Theoretical calculation on distance amplitude curve of ultrasonic phased array

Ultrasonic phased array technology has been gradually applied to industrial nondestructive testing in recent years. The sound field of the focusing and steering beam radiating from the phased array is a nonuniform distribution in the spatial position so that the echo signals of same size defects will be changed according to defect positions. To analyze these defects quantitatively, a model-based method for the distance amplitude correction is proposed for the phased array system. Based on a non-paraxial multi-Gaussian beam model and flaw scattering models, an ultrasonic measurement model for the phased array system is proposed to calculate the echo signals from side-drilled holes at different positions. Furthermore, these model-based distance amplitude curves are compared with the traditional experimental results for different focusing and steering beams. The two methods have a good agreement.     

基于分布式超声无损检测方法的零件内部缺陷检测

超声检测广泛应用于工业检测,比如超声相控阵检测法和超声A扫应用于零件内部缺陷检测。然而,这些方法可以检测出缺陷位置却很难精确地检测缺陷尺寸,缺陷定量成了急需解决并且很有意义的问题。本文提出了一种分布式超声无损检测方法,将超声探头均匀布置在检测表面,每一个超声探头可以同时发射和接收超声信号,通过对接收到的信号进行处理来重构缺陷轮廓。基于分布式超声无损检测方法,重构零件的人造缺陷并建立相应的声学仿真模型。通过多项式拟合法和聚类法分别处理实验和仿真所获得的数据并重构缺陷轮廓。实验结果和仿真结果显示重构的椭圆形缺陷和正方形缺陷具有一定的精度。结果表明分布式超声无损检测方法有潜在的应用价值和理论意义。     

基于空耦超声Lamb波的金属板状结构内部缺陷检测方法

针对接触式超声检测方法在金属板结构内部缺陷实际工程检测中存在的环境要求高、效率低、操作难度高等问题,提出了空耦超声Lamb波检测方法,该方法能更好地适应现场应用环境,提高检测效率,减少传感器数量。通过有限元仿真和实验分析比较了空耦超声检测与接触式超声检测两种方法接收到的信号和成像效果。结果表明:有限元仿真和实验中,空耦超声检测方法对缺陷位置的定位误差分别为2 mm和3.6 mm,接触式检测方法对缺陷位置的定位误差分别为2 mm和11.3 mm,空耦检测具有较高的定位精度;单侧激励条件下,适合采用A0模态Lamb波对板内缺陷进行检测;空耦超声检测可以通过调整信号接收角度接收单一模态Lamb波,避免伪像产生。该方法为后续金属板状结构内部缺陷的空耦超声检测提供参考。     

High-order spectra-based deconvolution of ultrasonic NDT signals for defect identification

In ultrasonic nondestructive testing (NDT) of materials, pulse-echo measurements are masked by the characteristics of the measuring instruments, the propagation paths taken by the ultrasonic pulses, and noise. This measured pulse-echo signal is modeled by the convolution of the defect impulse response and the measurement system response, added to noise. The deconvolution operation, therefore, seeks to undo the effect of the convolution and extract the defect impulse response which is essential for defect identification. In this contribution, we show that the defect ultrasonic model can be formulated in the higher-order-spectra (HOS) domain in which the processing is more suitable to unravel the effect of the measurement system and the additive Gaussian noise. In addition, a new technique is developed to faithfully recover the impulse response signal from its HOS. Synthesized ultrasonic signals as well as real signals obtained from artificial defects are used to show that the proposed technique is superior to conventional second-order statistics-based deconvolution techniques commonly used in NDT.     

Fractal properties of acoustic location responses

The fractal dimension of reflected ultrasonic signals in steel slabs with wittingly introduced defects is analyzed. The dependence of the fractal dimension on the defect size is demonstrated. The resolving power of a method used to estimate the fractal dimension of acoustic location responses and its applicability in practical flaw detection are considered.     

