Feature Assimilation for Vibration Based Damage Detection

Abstract

Structural health monitoring (SHM) technology for the early detection and mitigation of adverse structural effects, such as degradation or damage, is useful for enhancing the proactive maintenance of civil infrastructure. SHM techniques are advantageous because they eliminate the need for both a priori knowledge of the location of damage and access to the damaged portion of the structure. The underlying principle behind SHM involves measuring changes in a system’s vibration response, which ultimately indicate changes in physical properties due to structural damage. A challenge to the successful application of SHM to civil infrastructure is the selection of suitable vibration response features that are highly sensitive to the presence and extent of damage while also having low sensitivity to extraneous noise. This study reveals that both damage and the noise sensitivity of vibration response features vary for different states of structural health; therefore, the selection of optimum features is dependent on the damage severity, which is of course not known a priori. This study illustrates that assimilating multiple low-dimensional features lessens this dependence and improves the sensitivity of the damage indicators for SHM diagnosis.