Time reversal technique for health monitoring of metallic structure using Lamb waves

Time reversal active sensing using Lamb waves is investigated for health monitoring of a metallic structure. Experiments were conducted on an aluminum plate to study the time reversal behavior of A₀ and S₀ Lamb wave modes under narrow band and broad band pulse excitation. Damage in the form of a notch was introduced in the plate to study the changes in the characteristics of the time reversed Lamb wave modes experimentally. Time–frequency analysis of the time reversed signal was carried out to extract the damage information. A measure of damage based on wavelet transform was derived to quantify the hidden damage information in the time reversed signal. It has been shown that time reversal can be used to achieve temporal recompression of Lamb waves under broadband signal excitation. Further, the broad band excitation can also improve the resolution of the technique in detecting closely located defects. This is demonstrated by picking up the reflection of waves from the edge of the plate, from a defect close to the edge of the plate and from defects located near to each other. This study shows the effectiveness of Lamb wave time reversal for temporal recompression of dispersive Lamb waves for damage detection in health monitoring applications.     

Nonlinear approximation with general wave packets

We study nonlinear approximation in the Triebel-Lizorkin spaces with dictionaries formed by dilating and translating one single function g. A general Jackson inequality is derived for best m-term approximation with such dictionaries. In some special cases where g has a special structure, a complete characterization of the approximation spaces is derived.     

基于小波变换的数字胸片自适应增强

利用图像自适应增强原理, 推导出小波域中的等价表示. 根据视觉生理心理学原理, 具体的增益系数由图像的背景灰度确定. 同时考虑到胸片中重要的细节信息位于中间频率的特性, 增益系数需要进行调整. 实验结果表明, 调整增益后的小波自适应增强方法能有效的增强数字胸片中的细节信息.     

烟草组分的近红外光谱和支持向量机分析

测定了120个产自福建、安徽和云南烟草样品的近红外光谱. 在利用支持向量机(SVM)技术建立其定量、定性分析模型之前, 用小波变换技术对光谱变量进行了有效的压缩, 然后采用径向基核函数建立了75个烟草样品的分类模型, 同时建立了总糖、还原糖、烟碱和总氮4个组分的定量分析模型, 并利用45个烟草样品对模型进行了检验. 仿真实验表明, 建立的SVM分类模型分类准确率达到100%, 而4个组分的定量分析模型的预测决定系数(R2)、预测均方差(RMSEP)和平均相对误差(RME)3个指标值显示其模型泛化能力非常强, 预测效果良好, 可见这是一种有效的近红外光谱的建模分析方法.     

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.     

多菌灵农药的激光拉曼光谱分析

实验采集多菌灵农药的固体和液体拉曼光谱信号,对固体的原始拉曼光谱信号进行小波去噪预处理,利用正交试验方法筛选小波去噪参数的最优组合。结果表明,采用db2小波基函数、分解层数为2、阈值方案选择为rigrsure、重调方式为sln时,去噪效果最好,信噪比为62.483。根据不同官能团的振动模式,对去噪后的拉曼光谱分3个波数段(1 400～2 000,700～1 400,200～700 cm-1)进行谱峰归属和分析,得到了多菌灵农药分子在不同波数范围内的特征振动模式,其中,在619,725,964,1 022,1 265,1 274和1 478 cm-1处的拉曼信号较强,可作为固体多菌灵农药的特征峰。从多菌灵农药的液体拉曼光谱中,找到了629,727,1 001,1 219,1 258和1 365 cm-1特征峰,这些特征峰跟固体多菌灵农药的特征峰基本吻合。研究结果可为拉曼光谱分析技术在食品及农产品中农药残留的快速筛选提供判别依据。     

原子荧光光谱法研究贝壳堤岛贝壳沙中As的空间分布特征

用原子荧光光谱法测定了贝壳沙中As元素含量,研究了As在黄河三角洲贝壳堤岛贝壳沙中的空间分布规律,分析了贝壳沙中As与其他营养元素的相关性,并对影响其含量与空间分布的因素进行探讨。结果表明：贝壳沙样品中As的含量范围为0.78～8.76 mg·kg-1,平均值为3.11 mg·kg-1,整体上处于清洁的水平。贝壳沙中As含量有随剖面深度增加而增大的趋势,贝壳沙粒径大小也影响贝壳沙中As的含量,贝壳沙粒径越小,As含量越高,且不同粒径贝壳沙中As含量差异显著(p≤0.05)。贝壳沙中As与全磷(total phosphor,TP)和全钾(total potassium,TK)以及Cu, Zn, Mn均具有极显著的正相关关系,与全氮(total nitrogen,TN)和Fe的相关性不显著。综合分析认为,贝壳沙中As主要来自于风化后的贝壳沙对环境中As元素的吸附与固定而非贝壳形成过程中对该元素的富集作用。     

一种新的活动星系光谱红移自动测量方法

星系红移的自动测量对进行大样本天文学研究如宇宙学大尺度结构研究具有重要意义。星系一般分为正常星系和活动星系两种,活动星系光谱一般具有较明显的发射线特征。文章提出了一种不用精确提取谱线而快速测量活动星系光谱红移的方法。该方法包括步骤：(1)对待测光谱进行去噪;(2)利用小波变换提取低频成分光谱,并用去噪后光谱减去低频谱得到残差谱;(3)计算残差谱的均方差,并保留大于阈值的波长集合(4)根据标准谱线表计算所有候选红移;(5)利用Parzen窗估计方法计算红移密度最大点,并在邻域内求均值确定最终红移。对模拟数据和SDSS DR7部分实测数据的测试表明,该方法是鲁棒的并且具有较高的红移测量正确率。     

基于Haar小波特征的恒星光谱物理参量自动估计

恒星大气物理参数的自动测量是大型巡天计划中海量光谱数据自动处理中的一个重要内容。首先使用多尺度Harr小波对恒星光谱数据进行特征分解,然后选用相应的小波系数作为光谱的特征向量,最后采用非参数回归算法对光谱的物理参数进行估计。研究表明,只需对光谱进行四层小波分解, 并选择第四层小波系数作为光谱的特征向量,即可获得重力加速度和表面有效温度的较好估计。对于化学丰度的估计,选择第一层小波系数作为光谱特征向量可取得较好效果。选用文献相关研究中常用的恒星大气模拟模型合成光谱库ELODIE中光谱数据测试了该方法的有效性。结果表明,基于Harr小波分解的光谱特征提取方法对恒星表面温度、表面重力和化学丰度等物理参数的估计具有较高的精度和鲁棒性。     

低阈值单横模852nm半导体激光器

基于波导理论、等效折射率方法,设计并制备了非对称波导隔离双沟结构脊型边发射激光器,最终获得了低闽值单基侧模852 nm激光器.详细研究了不同脊型台深宽比参数设计对激光器侧向模式特性的影响规律,实现了腔面未镀膜情况下脊型波导边发射激光器的单基侧模稳定输出,同时激射波长可以精确调谐到852 nm;工作电流达到150 mA,工作温度30℃;斜率效率最高可达0.89 nW/mA,光谱半宽小于1 nm.研究结果为进一步实现超窄线宽激光器提供了参考和借鉴,并且为实现激光器稳定输出提供了实验基础.