摘要
为了满足全聚焦阵列超声扫查实时成像、图像缺损清晰可辨等要求,建立了一种全聚焦成像(TFM)相控阵列的稀疏优化模型,利用最小冗余度阵列(MRLA)进行稀疏设计,利用遗传算法(GA)对扫查图像信噪比进行优化;将最终优化后的稀疏阵列与满阵、最小冗余阵、遗传算法优化阵列的声场波束图进行对比,并以此阵列为基础建立全聚焦扫查环境,对连续的20个点缺陷进行扫查测试。实验证明:37选16的阵列利用此模型稀疏优化后,最高旁瓣可获得4.902 8 dB的优化,稀疏率为0.27的阵列较满阵成像效率提高了58.3%,且API值为0.539 7,得到的扫查图像既可获得最小冗余下的最大信息量,又具有良好的旁瓣特性,同时阵列稀疏化,极大地提高了全聚焦扫查效率。
In order to meet the requirements of real-time imaging of total focusing array ultrasound scanning, the image defect can be clearly identified. A sparse optimization model of total focus method(TFM) phased array was established, which uses minimum redundancy linear array(MRLA) for sparse design, and genetic algorithm(GA) to optimize the SNR of scanned images. The final optimized sparse array was compared with the full array, minimum redundancy array and genetic algorithm optimized array. Based on this array, a total-focus scanning environment was established to scan and test 20 consecutive point defects. Experiments have proved that after 16 arrays selected from 37 arrays are sparsely optimized using this model, the highest sidelobe can be optimized by 4.902 8d B. The imaging efficiency of 0.27 sparse array is 58.3% higher than that of full array, and the API value is 0.539 7. The scanned image obtained can have the maximum amount of information under the minimum redundancy and good sidelobe characteristics. At the same time, the array is sparse, which greatly improves the efficiency of total focus scanning.
作者
高铁成
王昊
李聪
远桂民
GAO Tie-cheng;WANG Hao;LI Cong;YUAN Gui-min(Tianjin Key Laboratory of Optoelectronic Detection Technology and Systems,Tianjin 300387,China;School of Elec-tronic and Information Engineering,Tiangong University,Tianjin 300387,China)
出处
《天津工业大学学报》
CAS
北大核心
2022年第6期63-69,共7页
Journal of Tiangong University
基金
国家自然科学基金青年基金项目(61605144)
天津市教委科研计划项目(2018KJ213)
天津市企业科技特派员项目(18JCTPJC60100)。
关键词
全聚焦成像
相控阵
最小冗余度阵列
遗传算法
阵列稀疏
total focusing method
phased array
minimum redundancy array
genetic algorithm
array sparsity
