Made available in DSpace on 2014-06-11T19:34:58Z (GMT). No. of bitstreams: 0 Previous issue date: 2009-10-19Bitstream added on 2014-06-13T19:04:56Z : No. of bitstreams: 1 goncalves_vd_dr_guara.pdf: 2777682 bytes, checksum: 5d4369fe1e30d71b1e79eccb5580ba09 (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Este trabalho descreve o desenvolvimento de um sistema de análise de imagens de partículas de desgaste encontradas em óleos lubrificantes de equipamentos industriais. Para tanto, foi utilizado um sistema de aquisição de imagem para capturar imagens de amostras de óleo retidas em membranas de filtro e, também, desenvolvida uma metodologia analítica que faz a classificação quantitativa e qualitativa das partículas, relacionando-as ao modo de desgaste na qual foram geradas. Para a classificação quantitativa utilizou-se a norma ISO 4406 e para a qualitativa, a análise por meio de Redes Neurais Artificiais. O sistema aplicado consiste em uma câmera digital, um microscópio óptico monocular, um sistema de filtragem de óleo e dois programas computacionais desenvolvidos para realização da análise automatizada das imagens das partículas de desgaste obtidas. Foram utilizados óleos minerais de redutores de máquinas industriais no processo de obtenção de amostras. As partículas de desgaste foram analisadas pelo processo de microscopia óptica para obtenção da imagem da amostra relacionada ao desgaste. Os resultados obtidos mostraram que o sistema de análise desenvolvido realiza a classificação individual das partículas, através de Redes Neurais Artificiais, com uma eficiência de até 96%, além de analisar as múltiplas partículas contidas nas amostras, exibindo um relatório de acompanhamento e evolução do desgaste. Os programas computacionais desenvolvidos para essa análise possuem interface gráfica de fácil utilização. Eles podem ser amplamente utilizados no estudo e avaliação das partículas de desgaste obtidas de amostras de óleos industriais em empresas ou em universidades para fins educacionais. O sistema pode ser utilizado para análise de superfícies de metais obtidos pelo processo de metalografia ou na análise de imagens de microorganismos obtidas... / This paper describes the development of an image analysis system for wear particles found in industrial equipment lubricating oil. Hence, it was utilized an image acquisition system to capture image samples of the oil held in filter membranes. An analytical methodology was also developed to classify the particles quantitatively and qualitatively, relating them to the wear mode where they had been generated. The ISO 4406 standard was applied for quantitative classification and Artificial Neural Networks were used for qualitative classification analysis. The applied system consists of a digital camera, a monocular optical microscope, one oil filtering system and two software programs developed to perform the automated analysis of the acquired wear particles images. Mineral oils of gearbox industrial machines were used in the process of achieving the samples. The wear particles were analyzed by an optical microscopy system, to obtain the sample image related to the wear. The results showed that the analysis system that was developed classifies the individual particles through Artificial Neural Networks with 96% accuracy, in addition to analyzing the multiple particles contained in the samples and generating an evaluation report and wear evolution. The software programs developed for the analysis have a graphical interface easy to use. They can be used in the study and evaluation of the wear particles obtained from industrial oil samples in the companies or in the universities for educational purposes. The system can be applied to analyze the surface of metals acquired by metallographic processes or in the image analysis of microorganisms acquired from blood samples, opening a wide field of application within universities and researches.

