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Communication Dans Un Congrès Année : 2016

VIBRATION SOURCE CHARACTERIZATION USING FORCE ANALYSIS TECHNIQUE AND A BAYESIAN REGULARIZATION

Résumé

The Force Analysis Technique (FAT) is a inverse method for the characterization of vibration sources applied on a structure, based on measurements of its displacement. From the knowledge of the local equation of motion of the structure, it allows both the localization and the quantifica-tion of sources, without the need of boundary conditions. As many inverse methods, the FAT is however highly sensitive to noise and includes traditionally a low pass filter to fix this instability. This work presents new strategies for the regularization step within the Bayesian framework. It introduces a priori probabilities which can lead to the Tikhonov regularization when Gaussian densities are used for both the source field and the noise, or to a sparse identification when using a Bernoulli-Gaussian a priori on sources. These two cases are performed by the Gibb's sampler, a particular Markov Chain Monte Carlo (MCMC) algorithm. It allows an unsupervised (or empirical) and automatic regularization besides confidence intervals on variables, especially on the source field.
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Dates et versions

hal-01717628 , version 1 (26-02-2018)

Identifiants

  • HAL Id : hal-01717628 , version 1

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Charly Faure, Frédéric Ablitzer, Charles Pezerat, Jérôme Antoni. VIBRATION SOURCE CHARACTERIZATION USING FORCE ANALYSIS TECHNIQUE AND A BAYESIAN REGULARIZATION. ICSV 23, Jul 2016, Athens, Greece. ⟨hal-01717628⟩
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