Uma prática colaborativa na construção do portifólio educacional

Acompanha: Unidade didática: elementos de astronomia e energia

Sensoriamento óptico quase-distribuído aplicado ao monitoramento de trocadores de calor de usinas hidrelétricas

This work aims to develop optical sensors for temperature monitoring in hydroelectric power plant heat exchangers. The proposed sensors are based on the Fiber Bragg Gratings technology. First of all, a prototype with three sensors inscribed in a same fiber was developed. This fiber was then fixed to a conventional Pt100 sensor rod and inserted in a thermowell. The ensemble was then calibrated in a workbench, presenting a maximum combined uncertainty of 2,06 °C. The sensor was installed in one of the heat exchangers of the Salto Osório’s hydroelectric power plant. This power plant is situated in the Iguaçu river, at the Paraná state. Despite the satisfactory results, the sensor was improved to a second version. In this, fifteen optical Bragg sensors were inscribed in a same fiber. The fixation with a conventional sensor was no longer necessary, because the first version results comproved the efficiency and response time in comparison to a conventional sensor. For this reason, it was decided to position the fiber inside a stainless steel rod, due to his low thermal expansion coefficient and high corrosion immunity. The utilization of fifteen fiber Bragg gratings aims to improve the sensor spatial resolution. Therefore, measurements every ten centimeters with respect to the heat exchanger’s height are possible. This provides the generation of a thermal map of the heat exchanger’s surface, which can be used for determination of possible points of obstruction in the hydraulic circuit of the heat exchanger. The heat exchanger’s obstruction in hydroelectric power plants usually occur by bio-fouling, and has direct influence in the generator’s cooling system efficiency. The obtained results have demonstrated the feasibility in application of the optical sensors technology in hydroelectric power plants.

Detecção de região saliente em imagens usando dissimilaridade de cor e amostragem por pixeis aleatórios

The purpose of this work is to demonstrate and to assess a simple algorithm for automatic estimation of the most salient region in an image, that have possible application in computer vision. The algorithm uses the connection between color dissimilarities in the image and the image’s most salient region. The algorithm also avoids using image priors. Pixel dissimilarity is an informal function of the distance of a specific pixel’s color to other pixels’ colors in an image. We examine the relation between pixel color dissimilarity and salient region detection on the MSRA1K image dataset. We propose a simple algorithm for salient region detection through random pixel color dissimilarity. We define dissimilarity by accumulating the distance between each pixel and a sample of n other random pixels, in the CIELAB color space. An important result is that random dissimilarity between each pixel and just another pixel (n = 1) is enough to create adequate saliency maps when combined with median filter, with competitive average performance if compared with other related methods in the saliency detection research field. The assessment was performed by means of precision-recall curves. This idea is inspired on the human attention mechanism that is able to choose few specific regions to focus on, a biological system that the computer vision community aims to emulate. We also review some of the history on this topic of selective attention.