Two signal processing techniques for the enhancement of the flaw-to-grain echo ratio

Two signal processing techniques are developed to improve the signal-to-noise ratio in the testing of coarse-grained materials. They are: the space minimization—frequency minimization (SMFM) algorithm and the space minimization—frequency threshold (SMFT) algorithm. Experimental data for austenitic stainless steel samples are presented which show encouraging flaw detection capabilities of the two algorithms.     

Reflectivity function reconstruction using the frequency deconvolution technique

Deconvolution of ultrasonic echo signals improves resolution and quality of ultrasonic images. A frequency deconvolution algorithm depends on the Fast Fourier transform is proposed for ultrasonic data. The stability of the algorithm and the influence of the truncation effect on the deconvoluted results were investigated with respect to the duration time of reflectivity function reconstruction and the signal to noise ratio. Reliability of the separation of reconstructing the reflectivity of a biological tissue is estimated by frequency deconvolution of the echo ultrasound signals.     

Time-varying prediction filter for structural noise reduction in ultrasonic NDE

Predominant physical phenomenon in highly scattering materials is the attenuation due to dispersion. Therefore, received echo has high frequencies more severely attenuated than low frequencies and the structural noise can be modeled as a non-stationary random process. Most of the proposed techniques for enhancing the flaw visibility do not exploit the frequency dependency of the incoming flaw signal, assuming homogeneous behaviour of the insonified material. In this work, a new technique based on exploiting the non-stationary nature of the incoming UT signal is presented. Proposed technique is based on the prediction error obtained with a linear and time-varying parametric model of the noise. By this method, when the analyzed UT echo has only structural noise, the prediction error is low, however, if it contains a flaw, high prediction error occurs because a flaw is a non-predictable alteration of the material structure. Experiments with stainless steel show that this method has an excellent performance on SNR enhancement.     

Flaw characterization based on diffraction of ultrasonic waves

A method of flaw characterization based on time domain analysis of the diffracted sound field from a flaw when irradiated by short ultrasonic pulses is described. The echo formation mechanism developed by Freedman has been utilized to predict the return pulse pattern. Experimental results that are in good agreement with theoretical predictions are presented. Using a microcomputer-based scanning and testing system the feasibility of reproducing planar, straight-edged flaw shapes has been successfully demonstrated.     

Stimulated spin echo upon excitation with pseudorandom pulses

Different regimes of excitation of a stimulated spin echo by pseudorandom pulses and short coherent delta-shaped pulses are considered. Radio pulses phase-shifted by a 127-element M sequence are used as pseudorandom signals. The shape of the complex envelope of the stimulated echo is simulated in linear and nonlinear regimes with respect to the phase-shifted pulses. It is demonstrated that the excitation pulses can be described by correlation functions. Appropriate conditions are determined under which the amplitude of the stimulated echo can be greater than the amplitude corresponding to the classical algorithm used for exciting a stimulated echo by three delta-shaped pulses. The results obtained can be used for analyzing the formation of a stimulated photon echo.     

超声探头的响应特性及暂态回波模型

建立检测系统的数学模型,可以更好地理解超声检测的物理本质。分析了超声波从产生、介质中传播、缺陷耦合以及接收的全过程,将缺陷回波表示为探头响应函数与缺陷响应的时域卷积。利用空间脉冲响应和基尔霍夫近似建立了超声波与平面型缺陷的耦合模型,用大平面试块底面回波和大平面响应进行反卷积求得了探头的响应函数,并详细分析了探头在不同偏置位置时不同大小缺陷响应的特点,发现缺陷回波由直达回波和边缘回波组成,直达回波和边缘回波极性相反,且直达回波的幅值远远大于边缘回波。      

声表面波检测铝板表面微缺陷深度实验研究

为了探究声表面波与不同深度微裂纹缺陷相互作用的关系,将脉冲激光作用于一系列不同缺陷的试件铝板上进行线光源激励,激发激光超声波。用超声传感器接收在铝板中传播的激光超声信号,通过数字荧光示波器采集激光超声在铝板中的传播数据。对采集到的反射波数据进行分离谱分离过程得到的铝板中激光超声的时域分布和透射波数据进行频域分析。实验发现:缺陷深度影响着反射回波两峰值特征点到达时间差,两者之间近似线性关系,也影响着透射波的截止频率且二者呈现递减关系。     

