Comparison of Signal Processing Methods for Bearing Fault Detection

Autor: Jitendra A. Gaikwad, Sanika S. Patankar, Prithiviraj Kamalapure, Prasad Patil, Tejas Kamble, Sumit Padole, Naseer Lahwal
Rok vydání: 2023
Předmět:
Zdroj: International Journal for Research in Applied Science and Engineering Technology. 11:3712-3722
ISSN: 2321-9653
DOI: 10.22214/ijraset.2023.51717
Popis: Bearings with rolling elements are a typical part of rotating machinery. Vibration analysis is one of them that is frequently used to gauge the general wellbeing and condition of rotating machinery. Finding bearing defects is important in the pursuit of extremely reliable operations. The main relationship between vibration signal-based features and measured signals is that they can be used in order to assess the condition of a bearing. In order to examine the effectiveness of non-parametric harmonic approaches for defect identification using real motor data, the study recommends utilizing Thomson's Multitaper Estimation and Welch Periodogram Estimation. The researches show that this approach can identify outer race faults and inner race fault. The conclusive evidence points to Thomson's Multitaper Periodogram Estimation method as a successful technique for bearing fault identification.
Databáze: OpenAIRE