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Alternative Measures of Dependence for Cyclic Behaviour Identification in the Signal with Impulsive Noise—Application to the Local Damage Detection.

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Title: Alternative Measures of Dependence for Cyclic Behaviour Identification in the Signal with Impulsive Noise—Application to the Local Damage Detection.
Authors: Hebda-Sobkowicz, Justyna, Nowicki, Jakub, Zimroz, Radosław, Wyłomańska, Agnieszka
Source: Electronics (2079-9292); Aug2021, Vol. 10 Issue 15, p1863-1863, 1p
Subject Terms: TIME series analysis, AUTOCORRELATION (Statistics), RANDOM noise theory, NOISE, ROTATING machinery, CARRIER transmission on electric lines
Abstract: The local damage detection procedures in rotating machinery are based on the analysis of the impulsiveness and/or the periodicity of disturbances corresponding to the failure. Recent findings related to non-Gaussian vibration signals showed some drawbacks of the classical methods. If the signal is noisy and it is strongly non-Gaussian (heavy-tailed), searching for impulsive behvaior is pointless as both informative and non-informative components are transients. The classical dependence measure (autocorrelation) is not suitable for non-Gaussian signals. Thus, there is a need for new methods for hidden periodicity detection. In this paper, an attempt will be made to use alternative measures of dependence used in time series analysis that are less known in the condition monitoring (CM) community. They are proposed as alternatives for the classical autocovariance function used in the cyclostationary analysis. The methodology of the auto-similarity map calculation is presented as well as a procedure for a "quality" or "informativeness" assessment of the map is proposed. In the most complex case, the most resistant to heavy-tailed noise turned out the proposed techniques based on Kendall, Spearman and Quadrant autocorrelations. Whereas in the case of the local fault disturbed by the Gaussian noise, the most efficient proved to be a commonly-known approach based on Pearson autocorrelation. The ideas proposed in the paper are supported by simulation signals and real vibrations from heavy-duty machines. [ABSTRACT FROM AUTHOR]
Copyright of Electronics (2079-9292) is the property of MDPI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Alternative Measures of Dependence for Cyclic Behaviour Identification in the Signal with Impulsive Noise—Application to the Local Damage Detection.
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  Data: <searchLink fieldCode="AR" term="%22Hebda-Sobkowicz%2C+Justyna%22">Hebda-Sobkowicz, Justyna</searchLink><br /><searchLink fieldCode="AR" term="%22Nowicki%2C+Jakub%22">Nowicki, Jakub</searchLink><br /><searchLink fieldCode="AR" term="%22Zimroz%2C+Radosław%22">Zimroz, Radosław</searchLink><br /><searchLink fieldCode="AR" term="%22Wyłomańska%2C+Agnieszka%22">Wyłomańska, Agnieszka</searchLink>
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  Data: Electronics (2079-9292); Aug2021, Vol. 10 Issue 15, p1863-1863, 1p
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  Data: <searchLink fieldCode="DE" term="%22TIME+series+analysis%22">TIME series analysis</searchLink><br /><searchLink fieldCode="DE" term="%22AUTOCORRELATION+%28Statistics%29%22">AUTOCORRELATION (Statistics)</searchLink><br /><searchLink fieldCode="DE" term="%22RANDOM+noise+theory%22">RANDOM noise theory</searchLink><br /><searchLink fieldCode="DE" term="%22NOISE%22">NOISE</searchLink><br /><searchLink fieldCode="DE" term="%22ROTATING+machinery%22">ROTATING machinery</searchLink><br /><searchLink fieldCode="DE" term="%22CARRIER+transmission+on+electric+lines%22">CARRIER transmission on electric lines</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The local damage detection procedures in rotating machinery are based on the analysis of the impulsiveness and/or the periodicity of disturbances corresponding to the failure. Recent findings related to non-Gaussian vibration signals showed some drawbacks of the classical methods. If the signal is noisy and it is strongly non-Gaussian (heavy-tailed), searching for impulsive behvaior is pointless as both informative and non-informative components are transients. The classical dependence measure (autocorrelation) is not suitable for non-Gaussian signals. Thus, there is a need for new methods for hidden periodicity detection. In this paper, an attempt will be made to use alternative measures of dependence used in time series analysis that are less known in the condition monitoring (CM) community. They are proposed as alternatives for the classical autocovariance function used in the cyclostationary analysis. The methodology of the auto-similarity map calculation is presented as well as a procedure for a "quality" or "informativeness" assessment of the map is proposed. In the most complex case, the most resistant to heavy-tailed noise turned out the proposed techniques based on Kendall, Spearman and Quadrant autocorrelations. Whereas in the case of the local fault disturbed by the Gaussian noise, the most efficient proved to be a commonly-known approach based on Pearson autocorrelation. The ideas proposed in the paper are supported by simulation signals and real vibrations from heavy-duty machines. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of Electronics (2079-9292) is the property of MDPI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.3390/electronics10151863
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      – Code: eng
        Text: English
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        Type: general
      – SubjectFull: AUTOCORRELATION (Statistics)
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      – SubjectFull: RANDOM noise theory
        Type: general
      – SubjectFull: NOISE
        Type: general
      – SubjectFull: ROTATING machinery
        Type: general
      – SubjectFull: CARRIER transmission on electric lines
        Type: general
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      – TitleFull: Alternative Measures of Dependence for Cyclic Behaviour Identification in the Signal with Impulsive Noise—Application to the Local Damage Detection.
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            NameFull: Nowicki, Jakub
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            – D: 01
              M: 08
              Text: Aug2021
              Type: published
              Y: 2021
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