Abstract
The present study is about an automatic diagnostic method for the structural health monitoring. In this study, a new diagnostic method applicable to existing structures from the present moment is proposed. In the proposed method, structural condition is diagnosed without information about damaged condition. The proposed method statistically diagnoses structural condition by means of investigating the change of a response surface. The response surface is calculated as a regression model of relationship between multiple sensors. The shape of the response surface is changed reflecting the change of the structural condition. In this method, the change of the response surface is statistically investigated with the F-test. In the F-test, the threshold of normal or damaged condition is decided with only theoretical F-probability distribution. This theoretical F-distribution is easily calculated using the response surface parameters. Therefore, diagnosis is conducted by means of only intact data used for the reference data. This means the proposed method doesn't require information about the damaged condition. Since the SI-F method is able to detect the damage in the structure by judging the deviation from the normal state, it is important to avoid the false positive detection for raising the reliability of the structure. In the present study, relationship between the condition of the false detection and the shape of the response surface is clarified. And several numerical simulations were carried out to declare the optimal condition of the damage detection for the structural health monitoring using the SI-F method.
