Scanning Laser Acoustic Microscope Tomography Algorithm Research

In recent years, many new kinds of materials have been widely used in many military and electronic fields. Because of the material's complexity in processing or in using, there are many types of defects that may affect its performance and safety seriously. In order to detect the flaw situation in the sample accurately, before detecting their two-dimensional flaws, it is very important to obtain the clear three-dimensional picture of the flaws.SLAM (Scanning Laser Acoustic Microscope) is a type of acoustic microscopy, as a new-type of high-efficient NDT( non-destructive testing) instrument, it is an useful method to study the internal structure of new materials or devices. Using SLAM image system, we can not only get the amplitude image of the internal of the detected object, but also can get its phase image. Therefore through a certain times of projecting, we can obtain the effective reconstruction data, using the corresponding tomography algorithms and the correction algorithms, we can obtain clear three dimensional tomography picture of the sample which provides the reliable basis for the accurate detecting.The background of this theme, the status of application and the development at home and abroad has been introduced in chapter one. The SLAM system studied in this theme has been explained in chapter two, on the SLAM system foundation, the methods to realize the STAM system have been introduced. Many kinds of tomography algorithm in the ultrasonic field have been introduced in chapter three. Through analysis of the STAM system, the non-linear diffraction tomography theoretical model has been established, and also the truncated total least squares method has been introduced. In order to realize the algorithm in the STAM system, it has been suitably approximated to the algorithm. The non-linear diffraction theory has been translated into the procedure code in chapter five. Using the multi-frequencies projection picture, the clear tomography pictures of the sample have been obtained, finally compared with other tomography algorithms. Phase error and the projection error have been estimated and corrected in chapter six.It should be noted that there are two achievements in this thesis. First, the application of non-linear diffraction tomography theoretical algorithm to the STAM system is one innovation, it has not been reported before. The regularization method to the non-linear diffraction tomography theoretical model in the STAM system introduced in chapter four is the other innovation. The actual...