环形光纤声发射传感器的相位调制特性研究

提出了一种基于光纤Sagnac干涉仪的环形传感器，用于固体表面传播的超声波的检测.这种传感器的特点是能够精确地检测由固体表面传播的超声波产生的微弱振动.当超声波信号通过光纤传感器的两个臂到达探测器时，干涉仪的输出光强度受到了超声信号的调制.通过检测干涉仪的输出光强度并利用Fourier变换，测得了超声信号的振幅和频率.而且对传感系统的位相调制特性进行了仿真，并对实验结果进行了分析，结果表明该系统可用于固体表面传播的超声波频率特征的识别.     

时域有限差分法的混凝土超声波损伤分析*

混凝土质量的好坏直接影响到建筑物的安全性,选用方便实用的方法对其内部裂纹进行检测具有显著意义。该文首先借助时域有限差分法,建立了混凝土声场数学模型。之后对不同内部缺陷尺寸的混凝土模型进行了超声波数值模拟,分别从时域和频域对接收到的超声信号进行了分析。结果发现,当内部存在缺陷时,接收信号时域幅值明显变小,接收信号的幅值与缺陷尺寸大小呈指数关系,且接收信号传播时间与缺陷宽度呈线性关系。最后以初次到达信号的频域能量为特征指标,得出其与混凝土内部开裂缺陷尺寸呈指数关系。该方法为混凝土超声无损检测建立合适的数学模型提供了参考。     

多胶接缺陷太赫兹检测信号的PSO-BP神经网络识别

采用太赫兹时域光谱无损检测技术对多胶接结构耐高温复合材料缺陷进行检测。为了识别同一位置上、下层同时存在脱粘缺陷,分析无缺陷区域、上层脱粘区域、下层脱粘区域的太赫兹信号波形,以特征峰峰度、偏度、最小值、峰谷值、波形因子以及信号幅值绝对平均值为特征,作为BP神经网络的输入。并通过粒子群算法优化BP神经网络的初始权重和阈值,解决了BP神经网络易陷入局部最优的问题。粒子群算法优化后的BP神经网络可实现上层100μm和下层100μm脱粘缺陷的识别,准确率达到90.71%和86.92%。     

超声波检测钢和铝中的缺陷特征

本文利用欧能达-3600型号超声波探伤仪研究钢与铝这两种金属材料中典型的缺陷伤口的超声波波形;通过对曲面反射型缺陷的超声检测波形以及超声动态波形的特征进行定性分析,研究材料中实际的气泡、缩孔等典型曲面反射型缺陷的反射脉冲式超声波波形的特征。研究结果表明:材料中气泡、缩孔等曲面反射型缺陷,其超声检测波形的特征非常相似;但是由于缺陷界面的声阻抗等声场特征参量的不同,会导致检测得到的缺陷波形会有一些细微的差别。     

应用混频超声检测微小缺陷

高端飞行器的可靠性往往受限于其发动机内部盘、板等构的结构强度和使用寿命,因此对这类部件的无损检测在制造业上具有巨大需求。超声检测作为一种应用广泛、高效、环保的检测方法,常常被应用于这类构件的检测中。但是,大厚度盘、板类构件内的微小缺陷反射能力弱,常规超声脉冲反射法无法进行有效检测。为实现大厚度盘、板类构件内部微小缺陷的识别和定位,采用共线异侧纵波混频法,通过和差频信号特征识别微小缺陷;研究缺陷埋深变化对混频效果的影响,通过测量和差频信号幅值变化,实现微小缺陷的深度定位。结果表明：该方法可有效识别7075铝合金中埋深80mm的φ0.2mm横孔微缺陷,且可实现微小缺陷的深度定位。     

虫蛀玉米种子的空气耦合超声波检测

提出了一种基于空气耦合超声波技术的玉米种子虫蛀孔洞颗粒和完好颗粒分类识别方法·首先根据玉米颗粒的弹性模量、泊松比和密度等物理量计算出了玉米颗粒的声速,并根据检测精度需求设定了激励信号频率。然后采用MATLAB对采集的两类种子超声波信号数据进行分析处理,并分析了种子厚度和摆放方位对超声波响应特征的影响。最后建立了K近邻(KNN)、簇类独立软模式法(SIMCA)、Fisher线性判别(LDA)和决策树(DT)识别模型,并对模型性能进行了测试.结果表明;种子孔洞深度、胚部厚度和正反面方位不同,即超声波在种子表面的反射程度不同、在种子中传播声程不同,则起声波信号衰减程度不同,导致接收到信号的幅值不同,且样本点在主成分分析(PCA)特征空间的分布也不同。4种识别模型均可以实现对两类玉米的分类识别,其中KNN模型性能最佳,其对虫蛀孔洞颗粒和完好颗粒的正确识别率分别为98%100%,误差带为2%,0。此结果说明采用空气耦合超声波技术可以实现对玉米种子虫蛀孔洞颗粒的检测。      

