Model-based frequency estimation for ultrasonic NDE applications

In the ultrasonic NDE of materials, spectral analysis of backscattered echoes is a useful tool for flaw detection, frequency-shift estimation, and dispersive echo characterization. In order to evaluate the local information, spectral analysis must be applied to short data segments and must offer high frequency resolution. In this paper three high resolution model-based spectral estimation techniques: the autoregressive (AR) method using the Burg algorithm, Prony's method for exponential signal representation, and MUltiple signal classification (MUSIC) method have been studied for ultrasonic NDE applications. These algorithms have been applied to both simulated data and experimental measurements for frequency estimation and flaw detection. The maximum energy frequency estimates using these methods show excellent sensitivity to changes in the frequency of ultrasonic echoes. The AR method shows a more robust performance for frequency estimation than the Prony or MUSIC methods