7 resultados para Direct Fourier Method
em Universidade Federal do Rio Grande do Norte(UFRN)
Resumo:
The rotary dryer is one of the most used equipments in processing industries. Its automatic control mode of operation is important specially to keep the moisture content of the final product in the desired value. The classical control strategies, like PID (proportional integral derivative) control, are largely used in the industrial sector because of its robustness and because they are easy to be implemented. In this work, a data acquisition system was implemented for monitoring the most relevant process variables, like: both inlet and outlet drying air temperature, dryer rotation, outlet air speed and humidity, and mass of the final product. Openloop tests were realized to identify a mathematical model able to represent the drying process for the rotary system. From this model, a PID controller was tuned using a direct synthesis method, assuming a first order trajectory. The PID controller was implemented in the system in order to control the inlet drying air temperature. By the end, closedloop tests (operating in automatic mode) were realized to observe the controller performance, and, after setting the best tune, experiments were realized using passion fruit seeds as raw material. The experiments realized in closedloop showed a satisfactory performance by the implemented control strategy for the drying air temperature of the rotary system
Resumo:
The mesoporous molecular sieves of the MCM-41 and FeMCM-41 type are considered promissory as support for metals used as catalysts in oil-based materials refine processes and as adsorbents for environmental protection proposes. In this work MCM-41 and FeMCM41 were synthesized using rice husk ash - RHA as alternative to the conventional silica source. Hydrothermal synthesis was the method chosen to prepare the materials. Pre-defined synthesis parameters were 100°C for 168 hours, later the precursor was calcinated at 550°C for 2 hours under nitrogen and air flow. The sieves containing different proportions of iron were produced by two routes: introduction of iron salt direct synthesis; and a modification post synthesis consisting in iron salt 1 % and 5% impregnation in the material followed by thermal decomposition. The molecular sieves were characterized by X ray diffraction XRD, Fourier transform infrared spectroscopy FT-IR, X ray fluorescence spectroscopy XFR, scanning electronic microscopy SEM, specific surface area using the BET method, Termogravimetry TG. The kinetic model of Flynn Wall was used with the aim of determining the apparent activation energy of the surfactant remove (CTMABr) in the MCM- 41 porous. The analysis made possible the morphology characterization, identifying the presence of hexagonal structure typical for mesoporous materials, as well as observation of the MCM41 and iron of characteristic bands.
Resumo:
Oil prospecting is one of most complex and important features of oil industry Direct prospecting methods like drilling well logs are very expensive, in consequence indirect methods are preferred. Among the indirect prospecting techniques the seismic imaging is a relevant method. Seismic method is based on artificial seismic waves that are generated, go through the geologic medium suffering diffraction and reflexion and return to the surface where they are recorded and analyzed to construct seismograms. However, the seismogram contains not only actual geologic information, but also noise, and one of the main components of the noise is the ground roll. Noise attenuation is essential for a good geologic interpretation of the seismogram. It is common to study seismograms by using time-frequency transformations that map the seismic signal into a frequency space where it is easier to remove or attenuate noise. After that, data is reconstructed in the original space in such a way that geologic structures are shown in more detail. In addition, the curvelet transform is a new and effective spectral transformation that have been used in the analysis of complex data. In this work, we employ the curvelet transform to represent geologic data using basis functions that are directional in space. This particular basis can represent more effectively two dimensional objects with contours and lines. The curvelet analysis maps real space into frequencies scales and angular sectors in such way that we can distinguish in detail the sub-spaces where is the noise and remove the coefficients corresponding to the undesired data. In this work we develop and apply the denoising analysis to remove the ground roll of seismograms. We apply this technique to a artificial seismogram and to a real one. In both cases we obtain a good noise attenuation
Resumo:
In the oil prospection research seismic data are usually irregular and sparsely sampled along the spatial coordinates due to obstacles in placement of geophones. Fourier methods provide a way to make the regularization of seismic data which are efficient if the input data is sampled on a regular grid. However, when these methods are applied to a set of irregularly sampled data, the orthogonality among the Fourier components is broken and the energy of a Fourier component may "leak" to other components, a phenomenon called "spectral leakage". The objective of this research is to study the spectral representation of irregularly sampled data method. In particular, it will be presented the basic structure of representation of the NDFT (nonuniform discrete Fourier transform), study their properties and demonstrate its potential in the processing of the seismic signal. In this way we study the FFT (fast Fourier transform) and the NFFT (nonuniform fast Fourier transform) which rapidly calculate the DFT (discrete Fourier transform) and NDFT. We compare the recovery of the signal using the FFT, DFT and NFFT. We approach the interpolation of seismic trace using the ALFT (antileakage Fourier transform) to overcome the problem of spectral leakage caused by uneven sampling. Applications to synthetic and real data showed that ALFT method works well on complex geology seismic data and suffers little with irregular spatial sampling of the data and edge effects, in addition it is robust and stable with noisy data. However, it is not as efficient as the FFT and its reconstruction is not as good in the case of irregular filling with large holes in the acquisition.
