A Pulse Compression Technique for Improving the Temporal Resolution of Ultrasonic Testing

Abstract

It is difficult to interpret ultrasonic signals when the echoes that are reflected from the various target features overlap. In this paper, a pulse compression technique based on a combination of Wiener filtering and autoregressive (AR) spectral extrapolation is used to process ultrasonic signals to improve their temporal resolution. The influence of the AR order and the width of the frequency window in AR spectral extrapolation are discussed in detail, and optimal parameters are obtained. The technique is then applied to measure the size of the defects in a plate and discern two adjacent defects in a block using a phased array. It is shown that the widths of the defects in the plate were measured accurately and the two adjacent defects were distinguished well by the proposed technique.

A nonlinear ultrasonic modulation approach for the detection and localisation of contact defects

“…In addition, the array elements can be excited in a specific order and according to pre-set delay laws to achieve steering or focusing of ultrasonic wave beams for improved localisation and sizing of damage [10,11]. Various studies on linear phased array methods demonstrated effective identification of contact flaws at a single interface in metallic or composite parts [12][13][14][15][16], but only few of them detected multiple defect interfaces through the material thickness [17,18]. This can be very challenging, depending on the mechanical contact between the surfaces at each damaged plane.…”

Improving Depth Resolution of Ultrasonic Phased Array Imaging to Inspect Aerospace Composite Structures

“…However, when the inspected material is not homogeneous, conventional ultrasonic imaging techniques are not effective, and we need to employ signal processing techniques to improve the temporal resolution of the ultrasonic signal [22]. Some studies suggest to use a combination of Wiener filtering and autoregressive (AR) spectral extrapolation to improve signal-to-noise ratio (SNR) and temporal (axial) resolution of the ultrasonic inspection [23][24][25]. They use Wiener filter for deconvolution, then, using a part of the deconvolved spectrum with high SNR, an AR model of the process is built.…”

“…Next, the rest of the spectrum is extrapolated by the obtained AR model. However, performance of this method strongly depends on the width of the frequency window and order of the AR filter [23,25].…”

Resolution Enhancement of Total Focusing Imaging Combining with Autoregressive Spectral Extrapolation

“…0 前言 超声成像分辨力是指在一定条件下区分两个相 邻反射体的能力 [1] 。相控阵超声检测技术通过灵活 控制声束的时空特性，声束聚焦区域可分辨相距 2  ～3  (  为超声波长)缺陷 [2][3][4][5] 。基于全矩阵数据 的全聚焦方法(Total focusing method，TFM)能够实 现待检测区域逐点聚焦，成像分辨力具有空间一致 性 [5][6][7] ，如采用 64 阵元相控阵探头实施成像，可分 辨相距约1 缺陷 [8] 。当缺陷间距进一步缩小时，受 超声波脉冲宽度影响， 相邻缺陷回波信号发生混叠， 成像后无法准确辨别缺陷数量和相对位置。 在提高 TFM 成像分辨力方面， 国内外学者开展 了相关研究。ZHOU 等 [9] 对钢中横向间隔1.7 点缺 陷实施 TFM 成像时， 将阵元指向性函数与延迟后的 回波信号加权相乘，改善了近场成像质量，提高了 成像分辨力。ZHANG 等 [10] 对铝中相距1 点缺陷进 行 TFM 成像， 并利用相位相干性构建表征相位分布 的相干因子， 降低重建图像中相位散乱的噪声幅值， 成像分辨力提高约 0.2 。 对全矩阵数据中各 A 扫描 信号进行脉冲压缩处理， 进而实施 TFM 成像也可提 高成像分辨力。焦敬品等 [11][12] 将维纳滤波和自回归 谱外推方法相结合，以试块底面回波为参考信号对 全矩阵数据进行解卷积处理，取自回归阶数 20，频 谱最大幅值下降 6 dB 对应频域窗口为有效频带， 对 解卷积后的全矩阵数据进行自回归谱外推处理， TFM 成像后分离了铝中两个中心间距约1.1 、 直径 0.7 圆孔。自回归谱外推方法能够拓宽有效频带， 压缩时域脉冲宽度，提高信号时间分辨力，但是有 效频带及自回归阶数的选择对信号处理效果存在较 大影响 [13][14][15] [16][17][18] [11,13] 。借鉴相关文献研究工作 [12][13] [11] [13] ，而高自 回归阶数会造成过拟合现象 [19] ，出现虚假信号峰。…”