特殊几何构件超声衍射时差法技术有限元模拟

衍射时差法(Time of flight diffraction,TOFD)技术是一种能够探测和精确测量缺陷尺寸的新型超声无损检测方法,针对该检测方法具有缺陷检出率高、缺陷定位定量精度高等优点。本文采用商业有限元软件ABAQUS,对汽包筒体与球形封头不等厚对接和超高压水晶釜两种特殊几何构件进行了超声TOFD技术的二维数值模拟研究,分析了超声波在这两种构件中的传播特性和规律。经分析从构件表面不同位置接收到的波型,当构件中存在损伤时,通过接收损伤所引起的衍射波,可判断构件中是否存在缺陷。模拟结果表明能够将超声TOFD技术应用于这两种特殊结构的压力容器构件,可扩大超声TOFD技术的应用范围。     

基于小波包变换的复合材料超声波检测信号特征提取

本文以碳纤维复合材料常见缺陷分层、孔隙、疏松的超声波检测缺陷信号为研究对象，对超声波检测信号进行小波包变换，提取包含信号绝大部分能量的近似系数波形特征及细节系数的统计量作为样本的特征值。应用BP神经网络分类器进行分类识别验证，取得较好的识别效果。该方法能以较小的特征维数表征原始信号特点。     

基于激光多普勒频移的钢轨缺陷监测

针对现阶段我国铁路上应用的探伤设备只能在天窗时间进行人工巡检,无法在线监测的问题,提出一种基于超声导波的激光多普勒频移法钢轨内部缺陷监测方法。首先,引入环境温度作为变量改进了半解析有限元方法,并应用该方法获得了我国无缝线路CHN60钢轨在特定温度下的频散曲线。通过分析振型并结合激励响应算法确定了适于检测缺陷的模态及其激励方式,从而激励该超声导波模态使其在钢轨中传播。然后,应用半反半透玻璃镜将激光分为参考光和测量光,测量光通过Bragg Cell进行频偏照射钢轨表面,通过反射光产生的多普勒频移与参考光干涉得到光强度变化曲线,经过信号处理及标定测得钢轨内部缺陷的回波速度信号,再经过数字化处理和计算得到缺陷的位置。最后,在北京环形铁路试验基地进行了现场实验,以钢轨接地孔模拟钢轨内部核伤,得到缺陷定位误差均小于0. 5 m,验证了该方法的可行性。使用激光多普勒频移方法检测导波信号从而定位缺陷的方法可以有效避免由于换能器接触性测量而产生的误差。该方法在不影响列车的正常运营的同时,实现了全天候无间断的在线监测,提高了检测效率。     

Non-linear filtering of ultrasonic signals using neural networks

Structure noise from inhomogeneous micro-structures makes the detection of flaws present in highly scattering materials difficult. Several techniques have been applied to improve the signal-to-noise ratio (SNR) in order to make flaw detection easier. Linear filtering does not provide good results because both structure noise and flaw signal concentrate energy in the same frequency band. Non-linear filtering can be used to reduce the structure noise of ultrasonic signals. Therefore, neural networks are applied in this work for this purpose. In order to use neural networks for non-linear filtering, dynamic structures must be applied. The easiest way to implement a neural network with the capability of processing temporal patterns is to consider them spatial ones, applying the signal into a tapped delay line of finite extension, that is the input of a static neural network (for example, a multi-layer perceptron). In this work, a dynamic neural network has been built to filter ultrasonic signals with structure noise, and has been trained with the real-time back-propagation algorithm, using as inputs 3000 synthetic ultrasonic signals of 896 samples each. Target signals for training are the same as the ones used as inputs but without noise. The neural network is trained in order to generate as output the target signal when the noisy input one is applied. For testing the performance of the non-linear filter, a new set of 500 noisy signals has been used. The SNR improvement is about 6 dB average. The results show that this non-linear filtering method is quite useful as pre-processing stage in flaw detection systems.     

Weak guided wave signal detection using period jump of Duffing system

A potential risk in ultrasonic guided wave testing is that weak echo signals from small defects may be submerged in noisy signals, which will cause missed detection. To overcome this shortcoming, a weak guided wave signal detection method based on period jump of the Duffing system is proposed in this paper. The critical state of the system period jump can be obtained by analyzing the bifurcation characteristics of the Duffing system with the variation of the driving force amplitude. A weak ultrasonic guided wave signal with the same frequency as the driving force is added to the driving force. This is equivalent to changing the driving force amplitude, which causes the period state to jump. Consequently, the weak guided wave signals can be identified based on the period jumps. The increase or decrease in the driving force amplitude due to the interference of the guided wave signal depends on the phase difference between the intercepted signal and the periodic driving force. The conditions for increasing and decreasing the driving force amplitude are out of phase with each other.They have an approximate phase difference of π within the same period. Two detection models for small-scale periodic states(SPS) and large-scale periodic states(LPS) are constructed, and the effectiveness of the models in identifying the guided wave signal is verified numerically and experimentally. The anti-noise interference capabilities of the two models are also compared.The results show that the SPS detection model provides unique results and a strong anti-noise ability, and effectively improves the sensitivity of small defect detection using ultrasonic guided waves.     

