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Previous issue date: 2016-05-06 / Com a intensa utiliza??o de rolamentos em diversos segmentos da ind?stria, h? um elevado n?mero de pausas necess?rias nos processos industriais para a realiza??o de manuten??es nesses dispositivos, tendo como estudo de caso os aerogeradores. O crescimento do setor de energia e?lica, incentivou a realizar uma pesquisa que auxilie a solu??o desse problema. Para contribuir com a manuten??o preventiva foi realizado uma an?lise de sinais aplicando t?cnicas que permitem a detec??o e a localiza??o do problema a fim de evitar acidentes e preju?zos ocasionados por falhas inesperadas nos equipamentos, visto que a baixa rota??o do sistema dificulta a detec??o da falha. Para solucionar esse item, realizou-se a determina??o de sinais padr?o para os defeitos nos rolamentos, facilitando o diagn?stico de poss?veis falhas. Com esse diagn?stico pode ser executada uma manuten??o preventiva, identificando a falha do sistema que foram testadas, como a introdu??o de gr?os de areia no rolamento, desgaste na pista externa do rolamento e oxida??o do rolamento. Atrav?s do processamento de sinais ? poss?vel construir os gr?ficos desenvolvendo um mapeamento dos defeitos atrav?s de diferentes picos nas faias de frequ?ncia. / With the heavy use of bearings in various segments of the industry, there are a large number of necessary interruptions in industrial processes to perform maintenance on these devices, with the case study wind turbines. The growth of the wind energy sector, encouraged to conduct research that helps to solve this problem. To contribute to predictive maintenance has been carried out a signal analysis using techniques which allow detection and location of the problem in order to prevent accidents caused and losses due to unexpected equipment failures, whereas low system rotation complicates the detection of the failure. To work around this problem, there was the indication of standard signals for defects in the bearings, making diagnosis of possible failures. With this diagnosis can be performed predictive maintenance, identifying the failure of the system that were tested, such as the introduction of grains of sand in the bearing, wear on the outer race of the bearing and bearing rust. By processing signals it is possible to construct graphs developing a mapping of defects by different peaks in the frequency band.
| Identifer | oai:union.ndltd.org:IBICT/oai:repositorio.ufrn.br:123456789/21176 |
| Date | 06 May 2016 |
| Creators | Almeida, Isac Barbosa de |
| Contributors | 21896458831, http://lattes.cnpq.br/5336356193599447, Oliveira, Adelci Menezes de, 67187366434, http://lattes.cnpq.br/7673440916658787, Silva, Jo?o Bosco da, 13163191487, http://lattes.cnpq.br/3305848313356239, Matamoros, Efrain Pantaleon |
| Publisher | Universidade Federal do Rio Grande do Norte, PROGRAMA DE P?S-GRADUA??O EM ENGENHARIA MEC?NICA, UFRN, Brasil |
| Source Sets | IBICT Brazilian ETDs |
| Language | Portuguese |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, info:eu-repo/semantics/masterThesis |
| Source | reponame:Repositório Institucional da UFRN, instname:Universidade Federal do Rio Grande do Norte, instacron:UFRN |
| Rights | info:eu-repo/semantics/openAccess |
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