Recursive maximum likelihood estimation for structural health monitoring: tangent filter implementations

Fabien Campillo 1 Laurent Mevel 2
1 ASPI - Applications of interacting particle systems to statistics
UR1 - Université de Rennes 1, Inria Rennes – Bretagne Atlantique , CNRS - Centre National de la Recherche Scientifique : UMR6074
2 I4S - Statistical Inference for Structural Health Monitoring
IFSTTAR/COSYS - Département Composants et Systèmes, Inria Rennes – Bretagne Atlantique
Abstract : Flutter monitoring can be handled by tracking the real time variations of the modal parameters of a specified civil structure, be it a bridge or an aircraft. Previous algorithmic attempts encompass automated batch identification and damage detection through hypothesis testing. Both approaches appear impractical, the first one because of computational time consid- erations and the difficulty to select a windows length with the best trade off between bias and variance, the second because of the difficulty to obtain reference data set close to flutter regime. Here, we investigate the capabilities of a sample wise recursive linear Kalman filter coupled with a tangent filter. We also consider the nonlinear case.
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Communication dans un congrès
44th IEEE Conference on Decision and Control, and the European Control Conference, Dec 2005, Seville, Spain. IEEE, pp.5923 - 5928, 2005, 〈10.1109/CDC.2005.1583109〉
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Fabien Campillo, Laurent Mevel. Recursive maximum likelihood estimation for structural health monitoring: tangent filter implementations. 44th IEEE Conference on Decision and Control, and the European Control Conference, Dec 2005, Seville, Spain. IEEE, pp.5923 - 5928, 2005, 〈10.1109/CDC.2005.1583109〉. 〈hal-00652103〉

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