Health Assessment of Large Two Dimensional Structures Using Limited Information: Recent Advances

Abstract

Some recent advances of a recently developed structural health assessment procedure proposed by the research team at the University of Arizona, commonly known as generalized iterative least-squares extended Kalman filter with unknown input (GILS-EKF-UI) are presented. The procedure is a finite elements-based time-domain system-identification technique. It can assess structural health at the element level using only limited number of noise-contaminated responses. With the help of examples, it is demonstrated that the structure can be excited by multiple loadings simultaneously. The method can identify defects in various stages of degradation in single or multiple members and also relatively less severe defect. The defective element(s) need not be in the substructure, but the defect detection capability increases if the defect spot is close to the substructure. Two alternatives are suggested to locate defect spot more accurately within a defective element. The paper advances several areas of GILS-EKF-UI to assess health of large structural systems.