Cyclogram: an effective method for selecting frequency bands for fault diagnosis of rolling element bearings
| Autor: | Bo Li, Xuefang Xu, Hang Tan, Peiming Shi, Zijian Qiao |
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| Rok vydání: | 2023 |
| Předmět: | |
| Zdroj: | Measurement Science and Technology. |
| ISSN: | 1361-6501 0957-0233 |
| DOI: | 10.1088/1361-6501/acd86b |
| Popis: | Frequency band selection for repetitive transient extraction using Kurtogram and its variants plays a vital role in fault diagnosis of rolling element bearings. However, cyclostationarity, one of the most typical symptoms of fault bearings, is always neglected in these methods, leading to the failure of the extraction of weak fault features. To address this disadvantage, a novel method for selecting frequency bands called Cyclogram is proposed based on kurtosis and cyclostationarity in this paper. In the proposed method, a signal is decomposed into several signals in different frequency bands by wavelet packet transform and squared envelopes (SE) are calculated for these decomposed signals. Then, a robust indicator of SE for evaluating repetitive transients is constructed based on cyclic spectral coherence and kurtosis, which helps to select useful frequency bands. Afterwards, envelope spectrums of these selected frequency bands are averaged rather than only select one frequency band to enhance fault features. Compared with traditional fault diagnosis methods of roller element bearings, the proposed method is able to identify faults from signals corrupted seriously with Gaussian and non-Gaussian noise. The effectiveness of Cyclogram is validated based on a simulation and three real vibration signals of fault bearings. |
| Databáze: | OpenAIRE |
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