Diagnóstico de falha de ignição em veículos automotivos através de vibração de smartphone

• Ano de defesa: 2018
• Autor(a) principal: Rodrigues, Nayara Formiga
• Tipo de documento: Dissertação
• 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: Acelerômetro de um smartphone; Detecção; Falhas; Fourier; Wavelet; Pistão; Accelerometer sensor of a smartphone; Detection; Failures; Piston; Motores de combustão interna; Veículos - Motor automotivo - Falhas mecânicas; Acelerômetro - Smartphone; Motores - Vibrações; CNPQ::ENGENHARIAS::ENGENHARIA MECANICA
• Link de acesso: https://repositorio.ufpb.br/jspui/handle/123456789/15954

According to data from RENAVAM, Brazil currently has a fleet of more than 42 million vehicles. In 2010, 182,900 accidents were recorded on public roads in Brazil, of which 7,073 were fatal. In addition to the crashes that cause accidents, there are those that affect the cars' capacity of locomotion, causing inconvenience to their passengers and putting them at risk of eventual car crashes. Most accidents are caused by mechanical failures that can occur in different parts of the car and could be avoided with proper diagnosis. Currently, automotive vehicles lack mechanisms that can detect most mechanical failures to which they are susceptible. The detection of failures in pistons is one of them. Besides damaging the car's proper operation, this type of failure causes engine degradation and increases the emission of noxious gases. The aim of this work is the implementation of a processing technique for detection of pistons failures of an automotive engine by reading the measurement of the vibration signal performed by the accelerometer sensor of a smartphone. Currently, it is possible to program complete systems for simulation of technical characteristics that are found in real systems. In this paper it was also validated a method through the analysis of the signal measured through MATLAB, using tools such as the fast Fourier transform and the Wavelet Packet Transform (WTP).