Validation is the key to all good modal identification. The value of any estimation is determined solely based on the validation.
Validation is an evaluation of the quality of the results and is performed on two levels:
Now, when we say 'models' we do not necessarily mean parametric models. Models in this sense is a more generalized concept, a way of thinking, a way of processing
data. At this step we try to justify the model, the way of thinking or whatever we are doing.
If it is a parametric model, we might look at how this individual model fits the data. For instance, we might look at how the model fits the spectral density functions,
the correlation functions, or even the raw time series.
If it is a non-parametric model, we might look at how well the results of the different signal processing comply with what we expect. For instance, in the Enhanced Frequency Domain Decomposition (EFDD) technique, we try to identify the single-degree-of freedom contribution to the singular value decomposition of the spectral density matrix. In this case, we know that this contribution is expected to be a nice single-bell spectral density function. Thus, in this case, the model validation is an evaluation of how the different bell-functions comply with our expectations.
An estimation should never be performed using only one model or one technique only. If only one technique is used, the user should perform several estimations using
the same technique but spreading over a suitable variation of user choices.
If the user wants to use a parametric model, one should perform identifications using several model orders. If the user wants to apply non-parametric estimation, one can vary some user choices to obtain different modal estimates.
The best is to use several different techniques, for instance to use a non-parametric technique and one or more parametric techniques, and to vary the user choices in
order to obtain several estimates for each technique.
In the end, the user validates the modal estimates against each other. This is the final and most important validation. Without this validation the user cannot know
if the identification is reliable.
However, the modal estimates that appear in all estimations with small deviations are the most reliable. The larger deviations, the smaller the reliability, and modes
that only appear in some identifications have the lowest reliability.
The user should validate all the results of the modal identification, the natural frequencies, the damping ratios and the mode shapes.