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.

Fault section estimation in electric power systems using an optimization immune algorithm

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

Comparing the Teaching-Learning Process With and Without the Use of Computerized Technological Resources

Computerized technological resources have become essential in education, particularly for teaching topics that require the performance of specific tasks. These resources can effectively help the execution of such tasks and the teaching-learning process itself. After the development of a Web site on the topic of nursing staff scheduling, this study aimed at comparing the development of students involved in the teaching-learning process of the previously mentioned topic, with and without the use of computer technology. Two random groups of undergraduate nursing students from a public university in São Paulo state, Brazil, were organized: a case group (used the Web site) and a control group (did not use the Web site). Data were collected from 2003 to 2005 after approval by the Research Ethics Committee. Results showed no significant difference in motivation or knowledge acquisition. A similar performance for the two groups was also verified. Other aspects observed were difficulty in doing the nursing staff scheduling exercise and the students' acknowledgment of the topic's importance for their training and professional lives; easy access was considered to be a positive aspect for maintaining the Web site.

Pulpal temperature increase with high-speed handpiece, ER : YAG laser and ultrasound tips

The aim of this study was to compare intrapulpal temperature increase produced by high-speed handpiece, Er:YAG laser and CVDentus ultrasound tips during cavity preparation. Thirty bovine mandibular incisors with an enamel/dentin thickness of 4 mm at buccal surface had their roots amputated and were allocated to the following groups (n=10): Group I- high-speed handpiece; Group II- noncontact Er:YAG laser (250 mJ/4Hz); and Group III- CVDentus ultrasouns tips. All devices were used with water cooling. Class V cavities were prepared to a depth of 3.5 mm, measured with a periodontal probe. A type T thermocouple was placed inside the pulp chamber to determine the temperature increase (degrees C), which was recorded by a data acquisition system ADS 2000 IP (Lynx Technology) linked to a notebook computer. Data were analyzed statistically by oneway ANOVA and Tukey's test (p=0.05). The mean temperature rises were: 1.10 degrees C ( 0.56) for Group 1, 0.84 degrees C (0.55) for Group II, and 3.00 degrees C (1.34) for Group III. There were no statistically significant differences (p > 0.05) between Groups I and II, but both of them differed significantly from Group III (p < 0.05). In conclusion, the use of Er:YAG laser and high-speed handpiece for cavity preparation resulted in similar temperature increase. Although ultrasound tips generated significantly higher intrapulpal temperature increase, it remained below the critical value of 5.5 degrees C and may be considered safe for use.

Sincronismo de dispositivos para o georreferenciamento de imagens digitais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Effect of maltodextrin on the freezing point and thermal conductivity of uvaia pulp (Eugenia piriformis Cambess)

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

A equipe de saúde como mediadora no desenvolvimento psicossocial da criança hospitalizada

Num primeiro momento a criança se apropria do conhecimento por mediações externas, nas quais um objeto externo a ela, que pode ser um adulto, faz uma mediação entre ela e o conteúdo a ser adquirido. Assim, a hospitalização pode tornar-se um fator de risco no desenvolvimento psicológico da criança, tanto no âmbito cognitivo quanto no afetivo, caso suas potencialidades não sejam mediadas pela equipe de saúde, pois esta tem grande contato com a criança durante a internação. Foi investigado, como objetivo do estudo, o conhecimento do processo de desenvolvimento infantil por parte dos profissionais da saúde envolvidos no cuidado com crianças hospitalizadas, em um hospital-escola público do Estado de São Paulo. Participaram da pesquisa onze profissionais, entre técnicas e auxiliares de enfermagem, e os resultados indicam que estas consideram importantes alguns aspectos no cuidado com a criança, tais como estimulação da linguagem, atenção, brincadeira, vinculação, contato físico, porém não reconhecem estes aspectos como importantes para o desenvolvimento, e elegem profissionais específicos para tratarem de aspectos relacionados ao desenvolvimento infantil na internação, não se percebendo como mediadoras no processo de desenvolvimento psicossocial da criança hospitalizada.

Dressing monitoring with a digital signal processor

Grinding is a finishing process in machining operations, and the topology of the grinding tool is responsible for producing the desired result on the surface of the machined material The tool topology is modeled in the dressing process and precision is therefore extremely important This study presents a solution in the monitoring of the dressing process, using a digital signal processor (DSP) operating in real time to detect the optimal dressing moment To confirm the monitoring efficiency by DSP, the results were compared with those of a data acquisition system (DAQ) and offline processing The method employed here consisted of analyzing the acoustic emission and electrical power signal by applying the DPO and DPKS parameters The analysis of the results allowed us to conclude that the application of the DPO and DPKS parameters can be substituted by processing of the mean acoustic emission signal, thus reducing the computational effort

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.

