Mode isolation: A new algorithm for modal parameter identification

Multiple degree of freedom (MDOF) algorithms are the dominant methods for e xtracting modal parameters from measured data. These methods are founded on the notion that because the response of a linear dynamic system is the sum of many modal contributions, the extraction technique must deal with all o f the modal parameters in a simultaneous fashion. The Mode Isolation Algori thm (MIA) described here is a frequency domain formulation that takes an al ternative viewpoint. It extracts the modal parameters of each mode in an it erative search, and then refines the estimation of each mode by isolating i ts effect from the other modal contributions. The first iteration estimates modes in a hierarchy of their dominance. As each mode is estimated, its co ntribution is subtracted from the data set, until all that remains is noise . The second and subsequent iterations subtract the current estimates for a ll other modes to identify the proper-ties of the mode under consideration. The various operations are described in detail, and then illustrated using data from a four-degree-of-freedom system that was previously used to asse ss the Eigensystem Realization Algorithm (ERA) and Enhanced ERA. Eigenvalue s and mode shapes are compared for each algorithm. Another example analyzes simulated data for a cantilever beam with three suspended one-degree-of-fr eedom subsystems, in which the parameters are adjusted to bring two natural frequencies into close proximity. The results suggest that MIA is more acc urate, and more robust in the treatment of noisy data, than either ERA vers ion, and that it is able to identify modes whose bandwidth is comparable to the difference of adjacent natural frequencies. (C) 2001 Acoustical Societ y of America.