Study on the cage slip of rolling bearing using a non-contact method
Author(s): |
Liwei Zhan
Fang Ma ZhengHui Li Haitao Li Chengwei Li |
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Medium: | journal article |
Language(s): | English |
Published in: | Structural Health Monitoring, December 2019, n. 6, v. 19 |
Page(s): | 2107-2121 |
DOI: | 10.1177/1475921720916227 |
Abstract: |
In this article, a novel, non-contact method is proposed to detect cage slip of rolling bearing. The proposed method can obtain the speed signal of cage and inner raceway by the introduction of weak magnetic field detection technology simultaneously. Meanwhile, to enhance the identified accuracy of cage slip, an adaptive filtering method is developed to suppress noise in weak magnetic field sensor output signal. The method adopts complementary complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) to decompose the weak magnetic field sensor output signal into a set of intrinsic mode functions adaptively. The intrinsic mode functions contain noisy component of detection signal (noisy intrinsic mode functions) as well as corresponding signal component of the roller and inner raceway (signal intrinsic mode functions). The noisy- and signal intrinsic mode functions are identified by the development of reconstruction criterion. The criterion is determined based on upper boundary of rotational frequency of roller under pure rolling conditions. Then, the noisy intrinsic mode functions are forced to zero, and signal intrinsic mode functions are reconstructed to extract the speed information of roller and inner raceway. An experiment system is developed to verify the effectiveness of proposed method. The experiment result shows that the cage slip decreases with the increment in load under the given speed conditions and increases with the increment in speed under the given load conditions, as well as the cage slip is more serious under given no-load conditions. It shows that the weak magnetic field detection technology can be used to detect the cage slip of rolling bearing. |
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data sheet - Reference-ID
10562414 - Published on:
11/02/2021 - Last updated on:
19/02/2021