A Probabilistic Novelty Detection Methodology Based on the Order-Frequency Spectral Coherence

  • Stephan SchmidtEmail author
  • Stephan Heyns
  • Konstantinos Gryllias
Conference paper
Part of the Applied Condition Monitoring book series (ACM, volume 15)


The purpose of this paper is to develop a methodology that utilises the order-frequency spectral coherence to detect novel (i.e. unobserved) second-order cyclostationary components. In the novelty detection methodology, a probabilistic model of the healthy data is utilised to detect, localise and trend novelties in the form of damage that manifest as second-order cyclostationary components in vibration signals. The methodology is unique in the sense that on the one hand, the spectral properties are retained and multiple harmonics of the fault frequency component are used during the condition inference process; while on the other hand, the methodology is simple and efficient to implement. A numerical gearbox model is used to generate vibration signals and to simulate bearing and distributed gear damage. The methodology is applied to the simulated vibration signals, generated under varying speed conditions, which demonstrates very promising results.


Novelty detection Order-Frequency Spectral Coherence Gearbox diagnostics 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Stephan Schmidt
    • 1
    Email author
  • Stephan Heyns
    • 1
  • Konstantinos Gryllias
    • 2
    • 3
  1. 1.Centre for Asset Integrity ManagementUniversity of PretoriaPretoriaSouth Africa
  2. 2.Department of Mechanical Engineering, PMA DivisionKU LeuvenLeuvenBelgium
  3. 3.Dynamics of Mechanical and Mechatronic SystemsFlanders MakeLeuvenBelgium

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