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Enhancing Readability of the Spectral Correlation Function using Multitaper Reassignment for Milling Vibration Feature Extraction

Persson, Jonatan LU ; Åkesson, Maria LU ; Lindvall, Rebecka LU ; Sridhar, Gautam LU ; Gutnichenko, Oleksandr LU and Sandsten, Maria LU (2026) 10th Conference on High Performance Cutting, CIRP-HPC 2026 In Procedia CIRP 141. p.394-399
Abstract

Many vibration signals produced by rotating machines have been shown to be second-order cyclostationary. This means that the spectral correlation function can be used to identify cyclic frequencies associated with e.g. faulty machine parts. However, due to spectral leakage, the spectral correlation function often has poor localization of signal components, leading to sub-par fault detection. Recently, the Reassigned Spectral Correlation (RSC) method has been introduced to improve the localization of the spectral correlation function. This work proposes combining the RSC method with multitapering to achieve more noise-robust spectral correlation reassignment. Although the standard RSC method leads to much improved readability in... (More)

Many vibration signals produced by rotating machines have been shown to be second-order cyclostationary. This means that the spectral correlation function can be used to identify cyclic frequencies associated with e.g. faulty machine parts. However, due to spectral leakage, the spectral correlation function often has poor localization of signal components, leading to sub-par fault detection. Recently, the Reassigned Spectral Correlation (RSC) method has been introduced to improve the localization of the spectral correlation function. This work proposes combining the RSC method with multitapering to achieve more noise-robust spectral correlation reassignment. Although the standard RSC method leads to much improved readability in situations with little noise, the RSC method still has problems identifying signal components for noisier signals due to sensitivity of the reassignment coordinates. Multitaper techniques are well-studied in the signal processing literature and involve averaging over multiple spectral estimates and reassignment coordinates using mutually orthogonal window functions. The performance of the proposed multi-taper RSC is investigated using simulated cyclostationary signals. Although most of the previous cyclostationary literature applied to mechanical systems has been devoted to fault diagnosis, the method is shown to be able to detect cyclic features for experimental milling vibration signals where the cutting tools are undergoing progressive wear. This opens up for future applications of cyclostationary analysis in machining.

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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Cyclostationary, Fault Diagnosis, Multitaper, Reassignment, Spectral Correlation, Tool Wear
in
Procedia CIRP
volume
141
pages
394 - 399
publisher
Elsevier
conference name
10th Conference on High Performance Cutting, CIRP-HPC 2026
conference location
Cluny, France
conference dates
2026-06-17 - 2026-06-19
external identifiers
  • scopus:105042608329
ISSN
2212-8271
DOI
10.1016/j.procir.2026.03.095
language
English
LU publication?
yes
id
ab80437e-6dfa-487e-88b7-8d7510594137
date added to LUP
2026-09-21 15:39:30
date last changed
2026-09-21 15:40:01
@article{ab80437e-6dfa-487e-88b7-8d7510594137,
  abstract     = {{<p>Many vibration signals produced by rotating machines have been shown to be second-order cyclostationary. This means that the spectral correlation function can be used to identify cyclic frequencies associated with e.g. faulty machine parts. However, due to spectral leakage, the spectral correlation function often has poor localization of signal components, leading to sub-par fault detection. Recently, the Reassigned Spectral Correlation (RSC) method has been introduced to improve the localization of the spectral correlation function. This work proposes combining the RSC method with multitapering to achieve more noise-robust spectral correlation reassignment. Although the standard RSC method leads to much improved readability in situations with little noise, the RSC method still has problems identifying signal components for noisier signals due to sensitivity of the reassignment coordinates. Multitaper techniques are well-studied in the signal processing literature and involve averaging over multiple spectral estimates and reassignment coordinates using mutually orthogonal window functions. The performance of the proposed multi-taper RSC is investigated using simulated cyclostationary signals. Although most of the previous cyclostationary literature applied to mechanical systems has been devoted to fault diagnosis, the method is shown to be able to detect cyclic features for experimental milling vibration signals where the cutting tools are undergoing progressive wear. This opens up for future applications of cyclostationary analysis in machining.</p>}},
  author       = {{Persson, Jonatan and Åkesson, Maria and Lindvall, Rebecka and Sridhar, Gautam and Gutnichenko, Oleksandr and Sandsten, Maria}},
  issn         = {{2212-8271}},
  keywords     = {{Cyclostationary; Fault Diagnosis; Multitaper; Reassignment; Spectral Correlation; Tool Wear}},
  language     = {{eng}},
  pages        = {{394--399}},
  publisher    = {{Elsevier}},
  series       = {{Procedia CIRP}},
  title        = {{Enhancing Readability of the Spectral Correlation Function using Multitaper Reassignment for Milling Vibration Feature Extraction}},
  url          = {{http://dx.doi.org/10.1016/j.procir.2026.03.095}},
  doi          = {{10.1016/j.procir.2026.03.095}},
  volume       = {{141}},
  year         = {{2026}},
}