![](/images/graphics-bg.png)
Applications of Fractional Lower Order Frequency Spectrum Technologies to Bearing Fault Analysis
Joint Authors
Long, Junbo
Wang, Haibin
Li, Peng
Source
Mathematical Problems in Engineering
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-24, 24 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-08-27
Country of Publication
Egypt
No. of Pages
24
Main Subjects
Abstract EN
The traditional spectral analysis method is used to study the characteristics of bearing fault signals in frequency domain, which is reasonable and effective in general cases.
However, it is proved that the fault signals have heavy tails in this paper, which are α stable distribution, and 1<α<2, and even the noises belong to α stable distribution.
Then the conventional spectral analysis methods degenerate and even fail under α stable distribution environment.
Several improved frequency spectral analysis methods are proposed employing fractional lower order covariation or fractional lower order covariance in this paper, including fractional lower order Blackman-Tukey covariation spectrum (FLOBTCS), fractional lower order periodogram covariation spectrum (FLOPCS), and fractional lower order welch covariation spectrum (FLOWCS).
In order to suppress side lobe and improve resolution, we present novel fractional lower order autoregression (FLO-AR) and fractional lower order autoregressive moving average (FLO-ARMA) parameter model frequency spectrum methods, and the calculation steps are summarized.
The proposed spectrum methods are compared with the existing methods based on second-order statistics under Gaussian and SαS distribution environments, and the results show that the new algorithms have better performance than the traditional methods.
Finally, the improved methods are applied to estimate frequency spectrums of the normal and outer race fault signals, and it is demonstrated that they are effective for fault diagnosis.
American Psychological Association (APA)
Long, Junbo& Wang, Haibin& Li, Peng. 2019. Applications of Fractional Lower Order Frequency Spectrum Technologies to Bearing Fault Analysis. Mathematical Problems in Engineering،Vol. 2019, no. 2019, pp.1-24.
https://search.emarefa.net/detail/BIM-1197154
Modern Language Association (MLA)
Long, Junbo…[et al.]. Applications of Fractional Lower Order Frequency Spectrum Technologies to Bearing Fault Analysis. Mathematical Problems in Engineering No. 2019 (2019), pp.1-24.
https://search.emarefa.net/detail/BIM-1197154
American Medical Association (AMA)
Long, Junbo& Wang, Haibin& Li, Peng. Applications of Fractional Lower Order Frequency Spectrum Technologies to Bearing Fault Analysis. Mathematical Problems in Engineering. 2019. Vol. 2019, no. 2019, pp.1-24.
https://search.emarefa.net/detail/BIM-1197154
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1197154