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Crystal Clear SSI |
A new feature resulting in extremely clear
stabilization diagrams
is now introduced as an add-on to the well-known SSI algorithms available in ARTeMIS Extractor Pro.
This new revolutionary feature is Crystal Clear Stochastic
Subspace Identification (CC-SSI).
Try it today by downloading
the 30 days evaluation version of ARTeMIS Extractor Pro. Just install it and run
one of the Example Files using the Preliminary Modal Analysis feature. This will
demonstrate the efficiency and ease-of-use of Crystal Clear SSI and Automatic
Mode Estimation for SSI in a matter of minutes
Download here
The basic idea is to specify the maximum number of significant poles (eigenvalues) present in the measurements that should be
estimated. The estimation algorithm will then focus on the modes
having these poles and any less significant noise poles are returned
with a natural frequency estimate much higher than the Nyquist
frequency, and a damping ratio of 100 %. The maximum number of poles
can be specified by the user, or is estimated automatically by the
software using a special data-dependent algorithm.
The algorithm has proven to be extremely robust in many difficult
cases such as:
·
Heavily damped modes
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Weak modes mixed with dominant deterministic signals (harmonics)
·
High number of modes in a narrow frequency range.
Due to the highly consistent estimation of the poles, the search
for the optimal model order is less critical when using this new
feature. Especially the damping estimates are much more robust now
than ever before.
Crystal Clear SSI analysis of a fighter jet wing with many
modes. The modes indicated with a red A on the top of the diagram are
extracted using the new Automatic Mode
Estimation features. See the close-up picture below.
Major Benefits of SSI in General
No matter if the new features are in use or not, there are some technical
benefits of SSI compared to other commercially available parametric model
estimators working in the frequency domain and relying on the estimation of
half-power spectral densities.
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