Uncertainty-aware order tracking using interval-valued spectral estimators.

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Title: Uncertainty-aware order tracking using interval-valued spectral estimators.
Authors: Mohammad, Suleiman Ibrahim1, Yogeesh N.1,2 yogeesh.r@gmail.com, Abdullah, Mustafa3, Varghese, Rosemary4, Vasudevan, Asokan5, Ashalatha K. S.6
Source: Sound & Vibration. 2026, Vol. 60 Issue 2, p1-20. 20p.
Subjects: Interval analysis, Power spectra, Statistics, Fault diagnosis, Rotating machinery, Signal frequency estimation, Signal processing
Abstract: Order tracking is central to diagnosing rotating machinery under variable speed; however, both tachometer-based and tacholess pipelines typically return point estimates of the order spectrum and therefore under-represent uncertainty due to speed estimation error, phase integration drift, resampling jitter, and finite-record spectral variance. This study develops an uncertainty-aware order tracking framework in which the diagnostic output is an interval-valued order power spectral density (PSD) envelope. The angular speed is modeled as an unknown-but-bounded process ω(t) ∈ [ω-(t), ω+(t)], which induces bounds on angular position ϑ(t) ∈ [ϑ-(t), ϑ+(t)]. These bounds are propagated through angle-domain resampling and a Welch-type spectral estimator to obtain order-wise PSD bounds S(m) ∈ [S-(m), S+(m)], together with interval band metrics formed by order-band integration and log-level reporting. A numerical run-up case study with physically plausible harmonic content and broadband noise shows that low-order components can remain stable in peak location, whereas higher orders exhibit measurable peak-shift intervals consistent with phase-warp amplification under bounded mapping uncertainty. The results also quantify a practical coverage-width trade-off: fast endpoint envelopes can lose inclusion under larger uncertainty, indicating when multi-map sampling or tighter set membership bounding should be applied. Overall, the proposed interval-valued spectral estimators enable decision-relevant reporting of uncertainty for order-based health indicators and reduce the risk of overconfident fault declarations in variable-speed condition monitoring. [ABSTRACT FROM AUTHOR]
Copyright of Sound & Vibration is the property of Academic Publishing and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. 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: Uncertainty-aware order tracking using interval-valued spectral estimators.
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  Data: <searchLink fieldCode="AR" term="%22Mohammad%2C+Suleiman+Ibrahim%22">Mohammad, Suleiman Ibrahim</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Yogeesh+N%2E%22">Yogeesh N.</searchLink><relatesTo>1,2</relatesTo><i> yogeesh.r@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Abdullah%2C+Mustafa%22">Abdullah, Mustafa</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Varghese%2C+Rosemary%22">Varghese, Rosemary</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AR" term="%22Vasudevan%2C+Asokan%22">Vasudevan, Asokan</searchLink><relatesTo>5</relatesTo><br /><searchLink fieldCode="AR" term="%22Ashalatha+K%2E+S%2E%22">Ashalatha K. S.</searchLink><relatesTo>6</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Sound+%26+Vibration%22">Sound & Vibration</searchLink>. 2026, Vol. 60 Issue 2, p1-20. 20p.
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  Data: <searchLink fieldCode="DE" term="%22Interval+analysis%22">Interval analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Power+spectra%22">Power spectra</searchLink><br /><searchLink fieldCode="DE" term="%22Statistics%22">Statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Fault+diagnosis%22">Fault diagnosis</searchLink><br /><searchLink fieldCode="DE" term="%22Rotating+machinery%22">Rotating machinery</searchLink><br /><searchLink fieldCode="DE" term="%22Signal+frequency+estimation%22">Signal frequency estimation</searchLink><br /><searchLink fieldCode="DE" term="%22Signal+processing%22">Signal processing</searchLink>
– Name: Abstract
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  Data: Order tracking is central to diagnosing rotating machinery under variable speed; however, both tachometer-based and tacholess pipelines typically return point estimates of the order spectrum and therefore under-represent uncertainty due to speed estimation error, phase integration drift, resampling jitter, and finite-record spectral variance. This study develops an uncertainty-aware order tracking framework in which the diagnostic output is an interval-valued order power spectral density (PSD) envelope. The angular speed is modeled as an unknown-but-bounded process ω(t) ∈ [ω-(t), ω+(t)], which induces bounds on angular position ϑ(t) ∈ [ϑ-(t), ϑ+(t)]. These bounds are propagated through angle-domain resampling and a Welch-type spectral estimator to obtain order-wise PSD bounds S(m) ∈ [S-(m), S+(m)], together with interval band metrics formed by order-band integration and log-level reporting. A numerical run-up case study with physically plausible harmonic content and broadband noise shows that low-order components can remain stable in peak location, whereas higher orders exhibit measurable peak-shift intervals consistent with phase-warp amplification under bounded mapping uncertainty. The results also quantify a practical coverage-width trade-off: fast endpoint envelopes can lose inclusion under larger uncertainty, indicating when multi-map sampling or tighter set membership bounding should be applied. Overall, the proposed interval-valued spectral estimators enable decision-relevant reporting of uncertainty for order-based health indicators and reduce the risk of overconfident fault declarations in variable-speed condition monitoring. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Sound & Vibration is the property of Academic Publishing and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. 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: 10.59400/sv4071
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        Text: English
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        PageCount: 20
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    Subjects:
      – SubjectFull: Interval analysis
        Type: general
      – SubjectFull: Power spectra
        Type: general
      – SubjectFull: Statistics
        Type: general
      – SubjectFull: Fault diagnosis
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      – SubjectFull: Rotating machinery
        Type: general
      – SubjectFull: Signal frequency estimation
        Type: general
      – SubjectFull: Signal processing
        Type: general
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      – TitleFull: Uncertainty-aware order tracking using interval-valued spectral estimators.
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            NameFull: Mohammad, Suleiman Ibrahim
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              M: 03
              Text: 2026
              Type: published
              Y: 2026
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