Modal parameter estimation of a reduced-scale rocket nozzle using blind source separation

Abstract

In this paper, two blind source separation (BSS) algorithms are used to estimate the modal parameters of a reduced-scale rocket nozzle using only measurements of deformation. The data is gathered using a single high-speed video camera, in combination with fluorescent markers placed on the nozzle lip illuminated by a Nd:YLF pulsed laser strobe. A marker tracking algorithm is used to measure the displacement of each fluorescent marker. The nozzle is excited using a conventional shaker with band-limited white noise input as well as an impact hammer. The results of the two BSS algorithms, namely the second order blind identification algorithm and the complexity pursuit algorithm, are compared to a well-established output-only modal analysis technique, the stochastic subspace identification algorithm, as well as finite element analysis predictions. It was found that both BSS algorithms correctly identified all modes compared to the stochastic subspace identification algorithm and the finite element analysis, and the calculated eigenfrequencies are within 0.1% of measured values. The BSS algorithms facilitate the accurate extraction of modal parameters from output-only measurements with a minimum of user interaction compared to conventional modal analysis algorithms.