This paper presents an efficient algorithm for estimation of damage location and
severity in structure using Probabilistic Neural Network(PNN). Artificial neural
network has been being used for damage assessment by many researchers, but there
are still some battiers that must be overcome to improve its accuracy and efficiency.
The mahor problems with the conventional neural network are the necessity of many
training data for neural network learning and ambiguity in the relation of neural
network architecture with convergence of solution. In this paper, PNN is used as
a pattern classsifier to overcome those problems in the conventional neural network.
The basic idea of damage assessment algorithm proposed in this paper is that modal
characteristics from a damaged structure are compared with the training patterns
which represent the damage in specific element used in producing the training
pattern is consideed as a damaged one. The proposed damage assessment algorithm
using PNN is applied to a 2-span continuous beam model structure to verify the
algorithm.