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Communication Dans Un Congrès Année : 2022

Kalman predictor subspace residual for mechanical system damage detection

Résumé

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.
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Dates et versions

hal-03722489 , version 1 (13-07-2022)

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Michael Döhler, Qinghua Zhang, Laurent Mevel. Kalman predictor subspace residual for mechanical system damage detection. 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⟩. ⟨hal-03722489⟩
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