油气管道弯头缺陷漏磁检测数值模拟研究

为研究油气管道弯头缺陷的漏磁信号特征,利用ANSYS软件进行了管道弯头缺陷有限元数值仿真,获得了不同缺陷漏磁信号,并进行了比较分析,得出了缺陷特征与漏磁场之间的对应关系,为漏磁检测过程中的弯头缺陷参数的定量识别提供了有效依据。     

一种热轧中厚板表面缺陷图像的特征提取方法

研究了快速傅立叶变换、不变矩的原理及特点,并应用于热轧中厚板表面缺陷图像特征提取。从现场在线采集热轧中厚板的表面缺陷图像,将每幅图像划分成64×64(像素)大小的子图像。对子图像进行快速傅立叶变换,得到子图像的幅值谱,再对幅值谱求七个不变矩,然后把求得的七个不变矩作为特征向量输入BP神经网络分类器进行识别。实验表明该方法具有较好的特征提取能力,能够很好的识别热轧中厚板表面缺陷。     

基于连续小波变换的厚壁管道周向导波扫描成像试验研究

采用周向导波用于厚壁管道中的缺陷扫描检测。基于连续小波变换提取特定频率下小波系数包络信号用于厚壁管道缺陷成像。试验中斜探头以步长为2 mm轴向扫描检测轴向缺陷,得到斜探头晶片覆盖轴向缺陷不同程度时的检测信号。截取包含缺陷回波和周向回波的信号并得到频率点500 kHz的小波变换系数包络信号,与频散曲线对比分析得到检测信号主要为周向类Lamb波模态CL3。进一步利用不同扫描点处检测信号的连续小波变换系数包络信号并进行幅值包络成像。利用该幅值包络成像重构得到轴向缺陷并有效确定该缺陷的长度。基于连续小波变换得到的特定频率点处幅值包络信噪比较好,且成像结果具有较高的聚焦性。因此,利用基于连续小波变换的幅值包络成像方法可提高检测信号识别以及缺陷识别能力。     

二维傅立叶变换在Lamb波模式识别研究中的应用

用二维傅立叶变换对实验测定的Lamb波信号进行分析。该方法是在波的传播路径方向上,对一系列等间距位置接收到的时间信号进行二维傅立叶变换。给出了各向同性和各向异性媒质中传播的Lamb波频散曲线的数值和实验结果。研究表明,二维傅立叶变换能有效地识别Lamb波模式。     

电涡流相位梯度及其在导电材料缺陷识别中的应用

使用空间域相频谱分析方法,将相位梯度作为缺陷检测信号特征量,对不同类型的缺陷进行检测和分类。数字相敏解调技术用于提取检测信号的相位梯度。采用双空气芯线圈涡流传感器并施加1～10 kHz多频激励信号,对平板金属样件进行表面缺陷、下表面缺陷、内部缺陷的识别及分类。实验结果证明,实验系统可以有效地检测出缺陷,并通过空间域相频谱分析得到可视化检测结果,采用相位梯度作为特征量有效抑制了提离噪声对检测结果的影响。     

基于平稳小波变换的悬臂梁微小缺陷检测方法研究

针对悬臂梁微小缺陷难以直接从模态振型进行有效识别的问题,提出了基于平稳小波变换的悬臂梁微小缺陷检测方法。通过利用有限元方法对悬臂梁进行建模和模态分析,得到了悬臂梁的模态参数。在此基础上,通过利用平稳小波变换对悬臂梁模态振型进行正交分解以得到平稳小波变换的近似系数(含模态振型的低频信号成份)和细节系数(含模态振型的高频信号成份)。最后,从平稳小波变换细节系数中提取了悬臂梁的微弱缺陷信息,实现了悬臂梁微小缺陷的有效定位和检测。从有限元模拟和平稳小波变换的结果可知,悬臂梁不同位置缺陷的前四阶细节系数都可以有效用于微小缺陷的定位。该方法具有较好的检测精度和可靠性,在结构缺陷萌生之初就可以有效识别缺陷的存在,避免结构灾难事故的发生,可推荐用于实际工程结构的检测。     

基于脉冲位相的红外热波无损检测测厚方法研究

为进一步实现红外热波无损检测中缺陷深度测量,提出基于脉冲位相分析的数据处理方法。对脉冲红外热波无损检测的时间信号进行傅立叶变换（FFT）,提取位相频率信息,根据热波频率与传导深度的关系完成缺陷深度的检测。以热传导较快的铝材料为例,对自行设计深度不同的平底洞缺陷给出此方法的实验结果,通过Matlab中FFT分析得到的不同深度平底洞缺陷在不同频率下的位相曲线及VC++中得到的位相序列热图,实验结果表明了脉冲位相对缺陷深度检测的可行性,缺陷实际深度关系与实验计算深度存在d≈1.98μ 的关系,同时位相图有效抑制了噪声的干扰,为材料和结构内部缺陷检测提供了一种有效处理方法。     

