| Title: |
Application of Blind Source Separation Methods in the Diagnosis of Rolling Bearings |
| Authors: |
Mika D.; Jozwik J.; Tofil A.; Pytka J.; Leccese F.; Ruggiero A. |
| Contributors: |
IEEE; Mika, D.; Jozwik, J.; Tofil, A.; Pytka, J.; Leccese, F.; Ruggiero, A. |
| Publisher Information: |
Institute of Electrical and Electronics Engineers Inc. |
| Publication Year: |
2025 |
| Subject Terms: |
blind source separation; fault diagnosi; independent component analysi; neural network; rolling element bearings |
| Description: |
The paper presents the concept of using a Blind Source Separation (BSS) algorithms to diagnose localized faults in rolling element bearings. These bearing faults usually result in strong harmonics of the fault frequencies along with sidebands in the spectrum of the vibration signals. We have shown that separation of vibration signal components containing these fault frequencies enables more effective bearing diagnostics. We have used linear BSS algorithms as well as nonlinear version. The conducted experiment showed an increase in the effectiveness of fault detection for all types of simulated bearing faults. The results achieved may enable the construction of an expert system in the future that diagnoses the condition of technical devices based on the analysis of the vibroacoustic signal generated by the operating device. |
| Document Type: |
conference object |
| Language: |
English |
| Relation: |
info:eu-repo/semantics/altIdentifier/wos/WOS:001572970000101; ispartofbook:2025 IEEE International Workshop on Metrology for AeroSpace, MetroAeroSpace 2025 - Proceedings; 12th IEEE International Workshop on Metrology for AeroSpace, MetroAeroSpace 2025; firstpage:570; lastpage:574; numberofpages:5; https://hdl.handle.net/11386/4922276 |
| DOI: |
10.1109/MetroAeroSpace64938.2025.11114575 |
| Availability: |
https://hdl.handle.net/11386/4922276; https://doi.org/10.1109/MetroAeroSpace64938.2025.11114575 |
| Accession Number: |
edsbas.B7594EA3 |
| Database: |
BASE |