A model-based approach to dispersion and parameter estimation for ultrasonic guided waves

A model-based algorithm is presented that adaptively estimates in situ ultrasonic guided wave system parameters. Dispersion curves, propagation loss, transducer distances, transmitted signal, and mode weighting coefficients are estimated using minimal a priori information and assumptions. The five-part algorithm is scalable to accommodate two or more receivers and one or more propagating modes, provided that mode separation can be achieved prior to use of the algorithm. Algorithmic performance is demonstrated on signals obtained both from theoretical dispersion curves and finite element modeling. Quantitative performance curves are presented that are based on algorithmic performance from multiple simulated test cases with varying amounts of additive noise. Results show excellent agreement between estimated and actual parameters, as well as between modeled and received signals.