In-process grinding monitoring by 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 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. The acoustic emission signals were acquired from a fixed sensor placed on the workpiece holder. A high sampling rate data acquisition system at 2.5 MHz was used to collect the raw acoustic emission instead of root mean square value usually employed. Many statistics have shown effective to detect burn, such as the root mean square (RMS), correlation of the AE, constant false alarm (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.

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.

Toxoplasma gondii: Comparison of a rhoptry-ELISA with IFAT and MAT for antibody detection in sera of experimentally infected pigs

Indirect ELISA and IFAT have been reported to be more sensitive and specific than agglutination tests. However, MAT is cheaper, easier than the others and does not need special equipment. The purpose of this study was to compare an enzyme linked immunosorbent assay using crude rhoptries of Toxoplasma gondii as coating wells (r-ELISA) with indirect fluorescence antibody test (IFAT) and modified agglutination test (MAT) to detect anti-T. gondii antibodies in sera of experimentally infected pigs. Ten mixed breed pigs between 6.5 and 7.5 weeks old were used. All pigs were negative for the presence of T. gondii antibodies by IFAT (titre < 16), r-ELISA (OD < 0.295) and MAT (titre < 16). Animals received 7 × 107 viable tachyzoites of the RH strain by intramuscular (IM) route at day 0. Serum samples were collected at days -6, 0, 7, 14, 21, 28, 35, 42, 50, and 57. IFAT detected anti-T. gondii antibodies earlier than r-ELISA and MAT. The average of antibody levels was higher at day 35 in IFAT (Log10 = 2.9) and in MAT (Log10 = 3.5), and at day 42 in r-ELISA (OD = 0.797). The antibody levels remained high through the 57th day after inoculation in MAT, and there was a decrease tendency in r-ELISA and IFAT. IFAT was used as gold standard and r-ELISA demonstrated a higher prevalence (73.3%), sensitivity (94.3%), negative predictive value (83.3%), and accuracy (95.6%) than MAT. Kappa agreements among tests were calculated, and the best results were shown by r-ELISA × IFAT (κ = 0.88, p < 0.001). Cross-reaction with Sarcocystis miescheriana was investigated in r-ELISA and OD mean was 0.163 ± 0.035 (n = 65). Additionally, none of the animals inoculated with Sarcocystis reacted positively in r-ELISA. Our results indicate that r-ELISA could be a good method for serological detection of T. gondii infection in pigs. © 2005 Elsevier Inc. All rights reserved.

Application of ARX neural networks to model the rate of penetration of petroleum wells drilling

Bit performance prediction has been a challenging problem for the petroleum industry. It is essential in cost reduction associated with well planning and drilling performance prediction, especially when rigs leasing rates tend to follow the projects-demand and barrel-price rises. A methodology to model and predict one of the drilling bit performance evaluator, the Rate of Penetration (ROP), is presented herein. As the parameters affecting the ROP are complex and their relationship not easily modeled, the application of a Neural Network is suggested. In the present work, a dynamic neural network, based on the Auto-Regressive with Extra Input Signals model, or ARX model, is used to approach the ROP modeling problem. The network was applied to a real oil offshore field data set, consisted of information from seven wells drilled with an equal-diameter bit.

Applying a genetic neuro-model reference adaptive controller in drilling optimization

Motivated by rising drilling operation costs, the oil industry has shown a trend toward real-time measurements and control. In this scenario, drilling control becomes a challenging problem for the industry, especially due to the difficulty associated with parameters modeling. One of the drillbit performance evaluators, the Rate Of Penetration (ROP), has been used as a drilling control parameter. However, relationships between operational variables affecting the ROP are complex and not easily modeled. This work presents a neuro-genetic adaptive controller to treat this problem. It is based on an auto-regressive with extra input signals, or ARX model and on a Genetic Algorithm (GA) to control the ROP. © [2006] IEEE.

