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Robust Interacting Particle-Kalman Filter based structural damage estimation using dynamic strain measurements under non-stationary excitation -an experimental study

Neha Aswal 1 Eshwar Kuncham 1 Subhamoy Sen 1 Laurent Mevel 2 
2 I4S - Statistical Inference for Structural Health Monitoring
Inria Rennes – Bretagne Atlantique , COSYS - Département Composants et Systèmes
Abstract : Sensor types and their positioning is a major factor in structural health monitoring (SHM) to ensure certainty in estimation. While acceleration has predominantly been employed for damage detection, they are known to be costly and not frame invariant (except for moderately accurate GPS based accelerometers). A thorough monitoring of a real life structure requires dense instrumentation which might become expensive with costly sensor types. Further, damages mostly occur at rare events, like seismic base excitation, for which typical accelerometers are not proper. This study employs strain as a cheaper alternative for damage sensitive measurement that is also frame invariant. An interacting filtering approach with particle and Kalman filters is employed that estimates structural health from measured dynamic strains. Further to account for extreme non-stationary events like seismic excitation, robustness against uncertain inputs is induced in the filtering environment following an output injection approach. The proposed algorithm is tested on a seven story-one bay frame model and a real experimental beam structure.
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https://hal.inria.fr/hal-03277241
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Submitted on : Friday, July 2, 2021 - 6:13:23 PM
Last modification on : Friday, June 17, 2022 - 1:28:33 PM
Long-term archiving on: : Sunday, October 3, 2021 - 8:33:06 PM

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  • HAL Id : hal-03277241, version 1

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Neha Aswal, Eshwar Kuncham, Subhamoy Sen, Laurent Mevel. Robust Interacting Particle-Kalman Filter based structural damage estimation using dynamic strain measurements under non-stationary excitation -an experimental study. SHMII-10 2021 – 10th International Conference on Structural Health Monitoring of Intelligent Infrastructure, Jun 2021, Porto, Portugal. pp.1-8. ⟨hal-03277241⟩

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