Desenvolvimento de uma rede de sensores sem fio aplicada no monitoramento da variabilidade térmica em casas de vegetação

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

In-process thermal damage detection in grinding with monitoring via Internet

This work aims the development of a dedicated system for detection of burning in surface grinding process, where the process will constantly be monitored through the acoustic emission and electric power of the induction motor drive. Acquired by an analog-digital converter, algorithms process the signals and a control signal is generated to inform the operator or interrupt the process in case of burning occurrence. Moreover, the system makes possible the process monitoring via Internet. Additionally, a comparative study between parameters DPO and FKS is carried through. In the experimental work one type of. steel (ABNT-1020 annealed) and one type of grinding wheel referred to as TARGA, model ART 3TG80.3 NVHB, were employed.

Automatic system for thermal damage detection in manufacturing process with Internet monitoring

This work involved the development of a smart system dedicated to surface burning detection in the grinding process through constant monitoring of the process by acoustic emission and electrical power signals. A program in Visual Basic® for Windows® was developed, which collects the signals through an analog-digital converter and further processes them using burning detection algorithms already known. Three other parameters are proposed here and a comparative study carried out. When burning occurs, the newly developed software program sends a control signal warning the operator or interrupting the process, and delivers process information via the Internet. Parallel to this, the user can also interfere in the process via Internet, changing parameters and/or monitoring the grinding process. The findings of a comparative study of the various parameters are also discussed here. Copyright © 2006 by ABCM.

Digital monitoring of broiler breeder behavior for assessment of thermal welfare

The assessment of welfare issues has been a challenge for poultry producers, and lately welfare standards needs to be reached in order to agree with international market demand. This research proposes the use of continuous behavior monitoring in order to contribute for assessing welfare. A software was developed using the language Clarium. The software managed the recording of data as well as the data searching in the database Firebird. Both software and the observational methodology were tested in a trial conducted inside an environmental chamber, using three genetics of broiler breeders. Behavioral pattern was recorded and correlated to ambient thermal and aerial variation. Monitoring video cameras were placed on the roof facing the used for registering the bird's behavior. From video camera images were recorded during the total period when the ambient was bright, and for analyzing the video images a sample of 15min observation in the morning and 15 min in the afternoon was used, adding up to 30 min daily observation. A specific model so-called behavior was developed inside the software for counting specific behavior and its frequency of occurrence, as well as its duration. Electronic identification was recorded for 24h period. Behavioral video recording images was related to the data recorded using electronic identification.. Statistical analysis of data allowed to identify behavioral differences related to the change in thermal environment, and ultimately indicating thermal stress and departure from welfare conditions.

Method of numerical correction of errors occasioned by delay of records during the monitoring of environmental variables of interest for animal production

As condições de ambiente térmico e aéreo, no interior de instalações para animais, alteram-se durante o dia, devido à influência do ambiente externo. Para que análises estatísticas e geoestatísticas sejam representativas, uma grande quantidade de pontos distribuídos espacialmente na área da instalação deve ser monitorada. Este trabalho propõe que a variação no tempo das variáveis ambientais de interesse para a produção animal, monitoradas no interior de instalações para animais, pode ser modelada com precisão a partir de registros discretos no tempo. O objetivo deste trabalho foi desenvolver um método numérico para corrigir as variações temporais dessas variáveis ambientais, transformando os dados para que tais observações independam do tempo gasto durante a aferição. O método proposto aproximou os valores registrados com retardos de tempo aos esperados no exato momento de interesse, caso os dados fossem medidos simultaneamente neste momento em todos os pontos distribuídos espacialmente. O modelo de correção numérica para variáveis ambientais foi validado para o parâmetro ambiental temperatura do ar, sendo que os valores corrigidos pelo método não diferiram pelo teste Tukey, a 5% de probabilidade dos valores reais registrados por meio de dataloggers.

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.

Automatic detection of thermal damage in grinding process by artificial neural network

Esse trabalho tem por objetivo o desenvolvimento de um sistema inteligente para detecção da queima no processo de retificação tangencial plana através da utilização de uma rede neural perceptron multi camadas, treinada para generalizar o processo e, conseqüentemente, obter o limiar de queima. em geral, a ocorrência da queima no processo de retificação pode ser detectada pelos parâmetros DPO e FKS. Porém esses parâmetros não são eficientes nas condições de usinagem usadas nesse trabalho. Os sinais de emissão acústica e potência elétrica do motor de acionamento do rebolo são variáveis de entrada e a variável de saída é a ocorrência da queima. No trabalho experimental, foram empregados um tipo de aço (ABNT 1045 temperado) e um tipo de rebolo denominado TARGA, modelo ART 3TG80.3 NVHB.

