Método de detecção de falhas em motores decorrente contínua sem escovas utilizando análise do caos

• Ano de defesa: 2018
• Autor(a) principal: Medeiros, Ramon Leonn Victor
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal da Paraíba; Brasil; Engenharia Mecânica; Programa de Pós-Graduação em Engenharia Mecânica; UFPB
• Palavras-chave em Português: Síncrono; RPA; Motores diagnosis; Faults; Synchronous; Multiplataform; Motors; Motores de corrente contínua - Detecção de falhas; Análise do caos - Método. Corrente do motor; Análise do caos - Método; Corrente do motor; CNPQ::ENGENHARIAS::ENGENHARIA MECANICA
• Link de acesso: https://repositorio.ufpb.br/jspui/handle/123456789/14495

This presented work contributes to the development of a novel fault diagnosis method in Brushless Direct Current (BLDC) motors. These have been used in several applications of electric vehicles. Some advantages, such as low maintenance demand and ability to work in hostile environments. One of the applications given to BLDC motors is in Remotely Piloted Aircraft (RPA), popularly known as drones, that have a wide variety of uses and applications. So, there is a growing need for security and safety solutions. Thus, it was noticed that there is a demand to develop a real-time diagnostic strategy to be embedded in RPA. This work present a technique for the diagnosis of working behavior in BLDC motors. From analysis of the chaotic behavior of the electric current signal, measured by the maximum density of the function, preliminary results demonstrated the efficacy of new technique under stationary and non-stationary conditions, opening the possibility of improving the technique and developing the embedded motor diagnostic solution.