Abstract
Structural health monitoring is a noticeable technology for aged civil structures. The present paper proposes a new diagnostic tool for the structural health monitoring that employs a statistical diagnosis of self-learning method. Most of the structural health monitoring systems adopt parametric method based on modeling or non-parametric method such as artificial neural networks. The new statistic diagnosis method does not require the complicated modeling and a large number of data for the training of the artificial neural networks. The present study deals monitoring of delamination of composite beam using change of strain judged by the statistical tools such as Response Surface and F-Statistics. The new method successfully diagnoses the damage without using modeling and a large number of data for training.
