Recursive maximum likelihood estimation for structural health monitoring: tangent filter implementations

Flutter monitoring can be handled by tracking the real time variations of the modal parameters of a specified civil structure, be it a bridge or an aircraft. Previous algorithmic attempts encompass automated batch identification and damage detection through hypothesis testing. Both approaches appear impractical, the first one because of computational time considerations and the difficulty to select a windows length with the best trade off between bias and variance, the second because of the difficulty to obtain reference data set close to flutter regime. Here, we investigate the capabilities of a sample wise recursive linear Kalman filter coupled with a tangent filter. We also consider the nonlinear case.