自适应串扰噪声消除技术在小孔径钻孔超声波检测中的应用

介绍了一种基于自适应滤波的噪声消除技术,分析了超声波用于小孔径钻孔检测中存在的同频串扰噪声的生成原因以及它对测量的影响,并对串扰噪声信号和待测信号进行建模;介绍了自适应噪声对消的原理,并针对应用给出了定步长自适应噪声的消除算法以及改进后的变步长自适应噪声消除算法,对两种算法在自适应学习速率上进行了比较,并给出经自适应去噪后的信号和原始信号的对比结果。     

一种基于LMS的振动信号相位差自适应无偏估计方法及应用

针对振动信号相位差估计问题,提出了一种基于LMS的自适应无偏估计方法。该方法通过一路信号与其正交的三角运算来配准另一路信号,相位差的正切值等于两个配准系数之比;根据均方误差最小原则对配准系数进行迭代更新,从而实现相位差自适应估计;理论推导出噪声引起的估计偏差,并据此对估计结果进行偏差补偿,实现相位差无偏估计,给出了补偿公式和方法流程。实验结果表明:该方法能准确估计出两路同频振动信号相位差,经偏差补偿后估计精度显著提高;在相位差发生突变时,能进行快速跟踪测量,具有较好动态测量特性;该方法在变化流量下科氏流量计振动信号相位差估计中的应用,验证了方法的工程实用性。     

基于单基元几何交汇法的被动目标测距测速研究

从理论上分析和推导了单传感器测距测速的几何交汇模型,该模型结合二维栅格搜索策略对具有稳定线谱的匀速直线运动目标进行距离和速度的估计。为满足交汇模型的测频精度要求,介绍了对短样本信号进行测频的谱估计法、过零法和Hilbert方法。把多组对应一定特征频率、正横距离、目标速度和信噪比的目标通过信号代入交汇模型进行计算机仿真,相应得出一系列测量误差曲线,分析结果表明,对于一定参数的通过信号该模型可以较精确的估计出目标的正横距离及速度。     

基于辐射噪声强度和线谱多普勒的目标运动参数估计

提出了一种利用辐射噪声强度和线谱多普勒频移联合估计匀速直线运动目标的速度和正横距离的方法。该方法基于单水听器观测,首先在球面波近似下利用目标辐射噪声强度估计出正横时刻并确定目标速度和正横距离之间满足的线性关系;然后利用线谱多普勒频移,通过对一个新定义的代价函数进行一维搜索的方法估计出目标速度和正横距离。与现有各种基于噪声强度和线谱多普勒频移进行测距测速的方法相比,该方法具有以下优点：（1）要求更少的先验知识,易于确定参数搜索范围;（2）参数估计过程中仅需一维搜索,并且算法可应用于需对目标参数进行预报的场合。数值仿真给出了不同参数条件下目标运动参数估计结果的统计误差。湖试结果验证了该方法的有效性。     

基于数字信号处理的时钟抖动测量与分析

讨论了时钟抖动测量中的一些问题,并给出了基于数字信号处理技术的一种测量方法.为了对新方法的性能进行估计,模拟了含有时间抖动的时钟信号,对不同抖动幅度和叠加不同噪声情况下的时钟抖动进行了测试.结果表明,新方法降低了测量精度对触发电平的稳定度、被测时钟叠加的噪声和上升沿斜率的敏感度.     

利用欠阻尼二阶线性随机共振抑噪的模型设计及实现

以经典力学模型——质量-阻尼-弹簧欠阻尼二阶线性系统为研究对象,当系统的阻尼系数和固有频率同时受乘性高斯噪声干扰时,利用此系统产生的随机共振来消除此类噪声.理论分析表明,欠阻尼二阶线性系统中存在随机共振现象,系统的平均输出幅度增益呈现非单调变化,不仅在一定条件下大于无噪声时的增益,而且调节适当的系统参数和噪声强度能够提高幅度增益.因此,采用可视化仿真软件SIMULINK建立仿真模型,并进行实例模拟.仿真进一步表明,通过调节适当的系统参数或噪声强度,使系统处于共振区域,就会把夹杂在噪声中的被测信号突现出来,从而实现了弱信号的检测,证实该方法消除乘性噪声的可行性和有效性.     

