| Autor: |
Diogo Stuani Alves, Tiago Henrique Machado, Felipe Wenzel da Silva Tuckmantel, Patrick S. Keogh, Katia Lucchesi Cavalca |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Alves, D, Machado, T, Tuckmantel, F, Keogh, P & Cavalca, K 2022, ' Investigation of Fault Modeling in the Identification of Bearing Wear Severity ', Journal of Tribology: Transactions of the ASME, vol. 144, no. 7, 71802 . https://doi.org/10.1115/1.4053178 |
| DOI: |
10.1115/1.4053178 |
| Popis: |
Recent research into machines involved in power generation processes has demanded deep investigation of model-based techniques for fault diagnosis and identification. The improvement of critical fault characterization is crucial in the maintenance process effectiveness, hence in time/costs saving, increasing performance and productivity of the whole system. Consequently, this paper deals with a common fault in hydrodynamically lubricated bearings assembled in rotating systems, namely, that of abrasive wear. Research on this topic points to an interesting query about the significance of model detail and complexity and the identification of its characteristic parameters for the important stages of fault diagnosis and fault identification. For this purpose, two models are presented and analyzed in their completeness concerning the fault signature by vibration measurements, as well as the identification of fault critical parameters which determine the machine lifetime estimation, maintenance procedures, and time costs regarding performance and productivity. From this study, the detailing in fault modeling has a substantial impact on fault parameter identification, even if its improvement is not so expressive in fault diagnosis procedures involving standard signal processing techniques of vibration signatures. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
|
