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Kalman predictor subspace residual for mechanical system damage detection
- Source :
- SAFEPROCESS 2022-11th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes, SAFEPROCESS 2022-11th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes, Jun 2022, Pafos, Cyprus. pp.1-6, ⟨10.1016/j.ifacol.2022.07.102⟩
- Publication Year :
- 2022
- Publisher :
- Elsevier BV, 2022.
-
Abstract
- International audience; For mechanical system structural health monitoring, a new residual generation method is proposed in this paper, inspired by a recent result on subspace system identification. It improves statistical properties of the existing subspace residual, which has been naturally derived from the standard subspace system identification method. Replacing the monitored system state-space model by the Kalman filter one-step ahead predictor is the key element of the improvement in statistical properties, as originally proposed by Verhaegen and Hansson in the design of a new subspace system identification method.
- Subjects :
- subspace system identification
[STAT.AP]Statistics [stat]/Applications [stat.AP]
Structural health monitoring
residual design
Control and Systems Engineering
[SPI.GCIV.DV]Engineering Sciences [physics]/Civil Engineering/Dynamique, vibrations
fault diagnosis
damage detection
vibration analysis
Subjects
Details
- ISSN :
- 24058963
- Volume :
- 55
- Database :
- OpenAIRE
- Journal :
- IFAC-PapersOnLine
- Accession number :
- edsair.doi.dedup.....e80b9bbb5e637e576b72c59f1a573a36