Blind Multiridge Detection and Reconstruction Using Ultrasonic Signals

Time-frequency signal analysis has been widely applied in the modern radar, acoustic, sonar and ultrasonic signal processing techniques. Recently, the nondestructive testing (NDT) techniques via the ultrasonic instrumentation have shown the striking capability of the quality control for the material fabrication industry. In this thesis, we first provide a general mathematical model for the ultrasonic signals collected by pulse-echo sensors and then design a totally blind, novel, signal processing NDT technique relying on neither a priori signal information nor any manual effort. The signature signal can be blindly extracted by using the automatic optimal frame size selection for further modeling and characterization of the ultrasonic signal using Gabor analysis. This modeled signature signal is used for multiridge detection and for reconstruction of the signal. The detected ridge information can be used to estimate the transmission and attenuation coefficients, shear modulus, and Young’s modulus associated with any arbitrary material sample for fabrication quality control. Thus, our algorithm can be applied for ultrasonic signal characterization and ridge detection in non-destructive testing for new material fabrication. Experimental results show that the ridge detection performance by our proposed method is superior to that of the existing techniques