A genetic neuro-model reference adaptive controller for petroleum wells drilling operations

Motivated by rising drilling operation costs, the oil industry has shown a trend towards real-time measurements and control. In this scenario, drilling control becomes a challenging problem for the industry, especially due to the difficulty associated to parameters modeling. One of the drill-bit performance evaluators, the Rate of Penetration (ROP), has been used in the literature as a drilling control parameter. However, the relationships between the operational variables affecting the ROP are complex and not easily modeled. This work presents a neuro-genetic adaptive controller to treat this problem. It is based on the Auto-Regressive with Extra Input Signals model, or ARX model, to accomplish the system identification and on a Genetic Algorithm (GA) to provide a robust control for the ROP. Results of simulations run over a real offshore oil field data, consisted of seven wells drilled with equal diameter bits, are provided. © 2006 IEEE.

Neural networks models for wear patterns recognition of single-point dresser

Grinding is a workpiece finishing process for advanced products and surfaces. However, the constant friction between workpiece and grinding wheel causes the latter to lose its sharpness, thereby impairing the result of the grinding process. When this occurs, the dressing process is essential to sharpen the worn grains of the grinding wheel. The dressing conditions strongly influence the performance of the grinding operation; hence, monitoring them throughout the process can increase its efficiency. The purpose of this study was to classify the wear condition of a single-point dresser using intelligent systems whose inputs were obtained by digitally processing acoustic emission signals. Two multilayer perceptron (MLP) neural networks were compared for their classification ability, one using the root mean square (RMS) statistics and another the ratio of power (ROP) statistics as input. In this study, it was found that the harmonic content of the acoustic emission signal is influenced by the condition of the dresser, and that the condition of the tool under study can be classified by using the aforementioned statistics to feed a neural network. © IFAC.

Classificação de níveis de desgaste de dressadores de ponta única utilizando sinais de emissão acústica e redes neurais artificiais

Pós-graduação em Engenharia Elétrica - FEB

Efeitos da mistura enantiomérica da bupivacaína(S75/R25), da bupivacaína racêmica e da ropivacaína sobre a funçao mecânica do músculo isolado de ratos

Pós-graduação em Anestesiologia - FMB

Early light reduction for preventing retinopathy of prematurity in very low birth weight infants

BackgroundRetinopathy of prematurity (ROP) is a complex condition of the developing retinal blood vessels and is one of the leading causes of preventable childhood blindness. Several risk factors for ROP have been studied over the past 50 years. Among them, general immaturity (low birth weight and low gestational age) and prolonged oxygen therapy have been consistently related to disease onset. However, it is understood that the progression of the disease is multifactorial and may be associated with others risk factors, such as multiple gestation, apnoea, intracranial haemorrhage, anaemia, sepsis, prolonged mechanical ventilation, multiple transfusions and light exposure. Furthermore, the precise role of these individual factors in the development of the disease has not yet been well established.ObjectivesTo determine whether the reduction of early environmental light exposure reduces the incidence of retinopathy of prematurity (ROP) or poor ROP outcomes among very low birth weight infants.Search methodsWe searched the following databases: the Cochrane Neonatal Group Specialised Register, CENTRAL (The Cochrane Library), MEDLINE, EMBASE, CINAHL, HealthSTAR, Science Citation Index Database, CANCERLIT, the Oxford Database of Perinatal Trials and www.clinicaltrials.gov. We also searched previous reviews including cross-references, abstracts, conference and symposia proceedings, and contacted expert informants. This search was updated in October 2012.Selection criteriaRandomised or quasi-randomised controlled trials that reduced light exposure to premature infants within the first seven days following birth were considered for this review. We also considered cluster-randomised controlled trials.Data collection and analysisData on clinical outcomes including any acute ROP and poor ROP outcome were extracted by both review authors independently and consensus reached. We conducted data analysis according to the standards of the Cochrane Neonatal Review Group.Main resultsData from four randomised trials with a total of 897 participants failed to show any reduction in acute ROP or poor ROP outcome with the reduction of ambient light to premature infants' retinas. The overall methodological quality of the included studies was about evenly split between those in which the classification was unclear and those in which the studies were categorised as low risk of bias. There was no report on the secondary outcomes considered in this review: quality of life measures; and time of exposure to oxygen.Authors' conclusionsThe evidence shows that bright light is not the cause of retinopathy of prematurity and that the reduction of exposure of the retinas of premature infants to light has no effect on the incidence of the disease.

Modelamento matemático para otimização de perfuração em seções de pré-pal: um foco em operações no oceano Atlântico sul

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)