Modelagem e análise dinâmica de um sistema de conversão de energia eólica dotado de gerador síncrono de imã permanente utilizando a plataforma ATP

Human development requires a broad balance between ecological, social and economic factors in order to ensure its own sustainability. In this sense, the search for new sources of energy generation, with low deployment and operation costs, which cause the least possible impact to the environment, has been the focus of attention of all society segments. To do so, the reduction in exploration of fossil fuels and the encouragement of using renewable energy resources for distributed generation have proved interesting alternatives to the expansion of the energy matrix of various countries in the world. In this sense, the wind energy has acquired an increasingly significant role, presenting increasing rates of power grid penetration and highlighting technological innovations such as the use of permanent magnet synchronous generators (PMSG). In Brazil, this fact has also been noted and, as a result, the impact of the inclusion of this source in the distribution and sub-transmission power grid has been a major concern of utilities and agents connected to Brazilian electrical sector. Thus, it is relevant the development of appropriate computational tools that allow detailed predictive studies about the dynamic behavior of wind farms, either operating with isolated load, either connected to the main grid, taking also into account the implementation of control strategies for active/reactive power generation and the keeping of adequate levels of voltage and frequency. This work fits in this context since it comprises mathematical and computational developments of a complete wind energy conversion system (WECS) endowed with PMSG using time domain techniques of Alternative Transients Program (ATP), which prides itself a recognized reputation by scientific and academic communities as well as by electricity professionals in Brazil and elsewhere. The modeling procedures performed allowed the elaboration of blocks representing each of the elements of a real WECS, comprising the primary source (the wind), the wind turbine, the PMSG, the frequency converter, the step up transformer, the load composition and the power grid equivalent. Special attention is also given to the implementation of wind turbine control techniques, mainly the pitch control responsible for keeping the generator under the maximum power operation point, and the vector theory that aims at adjusting the active/reactive power flow between the wind turbine and the power grid. Several simulations are performed to investigate the dynamic behavior of the wind farm when subjected to different operating conditions and/or on the occurrence of wind intensity variations. The results have shown the effectiveness of both mathematical and computational modeling developed for the wind turbine and the associated controls.

Classificação de atividade eletromiográfia facial de indivíduos saudáveis e com hanseníese por meio de máquina de vetores de suporte

A number of studies in the areas of Biomedical Engineering and Health Sciences have employed machine learning tools to develop methods capable of identifying patterns in different sets of data. Despite its extinction in many countries of the developed world, Hansen’s disease is still a disease that affects a huge part of the population in countries such as India and Brazil. In this context, this research proposes to develop a method that makes it possible to understand in the future how Hansen’s disease affects facial muscles. By using surface electromyography, a system was adapted so as to capture the signals from the largest possible number of facial muscles. We have first looked upon the literature to learn about the way researchers around the globe have been working with diseases that affect the peripheral neural system and how electromyography has acted to contribute to the understanding of these diseases. From these data, a protocol was proposed to collect facial surface electromyographic (sEMG) signals so that these signals presented a high signal to noise ratio. After collecting the signals, we looked for a method that would enable the visualization of this information in a way to make it possible to guarantee that the method used presented satisfactory results. After identifying the method's efficiency, we tried to understand which information could be extracted from the electromyographic signal representing the collected data. Once studies demonstrating which information could contribute to a better understanding of this pathology were not to be found in literature, parameters of amplitude, frequency and entropy were extracted from the signal and a feature selection was made in order to look for the features that better distinguish a healthy individual from a pathological one. After, we tried to identify the classifier that best discriminates distinct individuals from different groups, and also the set of parameters of this classifier that would bring the best outcome. It was identified that the protocol proposed in this study and the adaptation with disposable electrodes available in market proved their effectiveness and capability of being used in different studies whose intention is to collect data from facial electromyography. The feature selection algorithm also showed that not all of the features extracted from the signal are significant for data classification, with some more relevant than others. The classifier Support Vector Machine (SVM) proved itself efficient when the adequate Kernel function was used with the muscle from which information was to be extracted. Each investigated muscle presented different results when the classifier used linear, radial and polynomial kernel functions. Even though we have focused on Hansen’s disease, the method applied here can be used to study facial electromyography in other pathologies.

