Control of thermal damage in grinding by digital signal processing of raw acoustic emission

Grinding process is usually the last finishing process of a precision component in the manufacturing industries. This process is utilized for manufacturing parts of different materials, so it demands results such as low roughness, dimensional and shape error control, optimum tool-life, with minimum cost and time. Damages on the parts are very expensive since the previous processes and the grinding itself are useless when the part is damaged in this stage. This work aims to investigate the efficiency of digital signal processing tools of acoustic emission signals in order to detect thermal damages in grinding process. 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 e VC131 steels. The acoustic emission signals were acquired from a fixed sensor placed on the workpiece holder. A high sampling rate acquisition system at 2.5 MHz was used to collect the raw acoustic emission instead of root mean square value usually employed. In each test AE data was analyzed off-line, with results compared to inspection of each workpiece for burn and other metallurgical anomaly. A number of statistical signal processing tools have been evaluated.

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.

Evaluation of tropospheric and ionospheric effects on the geographic localization of data collection platforms

The Brazilian National Institute for Space Research (INPE) is operating the Brazilian Environmental Data Collection System that currently amounts to a user community of around 100 organizations and more than 700 data collection platforms installed in Brazil. This system uses the SCD-1, SCD-2, and CBERS-2 low Earth orbit satellites to accomplish the data collection services. The main system applications are hydrology, meteorology, oceanography, water quality, and others. One of the functionalities offered by this system is the geographic localization of the data collection platforms by using Doppler shifts and a batch estimator based on least-squares technique. There is a growing demand to improve the quality of the geographical location of data collection platforms for animal tracking. This work presents an evaluation of the ionospheric and tropospheric effects on the Brazilian Environmental Data Collection System transmitter geographic location. Some models of the ionosphere and troposphere are presented to simulate their impacts and to evaluate performance of the platform location algorithm. The results of the Doppler shift measurements, using the SCD-2 satellite and the data collection platform (DCP) located in Cuiabá town, are presented and discussed.

Modifying the stochastic model to mitigate GPS systematic errors in relative positioning

The GPS observables are subject to several errors. Among them, the systematic ones have great impact, because they degrade the accuracy of the accomplished positioning. These errors are those related, mainly, to GPS satellites orbits, multipath and atmospheric effects. Lately, a method has been suggested to mitigate these errors: the semiparametric model and the penalised least squares technique (PLS). In this method, the errors are modeled as functions varying smoothly in time. It is like to change the stochastic model, in which the errors functions are incorporated, the results obtained are similar to those in which the functional model is changed. As a result, the ambiguities and the station coordinates are estimated with better reliability and accuracy than the conventional least square method (CLS). In general, the solution requires a shorter data interval, minimizing costs. The method performance was analyzed in two experiments, using data from single frequency receivers. The first one was accomplished with a short baseline, where the main error was the multipath. In the second experiment, a baseline of 102 km was used. In this case, the predominant errors were due to the ionosphere and troposphere refraction. In the first experiment, using 5 minutes of data collection, the largest coordinates discrepancies in relation to the ground truth reached 1.6 cm and 3.3 cm in h coordinate for PLS and the CLS, respectively, in the second one, also using 5 minutes of data, the discrepancies were 27 cm in h for the PLS and 175 cm in h for the CLS. In these tests, it was also possible to verify a considerable improvement in the ambiguities resolution using the PLS in relation to the CLS, with a reduced data collection time interval. © Springer-Verlag Berlin Heidelberg 2007.

Search for Randall-Sundrum gravitons with 1 fb(-1) of data from p(p)over-bar collisions at root s=1.96 TeV

We search for decays of Kaluza-Klein excitations of the graviton in the Randall-Sundrum model of extra dimensions to e+e- and in 1 fb-1 of pp collisions at s=1.96 TeV collected by the D0 detector at the Fermilab Tevatron. We set 95% confidence level upper limits on the production cross section times branching fraction, which translate into lower limits on the mass of the lightest excitation between 300 and 900 GeV for values of the coupling k/M Pl between 0.01 and 0.1. © 2008 The American Physical Society.

A multi-agent architecture for intelligent data analysis

The present study introduces a multi-agent architecture designed for doing automation process of data integration and intelligent data analysis. Different from other approaches the multi-agent architecture was designed using a multi-agent based methodology. Tropos, an agent based methodology was used for design. Based on the proposed architecture, we describe a Web based application where the agents are responsible to analyse petroleum well drilling data to identify possible abnormalities occurrence. The intelligent data analysis methods used was the Neural Network.

A computer vision approach to quantify leaf anatomical plasticity: A case study on gochnatia polymorpha (less.) cabrera

Inferences about leaf anatomical characteristics had largely been made by manually measuring diverse leaf regions, such as cuticle, epidermis and parenchyma to evaluate differences caused by environmental variables. Here we tested an approach for data acquisition and analysis in ecological quantitative leaf anatomy studies based on computer vision and pattern recognition methods. A case study was conducted on Gochnatia polymorpha (Less.) Cabrera (Asteraceae), a Neotropical savanna tree species that has high phenotypic plasticity. We obtained digital images of cross-sections of its leaves developed under different light conditions (sun vs. shade), different seasons (dry vs. wet) and in different soil types (oxysoil vs. hydromorphic soil), and analyzed several visual attributes, such as color, texture and tissues thickness in a perpendicular plane from microscopic images. The experimental results demonstrated that computational analysis is capable of distinguishing anatomical alterations in microscope images obtained from individuals growing in different environmental conditions. The methods presented here offer an alternative way to determine leaf anatomical differences. © 2013 Elsevier B.V.

Desenvolvimento de um sistema de medição de baixo custo para a monitoração de alimentadores aéreos de distribuição de energia elétrica da classe 15 KV

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Extração semi-automática do eixo de rodovia em imagens de média e alta resolução usando programação dinâmica

Pós-graduação em Ciências Cartográficas - FCT

Análise de estruturas flexíveis com aplicação de materiais viscoelásticos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Identificação experimental e controle ativo de vibrações aplicadas em estruturas inteligentes

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Técnica de identificação de parâmetros no domínio do tempo utilizando funções ortogonais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Monitoramento da dressagem do processo de retificação

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Caracterização das propriedades físico-mecânica e de desempenho no lixamento de chapas particuladas (Dendrocalamus Giganteus)

Pós-graduação em Engenharia Mecânica - FEB

Metodologia para análise e interpretação de alarmes em tempo real de sistemas de distribuição de energia elétrica

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