Sistema de visão computacional aplicado à inspeção automática interna de tubos de pequeno diâmetro

Orientador: Alessandro ZimmerCoorientador: Alceu Britto JúniorDissertação (mestrado) - Universidade Federal do Paraná, Setor de Tecnologia, Programa de Pós-Graduação em Engenharia Elétrica. Defesa : Curitiba, 26/07/2018Inclui referências: p. 56-58Resumo: Esta dissertação apresenta os principais aspectos de desenvolvimento de um sistema de aquisição e processamento de imagens que pode ser inserido em sistemas de tubos metálicos de termoelétricas a fim de se capturar imagens da região interna de tais tubos para análise. Após a imagem ser capturada, esta é processada resultando vários segmentos, nos quais são aplicados uma análise de textura e então utilizado um classificador para identificar de maneira automática alguns tipos de corrosão ou defeito. Os testes experimentais feitos com base em um conjunto de 2,615 imagens mostraram que os modelos propostos de classificação podem atingir taxas de acerto entre 90% e 94% ao classificarem um conjunto de images para teste, obtidas com um modelo de câmera, factível as dimensões demandadas do projeto, e 100% nas imagens de teste, obtidas com outro modelo de câmera, com dimensões não factíveis ao projeto final. Palavras-chave: Inspeção visual. Textura. Fusão de características. Inspeção automática.Abstract: This dissertation presents the main aspects of the design of an image acquisition and processing approach that can be inserted into thermoelectric metal pipe systems and travel inside the pipes to capture images from the inner surface of such pipes for further analysis. After the image capture, a texture analysis of its internal surface is carried out to classify automatically segments from the image that present some type of corrosion or defects. The experimental results on a dataset of 2,615 images have shown that proposed classification models can achieve accuracy between 90% and 94% on the test set, using a feasible camera for the project and 100% using another camera model. Keywords: Visual inspection. Texture. Fusion of features. Automatic inspection

Safe Autonomous Driving in Adverse Weather: Sensor Evaluation and Performance Monitoring

The vehicle's perception sensors radar, lidar and camera, which must work continuously and without restriction, especially with regard to automated/autonomous driving, can lose performance due to unfavourable weather conditions. This paper analyzes the sensor signals of these three sensor technologies under rain and fog as well as day and night. A data set of a driving test vehicle as an object target under different weather conditions was recorded in a controlled environment with adjustable, defined, and reproducible weather conditions. Based on the sensor performance evaluation, a method has been developed to detect sensor degradation, including determining the affected data areas and estimating how severe they are. Through this sensor monitoring, measures can be taken in subsequent algorithms to reduce the influences or to take them into account in safety and assistance systems to avoid malfunctions.Comment: Accepted for the 35th IEEE Intelligent Vehicles Symposium (IV 2023), 6 page

Epiploic appendagitis – clinical characteristics of an uncommon surgical diagnosis

<p>Abstract</p> <p>Background</p> <p>Epiploic appendagitis (EA) is a rare cause of focal abdominal pain in otherwise healthy patients with mild or absent secondary signs of abdominal pathology. It can mimick diverticulitis or appendicitis on clinical exam. The diagnosis of EA is very infrequent, due in part to low or absent awareness among general surgeons. The objective of this work was to review the authors' experience and describe the clinical presentation of EA.</p> <p>Methods</p> <p>All patients diagnosed with EA between January 2004 and December 2006 at an urban surgical emergency room were retrospectively reviewed by two authors in order to share the authors' experience with this rare diagnosis. The operations were performed by two surgeons. Pathological examinations of specimens were performed by a single pathologist. A review of clinical presentation is additionally undertaken.</p> <p>Results</p> <p>Ten patients (3 females and 7 males, average age: 44.6 years, range: 27–76 years) were diagnosed with symptomatic EA. Abdominal pain was the leading symptom, the pain being localized in the left (8 patients, 80 %) and right (2 patients, 20%) lower quadrant. All patients were afebrile, and with the exception of one patient, nausea, vomiting, and diarrhea were not present. CRP was slightly increased (mean: 1.2 mg/DL) in three patients (33%). Computed tomography findings specific for EA were present in five patients. Treatment was laparoscopic excision (n = 8), excision via conventional laparotomy (n = 1) and conservative therapy (n = 1).</p> <p>Conclusion</p> <p>In patients with localized, sharp, acute abdominal pain not associated with other symptoms such as nausea, vomiting, fever or atypical laboratory values, the diagnosis of EA should be considered. Although infrequent up to date, with the increase of primary abdominal CT scans and ultrasound EA may well be diagnosed more frequently in the future.</p

Applicability evaluation of a laser light-mater interaction based computational tool on status tdentification of applied micro-structured coatings

The current work aims at evaluating a proposed method based on a computational tool developed using Object-Oriented Programming to identify the status of micro-structured surfaces. In this case, these are micro-structured coatings with riblet microstructure developed by Fraunhofer Institute–IFAM, by building a graphical reproduction of the analyzed surface and calculating an expected laser reflection intensity acquired by a laser sensor device, the proposed method is assessed by using the simplest case: a flat surface, and an optimal case: an intact riblet surface. The results corroborate the calculations to be applied to further steps from more complex cases of degradation and to diverse riblets geometries. Based on Huygens-Fresnel and Fraunhofer diffraction theories, the calculations developed and demonstrated in this paper improved the nondestructive tests to support the status identification of the microstructured coatings, e.g. riblet structures based on shark skin used in shipping and aerospace industries. This work is assured required quality of the riblet coating identifying the number of structures and expected geometry using implemented calculations to foresee the laser reflection intensity acquired by a laser sensor device with 3 detectors, for instance, a riblet structure could be graphically reproduced, analyzed and completely identified based on the application of the theoretical optics applied on this work