电触头钎焊接头超声检测信号的集成神经网络分类

研究电触头钎焊接头超声无损检测中的缺陷分类问题,提出了一种新的集成神经网络分类方法。该方法分四步：频率不变性预处理,多分辩分析,特征量预处理,集成 Ｂ Ｐ神经网络分类。使用不同中心频率探头检测得到的缺陷信号首先通过预处理变换到一个等效的参考频率上,然后利用离散小波变换提取特征量。特征量被预处理后,输入到集成 Ｂ Ｐ神经网络分类器中分类。本文用２１３ 个超声检测信号测试了集成神经网络的性能。实验结果表明了频率不变性技术和集成 Ｂ Ｐ神经网络分类技术的有效性。     

基于二维阻抗特征的管道环焊缝缺陷涡流检测

油气长输管道环焊缝处缺陷对管道安全的危害性巨大,管道缺陷造成的事故大部分发生在管道焊接处。目前,对管道进行无损检测(NTD)是预测事故隐患、保证管道安全运行的常用手段,但传统无损检测方法无法有效识别位于环焊缝处等表面形貌复杂位置的缺陷。为了克服传统检测方法的缺点,提出一种基于图像处理和神经网络的嵌入式涡流检测系统。从涡流信号合成的二维阻抗图入手,对其进行霍夫变换和轮廓提取得到特征分量,使用类内散布矩阵筛选分类特性好的特征用以训练基于FPGA加速的神经网络,实现在焊缝基底噪声较大的情况下对缺陷的自动分类与识别。实验结果表明,本系统可以有效识别位于环焊缝处等形貌复杂位置的缺陷信号,正确率可达92%,且系统体积小、功耗低,适合应用于管道内检测环境。     

基于小波包变换的梁体损伤识别

由于小波包变换在分析非平稳信号方面较傅立叶变换更为有效，提出了基于小波包变换的能量变化率指标进行损伤识别的方法。首先，将得到的结构响应信号进行小波包分解，然后通过小波包能量变化率指标来进行损伤定位。通过3种不同损伤工况的梁体室内试验证明．损伤指标可以准确地识别损伤位置。     

基于频率-波数的频域合成孔径导波成像研究

为实现管道中缺陷位置与尺寸的准确预测,在爆炸反射成像原理的基础上,提出了一种基于频率-波数的频域合成孔径导波成像算法。通过磁致伸缩方式在管道中激励出T(0,1)模态导波,对采集到的回波信号做二维傅里叶变换并进行角谱运算对频域内声场进行重构。最后,对其进行反傅里叶变换后实现目标区域内的聚焦成像。通过实验验证成像结果,同时与原始B扫结果进行了对比。结果表明,所提算法有效抑制了旁瓣效应产生,使成像分辨率提高了约30%,定量误差缩减了26.1%;同时研究表明在缺陷轴向位置、深度及倾斜角度发生改变时,利用该算法实现缺陷图像重构后,其检测准确度只受缺陷周向范围的绝对尺寸影响,对周向表面缺陷检测具体较高的灵敏度。     

Rolling element bearing defect detection using the generalized synchrosqueezing transform guided by time–frequency ridge enhancement

Healthy rolling element bearings are vital guarantees for safe operation of the rotating machinery. Time–frequency (TF) signal analysis is an effective tool to detect bearing defects under time-varying shaft speed condition. However, it is a challenging work dealing with defective characteristic frequency and rotation frequency simultaneously without a tachometer. For this reason, a technique using the generalized synchrosqueezing transform (GST) guided by enhanced TF ridge extraction is suggested to detect the existence of the bearing defects. The low frequency band and the resonance band are first chopped from the Fourier spectrum of the bearing vibration measurements. The TF information of the lower band component and the resonance band envelope are represented using short-time Fourier transform, where the TF ridge are extracted by harmonic summation search and ridge candidate fusion operations. The inverse of the extracted TF ridge is subsequently used to guide the GST mapping the chirped TF representation to the constant one. The rectified TF pictures are then synchrosqueezed as sharper spectra where the rotation frequency and the defective characteristic frequency can be identified, respectively. Both simulated and experimental signals were used to evaluate the present technique. The results validate the effectiveness of the suggested technique for the bearing defect detection.     

试采用FFT方法实现加速度、速度与位移的相互转换

指出了用微积分电路进行加速度、速度与位移的相互转换存在的弊端和使用范围上的局限性，提出了一种新的转换方法，即采用FFT方法进行加速度、速度与位移相互转换的方法，实验证明该方法是行之有效的。     

A hybrid signal pre-processing approach in processing ultrasonic signals with noise

Ultrasonic techniques have the potential to be used to detect sub-surface defects in aluminium castings. However, ultrasonic sensing techniques have not been successfully used to detect sub-surface defects in aluminium die castings with rough surfaces or in the ‘as-cast’ state due to the poor quality of signals. Ultrasonic signal noise caused by rough surfaces and grain size variations of the castings is difficult to eliminate. Hence, there is a need to process noisy ultrasonic signals to identify defects within the rough surface castings. This paper documents an investigation of ultrasonic signal analysis using artificial neural networks and hybrid signal pre-processing approaches for the purpose of detecting defects from noisy ultrasonic signals. In this investigation, ultrasonic signals were obtained from aluminium castings with different levels of surface roughness. The signals were first pre-processed using hybrid signal analysis techniques and then classified using an artificial neural network classifier. The hybrid pre-processing techniques utilised various combinations of fast Fourier transform (FFT), wavelet transform (WT) and principal component analysis. The best signal classification performance was generally achieved with a hybrid WT/FFT signal pre-processing technique.     

