In this paper, a damage identification method called local flow variation is introduced. It is a practical implementation of a phase space warping concept. A hierarchical dynamical system is considered where a slow-time damage process causes drifts in the parameters of fast-time system describing measurable response of a structure. The method is based on the hypothesis that the probability distribution function of the fast-time trajectory in its phase space is a function of damage state. In this method, an ensemble of estimated expectations of trajectory in different locations of the reconstructed phase space is used as a damage feature vector. Using these feature vectors, damage identification is realized by a smooth orthogonal decomposition. An experiment is conducted to validate the method. A two dimensional slow-time damage process is identified from experimental fast-time data. Although damage identification through the local flow variation is not as accurate as trough phase space warping, the required computing time is about two-orders-of-magnitude shorter.

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