Damage diagnosis for SHM of existing civil structure with statistical diagnostic method

Abstract

The present research proposes a new automatic damage diagnostic method that does not require data of damaged state. Structural health monitoring is a noticeable technology for civil structures. Multiple damage diagnostic method for has been proposed, and most of them employ parametric method based on modeling or non-parametric method such as artificial neural networks. These methods demand much costs, and first of all, it is impossible to obtain data for training of damaged existing structures. That causes importance of development of the method, which diagnoses damage just from data of the intact state structure for existing structures. Therefore we purpose new statistical diagnostic method for structural damage detection. In the present method, system identification using a response surface is performed and damage is diagnosed by testing the change of this identified system by statistical test. The new method requires data of non-damaged state and does not require the complicated modeling and data of damaged state structure. As an example, the present study deals damage diagnosis of a jet-fan which installed to a tunnel on an expressway as a ventilator fan. Damages are detected from load of turnbuckles. As a result, the damage is successfully diagnosed with the method.