Nonlinear Structural Damage Detection Based on Adaptive Volterra Filter Model

The majority of the existing damage diagnostic techniques are based on linear models. Changes in the state of the dynamics of these models, before and after damage in the structure based on the vibration measurements, are popularly used as damage indicators. However, the system may initially behave linearly and subsequently exhibit nonlinearity due to the incipience of damage. Breathing cracks that exhibit bilinear behavior are one such example of the damage induced due to nonlinearity. Further many real world structures even in their undamaged state are nonlinear. Hence, in this paper, we present a nonlinear damage detection technique based on the adaptive Volterra filter using the nonlinear time history response. Three damage indices based on the adaptive Volterra filter are proposed and their sensitiveness to damage and noise is assessed through two numerically simulated examples. Numerical investigations demonstrate the effectiveness of the adaptive Volterra filter model to detect damage in nonlinear structures even with measurement noise.