涡流检测的数值模拟与缺陷定量分析

随着涡流检测技术的不断发展，不仅要求准确检测出缺陷，且还需对缺陷进行定量、定性评价。涡流检测中阻抗信号变化是进行缺陷检测和定量分析的依据：测量或计算缺陷的阻抗信号，称为涡流检测的正向问题；从阻抗信号推断出缺陷的定量定性特征，则是逆向问题。借助于有限元模拟方法，对涡流检测时的正向问题进行了求解计算；利用傅里叶变换和神经网络方法，对涡流检测时的逆向问题进行了分析。     

水平连铸圆钢超声检测结果的信号处理

水平连铸圆钢为多晶种的不均匀粗晶材料，当采用超声波对其进行检测时，将产生较强的组织散射噪声，从而使得对缺陷回波的判断与评价无法进行本文采用分离频谱的方法对原始检测信号进行处理，再用截止地对缺陷回波进行恢复运算。实验结果本文所采用的方法能较为有效地消除原始检测信号中的组织噪声，从而提高超声检测的信噪比。     

基于分布式激光超声的带筋构件R区缺陷检测方法

针对带筋构件R区多类型缺陷的快速检测和精确识别等难题，提出基于分布式激光超声的带筋构件R区缺陷检测和分类识别方法。通过建立有限元模型研究了激光超声在带筋构件中的传播规律及其与R区表面裂纹、近表面气孔等缺陷的相互作用机理，进而设计制作了含典型人工缺陷的6061铝合金带筋构件试样，开展激光超声检测实验。实验获得的缺陷时域信号与B-scan特征图像及仿真结果一致，基于反射与衍射原理实现了对带筋构件R区缺陷定位与定量检测，从而验证了所提分布式激光超声检测方法的可行性，为带筋构件制造缺陷的快速检测和分类识别提供了新思路。     

滚动轴承声信号特征提取和诊断试验研究

为解决振动检测方法不能有效识别低速旋转机械滚动轴承故障问题,利用声发射检测方法,建立了滚动轴承低速声发射信号采集试验装置,对模拟人工缺陷滚动轴承声发射信号进行了采集,进而对滚动轴承声发射信号进行总体平均经验模式分解,结合能量矩及相关系数法综合判断分解后各模态分量的真伪,据此提取出特征信号并做出其局部Hilbert边际谱,最后对滚动轴承各种故障模式进行诊断。试验结果表明该诊断方法能准确识别滚动轴承声发射信号故障频率,依据特征频率及幅值大小可对低速滚动轴承故障进行有效诊断。     

超声非线性效应表征的动态小波指纹分析方法

针对结构早期损伤超声非线性检测中损伤表征问题,发展了一种基于动态小波指纹的超声信号分析方法,从超声信号的动态小波指纹分布中提取出一种可用于结构早期损伤表征的超声非线性特征参数。研究了小波基函数及分析尺度对超声非线性效应提取效果的影响,优选出对结构早期损伤敏感的小波基函数以及尺度范围。将提出的动态小波指纹分析方法应用于二次谐波及混频非线性超声检测信号分析,结果表明,动态小波指纹分析方法可有效提取出检测信号中的二次谐波及混频分量,基于小波指纹分布的非线性特征参数可用于板结构中微裂纹的定量表征.本文研究工作为结构早期损伤超声非线性检测中的弱非线性效应提取作了有益探索。      

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.     

Reflectivity function reconstruction using adaptive lattice deconvolution technique

Deconvolution of ultrasonic echo signals improves resolution and quality of ultrasonic images. The problem of reconstructing the reflectivity of a biological tissue is examined by adaptive lattice deconvolution of the echo ultrasound signals. The simulation of the signal formation process in an ultrasonic-echo scan line in noisy conditions is estimated. The reflectivity of a biological tissue is estimated as cross-correlation coefficients between forward and backward predication errors in each stage of the adaptive lattice filter.     

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.     

Characterization and analysis of coded excitation ultrasound parameters for rock properties

Coded excitation technology(CET) can effectively enhance the penetration and resolution of ultrasonic testing.To analyze the influence of rock properties on pulse compression performance(PCP) of coded excitation signals(CES),a numerical simulation,and an ultrasonic experiment on different rock samples are performed;and the detection ability of several CESs are also investigated and compared.The results of experiments showed that the loss of the signal-to-noise ratio(SNR) of Barker coded signal with tapered linear frequency modulated carrier(BTLFM) is always less than Barker coded signal with sine carrier(BS),while the resolution loss of BTLFM is lower than tapered linear frequency modulated signal(TLFM).In sum,the results not only verifiy the effectiveness of CET,but also provide a basis for the parameter settings of coded signals used in rock ultrasonic testing.     