基于长程泄漏补偿的迭代插值FFT方法及应用

针对传统频域插值傅里叶变换参数估计精度低的问题,在分析频谱泄漏产生原理基础上,提出适用于多频信号的高精度频域迭代插值方法。该方法先利用传统插值法估算信号各频率参数,然后利用信号的估计参数值计算泄漏补偿因子,并用补偿因子重新计算信号各频率参数,最后通过多次迭代实现所需的计算精度。通过对方法的估计结果进行噪声干扰敏感性分析、参数变化对估计精度影响及对方法敏感性分析结果表明,在噪声干扰与长程泄漏明显情况下,所提方法仍具最好估计精度及稳定性,且收敛速度快,可作为改进信号参数估值精度的可选方法。对IC芯片封装中引线键合过程数据处理与分析结果表明,所提方法能较好抑制长程泄漏影响,提高参数估计精度。     

毫米波雷达阶跳频信号分析及运动补偿方法的实现

分析了毫米波雷达阶跳频信号参数以及复杂目标运动对该信号合成目标一维距离像的影响,研究了三角波调制下运动速度参数的估计方法。仿真表明,该方法具有较高的测速精度和较好的抗噪声性能,能ADSP21062信号处理板上运行时间为1．2ms。     

《二值噪声作用下线性系统的随机共振》

研究了二值噪声用下的二阶过阻尼线性系统的随机共振现象。基于线性系统理论和相关删去法方法,得到了系统平均输出幅度增益的精确表达式。研究表明：输出幅度增益是噪声的强度和相关时间、系统阻尼系数,以及激励信号的频率的非单调函数;另外,适当的噪声参数和系统参数可以使噪声情况下的输出幅度增益大于无噪声时的输出幅度增益。     

消除噪声干扰的动态测量方法研究

由于测量噪声和补偿器的频率特性,使得传感器的动态补偿器存在严重的噪声干扰,影响到补偿器的参数辨识和补偿后的测量精度。研究了一种消除噪声干扰的动态测量方法,先通过小波变换估计噪声的方差,再由估计得到的方差,通过偏差消除的递推最小二乘法,对补偿器的参数进行无偏辨识;同时,采用多项式实时滤波器,消除高频噪声对测量精度的影响。最后,通过实验验证了该方法的有效性。     

基于FPGA和DSP的气体超声流量计驱动和数字信号处理系统

采用FPGA+DSP双核芯结构,研制气体超声流量计驱动和数字信号处理系统。利用FPGA很高的工作频率和丰富的内部资源,实现高速DAC和ADC的驱动控制和数据存储;利用DSP的高速运算能力,实现数字信号的实时处理。针对利用正弦波驱动产生的超声波回波信号,基于实验数据统计,提出跟踪回波信号峰值的可变阈值法,准确地提取特征波,有效地克服了噪声的影响,扩展了量程比。气体标定实验结果验证了方法和系统的有效性。     

选带细化频谱分析在超声波流量测量中的应用

通过中频调制为基础提取流体速度方向信息,引入选带细化频谱分析技术对解调后多普勒信号进行高精度的频谱估计,该方法主要有三个方面的优点:能判断流速的方向;降低流速测量下限;提高了流速测量的动态响应速度、实时性以及稳定性.在此基础上,以数字信号处理器(DSP)为平台设计了超声流量计,实验分析表明1 024点ZOOM-FFT算法在选定频带范围内与16 384点FFT有相近的分辨率.     

基于可变阈值和过零检测的四声道气体超声波流量变送器

针对四声道气体超声波流量计,提出基于可变阈值和过零检测的数字信号处理方法,快速、准确定位回波信号,提高系统抗干扰能力。设计了集中采集-集中处理数据的工作模式和双发双收的收发方式,采用FPGA和DSP双核架构,研制了四声道气体超声波流量变送器。利用FPGA擅长并行处理和复杂逻辑控制的优势,实现换能器双发双收、高速DAC和ADC的驱动控制以及数据存储,完成信号的集中采集;利用DSP擅长数字信号处理的优势,实时实现数字信号处理方法,完成信号的集中处理。气体流量标定实验结果表明:研制的四声道气体超声波流量计满足0.5级精度相关技术指标的要求。     

EMAT noise suppression using information fusion in stationary wavelet packets

An important issue in ultrasonic nondestructive testing is the detection of flaw echoes in the presence of background noise created by instrumentation and by clutter noise. Signal averaging, autoregressive analysis, spectrum analysis, matched filtering, and the wavelet transform have all been used to filter noise in ultrasonic signals. Widely-used wavelet threshold estimation algorithms are not designed for electromagnetic acoustic transducer (EMAT) pulse-echo signals, and therefore do not exploit their unique impulse nature. The approach to ultrasonic signal filtering proposed in this paper is based on stationary wavelet packet denoising with a threshold influenced by several information sources: a statistical echo detection, the amplitude distribution of the wavelet transform coefficients, and a priori known system frequency characteristics. The proposed method was evaluated on signals measured with EMAT probes and under various SNR conditions; it outperforms the wavelet transform with the Stein unbiased risk estimate (SURE) threshold estimation method and split-spectrum processing (SSP). The results indicate SNR enhancement of 19 dB with real EMAT data.     

