In damage assessment(damage location) of structure using neural networks, Until now existing method is to learn about entire model element. But this method takes long time to learn, and don't converge.
In this paper, Proposed method was composed seeking for a damaging part in entire model and the next seeking for a damaging element in damaged part.
Damage Assessment(damage locations) is accomplished by using neural net-works. Among the neural networks, backpropagation neural network is adopted to fulfill the damage assessment. When the damages occur, the structural responses are changed and the responses contain the damage locations. Throughout the changes of the structural responses, the neural networks detect damage locations. Because this scheme is to find the causes from the results, we call it the inverse process. When we use the neural networks for the damage assessments.
The vibration of a power transmission tower is induced by the sweep load. The acceleration is captured. This is the input of the neural networks. The neural network is trained and tested with the acceleration data. The simulation informs that it is efficient to apply the neural network to the damage assessment.
