Desenvolvimento de um sistema sem fio para o monitoramento da vibração na operação de fresamento

Detalhes bibliográficos
Ano de defesa: 2020
Autor(a) principal: Pedro Ivo Alves Vianello
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal de Minas Gerais
Brasil
ENG - DEPARTAMENTO DE ENGENHARIA MECÂNICA
Programa de Pós-Graduação em Engenharia Mecanica
UFMG
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://hdl.handle.net/1843/49627
https://orcid.org/0000-0002-0216-5162
Resumo: Some of machining processes qualities are good surface finish at the component and the possibility of small batches production in contrast to casting and forming. Machining processes are relevant and widely used in industrial manufacture due to these features, despite their high production cost and large amount of chips produced. Milling stands out due to its high material removal rate and complex geometry production capability. Manufacture of dies and molds is one well known application of milling. As the production cost increases, the need to a tougher process control parameter is required in order to guarantee a desirable product tolerance and quality and to reduce material losses. Tool wear must be constantly supervised to assure acceptable product dimension and surface finish. Taking into account Industry 4.0 and technology advance in software communication, this study presents a wear monitoring method based on tools vibration signal during milling of annealed AISI H13 tool steel with WC inserts using a low-cost accelerometer and a microcontroller connected via wi-fi. Experimental tests were conducted to validate its functionality. Varying cutting speed, feed rate and depth of cut order to verify the sensor sensibility on tool wear evolution and cut parameters variation. The results shown that the low-cost sensor presents satisfactory response to cutting parameters variations and cutting speed and depth of cut are the most influent in the first harmonic spectral amplitudes. On the other hand, wear increasement was not statistically responsive to wear level measured (≈ 0,3mm).