Comparison of selected point estimators of vibration signals for purposes of fault detection in rolling bearings

• Autorzy: Krol Adrian , Fidali Marek , Jamrozik Wojciech
• Języki publikacji: EN

Abstrakty

EN

Most of machine breakdowns relate to bearing failures thus it is very important to diagnose bearing conditions. The main purpose of the study was to classify the condition of bearings and identify defective ones based on visual inspection and the values of classic parameters of the acceleration signal vibration, such as Peak, RMS, Kurtosis. The results were compared to parameters provided by the SPM method. All vibration parameters were estimated for high pass filtered signals where filters had following cut-off frequencies 0.5; 1, 2, 5 and 8 kHz. Bearings were tested on the laboratory test bench being built at the Silesian University of Technology. Based on the signal analysis and visual inspections it can be stated that there is agreement in the assessment of the conditions between the parameters of the SPM method and the Peak and RMS parameters. It was observed that the sensitivity to the existence of low-intensity defects increases when the vibration parameters are determined for signals in the band above 2kHz.

Słowa kluczowe

EN

vibration; analysis; bearings; defects; diagnosis

PL

drgania; analiza; łożyska; uszkodzenia; diagnoza

• Wydawca: Poznan University of Technology. Institute of Applied Mechanics
• Czasopismo: Vibrations in Physical Systems
• Rocznik: 2020
• Tom: Vol. 31, nr 2
• Strony: art. no. 2020212
• Opis fizyczny: Bibliogr. 5 poz., il. kolor., fot., wykr.

Twórcy

autor

Krol Adrian

• Silesian University of Technology

autor

Fidali Marek

• Silesian University of Technology

autor

Jamrozik Wojciech

• Silesian University of Technology

Bibliografia

• 1. T. Williams , X. Rbadeneira, S. Billington, T. Kurfess, Rolling element bearing diagnostics in run-to-failure lifetime testing. Mechanical Systems and Signal Processing 15(5) (2001) 979 - 993, doi:10.1006/mssp.2001.1418.
• 2. R. B. Randall, J. Antoni, Rolling element bearing diagnostics—A tutorial, Mechanical Systems and Signal Processing 25 (2011) 485-520.
• 3. A. Boudiaf, A, Djebala, et al, A summary of vibration analysis techniques for fault detection and diagnosis in bearing, 8th International Conference on Modelling, Identification and Control (ICMIC), 2016.
• 4. A. Nabhan, N. M. Ghazaly, A. Samy, M.O Mousa, Bearing Fault Detection Techniques -A Review, Turkish Journal of Engineering, Sciences and Technology 3 (2015).
• 5. T. Lin, Y. Chen, D. Yang and Y. Chen, New Method for Industry 4.0 Machine Status Prediction - A Case Study with the Machine of a Spring Factory, 2016 International Computer Symposium (ICS), Chiayi, 2016 322-326.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).