| Texto completo | |
| Autor(es): |
Pereira, Andre Luis Vinagre
[1]
;
Goncalves, Aparecido Carlos
[2]
;
Ribeiro, Rubens
[1]
;
Chavarette, Fabio Roberto
[3]
;
Outa, Roberto
[4]
Número total de Autores: 5
|
| Afiliação do(s) autor(es): | [1] FEIS UNESP, DEM, PPG Mech Engn, Ilha Solteira - Brazil
[2] FEIS UNESP, DEM, Dept Mech Engn, Ilha Solteira - Brazil
[3] FEIS UNESP, MAT, Dept Math, Ilha Solteira - Brazil
[4] FATEC, Dept Biofuels, Aracatuba Technol Coll, Sorocaba - Brazil
Número total de Afiliações: 4
|
| Tipo de documento: | Artigo Científico |
| Fonte: | SHOCK AND VIBRATION; v. 2020, SEP 15 2020. |
| Citações Web of Science: | 0 |
| Resumo | |
In predictive maintenance, vibration signal analyses are frequently used to diagnose reducer failures because these analyses contain information about the conditions of the mechanical components. Reducer vibration signals are very noisy and the signal-to-noise ratio is so low that extracting information from the signal components is complex, especially in practical situations. Therefore, signal processing techniques are used to solve this problem and facilitate the retrieval of information. In this work, the adopted technique included noise-canceling technique, synchronous temporal mean (TSA), and continuous Morlet wavelet transform (CWT), designed to extract resources and diagnose local gear damage. These techniques are used in measured signals in an experimental workbench consisting of the gear pair coupled to a motor and a generator. The experiment was monitored according to the conditions of a gear pair throughout its useful life. The continuous wavelet transforms accurately identified faults in the gear teeth, and it was possible to detect in which tooth the fault was occurring. (AU) | |
| Processo FAPESP: | 14/14360-1 - Avaliação da substituição dos lubrificantes minerais por óleos vegetais aditivados e do aproveitamento dos descartes |
| Beneficiário: | Aparecido Carlos Gonçalves |
| Modalidade de apoio: | Auxílio à Pesquisa - Regular |