The Application In Detection Of Defects In Compound Material With Ultrasonic Phased Technology

Recently, composites are widely used in aerospace field, automotive industry and construction industry because of their excellent performance of light and strong. As the result of the complexity of their molding and the potential problem of making process, defects and damage are easily introduced on composites. Thus, it is necessary to do non-destructive testing. Due to the heavy use of composites, their stabilities have come to the forefront. So non-destructive testing is needed to develop for advanced. Ultrasonic phased array technology has become hot spot in worldwide research, and its efficiency is better than traditional one.Besides, Ultrasonic phased array technology asks lower requirement to operating person, so it has some real meaning for the research of Ultrasonic phased array technology.The basis of this paper is the characteristics of usual damage and the advantage of non-destructive testing. And complete testing has been designed through theoretical analysis and computer simulation of directivity of Ultrasonic phased array technology. In addition, this paper discusses element spacing, element length, element number, element width and angular deflection, and their influence of deflection focusing of sonic beam. Besides, this paper takes approach of controlling delay time to get good effect of sonic beam focusing. Finally, it provides theoretical basis to the option of phased array ultrasonic testing parameter.The point of paper is to do defect detecting to composites. Firstly, according to the characteristic of sound field directivity, choose suitable phased array ultrasonic testing parameter. Secondly, analyze the returning scan photos. Thirdly, judge the defect type and relative data. Thus, the advantage of Ultrasonic phased array technology in testing the defect of new type composites. Recently, in the test process of Ultrasonic phased array technology,the working experience is needed for recognizing the defect of testing result. To better analyze and recognize the testing result of composites, this paper uses BP neural network and RBF neural network and compares them. Finally, we draw the conclusion, within a margin of error, the method which base on RBF neural network is more suitable.