Sparse signal representation and its applications in ultrasonic NDE

Many sparse signal representation (SSR) algorithms have been developed in the past decade. The advantages of SSR such as compact representations and super resolution lead to the state of the art performance of SSR for processing ultrasonic non-destructive evaluation (NDE) signals. Choosing a suitable SSR algorithm and designing an appropriate overcomplete dictionary is a key for success. After a brief review of sparse signal representation methods and the design of overcomplete dictionaries, this paper addresses the recent accomplishments of SSR for processing ultrasonic NDE signals. The advantages and limitations of SSR algorithms and various overcomplete dictionaries widely-used in ultrasonic NDE applications are explored in depth. Their performance improvement compared to conventional signal processing methods in many applications such as ultrasonic flaw detection and noise suppression, echo separation and echo estimation, and ultrasonic imaging is investigated. The challenging issues met in practical ultrasonic NDE applications for example the design of a good dictionary are discussed. Representative experimental results are presented for demonstration.     

超声波流速测量的多普勒频移提取方法研究

为了提高超声波多普勒法测量复杂流体流量的精度,针对流体的超声回波频率的复杂性,本文研究多普勒流速测量中的频偏提取方法。以傅里叶分析为理论基础,设计了硬件电路并获得代表回波平均频率的信号,然后以该信号作为输入,以数字鉴频法获得回波多普勒频移。基于该方法设计了一种超声多普勒流量测量系统,实验结果显示:油水混合流体流量的测量误差在3%以内,从而证实了此频偏提取方法的有效性。     

啸叫快速抑制的助听器回声抵消算法

针对助听器回声路径快速变化下易产生啸叫的问题,本文提出一种变步长标准最小均方差-陷波器(Variable Step Normalized least mean square-Notch Filter,VSN-NF)算法。在回声路径相对稳定时,提出一种基于状态分类的变步长标准最小均方差算法来估计回声信号。算法根据滤波器系数能量的长时平均值和短时平均值,将滤波器当前状态分为收敛态、过渡态与稳态,并根据不同状态选择不同的步长。在路径突然变化并产生啸叫时,算法通过关闭变步长NLMS算法来稳定啸叫频点,然后基于ZoomFFT算法动态生成陷波器来进行啸叫抑制;当啸叫抑制后,再开启变步长NLMS进行回声估计。针对易产生多频点啸叫的回声路径,VSN-NF算法还引入不同频带的两个陷波器来进行双频点啸叫抑制。同其它助听器回声抵消算法的对比实验显示,VSN-NF算法的回波抵消性能最好,尤其具有快速啸叫抑制能力。此外,算法生成的语音质量较高,实时性能好,适合于像助听器类的低功耗、小体积产品。      

Detecting small flaws near the interface in pulse-echo

Flaw detection near the interface surface is a common problem in many pulse-echo NDT applications due to interference with the interface echo, orders of magnitude above the flaw echoes. Several digital signal processing techniques like deconvolution, Hilbert transform and cepstrum analysis have been proposed to improve axial resolution. However, they require strict linearity, which takes a large portion of the system dynamic range just to fit the interface echo, thus reducing the dynamic range available for flaw detection. This work presents a new alternative based on the time-domain phase analysis of the received signals. Differently from conventional approaches, it works quite well with saturated signals resulting when a high gain is applied to detect small flaws. These can be detected in a range of a fraction of one wavelength from the interface surface, even using narrow-band transducers, as it has been experimentally verified. The method can be easily hardware implemented for real-time processing.     

Speckle reduction by energy time-frequency filtering

Structural noise is a very important limitation to the visibility of flaw echoes in ultrasonic testing and evaluation of highly scattering materials. In order to enhance the signal-to-noise ratio, different algorithms have been developed. One of these techniques is based on filtering the spectrum low band of the received echo to obtain a significant improvement of the defect visibility. Based on this idea, in this work a new time-frequency technique is presented. In this method, block-processing autoregressive techniques are used to estimate the instantaneous center frequency of the traveling wave. From this information, a time-frequency filter is designed tuned at half the estimated instantaneous center frequency. Experimental results and the comparison with the non-time-frequency filtering technique are also included, showing that the proposed method has an excellent performance on SNR enhancement.     

