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Many authors studied algorithms adjusting the structure model based on modal data. This paper proposes an algorithm to detect the structure model using correlation factors between experimental and theoretical modal data in a damage library. The result from an experiment on 1-40 bridge (New Mexico USA) is presented to illustrate. | Vietnam Journal of Mechanics, NOST of Vietnam Vol. 22, 2000, No 4 (225 - 234) THE USE OF VIBRATION CHARACTERISTIC TO UPDATE THE STRUCTURE MODEL . PHAM XUAN KHANG Research Institute for Transportation Science and Technology ABSTRACT. Many authors studied algorithms adjusting the structure model based on modal data. This paper proposes an algorithm to detect the structure model using correlation factors between experimental and theoretical modal data in a damage library. The result from an experiment on 1-40 bridge (New Mexico USA) is presented to illustrate. 1. Introduction Recently, the research of structure diagnosis using modal data has been developing rapidly. Many damage detection algorithms have been proposed to identify whether or not damage has occurred and to locate damage. However, in order to evaluate the load carrying capacity of a structure, its mathematical model need to be built correctly, relying on experimental data. The model will be complete if its modal data approximates the experimental modal data. The major problem in ·most identification algorithms is the incompleteness of the measured data: only a few points in structure are measured over a limited frequency range, but the finite element (FE) model of the structure contains a large number of degree of freedom. Therefore, updating a structure model relying on vibration data is difficult. Detecting a model according to statistical technique is one of the algorithms used by many researchers, This technique was first suggested by Cawley and . Adams [5]. By this technique, many possible damage scenarios within the finite element model are considered, and their effects on the predicted natural vibrations computed. The damage model is then identified as the one that seems to be closest to measured data. The two major problems with this technique are: 1) the time required to calculate a new set of natural vibration for every damage scenario and, 2) the algorithms to determine the actual damage .
