Experimental Identification of Distributed Damping Matrices Part 2: Experimental Case Studies

Despite tremendous advances in modern computational technology, there still remain many engineering problems that do not allow numerical solutions of reasonable accuracy. In many of these problems the main difficulty stems from lack of our ability to accurately model damping. Such examples are simulation of structure-borne noise, stability analysis of dynamic systems and numerical prediction of fatigue failure. In these problems small difference in damping description results in a completely different solution, while the current state of the art of damping modeling cannot provide such accuracy.

A new concept, which had been proposed by one of the authors as a potential break-through for damping modeling, is studied in this two-part paper. Advantages of the method and practical issues to overcome are discussed in both papers. The method obtains the damping model directly from measured data; therefore is completely independent of classical damping models. The method can describe the spatial distribution of damping accurately as is, and has a very simple algorithm, which minimizes the effect of numerical and measurement errors. This paper contains an experimental study of the algorithm using a simple structure. Diagnostic tools presented in part 1 will be applied to the experimental data in order to identify data quality and structural properties. The feasibility of the DSM algorithm will also be discussed within the context of current experimental equipment and methods.