Though modal analysis is a common tool to evaluate the dynamic properties of a
structure, there are still many individual decisions to be made during the
process which are often based on experience and make it difficult for occasional
users to gain reliable and correct results. One of those experience-based
choices is the correct number and placement of reference points. This decision
is especially important, because it must be made right in the beginning of the
process and a wrong choice is only noticeable by chance in the very end of the
process. Picking the wrong reference points could result in incomplete modal
analysis outcomes, as it might make certain modes undetectable, compounded by
the user's lack of awareness about these missing modes.
In the paper an innovative approach will be presented to choose the minimal
number of mandatory reference points and their placement. While other approaches
use results of numerical simulations or rely on a visual evaluation of
measurement data by the user, the presented approach is based on a few simple
measurements and works automatically without any further user-interaction. In
addition to traditional methods such as the Least-Squares Complex
Frequency-domain (LSCF) estimator the presented approach takes advantage of a
Neural Network to make user-interaction redundant.
The advantage of the presented approach will be shown based on the example of a
real structure under test.