Using artificial intelligence for the control of medium voltage substations

This paper introduces a method for the supervision and control of devices in electric substations using fuzzy logic and artificial neural networks. An automatic knowledge acquisition process is included which allows the on-line processing of operator actions and the extraction of control rules to replace gradually the human operator. Some experimental results obtained by the application of the implemented software in a simulated environment with random signal generators are presented.

Conceptual model for adaptable and extensible visual data exploration

Interactive visual representations complement traditional statistical and machine learning techniques for data analysis, allowing users to play a more active role in a knowledge discovery process and making the whole process more understandable. Though visual representations are applicable to several stages of the knowledge discovery process, a common use of visualization is in the initial stages to explore and organize a sometimes unknown and complex data set. In this context, the integrated and coordinated - that is, user actions should be capable of affecting multiple visualizations when desired - use of multiple graphical representations allows data to be observed from several perspectives and offers richer information than isolated representations. In this paper we propose an underlying model for an extensible and adaptable environment that allows independently developed visualization components to be gradually integrated into a user configured knowledge discovery application. Because a major requirement when using multiple visual techniques is the ability to link amongst them, so that user actions executed on a representation propagate to others if desired, the model also allows runtime configuration of coordinated user actions over different visual representations. We illustrate how this environment is being used to assist data exploration and organization in a climate classification problem.

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.

Freezing point and thermal conductivity of tropical fruit pulps: Mango and papaya

The freezing point depression of mango and papaya pulps was measured by using a simple apparatus, consisting of two major sections: a freezing vessel and a data acquisition system. The thermal conductivity of both pulps as a function of frozen water fraction and temperature was also investigated by using a coaxial dual-cylinder apparatus. Thermal conductivity above the initial freezing point was well fitted by polynomial equations. Below the freezing point, the thermal conductivity was strongly affected by both the frozen water fraction and temperature. Simple equations in terms of frozen water fraction and temperature could be fitted to the experimental data of freezing point depression and thermal conductivity.

Neural network approach for surface roughness prediction in surface grinding

Several systems are currently tested in order to obtain a feasible and safe method for automation and control of grinding process. This work aims to predict the surface roughness of the parts of SAE 1020 steel ground in a surface grinding machine. Acoustic emission and electrical power signals were acquired by a commercial data acquisition system. The former from a fixed sensor placed near the workpiece and the latter from the electric induction motor that drives the grinding wheel. Both signals were digitally processed through known statistics, which with the depth of cut composed three data sets implemented to the artificial neural networks. The neural network through its mathematical logical system interpreted the signals and successful predicted the workpiece roughness. The results from the neural networks were compared to the roughness values taken from the worpieces, showing high efficiency and applicability on monitoring and controlling the grinding process. Also, a comparison among the three data sets was carried out.

Lumbo-pelvic stability and electromyography of abdominal muscles in ballet dancers

Evaluating the ability to rectify and maintain lumbar adjustment can contribute toward the understanding of the behavior of abdominal muscles and their participation in the stability of pelvic muscles in dancers during the posterior pelvic tilt and double straight leg lowering tests. Nine healthy volunteers (male and female ballet dancers; age mean: 25.9 ±7.37 years) underwent maximal isometric voluntary contraction (MIVC), isometric voluntary contraction at 50% of MIVC, posterior pelvic tilt (PPT) and double straight leg lowering (DSLL) tests. The tests were carried out in a single day, with 3 repetitions each. During the tests, electromygraphic signals of the rectus abdominis, obliquus internus and obliquus externus were recorded. The signal acquisition system was made up of bipolar surface electrodes, electrogoniometer and an electromechanic device (pressure sensor), which were connected to a signal conditioner module. Root mean square values of each muscle during the DSLL and PPT were converted into percentage of activation of 50% MIVC. Lower back pressure was submitted to the same process. ANOVA with repeated measures was performed, with the level of significance set at p < 0.05. The results revealed that all dancers were able to maintain posterior pelvic tilt and there was trend toward greater activation of the bilateral obliquus internus muscle. In an attempt to keep the pelvic region stabilized during DSLL, there was a greater contribution from the obliquus externus muscle in relation to other abdominal muscles.