基于幅度调制的非线性超声相控阵成像方法*

超声相控阵是超声检测领域常用的材料缺陷定位和成像技术,可便捷快速地对裂纹、孔洞等缺陷进行成像。但是,传统超声相控阵方法对较小缺陷如闭合裂纹不太敏感。非线性超声信号因对材料性能退化以及微小缺陷敏感而广受关注。本文针对疲劳闭合裂纹检测,提出一种基于幅度调制的非线性超声相控阵成像方法,通过测量物理聚焦和虚拟聚焦两种聚焦模式下超声扩散场中的声能差,并将其作为非线性参量,实现疲劳裂纹闭合部分的定位成像和定量表征。将该法应用于7075铝合金试样疲劳裂纹的实验测量,并研究了扩散场信号延迟时间对非线性超声相控阵成像结果的影响。结果表明：相较于传统超声相控阵全聚焦法,基于幅度调制的非线性超声相控阵成像方法能够更准确地定位和成像疲劳裂纹闭合部分;延迟时间的选择对疲劳裂纹长度的表征精度影响较大,本文研究了该延迟时间的选择方法并实现了检测结果的优化。     

卷积神经网络的缺陷类型识别分析

该文提出一种基于卷积神经网络直接对阵列超声检测原始信号进行缺陷类型识别的方法,该方法无需对超声回波原始信号进行特征提取.文章研究对比了不同卷积神经网络及其优化的识别性能.首先采用超声相控阵系统对不同试块上的平底孔、球底孔、通孔三种缺陷进行超声检测,然后利用LeNet5、VGG16和ResNet三种卷积神经网络对一维和二...     

基于多模态信号的金属材料缺陷无损检测方法

金属材料缺陷检测对于经济发展具有重要意义.针对现有无损检测技术信号模态单一、检测范围有限等不足,提出了一种基于多模态信号的金属材料缺陷无损检测方法.该方法以光声无损检测方法为主体,首先利用有限元方法分析了缺陷对激光能量吸收量和光声表面波传播的影响,提出了基于激光吸收量和光声表面波的缺陷检测方法;然后搭建了多模态信号检测平台,采集了缺陷的光学、光声和超声三种模态的信号,检测出了裂纹的宽度和分布信息,以及深度和在内部的延伸状况.研究结果表明,本文提出的基于金属材料多模态信号的无损检测方法能够准确、全面地检测出金属材料的杂质和裂纹的尺寸信息,弥补了现有无损检测方法在检测范围上的不足,为缺陷定量检测和全面诊断提供了一个新的思路.     

A new technique for the identification of ultrasonic flaw signals using deconvolution

The identification of ultrasonic flaw signals is a difficult task in the angle beam ultrasonic testing of welded joints due to the presence of non-relevant signals from the geometric reflectors such as weld-roots and counter-bores. This paper describes a new approach to identify ultrasonic flaw signals in such a problematic situation. A similarity function is defined as the deconvolution of a target signal by a reference signal. The similarity functions for the same type of flaws/references are symmetric bandlimited impulse-like patterns with larger amplitudes while those for different types of flaws/references are asymmetrical broad patterns with relatively smaller amplitudes. Therefore, ultrasonic signals could be identified by the pattern of the similarity function. In the initial experiments, the proposed technique showed great potential for identifying ultrasonic flaw signals in the inspection of weld joints.     

