This short paper presents a data-driven method for identification of stability margin in rotorcraft system dynamics and the underlying concept is built upon the principles of Symbolic Dynamics. The algorithm involves wavelet-packet-based pre-processing to remove spurious disturbances and to improve the signal-to-noise ratio (SNR) of sensor time series. A quantified measure, called Instability Measure, is constructed from the processed time series data to obtain an estimate of the relative instability of the dynamic modes of interest on the rotorcraft system. The proposed method has been tested with numerical simulations; and correlations between the Instability Measure and the damping parameters of selected dynamic modes of the rotor blade have been established.

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