate this proposal a functional prototype was developed and it is presented in the development of this work.

Conversor CA-CA de elevado fator de potência para aplicações com geradores de Ímã permanente

This paper proposes and describes a high power factor AC-AC converter for naval applications using Permanent Magnet Generator (PMG). The three-phase output voltages of the PMG vary from 260 Vrms (220 Hz) to 380 Vrms (360 Hz), depending on load conditions. The proposed converter consists of a Y-/ΔY power transformer, which provides electrical isolation between the PMG and remaining stages, and a twelve-pulse uncontrolled rectifier stage directly connected to a single-phase inverter stage, without the use of an intermediary DC-DC topology. This proposal results in more simplicity for the overall circuitry, assuring robustness, reliability and reduced costs. Furthermore, the multipulse rectifier stage is capable to provide high power factor and low total harmonic distortion for the input currents of the converter. The single-phase inverter stage was designed to operate with wide range of DC bus voltage, maintaining 120 Vrms, 60 Hz output. The control philosophy, implemented in a digital signal processor (DSP) which also contains protection routines, alows series connections between two identical converters, achieving 240 Vrms, 60 Hz total output voltage. Measured total harmonic distortion for the AC output voltage is lower than 2% and the input power factor is 0.93 at 3.6kW nominal load. © 2010 IEEE.

ENCORE: Enhanced code Galileo receiver for land management applications in Brazil

Taking benefit of the new Galileo ranging signals, the ENCORE (Enhanced Code Galileo Receiver) project aims to develop a low-cost Land Management Application to cover needs of the Brazilian market in terms of geo-referencing and rural/urban cadastre, using a low-cost Enhanced Galileo Code Receiver as baseline. Land management applications require precision and accuracy levels from a few to several decimetres that are under-met with current pseudorange-based receiver and over-met with phase observations. This situation leads either to a waste of resources, or to lack of accuracy. In this project, it is proposed to fill this gap using the new possibilities of the Galileo ranging signals, in particular E5 AltBOC and E1 CBOC. This approach reduces the cost of the end-user solution, helping the rapid penetration of Galileo technology outside Europe. ©2010 IEEE.

Preprocessing data for short-term load forecasting with a general regression neural network and a moving average filter

This paper proposes a filter based on a general regression neural network and a moving average filter, for preprocessing half-hourly load data for short-term multinodal load forecasting, discussed in another paper. Tests made with half-hourly load data from nine New Zealand electrical substations demonstrate that this filter is able to handle noise, missing data and abnormal data. © 2011 IEEE.