Resumo:
In the oil prospection research seismic data are usually irregular and sparsely sampled along the spatial coordinates due to obstacles in placement of geophones. Fourier methods provide a way to make the regularization of seismic data which are efficient if the input data is sampled on a regular grid. However, when these methods are applied to a set of irregularly sampled data, the orthogonality among the Fourier components is broken and the energy of a Fourier component may "leak" to other components, a phenomenon called "spectral leakage". The objective of this research is to study the spectral representation of irregularly sampled data method. In particular, it will be presented the basic structure of representation of the NDFT (nonuniform discrete Fourier transform), study their properties and demonstrate its potential in the processing of the seismic signal. In this way we study the FFT (fast Fourier transform) and the NFFT (nonuniform fast Fourier transform) which rapidly calculate the DFT (discrete Fourier transform) and NDFT. We compare the recovery of the signal using the FFT, DFT and NFFT. We approach the interpolation of seismic trace using the ALFT (antileakage Fourier transform) to overcome the problem of spectral leakage caused by uneven sampling. Applications to synthetic and real data showed that ALFT method works well on complex geology seismic data and suffers little with irregular spatial sampling of the data and edge effects, in addition it is robust and stable with noisy data. However, it is not as efficient as the FFT and its reconstruction is not as good in the case of irregular filling with large holes in the acquisition.
Resumo:
The classifier support vector machine is used in several problems in various areas of knowledge. Basically the method used in this classier is to end the hyperplane that maximizes the distance between the groups, to increase the generalization of the classifier. In this work, we treated some problems of binary classification of data obtained by electroencephalography (EEG) and electromyography (EMG) using Support Vector Machine with some complementary techniques, such as: Principal Component Analysis to identify the active regions of the brain, the periodogram method which is obtained by Fourier analysis to help discriminate between groups and Simple Moving Average to eliminate some of the existing noise in the data. It was developed two functions in the software R, for the realization of training tasks and classification. Also, it was proposed two weights systems and a summarized measure to help on deciding in classification of groups. The application of these techniques, weights and the summarized measure in the classier, showed quite satisfactory results, where the best results were an average rate of 95.31% to visual stimuli data, 100% of correct classification for epilepsy data and rates of 91.22% and 96.89% to object motion data for two subjects.
Resumo:
The mesoporous molecular sieves of the MCM-41 and FeMCM-41 type are considered promissory as support for metals used as catalysts in oil-based materials refine processes and as adsorbents for environmental protection proposes. In this work MCM-41 and FeMCM41 were synthesized using rice husk ash - RHA as alternative to the conventional silica source. Hydrothermal synthesis was the method chosen to prepare the materials. Pre-defined synthesis parameters were 100°C for 168 hours, later the precursor was calcinated at 550°C for 2 hours under nitrogen and air flow. The sieves containing different proportions of iron were produced by two routes: introduction of iron salt direct synthesis; and a modification post synthesis consisting in iron salt 1 % and 5% impregnation in the material followed by thermal decomposition. The molecular sieves were characterized by X ray diffraction XRD, Fourier transform infrared spectroscopy FT-IR, X ray fluorescence spectroscopy XFR, scanning electronic microscopy SEM, specific surface area using the BET method, Termogravimetry TG. The kinetic model of Flynn Wall was used with the aim of determining the apparent activation energy of the surfactant remove (CTMABr) in the MCM- 41 porous. The analysis made possible the morphology characterization, identifying the presence of hexagonal structure typical for mesoporous materials, as well as observation of the MCM41 and iron of characteristic bands.