Machine condition monitoring using signal classification techniques

M. Ch Pan, P. Sas, H. Van Brussel

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


Two signal classification approaches, based on Wigner-Ville distribution and extended symmetric Itakura distance, are proposed to post-process the time-frequency representations (TFRs) of vibration signatures, with the final aim to arrive at an automated procedure of machine condition monitoring. Three synthetical signals are used to evaluate and compare the classification performance of these techniques. Some related computation issues, such as characters of different TFRs and weighted window length, are discussed. Experimental case studies, joint fault diagnosis, are realized.

Original languageEnglish
Pages (from-to)1103-1120
Number of pages18
JournalJVC/Journal of Vibration and Control
Issue number10
StatePublished - Oct 2003


  • Feature detection
  • Machine condition monitoring
  • Signal analysis
  • Vibration of machinery


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