齿轮焊缝超声检测信号降噪方法研究

汽车变速箱齿轮焊缝的超声检测过程中,超声回波信号存在信噪比较低导致误检率较高的问题。该文根据齿轮焊缝超声检测信号中噪声的特点,提出利用经验模态分解进行滤波的方法。针对经验模态分解过程中出现的虚假频率现象,提出镜像扩展的解决算法,把镜内信号映射成一个周期性的信号,抑制端点效应,避免虚假频率现象。仿真结果表明该方法可有效提高信噪比且抑制虚假频率的产生,通过标准伤试块的实验结果表明,该文提出的方法可以在较小硬件开销的情况下,有效减小噪声信号干扰,将噪声峰值从高于闸门8.4%降低到低于闸门7.9%,提高检测效率。     

基于相关函数包络峰细化的高精度超声测距法

建立了超声测距时延估计模型,由于窄带超声回波参考信号与接收信号的相关函数在极值点附近具有慢衰减高频振荡特性,所以有必要将搜索直接相关函数的极值点转化为搜索相关函数包络的极值点.针对相关峰常规插值方法在多倍插值的情况下存在计算复杂、时延估计精度不高等缺点,结合超声回波信号的窄带带通特性和相关峰细化(Fine Interpolation of Correlation Peak)原理,提出了直接提取相关函数包络及包络峰细化方法,并分析了其计算复杂度.仿真与实验研究表明,该方法能大大提高相关函数包络峰值分辨率,适用于类超声回波信号的带通信号精细时延估计问题.     

利用复相关法估计信号的平均频率

文章介绍了利用复相关估计信号平均频率的方法，并就其采样周期的选取与频率估计误差间的关系作了分析，最后给出最佳采样频率以及平均频率测量误差的实测结果。     

Model-based estimation of ultrasonic echoes. Part II: Nondestructive evaluation applications

For Part I see ibid., vol.48, no.3, pp.787-802 (2001). Accurate estimation of the ultrasonic echo pattern leading to the physical property of the object is desirable for ultrasonic NDE (nondestructive evaluation) applications. In Part I of this study, we have presented a generalized parametric ultrasonic echo model, composed of a number of Gaussian echoes corrupted by noise, and algorithms for accurately estimating the parameters. In Part II of this study, we explore the merits of this model-based estimation method in ultrasonic applications. This method produces high resolution and accurate estimates for ultrasonic echo parameters, i.e., time of flight (TOF) amplitude, center frequency, bandwidth, and phase. Furthermore, it offers a solution to the deconvolution problem for restoration of the target response, i.e., ultrasonic reflection and transmission properties of materials, from the backscattered echoes. The model-based estimation method makes deconvolution possible in the presence of significant noise. It can also restore closely spaced overlapping echoes beyond the resolution of the measuring system. These properties of the estimation method are investigated in various ultrasonic applications such as transducer pulse-echo wavelet estimation, subsample time delay estimation, and thickness sizing of thin layers     

A robust correlation receiver for distance estimation

Many methods for distance estimation, such as the ultrasonic pulse-echo method, involve the estimation of a time-of-flight (TOF). In this paper, a signal model is developed that, apart from the TOF, accounts for an unknown, linear frequency dependent distortion as well as for additive noise. We derive a TOF estimator for this model based on the criteria of maximum likelihood. The resulting receiver can be seen as an extension or generalization of the well known cross-correlation, or “matched filter”, estimator described, e.g., by Nilsson. The novel receiver is found to be more robust against unknown pulse shape distortion than the cross-correlation estimator, giving less biased TOF estimates. Also, bias versus noise sensitivity can be controlled by proper model order selection     

A fundamental limit on delay estimation using partially correlatedspeckle signals

Delay estimation is used in ultrasonic imaging to estimate blood or soft tissue motion, to measure echo arrival time differences for phase aberration correction, and to estimate displacement for tissue elasticity measurements. In each of these applications delay estimation is performed using speckle signals which are at least partially decorrelated relative to one another. Delay estimates which utilize such data are subject to large errors known as false peaks and smaller magnitude errors known as jitter. While false peaks can sometimes be removed through nonlinear processing, jitter errors place a fundamental limit on the performance of delay estimation techniques. The authors apply the Cramer-Rao Lower Bound to derive an analytical expression which predicts the magnitude of jitter errors incurred when estimating delays using radio frequency (RF) data from speckle targets. The analytical expression presented includes the effects of signal decorrelation due to physical processes, corruption by electronic noise, and a number of other factors. Simulation results are presented which show that the performance of the normalized cross correlation algorithm closely matches theoretical predictions. These results indicate that for poor signal to noise ratios (0 dB) a small improvement in signal to noise ratio can dramatically reduce jitter magnitude. At high signal to noise ratios (30 dB) small amounts of signal decorrelation can significantly increase the magnitude of jitter errors