Cyclostationarity and real order derivatives in roller bearing fault detection
Karioja, Konsta; Nikula, Riku-Pekka; Nissilä, Juhani (2024-06-27)
Institute of physics publishing
27.06.2024
K Karioja et al 2024 Meas. Sci. Technol. 35 096136
https://creativecommons.org/licenses/by-nc-nd/4.0/
This Accepted Manuscript is available for reuse under a CC BY-NC-ND licence after the 12 month embargo period provided that all the terms of the licence are adhered to.
https://creativecommons.org/licenses/by-nc-nd/4.0/
This Accepted Manuscript is available for reuse under a CC BY-NC-ND licence after the 12 month embargo period provided that all the terms of the licence are adhered to.
https://creativecommons.org/licenses/by-nc-nd/4.0/
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202408205500
https://urn.fi/URN:NBN:fi:oulu-202408205500
Tiivistelmä
Abstract
Various methods are used in the field of machine diagnostics for recognizing cyclostationarity in signals. The real order derivatives of vibration signals, however, have been rarely reported from the perspective of their effect on the performance of cyclostationarity detection methods. In this paper, we use real order derivatives together with spectral correlation, spectral coherence and squared envelope. Our results suggest that adjusting the order of derivative can enhance the analysis outcome of spectral correlation and squared envelope in particular. Remarkably, the results also suggest that squared envelope, when used alongside real-order derivatives, may replace spectral correlation and spectral coherence. This approach allows obtaining results with reduced computational power, making it advantageous for applications like industrial edge computing, where cost-effective hardware is crucial.
Various methods are used in the field of machine diagnostics for recognizing cyclostationarity in signals. The real order derivatives of vibration signals, however, have been rarely reported from the perspective of their effect on the performance of cyclostationarity detection methods. In this paper, we use real order derivatives together with spectral correlation, spectral coherence and squared envelope. Our results suggest that adjusting the order of derivative can enhance the analysis outcome of spectral correlation and squared envelope in particular. Remarkably, the results also suggest that squared envelope, when used alongside real-order derivatives, may replace spectral correlation and spectral coherence. This approach allows obtaining results with reduced computational power, making it advantageous for applications like industrial edge computing, where cost-effective hardware is crucial.
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