Made available in DSpace on 2014-06-11T19:27:14Z (GMT). No. of bitstreams: 0 Previous issue date: 2007-11-05Bitstream added on 2014-06-13T18:31:06Z : No. of bitstreams: 1 malpica_lgt_me_ilha.pdf: 964002 bytes, checksum: 9482c67364eb81b4816fbb74b725bdb5 (MD5) / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / Em um motor de combustão interna todas as peças possuem uma vida útil prevista, sendo essa duração maior ou menor, de acordo com a função específica a elas atribuída. Cada uma das peças tem a sua vida pré-determinada que, em condições normais de funcionamento de todo o conjunto, atende as expectativas. Pela análise do óleo podem-se monitorar as condições destas peças. A técnica de análise de óleo é um tipo de manutenção preditiva. Ela pode ser feita coletando-se o óleo de um equipamento e analisando-o posteriormente ou analisando-o diretamente em sistemas “on line”. A análise dos óleos permite identificar os primeiros sintomas de desgaste de um componente. A identificação é feita a partir do estudo da quantidade de partículas, tamanho, forma e composição, que forneceram informações precisas sobre as condições das superfícies em movimento sem a necessidade de se desmontar o conjunto a qual estas partes pertencem. Tais partículas sólidas são geradas pelo atrito dinâmico entre peças em contato. De acordo com o estudo destas partículas pode-se relacionar as situações de desgastes do conjunto e atribuí-las a condições físicas e químicas. A análise dos óleos é feita por meio de técnicas laboratoriais que envolvem, reagentes, instrumentos e equipamentos. Assim, para se estudar a manutenção preditiva em motores de combustão interna, foi feito um estudo teórico sobre estes motores, sobre os lubrificantes, sobre os problemas e possíveis causas associados a falhas destes, sobre os tipos de manutenção preditivas aplicadas a estes e sobre trabalhos que tratam da manutenção preditiva em motores realizados por outros autores. Para auxiliar os estudos foi proposta a construção de duas bancadas de ensaios compostas de motores de quatro tempos, a gasolina, acoplados a um redutor de velocidades para fornecer carga aos mesmos... / In an internal combustion engine every pieces have a foreseen useful life. This duration is large or small according to the specific function to them attributed. Each piece has its own pre determined life that in normal operation conditions of the set attend to the expectations. By oil analysis one can monitor the pieces conditions. The oil analysis technique is a type of predictive maintenance. It can be done collecting the oil of an equipment and analyzing it latter on or analyzing it directly in systems “on line”. The oil analysis allows identifying the early symptoms of a component wear. The identification is done starting from the study of the particle quantity, size, forms and composition that supplies precise information about the moving superficial conditions without the need of disassembling the set which these parts belong to. Such solid particles are generated by dynamic friction among pieces in contact. According to the study of those particle one can relate the wear set situation and to attribute them to physical and chemical conditions. The oil analysis is done by means of laboratories techniques that involve reagent, instruments and equipments. So, to study the predictive maintenance in internal combustion engine it was done a theoretical study about those engine, about lubricants, about problems and possible causes related to fault of them, about the types of predictive maintenance associated to them and about papers that deal to predictive maintenance in internal combustion engine. To aid the studies it was proposed the construction of two test rig composed of gasoline four cycle internal combustion engine coupled to a reducer to supply load to them. In the first test rig it was used an internal combustion engine in advanced state of deterioration and on the second one it was used a new internal combustion engine. The results showed that even in advanced state ...(Complete abstract, click electronic access below)

Orientador: Mauro Hugo Mathias / Co orientador: Mauro Pedro Peres / Banca: José Elias Tomazini / Banca: João Zangrandi Filho / Banca: Francisco Carlos Parquet Bizarria / Banca: Edson Antonio Capello Sousa / Resumo: Este trabalho descreve o desenvolvimento de um sistema de análise de imagens de partículas de desgaste encontradas em óleos lubrificantes de equipamentos industriais. Para tanto, foi utilizado um sistema de aquisição de imagem para capturar imagens de amostras de óleo retidas em membranas de filtro e, também, desenvolvida uma metodologia analítica que faz a classificação quantitativa e qualitativa das partículas, relacionando-as ao modo de desgaste na qual foram geradas. Para a classificação quantitativa utilizou-se a norma ISO 4406 e para a qualitativa, a análise por meio de Redes Neurais Artificiais. O sistema aplicado consiste em uma câmera digital, um microscópio óptico monocular, um sistema de filtragem de óleo e dois programas computacionais desenvolvidos para realização da análise automatizada das imagens das partículas de desgaste obtidas. Foram utilizados óleos minerais de redutores de máquinas industriais no processo de obtenção de amostras. As partículas de desgaste foram analisadas pelo processo de microscopia óptica para obtenção da imagem da amostra relacionada ao desgaste. Os resultados obtidos mostraram que o sistema de análise desenvolvido realiza a classificação individual das partículas, através de Redes Neurais Artificiais, com uma eficiência de até 96%, além de analisar as múltiplas partículas contidas nas amostras, exibindo um relatório de acompanhamento e evolução do desgaste. Os programas computacionais desenvolvidos para essa análise possuem interface gráfica de fácil utilização. Eles podem ser amplamente utilizados no estudo e avaliação das partículas de desgaste obtidas de amostras de óleos industriais em empresas ou em universidades para fins educacionais. O sistema pode ser utilizado para análise de superfícies de metais obtidos pelo processo de metalografia ou na análise de imagens de microorganismos obtidas... