超声相控技术在复合材料缺陷检测中的应用

发布时间：2018-08-21 20:17

【摘要】：目前,复合材料凭借轻质高强的优良特性,在航天、航空领域、汽车和建筑等行业得到了越来越多地应用。由于其成型的复杂性以及制作时可能出现的问题,复合材料很容易出现各种缺陷损伤,因此,对其进行无损检测十分必要。鉴于新型复合材料在工业领域中的大量使用,它的稳定性已成为人们日益关注的焦点,所以对复合材料的无损检测又提出新的要求。超声相控阵技术作为无损检测的一种方式,已经成为国际上研究的热点,其检测效率比传统无损检测技术的效率高,对操作人员的专业素质要求相对较低,因此对超声相控阵技术的研究具有一定的实际意义。本文研究了复合材料常见损伤的特点及超声相控阵检测的优势,设计了完整的检测方案,通过对超声相控阵声场指向性的理论分析和计算仿真,探讨了阵元间距,阵元长度,阵元数量,阵元宽度以及偏转角度等参数对声束偏转聚焦的影响,采取了通过控制延迟时间的方法获得良好的声束聚焦效果,对最终的相控阵换能器参数的选择提供了理论依据。对复合材料进行缺陷检测是研究的重点,根据声场指向性的特点,选择合适的相控阵探头参数,然后对返回的扫描图片分析,判断缺陷类型及其相关数据,分析可得超声相控阵技术在检测新型复合材料缺陷方面有着很大的优势。目前,在超声相控阵检测过程中,对检测结果的缺陷识别还是需要依靠检测人员的工作经验来分析,因此,为了更好的对复合材料的缺陷检测的结果进行分析和识别,分别用BP神经网络和RBF神经网络算法相互比较,最终得出:在误差允许的范围内,基于RBF神经网络的缺陷自动识别方法更适合于铝合金复合材料检测。
[Abstract]:At present, composite materials have been applied more and more in aerospace, aviation, automobile and construction industries because of their light, high strength and excellent properties. Because of the complexity of molding and the possible problems in fabrication, the composites are prone to various defects and damage, so it is necessary to carry out nondestructive testing. In view of the extensive use of new composite materials in the industrial field, its stability has become the focus of increasing attention, so a new requirement for nondestructive testing of composite materials is put forward. As a way of nondestructive testing, ultrasonic phased array technology has become a hot spot in international research. Its detection efficiency is higher than that of traditional nondestructive testing technology, and the professional quality of operators is relatively low. Therefore, the study of ultrasonic phased array technology has certain practical significance. In this paper, the characteristics of common damage of composite materials and the advantages of ultrasonic phased array detection are studied, and a complete detection scheme is designed. Through theoretical analysis and calculation simulation of sound field directivity of ultrasonic phased array, the array element spacing and array length are discussed. The effect of the number of array elements, the width of array elements and the deflection angle on the beam deflection focusing is obtained by controlling the delay time. It provides a theoretical basis for the final selection of phased array transducer parameters. According to the characteristics of sound field directivity, the appropriate parameters of phased array probe are selected, and then the returned scanning images are analyzed to judge the defect type and related data. The ultrasonic phased array technology has a great advantage in detecting the defects of new composite materials. At present, in the process of ultrasonic phased array detection, the defect identification of the testing results still needs to be analyzed by the work experience of the examiners. Therefore, in order to better analyze and identify the defect detection results of composite materials, By comparing BP neural network and RBF neural network algorithm, it is concluded that the automatic defect recognition method based on RBF neural network is more suitable for aluminum alloy composite material detection within the range of error.
【学位授予单位】：中国民航大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TB33;TB302.5

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