Structural and sensor damage identification using the bond graph approach

Abstract

This paper develops a new and efficient hybrid qualitative–quantitative system identification methodology for structures using the bond graph approach. Bond graphs provide a modeling framework that includes parametric models of both the physical system and the sensors. Structural damage is modeled as reductions in the parameter values of the structural components. Sensor faults are modeled as biases or drifts from true responses. The damage detection uses a statistical method to identify significant deviations of measurements from nominal healthy behavior of the structure. Damage isolation is carried out by comparing the predicted signatures of various damage scenarios with the observed behavior of the structure. The damage signatures are derived off-line before sensor data collection. Quantitative identification of the damage amount uses the least-squares method, analyzing only the sub-structure containing the damaged component. Numerical illustrations of damage identification of frame structures driven by time-varying loads are provided, highlighting the advantages with respect to sensor fault identification and computational efficiency. Copyright © 2008 John Wiley & Sons, Ltd.