Modal Parameter Estimation for Large, Complicated MIMO Tests

Abstract

Multiple-input, multiple-output (MIMO) experimental modal testing is often used for large structures. The data collected are used in multiple-reference reduction schemes to find the best set of modal parameters to describe the system. Often several or many of the reference shakers do not adequately excite all of the modes from each reference location. When this is the case, using all of the reference data may produce modes that are not optimum. A careful selection of references for generating modal parameters is critical for developing a good modal database for design, analysis, simulation and correlation efforts. While this is true of earlier modal parameter estimation algorithms, the latest PolyMAX estimation algorithm has significant advantages over historically used techniques. Experimental modal tests are often conducted using a multiple–input, multiple-output testing strategy. Depending on the complexity of the structure to be tested, two or more shakers may be used for the excitation of the system. Many times it is very difficult, if not impossible, to have all the shakers excite all the modes of the system equally. This is especially true when the structure exhibits directional global modes or when the structure has an abundance of local modes due to appendage or subcomponent modal energy. When this is the case,