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Damage Localization in Mechanical Systems by Lasso Regression

Michael Döhler 1, 2 Qinghua Zhang 1, 2 Laurent Mevel 1, 2 
1 I4S - Statistical Inference for Structural Health Monitoring
Inria Rennes – Bretagne Atlantique , COSYS - Département Composants et Systèmes
Abstract : Early signs of mechanical characteristic changes are essential for structural health monitoring (SHM). Due to the complexity of civil, mechanical or aeronautical structures, SHM is often faced with high dimensional mechanical characteristics together with limited sensor instrumentation. In this paper, Lasso regression is applied to address this complexity issue, based on its ability for solving large regression problems. The mechanical vibration model is first appropriately transformed into a linear regression model, with its parameters corresponding to small changes in the monitored mechanical characteristics, then these parameters are estimated from mechanical sensor signals under the assumption that most of the parameters are zeros. The performance of the proposed method is illustrated with a simulated truss structure.
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https://hal.inria.fr/hal-03292476
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Submitted on : Tuesday, July 20, 2021 - 2:34:53 PM
Last modification on : Friday, June 17, 2022 - 1:27:06 PM
Long-term archiving on: : Thursday, October 21, 2021 - 6:46:48 PM

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  • HAL Id : hal-03292476, version 1

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Michael Döhler, Qinghua Zhang, Laurent Mevel. Damage Localization in Mechanical Systems by Lasso Regression. SYSID 2021 - 19th IFAC Symposium on System Identification, Jul 2021, Padua / Virtual, Italy. pp.1-6. ⟨hal-03292476⟩

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