Rolling element bearing fault identification using a novel three-step adaptive and automated filtration scheme based on Gini index
| Autor: | Nader Sawalhi, M. G. A. Nassef, Muhammad N. Albezzawy |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Bearing (mechanical) business.industry Computer science Noise (signal processing) Applied Mathematics 020208 electrical & electronic engineering Pattern recognition 02 engineering and technology Fault (power engineering) Fault detection and isolation Computer Science Applications law.invention Filter design 020901 industrial engineering & automation Morlet wavelet Control and Systems Engineering Rolling-element bearing law 0202 electrical engineering electronic engineering information engineering Demodulation Artificial intelligence Electrical and Electronic Engineering business Instrumentation |
| Zdroj: | ISA transactions. 101 |
| ISSN: | 1879-2022 |
| Popis: | For early detection of rolling element bearings (REBs) faults in contaminated signals, kurtosis-derived indices are involved in the filtration process prior to demodulation. However, they were found either sensitive to impulsive outliers or requiring many input arguments. In this study, a novel three-step adaptive and automated filtration scheme using Gini index (GI) is proposed as an alternative to kurtosis-based techniques to enhance the weak fault features and eliminate noise and interferences from the raw vibration signal. The proposed approach was tested using experimental signals with different bearing faults. The filtered signals were greatly denoised and the fault impulses were successfully isolated, which indicates the effectiveness of the proposed approach and the superiority of GI over kurtosis-derived indices as a criterion for proper filter design for REBs fault detection. |
| Databáze: | OpenAIRE |
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