光源对激光超声信号特性的影响分析

通过已搭建好的激光超声检测实验平台，在保持相同激光脉冲能量和相同探测位置的条件下，重点研究了点光源与线光源产生的超声信号的特点和区别。研究了不同探测位置点光源与线光源激发出的超声信号幅值以及产生的超声信号波形。实验发现:在同一探测位置下，将点光源换成线光源后，产生的超声信号幅值由1.3 V提高到1.7 V，提高了0.4 V；在探测位置逐渐增大的情况下，点光源激发出超声信号幅值的衰减幅度为75.78%，而线光源激发出的超声信号幅值的衰减幅度为34.92%。结果表明，在功率密度相同的情况下，线光源产生的超声信号要比点光源产生的超声信号幅值提高40.86%，产生较强的表面波，提高了信噪比。     

Signal-to-noise ratio enhancement based on wavelet filtering in ultrasonic testing

In ultrasonic non-destructive testing of materials with a coarse-grained structure the scattering from the grains causes backscattering noise, which masks flaw echoes in the measured signal. Several filtering methods have been proposed for improving the signal-to-noise ratio. In this paper we present a comparative study of methods based on the wavelet transform. Experiments with stationary, discrete and wavelet packet de-noising are evaluated by means of signal-to-noise ratio enhancement. Measured and simulated ultrasonic signals are used to verify the proposed de-noising methods. For comparison, we use signal-to-noise ratio enhancement related to fault echo amplitudes and filtering efficiency specific for ultrasonic signals. The best results in our setup were achieved with the wavelet packet de-noising method.     

Effect of trabecular bone material properties on ultrasonic backscattering signals

In this study, ultrasonic backscattering signals in cancellous bones were obtained by finite difference time domain （FDTD） simulations, and the effect of trabecular material properties on these signals was analyzed. The backscatter coefficient （BSC） and integrated backscatter coefficient （IBC） were numerically investigated for varying trabecular bone material properties, including density, Lame coefficients, viscosities, and resistance coefficients. The results show that the BSC is a complex function of trabecular bone density, and the IBC increases as density increases. The BSC and IBC increase with the first and second Lame coefficients. While not very sensitive to the second viscosity of the trabeculae, the BSC and IBC decrease as the first viscosity and resistance coefficients increase. The results demonstrate that, in addition to bone mineral density （BMD） and microarchitecture, trabecular material properties significantly influence ultrasonic backseattering signals in cancellous bones. This research furthers the understanding of ultrasonic backscattering in cancellous bones and the characterization of cancellous bone status.     

一种强噪声背景下微弱超声信号提取方法研究

为解决在强噪声背景下获取超声信号的难题，基于粒子群优化算法和稀疏分解理论提出一种强噪声背景下微弱超声信号提取方法.该方法将降噪问题转换为在无穷大参数集上对函数进行优化的问题，首先以稀疏分解理论和超声信号的结构特点为依据构建了粒子群优化算法运行所需要的目标函数及去噪后信号的重构函数，从而将粒子群优化算法和超声信号降噪联系在一起；然后根据粒子群优化算法可以在连续参数空间寻优的特点建立了用于匹配超声信号的连续超完备字典，并采用改进的自适应粒子群优化算法在该字典中对目标函数进行优化；最后根据对目标函数在字典上的优化结果确定最优原子，并利用最优原子按照重构函数重构出降噪后的超声信号.通过对仿真超声信号和实测超声信号的处理，结果表明本文提出的方法可以有效提取信噪比低至-4 dB的强噪声背景下的微弱超声信号，且和基于自适应阈值的小波方法相比本文方法表现出更好的降噪性能.     

基于双高斯衰减模型的超声回波处理方法

信号降噪与特征提取是超声检测数据处理的关键技术.基于超声信号有特定结构而噪声和超声信号的结构无关,本文提出一种旨在解决强噪声背景下超声回波的参数估计和降噪问题的方法.该方法将超声回波的参数估计和降噪问题转换为函数优化问题,首先根据工程经验建立超声信号的双高斯衰减数学模型,然后根据观测回波和建立的超声信号模型确定目标函数,接着选择人工蜂群算法对目标函数进行优化从而得到参数的最优估计值,最后由估计出的参数根据建立的超声信号数学模型重构出无噪的超声估计信号.通过仿真和实验表明本文方法可以准确估计出信噪比大于-10 dB的含噪超声回波中的无噪信号,且效果优于基于自适应阈值的小波降噪方法和经验模态分解方法;此外相比常用的指数模型和高斯模型,本文提出的双高斯衰减超声信号模型与实测超声信号更接近,其均方误差为9.4×10~(-5),波形相似系数为0.98.