Sensitivity of the identified modal parameters on imprecise experimental data

In the field of structural analysis, many factors are sources of errors on finite element modelling. Many sources, identified or not, could create a model more or less erroneous. An important research consists in developing, by inverse analysis, some methods allowing to correct finite element models in relation to the experimental data. In these methods, the hypothesis is the following: the observed reality is the aim to reach, consequently, the complete error is-imputable to the model. However, the experimental data contain a part of the error due to the measurement system and the role of the human factor. This type of uncertainty is moreover difficult to quantify. In this paper, we have developed an algorithm allowing us to identify the eigensolutions of a prototype considering imprecise frequency response functions. This algorithm is based on both a classical identification technique and the used of fuzzy number for modelling imprecise experimental data. This methodology have two potentials of interest : -the ability to supply imprecise data to modal updating tools, -the capacity to filter the imprecision on the measured data.