基于一维稀疏阵列的超声相控阵列优化设计研究

发布时间：2018-12-21 18:07

【摘要】：超声相控阵成像技术可控制阵列中各阵元发射(或接收)超声波的时间(相位),实现各阵元的声束在声场中偏转、聚焦,达到成像检测的高端技术。与常规超声方法相比,它具有快速灵活,机械可靠性强等特点。根据目前国内外对相控阵超声检测技术的研究进展,超声相控阵阵列换能器的设计和多通道超声发射与接收系统已成为相控阵检测的两大关键技术。作为超声相控阵检测系统的电控核心,多通道超声发射与接收系统实现了波束时空控制的多项关键技术；而阵列换能器是实现超声成像检测的直接部件,它承担了与检测对象的直接接触,对相控阵检测的性能和成像质量有着直接的影响。在相控阵超声阵列设计中,往往以缩小阵元间距,增加阵元密度的方式来消除栅瓣,解决成像空间模糊的问题,但也带来了提高阵列成本,增加制作难度,而且使阵元间的互辐射效应变得严重的弊端,这在大型阵列换能器的设计中尤为明显。而稀疏阵列正是解决上述弊端的有效途径。本文提出一种改进的粒子群算法,对不同的相控阵一维稀疏阵列进行仿真优化分析,计算出能反映成像的空间分辨率和对比度分辨率的阵列方向图,得到了综合声学性能接近参考满阵阵列的稀疏阵列。实验分析表明,粒子群算法的引用能为稀疏阵列提供有效的优化设计。在改进粒子群算法的基础上,结合了最小冗余度阵列,使稀疏阵列保持高空间分辨率的同时,也改善了对比度分辨率,并且解决了单纯靠粒子群算法得到的稀疏阵列一致性差的问题。采用MATLAB与Visual Studio 9.0混合编程,开发了超声相控阵稀疏阵列控制平台,它可实现任意孔径、任意有效阵元数的阵列换能器稀疏控制,也能实现不同孔径的稀疏阵列优化设计与性能评估,并基于此平台设计了超声相控阵稀疏阵列检测系统。通过稀疏阵列检测系统,使用两种算法得到的稀疏阵列,以及相应孔径参考阵列,对不同板厚的具有气孔、未熔合、未焊透、夹渣、裂纹典型焊缝缺陷试块进行检测成像对比,建立典型稀疏阵列与焊缝缺陷数据库。缺陷检测实验表明,粒子群算法结合最小冗余度阵列的方法,可以在提高稀疏阵列成像空间分辨率的同时,也改善检测成像的对比度分辨率,并能提供较高质量的超声检测成像。
[Abstract]:The ultrasonic phased array imaging technology can control the time (phase) of each array element to transmit (or receive) ultrasonic wave, realize the sound beam of each array element to deflect in the sound field, focus, reach the high-end technology of imaging detection. Compared with the conventional ultrasonic method, it has the advantages of fast and flexible, strong mechanical reliability and so on. According to the research progress of phased array ultrasonic detection technology at home and abroad, the design of ultrasonic phased array transducer and the multi-channel ultrasonic transmitting and receiving system have become two key technologies of phased array detection. As the electronic control core of ultrasonic phased array detection system, multi-channel ultrasonic transmitting and receiving system realizes several key technologies of space-time control of beam. The array transducer is the direct component of ultrasonic imaging detection, which bears direct contact with the detection object, and has a direct impact on the performance and imaging quality of phased array detection. In the design of phased array ultrasonic array, the method of reducing the distance between array elements and increasing the density of array elements is often used to eliminate the grating lobe and solve the problem of blurred imaging space, but it also increases the cost of array and makes it more difficult. Moreover, the mutual radiation effect between array elements becomes a serious drawback, which is especially obvious in the design of large array transducers. Sparse array is an effective way to solve these problems. In this paper, an improved particle swarm optimization algorithm is proposed to simulate and optimize the one-dimensional sparse array of different phased arrays, and to calculate the array pattern which can reflect the spatial resolution and contrast resolution of the imaging. A sparse array with a comprehensive acoustic performance close to the reference full array is obtained. Experimental analysis shows that the reference of particle swarm optimization algorithm can provide an effective optimization design for sparse array. Based on the improved particle swarm optimization (PSO) algorithm, the minimum redundancy array is combined to keep the sparse array with high spatial resolution and to improve the contrast resolution. The problem of poor consistency of sparse array based on particle swarm optimization is solved. The control platform of ultrasonic phased array sparse array is developed by mixed programming of MATLAB and Visual Studio 9.0. It can realize sparse control of array transducer with arbitrary aperture and arbitrary effective array element number. The optimal design and performance evaluation of sparse array with different aperture can also be realized, and the ultrasonic phased array sparse array detection system is designed based on this platform. Through the sparse array detection system, using the sparse array obtained by the two algorithms, and the corresponding aperture reference array, the different plate thickness with porosity, not fused, not welded through, slag, crack typical weld defect test blocks were detected and compared. The database of typical sparse array and weld defect is established. The defect detection experiments show that the particle swarm optimization algorithm combined with the minimum redundancy array method can improve the spatial resolution of sparse array imaging and improve the contrast resolution of detection imaging. It can provide high quality ultrasonic imaging.
【学位授予单位】：福州大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TB559

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