Dielectric thermal analysis as a tool for quantitative-evaluation of the viscosity and the kinetics of epoxy resin cure

Dielectric thermal analysis has been proved as a valuable tool for monitoring the epoxy curing process and the related rheological properties in the fabrication of polymer-matrix composite materials. This technique also has the potential to be applied in the monitoring of magnet impregnation processes as well as in quality control. In this work we present the quantitative evaluation of the viscosity changing and the curing kinetics for a commercial Stycast epoxy resin system at different temperatures through the impedance analysis. The results showed correlation between the real component of the complex impedance and the isothermal reaction extent. Comparing the dielectric analysis result with the viscosity measured by rotational rheometer we observed a similar behavior reported for dynamic mechanic analysis. The results comparison have shown that the kinetics parameters obtained from DSC and DETA analysis showed different sensitivities related to the characteristics of curing stages. We concluded that the dielectric thermal analysis should be applied in quantitative evaluation of cure kinetics.

Effect of thermal stress on physiological parameters, feed intake and plasma thyroid hormones concentration in Alentejana, Mertolenga, Frisian and Limousine cattle breeds

The aim of the present study was to assess the heat tolerance of animals of two Portuguese (Alentejana and Mertolenga) and two exotic (Frisian and Limousine) cattle breeds, through the monitoring of physiological acclimatization reactions in different thermal situations characterized by alternate periods of thermoneutrality and heat stress simulated in climatic chambers. In the experiment, six heifers of the Alentejana, Frisian and Mertolenga breeds and four heifers of the Limousine breed were used. The increase in chamber temperatures had different consequences on the animals of each breed. When submitted to heat stress, the Frisian animals developed high thermal polypnea (more than 105 breath movements per minute), which did not prevent an increase in the rectal temperature (from 38.7 degrees C to 40.0 degrees C). However, only a slight depression in food intake and in blood thyroid hormone concentrations was observed under thermal stressful conditions. Under the thermal stressful conditions, Limousine animals decreased food intake by 11.4% and blood triiodothyronine (T3) hormone concentration decreased to 76% of the level observed in thermoneutral conditions. Alentejana animals had similar reactions. The Mertolenga cattle exhibited the highest capacity for maintaining homeothermy: under heat stressful conditions, the mean thermal polypnea increased twofold, but mean rectal temperature did not increase. Mean food intake decreased by only 2% and mean T3 blood concentration was lowered to 85,6% of the concentration observed under thermoneutral conditions. These results lead to the conclusion that the Frisian animals had more difficulty in tolerating high temperatures, the Limousine and Alentejana ones had an intermediate difficulty, and the Mertolenga animals were by far the most heat tolerant.

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.

Fuzzy logic to predict thermal damages of ground parts

One of the critical problems in implementing an intelligent grinding process is the automatic detection of workpiece surface burn. This work uses fuzzy logic as a tool to classify and predict burn levels in the grinding process. Based on acoustic emission signals, cutting power, and the mean-value deviance (MVD), linguistic rules were established for the various burn situations (slight, intermediate, severe) by applying fuzzy logic using the Matlab Toolbox. Three practical fuzzy system models were developed. The first model with two inputs resulted only in a simple analysis process. The second and third models have an additional MVD statistic input, associating information and precision. These two models differ from each other in terms of the rule base developed. The three developed models presented valid responses, proving effective, accurate, reliable and easy to use for the determination of ground workpiece burn. In this analysis, fuzzy logic translates the operator's human experience associated with powerful computational methods.

Monitoring the process of densification of 3D and 4D (tridirectional and tetradirectional) carbon/carbon composites

Carbon fiber reinforced carbon composites can be made by iterative liquid impregnation or gas phase carbon deposition routes. In both cases, at the final processing stage the carbon fiber is embedded in carbon matrix which results in unique properties such as low density, high thermal conductivity and thermal shock resistance, low thermal expansion and high modulus, in relation to other refractory materials. In the present study assembled three-directional and four-directional preforms, having 50% volume of pores, were densified by iterative cycles of thermoset resin impregnation followed by pyrolysis under inert atmosphere, until appropriate densities were achieved. The thermoset resin is converted in a carbon matrix during pyrolysis. The iterative manufacturing process of the carbon fiber reinforced carbon composites is evaluated by means of nondestructive techniques based on X-ray computed tomography and electrical resistivity. X-ray computed tomography gives a general mapping view of the filling pores of the preforms which impacts results of the electrical resistivity. After six processing cycles and heat treatments up to 2000?, the final densities of the three-directional and four-directional carbon fiber reinforced carbon composites were 1.16g/cm(3) and an electrical resistivity of approximate to 0.07m. The configuration of preforms, three-directional or four-directional, did not alter the densification profile, in terms of increasing density and reducing porosity during the processing cycles.

Development of technologies and methods for monitoring the spatial variability of air temperature in greenhouse environment

Climatic factors directly influence growth and productivity of plants inside greenhouses, where temperature can be considered one of the major parameter in this context. Thus, the aim of this research was to develop a low cost device for thermal sensing and data acquisition, and use it in data collection and analysis of spatial variability of temperature inside a greenhouse with tropical climate. The developed equipment for thermal measurements showed a high degree of accuracy and fast responses in measurements, proving its efficiency. The data analysis interpretations were made from the elaborations of variograms and of tridimensional maps generated by a geostatistical software. The processed data analysis presented that a greenhouse without thermal control has spatial variations of air temperature, both in the sampled horizontals layers as in the three analyzed vertical columns, presenting variations of up to 3.6 ºC in certain times.