Abstract: Information fusion technology is applied to identify structural multiple damaged locations. It is considered that the multiple evidence from different information sources of different importance or reliability are not equally important when they are combined according to Dempster-Shafer theory, which is seldom considered in the existent combination methods. A new method, I.e. weighted evidence balance method, is presented to solve this problem. The method first searches for the optimal weighting coefficients of different evidences using genetic algorithms, then balances the considered evidences according to the weighted average of all and the preferred evidence, and finally combines them. Thus, It is guarantied that the balanced evidences won’t change the weighted average of all and the preferred evidence. The simulation results demonstrate the excellent performance of the weighted evidence balance method to identify multiple damage locations as compared with other methods, such as those methods based on mode shape change or frequency change, basic evidence theory and other weighted evidence combination methods.

Key words: Damage identification, Evidence theory, Genetic algorithms, Information fusion, Stiffness characteristics., Cross-spring pivot, Quasi-constant rotational stiffness, Vertical loads