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: This paper describes the development of an image analysis system for wear particles found in industrial equipment lubricating oil. Hence, it was utilized an image acquisition system to capture image samples of the oil held in filter membranes. An analytical methodology was also developed to classify the particles quantitatively and qualitatively, relating them to the wear mode where they had been generated. The ISO 4406 standard was applied for quantitative classification and Artificial Neural Networks were used for qualitative classification analysis. The applied system consists of a digital camera, a monocular optical microscope, one oil filtering system and two software programs developed to perform the automated analysis of the acquired wear particles images. Mineral oils of gearbox industrial machines were used in the process of achieving the samples. The wear particles were analyzed by an optical microscopy system, to obtain the sample image related to the wear. The results showed that the analysis system that was developed classifies the individual particles through Artificial Neural Networks with 96% accuracy, in addition to analyzing the multiple particles contained in the samples and generating an evaluation report and wear evolution. The software programs developed for the analysis have a graphical interface easy to use. They can be used in the study and evaluation of the wear particles obtained from industrial oil samples in the companies or in the universities for educational purposes. The system can be applied to analyze the surface of metals acquired by metallographic processes or in the image analysis of microorganisms acquired from blood samples, opening a wide field of application within universities and researches. / Doutor

Orientador: Aparecido Carlos Gonçalves / Banca: Marcio Antonio Bazani / Banca: Roberto Hideaki Tsunaki / Resumo: Em um motor de combustão interna todas as peças possuem uma vida útil prevista, sendo essa duração maior ou menor, de acordo com a função específica a elas atribuída. Cada uma das peças tem a sua vida pré-determinada que, em condições normais de funcionamento de todo o conjunto, atende as expectativas. Pela análise do óleo podem-se monitorar as condições destas peças. A técnica de análise de óleo é um tipo de manutenção preditiva. Ela pode ser feita coletando-se o óleo de um equipamento e analisando-o posteriormente ou analisando-o diretamente em sistemas "on line". A análise dos óleos permite identificar os primeiros sintomas de desgaste de um componente. A identificação é feita a partir do estudo da quantidade de partículas, tamanho, forma e composição, que forneceram informações precisas sobre as condições das superfícies em movimento sem a necessidade de se desmontar o conjunto a qual estas partes pertencem. Tais partículas sólidas são geradas pelo atrito dinâmico entre peças em contato. De acordo com o estudo destas partículas pode-se relacionar as situações de desgastes do conjunto e atribuí-las a condições físicas e químicas. A análise dos óleos é feita por meio de técnicas laboratoriais que envolvem, reagentes, instrumentos e equipamentos. Assim, para se estudar a manutenção preditiva em motores de combustão interna, foi feito um estudo teórico sobre estes motores, sobre os lubrificantes, sobre os problemas e possíveis causas associados a falhas destes, sobre os tipos de manutenção preditivas aplicadas a estes e sobre trabalhos que tratam da manutenção preditiva em motores realizados por outros autores. Para auxiliar os estudos foi proposta a construção de duas bancadas de ensaios compostas de motores de quatro tempos, a gasolina, acoplados a um redutor de velocidades para fornecer carga aos mesmos...(Resumo completo, clicar acesso eletrônico abaixo) / Abstract: In an internal combustion engine every pieces have a foreseen useful life. This duration is large or small according to the specific function to them attributed. Each piece has its own pre determined life that in normal operation conditions of the set attend to the expectations. By oil analysis one can monitor the pieces conditions. The oil analysis technique is a type of predictive maintenance. It can be done collecting the oil of an equipment and analyzing it latter on or analyzing it directly in systems "on line". The oil analysis allows identifying the early symptoms of a component wear. The identification is done starting from the study of the particle quantity, size, forms and composition that supplies precise information about the moving superficial conditions without the need of disassembling the set which these parts belong to. Such solid particles are generated by dynamic friction among pieces in contact. According to the study of those particle one can