Ultrasonic chirplet signal decomposition for defect evaluation and pattern recognition

In this study, a quantitative method using chirplet signal decomposition (CSD) is presented for pattern recognition and defect characterization. The CSD algorithm is utilized to decompose the ultrasonic signal into a linear combination of chirplets, and efficiently estimate the echo parameters. These parameters can be correlated to the structure of defects. For experimental studies, planar and focused transducers with different center frequencies have been used for testing the embedded defects in specimen at normal or oblique refracted angles. It has been shown that the CSD successfully associates the estimated chirplets and their parameters as a quantitative method to characterize defects.