摘要: Autofocus is a methodology for estimating and correcting errors in the assumed parameters of an imaging algorithm. It provides improved image quality and, therefore, better defect detection and characterization capabilities. In th... 展开 Autofocus is a methodology for estimating and correcting errors in the assumed parameters of an imaging algorithm. It provides improved image quality and, therefore, better defect detection and characterization capabilities. In this paper, we present a new autofocus algorithm developed specifically for ultrasonic non-destructive testing and evaluation (NDE). We consider the estimation and correction of errors in the assumed element positions for a flexible ultrasonic array coupled to a specimen with an unknown surface profile. The algorithm performs a weighted least-squares minimization of the time-of-arrival errors in the echo data using assumed models for known features in the specimen. The algorithm is described for point and planar specimen features and demonstrated using experimental data from a flexible array prototype. 收起