单一缺陷航天轴承的摩擦力矩判据

轴承套圈的圆度、表面粗糙度以及沟道形状误差都是影响灵敏轴承摩擦力矩的重要因素,以陀螺仪框架灵敏轴承为研究对象,对轴承外圈沟道形状误差、内圈沟道形状误差、内圈沟道圆度和内圈沟道表面粗糙度超差时的动态摩擦力矩进行了试验,运用Matlab,Fourier变换和小波分析等数学工具,通过对一些参数指标的计算和分析得出了辨别该轴承缺陷的初步判据。     

Evaluation of the health of riveted joints with active and passive structural health monitoring techniques

Many active and passive structural health monitoring (SHM) techniques have been developed for detection of the defects of plates. Generally, riveted joints hold the plates together and their failure may create accidents. In this study, well known active and passive methods were modified for the evaluation of the health of the riveted joints between the plates. The active method generated Lamb waves and monitored their propagation by using lead zirconate titanate (PZT) disks. The signal was analyzed by using the wavelet transformations. The passive method used the Fiber Bragg Grating (FBG) sensors and evaluated the spectral characteristics of the signals by using Fast Fourier Transformation (FFT). The results indicated that the existing methods designed for the evaluation of the health of individual plates may be used for inspection of riveted joints with software modifications.     

Application of principal component analysis in dynamic thermal testing data processing

The principles and features of the application of statistical principal component analysis (PCA) in active thermal testing are considered. A comparison between PCA and Fourier analysis in finding defects in composite materials, detecting corrosion in aluminum, and determining moisture content in construction materials is performed. It is concluded that, generally, images of principal components increase the signal-to-noise ratio and are close in performance to phase diagrams; nevertheless, the results of this method are poorly predictable and require further analysis.     

主动红外热成像焊球缺陷检测方法研究

IC产品的小型化和多功能化使微电子封装密度不断提高,微焊球技术得以广泛应用,而微焊球尺寸和间距日益缩减,使隐藏于芯片或封装内部的微焊球缺陷检测变得十分困难。主动红外热成像技术被深入研究并应用于微焊球缺陷检测,构建了主动红外微焊球缺陷检测模型,并展开试验研究。对直径和间距较大的BGA焊球采用红外透射式测量法进行检测,对获得的热图像进行空间自适应滤波,然后通过边缘检测分割出焊球区域,减小了热噪声和焊球间隙噪声对缺陷识别的干扰,并通过有效热斑面积进行量化分析;对凸点直径和间距较小的FA10倒装芯片采用红外反射式测量法进行检测,利用改进的自适应滤波算法去除空间椒盐噪声,然后提取像素点温度序列值进行时间域移动平均降噪,并以指数形式进行曲线拟合,通过傅里叶变换进行时频转换,采用脉冲相位法解决了表面发射率差异引起的缺陷辨识度下降等问题,并使用低频段的相位信息进行表征分析。利用主动红外热成像技术实现了焊球缺陷的有效检测,为高密度IC封装及其可靠性分析提供了一种快速、有效的方法。     

也论分数傅里叶变换与菲涅耳衍射的等效性

介绍了分数傅里叶变换的定义及其用于光学衍射时必须满足的自洽性条件 ,推导了分数傅里叶变换的缩放性质 ;分析了菲涅耳衍射和分数傅里叶变换的等效性关系 ;运用 MATLAB程序设计语言编程模拟实现了菲涅耳衍射 ,给出了对分数傅里叶变换和菲涅耳衍射等效性有决定意义的三个参数之间的关系曲线     

High‐Speed Scanning of Critical Structures in Aviation Using Coordinate Measurement Machine and the Laser Ultrasonic

Aviation is one of the know‐how spheres containing a great deal of responsible sub‐assemblies, in this case landing gear. The necessity for reducing production cycle times while achieving better quality compels metrologists to look for new and improved ways to perform inspection of critical structures. This article describes the ability to determine the shape deviation and location of defects in landing gear using coordinate measuring machines and laser ultrasonic with high‐speed scanning. A nondestructive test is the basis for monitoring microcrack and corrosion propagation in the context of a damage‐tolerant design approach. This article presents an overview of the basics and of the various metrological aspects of coordinate measurement and a nondestructive testing method in terms of high‐speed scanning. The new test method (laser ultrasonic) promises to produce the necessary increase in inspection quality, but this is limited by the wide range of materials, geometries, and structure aeronautic parts used. A technique combining laser ultrasonic and F‐SAFT (Fourier‐Synthetic Aperture Focusing Technique) processing has been proposed for the detection of small defects buried in landing gear. The experimental results of landing gear inspection are also presented. SCANNING 34: 387‐394, 2012. © 2012 Wiley Periodicals, Inc.