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.

Oropharyngeal dysphagia identification using wavelets and optimum path forest

The swallowing disturbers are defined as oropharyngeal dysphagia when present specifies signals and symptoms that are characterized for alterations in any phases of swallowing. Early diagnosis is crucial for the prognosis of patients with dysphagia and the potential to diagnose dysphagia in a noninvasive manner by assessing the sounds of swallowing is a highly attractive option for the dysphagia clinician. This study proposes a new framework for oropharyngeal dysphagia identification, having two main contributions: a new set of features extract from swallowing signal by discrete wavelet transform and the dysphagia classification by a novel pattern classifier called OPF. We also employed the well known SVM algorithm in the dysphagia identification task, for comparison purposes. We performed the experiments in two sub-signals: the first was the moment of the maximal peak (MP) of the signal and the second is the swallowing apnea period (SAP). The OPF final accuracy obtained were 85.2% and 80.2% for the analyzed signals MP and SAP, respectively, outperforming the SVM results. ��2008 IEEE.

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.

Mandible protrusion and decrease of TMJ sounds: An electrovibratographic examination

This study quantified by, electrovibratography, the amount of mandible protrusion required to decrease significantly temporomandibular joint (TMJ) vibratory energy as an aid in the diagnosis of the recapture of anteriorly displaced disk. Eighteen patients diagnosed as having anterior disk displacement with reduction and TMJ clicking were submitted to electrovibratographic examination at the first appointment and treated with a stabilizing appliance and anterior positioning appliance with 1 to 5 mm protrusion. Vibratory energy was checked in each of these positions. Baseline data were used as control. At the first appointment, the patients had vibrations with more elevated intensities at the middle and late phases of the mouth opening cycle. At only one clinical step, mandible protrusion was obtained with the anterior repositioning appliance, ranging from 1 to 5 mm protusion. At each new position, a new electrovibratographic exam was made. After the 5-mm mandibular projection, only 2 patients presented vibration, with means between 0.6 and 2.8 Hz. Data were analyzed statistically by ANOVA and Tukey's test (��=0.05). The outcomes of this study indicate that 3 mm is the minimum amount of mandible protrusion to significantly decrease the TMJ vibratory energy and to recapture the displaced articular disk.

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 pot��ncia para aplica����es com geradores de ��m�� 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-/��Y 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.

Improving synthetic aperture image by image compounding in beamforming process

In this work, signal processing techniques are used to improve the quality of image based on multi-element synthetic aperture techniques. Using several apodization functions to obtain different side lobes distribution, a polarity function and a threshold criterium are used to develop an image compounding technique. The spatial diversity is increased using an additional array, which generates complementary information about the defects, improving the results of the proposed algorithm and producing high resolution and contrast images. The inspection of isotropic plate-like structures using linear arrays and Lamb waves is presented. Experimental results are shown for a 1-mm-thick isotropic aluminum plate with artificial defects using linear arrays formed by 30 piezoelectric elements, with the low dispersion symmetric mode S0 at the frequency of 330 kHz. �� 2011 American Institute of Physics.

Fault location in underground systems through optimum-path forest

In this paper we propose an accurate method for fault location in underground distribution systems by means of an Optimum-Path Forest (OPF) classifier. We applied the Time Domains Reflectometry method for signal acquisition, which was further analyzed by OPF and several other well known pattern recognition techniques. The results indicated that OPF and Support Vector Machines outperformed Artificial Neural Networks classifier. However, OPF has been much more efficient than all classifiers for training, and the second one faster for classification. �� 2011 IEEE.

Galileo's surveying potential E5 pseudorange precision

New Galileo signals have great potential for pseudorange-based surveying and mapping in both optimal open-sky conditions and suboptimal under-canopy environments. This article reviews the main features of Galileo's E5 AItBO( and El (BOC signals, describes generation of realistic E5 and El pseudoranges with and without multipath sources, and presents anticipated horizontal positioning accuracy results, ranging from 4 centimeters (open-sky) to 14 centimeters (under-canopy) for E5/El.