Classificação de atividade eletromiográfia facial de indivíduos saudáveis e com hanseníase por meio de máquina de vetores de suporte

A number of studies in the areas of Biomedical Engineering and Health Sciences have employed machine learning tools to develop methods capable of identifying patterns in different sets of data. Despite its extinction in many countries of the developed world, Hansen’s disease is still a disease that affects a huge part of the population in countries such as India and Brazil. In this context, this research proposes to develop a method that makes it possible to understand in the future how Hansen’s disease affects facial muscles. By using surface electromyography, a system was adapted so as to capture the signals from the largest possible number of facial muscles. We have first looked upon the literature to learn about the way researchers around the globe have been working with diseases that affect the peripheral neural system and how electromyography has acted to contribute to the understanding of these diseases. From these data, a protocol was proposed to collect facial surface electromyographic (sEMG) signals so that these signals presented a high signal to noise ratio. After collecting the signals, we looked for a method that would enable the visualization of this information in a way to make it possible to guarantee that the method used presented satisfactory results. After identifying the method's efficiency, we tried to understand which information could be extracted from the electromyographic signal representing the collected data. Once studies demonstrating which information could contribute to a better understanding of this pathology were not to be found in literature, parameters of amplitude, frequency and entropy were extracted from the signal and a feature selection was made in order to look for the features that better distinguish a healthy individual from a pathological one. After, we tried to identify the classifier that best discriminates distinct individuals from different groups, and also the set of parameters of this classifier that would bring the best outcome. It was identified that the protocol proposed in this study and the adaptation with disposable electrodes available in market proved their effectiveness and capability of being used in different studies whose intention is to collect data from facial electromyography. The feature selection algorithm also showed that not all of the features extracted from the signal are significant for data classification, with some more relevant than others. The classifier Support Vector Machine (SVM) proved itself efficient when the adequate Kernel function was used with the muscle from which information was to be extracted. Each investigated muscle presented different results when the classifier used linear, radial and polynomial kernel functions. Even though we have focused on Hansen’s disease, the method applied here can be used to study facial electromyography in other pathologies.

A crença sobre a morte e o coping religioso-espiritual em pacientes internados com doenças crônicas

The human being is understood as an integral being, complex, which has multiple dimensions: social, biological, psychological, anthropological, spiritual and others. As its biological dimension, the man presents the possibility of physical illness, which means that the body requires care. The sick away from humans in health and safety conditions, approaching them directly from the finitude and vulnerability condition, leading us to contact the major uncertainties of life: suffering of disease and death. Religiosity and spirituality are important coping strategy for human when faced with borderline situations. When people turn to religion to cope with stress is the religious and spiritual coping. The objective of this research was to evaluate the relationship between the views on death and the religious-spiritual coping in patients with chronic diseases hospitalized. The study included ten patients hospitalized for chronic disease complications Medical Clinic Unit of a public hospital in the city of Uberlândia/MG. two psychological scales were used: Scale Religious-Spiritual Coping Brief (CRE-Brief Scale) and Scale Brief Diverse Perspectives of Death and a structured interview (audiogravada) on the subject of death and religious and spiritual coping. The results indicated that 80% of the sample (N = 8) consisted of patients hospitalized due to chronic diseases, while 20% accounted for patients with AIDS complications. Analyzing the results of scale CRE-Brief, it emphasizes the use of strategies of religious and spiritual coping by participants as compared to CRE Total, all study participants had average or high scores for this index, with a low utilization CRE negative and average utilization CRE Positive. Regarding views on death, the results obtained by the Different Perspectives Quick Scale on Death suggest that this sample agrees with the view death as something that is part of the natural cycle of life (M8 - Death as a natural end) and features the prospect of death as uncertainty, mystery and ignorance (M4 - death as Unknown). The correlations between the measures the factors and items of CRE-Bref and dimensions of Short scales on different perspectives of Death notes the prevalence of correlations of M4 dimensions - Death as unknown and M8 - Death as a natural order to the creditor scale soon. In the interview analysis revealed a positive influence of religion/ spirituality on health, from the perspective of the respondent, highlighting the protection promoted by religion. It also noticed the use of prayer as a coping strategy of hospitalization and illness. Regarding the interview about the topic of death, there was a predominance of issues related to "afterlife", "unknown" and "abandonment", which are associated with the visions of death and mystery and death as a natural end. In the interviews there belief clues about death as a terrifying mystery connected, so the unknown and the feeling of fear on the same. The experience of illness can therefore be considered as a source of vulnerability, since it is present personal perception of danger (external) - own illness and possible death, especially in those patients undergoing ICU - and where control is insufficient for the sense of security, since the hospital providing care to the patient are delegated to third parties and patients assume a passive role. This fact is important and relevant to health professionals who deal daily with patients hospitalized for chronic diseases, since the recourse to religion and spirituality as a coping strategy that psychic movement was not constituted in a form of negative distance or even denial of health condition. On the contrary, it refers to a movement in search of comfort and security provided by the religion and spirituality.