用于铝板缺陷无损检测的激光超声有限元模拟研究

激光超声技术能够在材料表面形成超声波，是实现材料缺陷无损检测的重要环节。借助Abaqus有限元分析工具，基于激光超声热弹机制建立了轴对称铝板的表面缺陷模型，模拟了激光激发产生的表面波在材料中的传播特性及其与铝板缺陷的相互作用过程。数值模拟实验表明，铝板表面缺陷的分布深度值越大，反射波越强，并且当缺陷深度达到一定程度时，反射波的幅值趋于稳定；但缺陷的分布宽度对于反射波的影响则十分有限。所得结论为基于激光超声的材料缺陷的定量检测及识别提供有效的理论依据。     

Wavelet based noise suppression technique and its application to ultrasonic flaw detection

The noise suppression techniques with wavelet transform (WT) are widely used in non-destructive testing and evaluation (NDT&E), especially in ultrasonics. Complete reconstruction theory with hard or soft thresholds, reconstruction technique based on the singularities of noise and signal, matched filter with an impulse response, and optimal frequency-to-bandwidth ratio of wavelet technique have all been used to analyze ultrasonic signals for noise suppression. But a more simple and effective technique has been pursued for decades. This paper develops a new technique using WT for the right purpose. In this work, WT is treated as a band-pass filter whose central frequency and frequency bandwidth (CF&FB) are determined by the spectra distribution of an ultrasonic signal captured from real testing situation. For the purpose of matching their CF&FB well, a technique for evaluating the optimal scale of a daughter wavelet is carried out too. By acting this daughter wavelet as a band-pass filter, we can obtain excellent de-noising results, even when the signal to noise ratio (SNR) is below -18 dB. The performance of the technique has been done by ultrasonic signals with computer generated white noises. Finally, the experimental verification is performed on a pipeline specimen with man-made small flaws with good results obtained. The results show that the technique is more suitable for processing heavy noised ultrasonic signals, and it can also be used in automatic flaw detection.     

基于LabVIEW的时间反转超声检测系统的开发

时间反转技术在超声无损检测中的应用非常广泛,它可以忽略介质的非均匀性及初始信号源的位置,能够在时间和空间上聚焦超声波,实现对介质缺陷的聚焦检测。基于LabVIEW图形化编程软件,结合计算机、信号发生器、示波器、超声换能器、GPIB等的使用,对超声检测系统实验平台进行了构建,实现了超声信号的发射、接收以及时间反转一系列的信号处理过程。系统工作过程中,采用了三种不同的时间反转技术：经典时间反转技术(Time Reversal：TR)、反向滤波技术(Inverse Filter：IF)及1位处理技术(1Bit Processing),来实现信号的聚焦。实验验证该系统可以有效的实现时间反转超声检测过程中对信号的激励、接收、处理和存储等功能,有良好的精确性和适用性。     

跑道线圈换能器在铁路重载货车探伤中的应用*

针对在线车轮超声探伤系统的工程应用,研究了跑道线圈电磁超声换能器由洛伦兹力换能机制在钢中产生的辐射声场。根据外磁场和线圈配置,将表面力源近似为非均匀的水平剪切力源,数值计算得到了此力源的辐射声场指向性图,并与实验结果进行比对,结果表明辐射的水平偏振横波具有中间强两侧弱的指向性,对理解跑道形电磁线圈超声换能器的辐射声场和在重载货车车轮辋裂缺陷探伤中的工程应用具有一定的指导意义。     

虚拟式声显微镜及应用技术研究

本文描述一台虚拟式扫描声显微镜及应用技术研究，它的硬件特别简单，仅由一台带有超高速A/D卡和快脉冲收发卡的PC机和机械扫描系统组成，主要的功能均由软件完成，脉冲收发卡仅包括脉冲产生和高频放大器，A/D卡采用PCI总线，采样率1GSPS，数据传输率100MB/s，系统能采集并实时显示频率达百兆的未检波回波信号，采修订本以的信号经软件处理，可在屏幕上实时显示样品的A、B、C型幅度像或相位像，仪器利用信号处理技术提高信号的信噪比；进行特征提取，识别，该仪器在材料识别，电子、光电子器件和焊接质量检测等方面功能较强，具有广阔的开发应用前景。     

微小缺陷的非线性超声检测及其成像技术

采用通用超声检测设备并结合高通滤波技术获取了非线性超声的高次谐波信号,并将其用于薄板点焊焊核的微小缺陷检测及焊核的超声C扫描成像中。较之传统超声检测方法,采用非线性高次谐波检测薄板点焊焊核缺陷具有更高的时域分辨率及缺陷敏感度,能够更加准确的确定内部缺陷的位置及尺寸。此外,本研究还采用非线性高次谐波对薄板焊核进行超声成像分析,获得了清晰准确的焊核结构图像。非线性超声检测技术具有更高的检测效力,能够显著拓展检测系统的检测能力。