TWO-STEP STRUCTURAL DAMAGE LOCALIZATION METHOD BASED ON MODE SHAPES OF STRUCTURE UNDER CONTROL

The paper proposes a two-step structural damage localization method based on a neural network and the mode shapes of structures under control. In the study, the state feedback control method is first employed to place the poles of the structure intentionally and the prescribed characteristic frequencies and mode shapes of the controlled structure are obtained accordingly. The structure is divided into several sub-domains and damaged sub-domain is identified using a probabilistic neural network, in which the mode differences between undamaged and damaged controlled structures are chosen as the input vectors. Then the multiple damage location assurance criterion is taken as the damage indicator to locate the specific damaged element. Numerical results show that the damaged sub-domain can be identified using the probabilistic neural network and the search domain for locating the specific damaged element is greatly reduced by the adoption of the proposed two-step identification strategy. The use of dynamic characteristic data of the structure under control can improve the sensitivity of the damage indicator and consequently the accuracy of damage identification.