Normalized split-spectrum: a detection approach

We consider in this paper the problem of automatic detection of ultrasonic echo pulses in a grain noise background. We start by assuming a reference model for grain noise: multivariate correlated Gaussian model having, in general, different variances under every hypothesis. We show that, even for this simple model, there is not practical optimum solution, except if the variances are equal under every hypothesis and the echo pulse satisfies a spectral constraint. Then we consider split-spectrum (SS) suboptimum solutions. Firstly, SS algorithms are formulated following an algebraic approach which is appropriate in an automatic detection framework. Popular minimization and polarity thresholding algorithms are considered under this framework. Then a new detector called normalized SS (NSS) is proposed. The underlying idea is to actually exploit the tuning frequency sensitivity (i.e., variability of the output magnitudes from one SS channel to another), making this measurement independent of the absolute magnitudes. Different experiments with simulated and real data show evidences of the interest of the new method in an automatic detection framework. Derivations of the formulas for fitting the probability of false alarm in every detector are included in the paper.     

A practical ultrasound axicon for non-destructive testing

A practical water-coupled ultrasound axicon has been developed, which is realized by a combination of an annular PZT and a conical plexiglass wedge bonded to it. The acoustic beam from the PZT is refracted by the wedge and focused over a certain range in the axial direction. Two kinds of axicon are prepared for flaw examination of metals or ceramics. Suppression of the surface echo and sidelobes is discussed. Some examples which show the abilities of the axicons are also presented.     

Ultrasonic flaw detection in NDE of highly scattering materials using wavelet and Wigner-Ville transform processing

In ultrasonic non-destructive evaluation of highly scattering materials the backscattering noise may attain peak values greater than the searched flaw pulse and the mean value of noise spectrum is very similar to the searched echo spectrum. Several specific methods have been proposed for the reduction of this type of noise, but the comparison of the performance of different methods is still an open problem. In this paper, we make a comparison among some methods based on simultaneous representations in time and frequency/scale domains of the ultrasonic traces. Synthetic and experimental traces are de-noised using a discrete wavelet processor with decomposition level-dependent threshold selection and a method that combines Wigner-Ville transform and filtering in the time-frequency domain. The results are comparatively evaluated in terms of signal to noise ratio and probability of detection.     

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。     

德拜色散媒质的三维时域电磁逆散射技术

生物组织、土壤、水等媒质的电特性是频率相关的(称为色散媒质),常利用单极德拜(Debye)模型描述.为重建这一类媒质的色散特性,基于泛函分析和变分法,提出一种三维(3-D)时域电磁(EM)逆散射技术,主要流程为:①根据最小二乘准则,转化逆散射问题为约束最小化问题;②应用罚函数法,转化约束最小化问题为无约束最小化问题;③通过变分计算,解析导出梯度(Fréchet导数)表达式;④利用梯度法求解.此外,引入一阶吉洪诺夫(Tikhonov)正则化以应对逆问题的病态特性和噪声影响.数值应用中,将提出的目的 应用到一个简单的三维癌变乳房模型,借助PRP共轭梯度(CG)算法和时域有限差分(FDTD)法,仿真结果初步证实本文目的 的可行性、有效性和鲁棒性.     

二维有耗色散介质的时域逆散射方法

为了重建二维有耗色散介质的电参数分布,基于Debye模型,应用泛函分析和变分法,提出一种时域逆散射新方法.该方法首先以最小二乘准则构造目标函数,将逆问题表示为约束最小化问题,接着应用罚函数法转化为无约束最小化问题,然后基于变分计算导出闭式的Lagrange函数关于特征参数的Fréchet导数,最后借助梯度算法和时域有限差分法迭代反演Debye模型参数.为了对抗噪声污染和逆问题的病态特性,采用了一阶Tikhonov正则化方法.数值应用中,利用Polak-Ribière-Polyak非线性共轭梯度法,对二维乳     

Ultrasonic flaw detection using radial basis function networks (RBFNs)

Ultrasonic flaw detection has been studied many times in the literature. Schemes based on thresholding after a previous matched filter use to be the best solution, but results obtained with this method are only satisfactory when scattering and attenuation are not considered. In this paper, we propose an alternative solution to thresholding detection method. We deal with the usage of different flaw detection methods comparing them with the proposed one. The experiment tries to determinate whether a given ultrasonic signal contains a flaw echo or not. Starting with a set of 24,000 patterns with 750 samples each one, two subsets are defined for the experiments. The first one, the training set, is used to obtain the detection parameters of the different methods, and the second one is used to test the performance of them. The proposed method is based on radial basis functions networks, one of the most powerful neural network techniques. This signal processing technique tries to find the optimal decision criterion. Comparing this method with thresholding based ones, an improvement over 25-30% is obtained, depending on the probability of false alarm. So our new method is a good alternative to flaw detection problem.