Fault Detection for Precision Mechatronics: Online Estimation of Mechanical Resonances

Classens, Koen; Mostard, Mike; Van De Wijdeven, Jeroen; Maurice Heemels, W. P.M.H.; Oomen, T.A.E.

doi:10.1016/j.ifacol.2022.11.271

Fault Detection for Precision Mechatronics

Title

Fault Detection for Precision Mechatronics: Online Estimation of Mechanical Resonances

Author

Classens, Koen (Eindhoven University of Technology)
Mostard, Mike (Eindhoven University of Technology)
Van De Wijdeven, Jeroen (ASML)
Maurice Heemels, W. P.M.H. (Eindhoven University of Technology)
Oomen, T.A.E. (TU Delft Team Jan-Willem van Wingerden; Eindhoven University of Technology)

Date

2022

Abstract

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.

Subject

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

To reference this document use:

http://resolver.tudelft.nl/uuid:b1395c66-e175-4392-b181-d95627cb1ed4

DOI

https://doi.org/10.1016/j.ifacol.2022.11.271

ISSN

1474-6670

Source

IFAC-PapersOnLine, 55 (37), 746-751

Event

2nd Modeling, Estimation and Control Conference, MECC 2022, 2022-10-02 → 2022-10-05, Jersey City, United States