relate the wear set situation and to attribute them to physical and chemical conditions. The oil analysis is done by means of laboratories techniques that involve reagent, instruments and equipments. So, to study the predictive maintenance in internal combustion engine it was done a theoretical study about those engine, about lubricants, about problems and possible causes related to fault of them, about the types of predictive maintenance associated to them and about papers that deal to predictive maintenance in internal combustion engine. To aid the studies it was proposed the construction of two test rig composed of gasoline four cycle internal combustion engine coupled to a reducer to supply load to them. In the first test rig it was used an internal combustion engine in advanced state of deterioration and on the second one it was used a new internal combustion engine. The results showed that even in advanced state ...(Complete abstract, click electronic access below) / Mestre

Monitoring wear particles in lubricating oils allows specialists to evaluate thehealth and functionality of a mechanical system. The main analysis techniquesavailable today are manual particle analysis and automatic optical analysis. Man-ual particle analysis is effective and reliable since the analyst continuously seeswhat is being counted . The drawback is that the technique is quite time demand-ing and dependent of the skills of the analyst. Automatic optical particle countingconstitutes of a closed system not allowing for the objects counted to be observedin real-time. This has resulted in a number of sources of error for the instrument.In this thesis a new method for counting particles based on light microscopywith image analysis is proposed. It has proven to be a fast and effective methodthat eliminates the sources of error of the previously described methods. Thenew method correlates very well with manual analysis which is used as a refer-ence method throughout this study. Size estimation of particles and detectionof metallic particles has also shown to be possible with the current image analy-sis setup. With more advanced software and analysis instrumentation, the imageanalysis method could be further developed to a decision based machine allowingfor declarations about which wear mode is occurring in a mechanical system.

CHARLES UNIVERSITY IN PRAGUE FACULTY OF SCIENCE DEPARTMENT OF BIOCHEMISTRY PRAGUE 2010 Supervisor: Doc. MUDr. Jiří Gallo, PhD. Supervisor-consultant: Prof. RNDr. Gustav Entlicher, CSc. Eva Zolotarevová Summary of PhD Thesis POLYETHYLENE WEAR PARTICLES AROUND TOTAL JOINT REPLACEMENTS - THEIR PROPERTIES, DISTRIBUTION AND POSSIBLE MECHANISM OF THEIR ADVERSE BIOLOGICAL EFFECTS PRAGUE 2010 The research project was supported by the Grant project of National research program II. (no. 2B06096) of the Czech Ministry of Education, Youth and Sports named "Observation and minimization of UHMWPE wear in joint replacements". Front-page picture: Polyethylene wear particle isolated from granuloma tissue surrounding total hip replacement; Electron microscope microphotograph; particle size app. 90 x 80 µm; retouched Eva Zolotarevová Introduction Introduction For many people all over the world a replacement with an implant of irreversibly damaged joint is often the only way how to come back to normal life without pain and mobility limitation. Nowadays, greater and greater requirements are asked of quality of all replacement components, especially in terms of quality of used materials. Biomechanical properties of hip and knee replacements have been already solved. The most often used materials for manufacturing joint...

Image analysis of wear particles is a suitable support tool for detail analysis of engine, gear, hydraulic and industrial oils. It allows to obtain information not only of basic parameters of abrasion particles but also data that would be very difficult to obtain using classical ways of evaluation. Based on the analysis of morphological or image characteristics of particles, the progress of wearing the machine parts out can be followed and, as a result, possible breakdown of the engine can be prevented or the optimum period for changing the oil can be determined. The aim of this paper is to explore the possibilities of using the image analysis combined with the method of analytical ferrography and suggest a tool for automated particle classification. Current methods of wear particle analysis are derived from the evaluation that does not offer an exact idea of processes that take place between the friction surfaces in the engine system. The work is based upon the method of analytical ferrography which allows to evaluate the state of the machine. The benefit of use of classifiers defined in this wirk is the possibility of automated evaluation of analytical ferrography outputs; the use of them eliminates the crucial disadvantage of ferrographical analysis which is its dependence on the subjective evaluation done by the expert who performs the analysis. Classifiers are defined as a result of using the methods of machine learning. Based on an extensive database of particles that was created in the first part of the work, the classifiers were trained as a result, they make the evaluation of ferrographically separated abrasion particles from oils taken from lubricated systems possible. In the next stage, experiments were carried out and optimum classifier settings were determined based on the results of the experiments.