Fault Detection for Precision Mechatronics: Online Estimation of Mechanical Resonances

Koen Classens, Mike Mostard, Jeroen Van De Wijdeven, W. P.M.H. Maurice Heemels, Tom Oomen

Research output: Contribution to journalConference articleScientificpeer-review

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The condition of mechatronic production equipment slowly deteriorates over time, increasing the risk of failure and associated unscheduled downtime. A key indicator for an increased risk for failures is the shifting of resonances. The aim of this paper is to track the shifting resonances of the equipment online and during normal operation. This paper contributes to real-time parametric fault diagnosis by applying and comparing parameter estimators in this new context, highly relevant for next-generation mechatronic systems. The proposed fault diagnosis systems consist of recursive least squares algorithms and the effectiveness is illustrated on an overactuated and oversensed flexible beam setup, allowing to artificially manipulate its effective resonances in a controlled manner.

Original languageEnglish
Pages (from-to)746-751
Issue number37
Publication statusPublished - 2022
Event2nd Modeling, Estimation and Control Conference, MECC 2022 - Jersey City, United States
Duration: 2 Oct 20225 Oct 2022


  • Fault Detection
  • Fault Diagnosis
  • Fault Estimation
  • Fault Isolation
  • Mechatronic System
  • Multiplicative Fault
  • Parametric Fault
  • Predictive Maintenance


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