小波分析对奇异性检测用于滴定终点确定的研究

在分析化学领域中，利用数学判断法确定滴定终点，随着计算机的日益普及而备受关注。此文在介绍当前普遍采用的二进小波变换奇异性检测方法的基础上，提出基于多分辨率分析和连续小波变换两种奇异性检测方法，并应用于氢氧化钠对盐酸和磷酸滴定曲线判断终点的试验中，取得了良好的效果。     

基于小波变换的电位滴定法测定喷气燃料总酸值

在电位滴定法测定喷气燃料总酸值中采用小波变换法检测电位滴定终点。以二次样条小波为基函数对电位滴定曲线进行离散二进小波分解,在适当尺度上基本滤除曲线的干扰噪声,通过分析细节信号得到滴定曲线的突跃点,从而判定滴定终点。与指示剂法相比,本方法的测定结果具有相当的准确度和更高的精密度。本方法可快速测定喷气燃料的总酸值。     

小波变换用于电位滴定法测定极弱酸

研究了用小波变换确定电位滴定终点方法测定硼酸和苯酚两种极弱酸,同经典方法及其它数学方法的结果进行比较,说明用小波变换电位滴定法测定极弱酸快速,准确,可为极弱酸的计算机联机测定提供一种新的途径。     

小波变换在自动电位滴定仪测定铁矿石中铁含量的应用

应用计算机化的自动电位滴定仪分析了铁矿石中铁量,并采用小波变换法测定滴定终点。试样溶液中的三价铁直接用三氯化钛还原至二价,溶液中共存的二价铁和过量的三价钛在滴定中都被重铬酸钾标准溶液所氧化,但两者的等当点电位可明显地相互区别,不影响二价铁的滴定及其定量计算。用所提出的方法分析了铁矿石标准物质,测得的铁量与标准值相符。     

用小波变换确定电位滴定终点

将小波变换在信号和图象处理过程中边缘检取的思想方法引入到化学中，以确定电位滴定的终点，能直接对测量的数据进行处理，不会引入人为的误差因素。计算精度可达实验精度的下限，且处理结果的判断非常简便，用本方法对实验数据进行处理，获得满意的结果。     

基于多尺度小波变换的红外光谱谱峰识别算法

传统的谱峰检测方法一般分为3个步骤:谱线平滑、基线校正和谱峰识别.现有的基于小波变换的峰值检测方法能较好地将基线校正和谱峰识别两个步骤融为一步.在此基础之上,本研究将谱线平滑也很好地融入到小波变换的峰值检测算法中,使整个峰值检测算法成为一个整体.在峰值提取时,原始谱图直接处理,不再是处理加工过的谱图,减小了谱峰检测结果...     

基于小波变换平滑主成分分析

小波变换具有很强的信号分离能力,很容易把随机噪音从信号中分离出来,从而提高信号的信噪比。本文把小波变换引入到因子分析中,提出了基于小波变换平滑主成分分析,该算法既保留普通主成分分析的正交分解,又具备了小波变换的信号分离能力。模拟数据和实验数据的结果表明,该算法具有从低信噪比的数据中提取出有用信息,并提高信号的信噪比。迭代目标变换因子分析处理实验数据的结果表明,基于小波变换平滑主成分分析的处理结果优     

毛细管电泳激光诱导荧光检测信号的小波滤噪

采用小波滤噪方法对毛细管电泳激光诱导荧光检测信号进行了处理，研究了小波变换中小波基的选择及噪声阈值的选择对滤噪的影响。结果表明，采用DB4小波基能有效消除毛细管电泳激光诱导荧光检测信号中存在的噪声，使信噪比得到较大改善。     

小波降噪技术在差分吸收光谱浓度检测中的应用

为了实现对工业气体SO₂的浓度进行监控,基于紫外差分吸收光谱法开发了SO₂在线检测系统。针对系统噪声和Mie散射使吸收光谱叠加带来的误差,本文提出采用小波变换降噪技术代替传统光谱处理方法中的多项式平滑滤波技术来提高检测精度。通过对应用了Symlets、Daubechies、Coiflet和Biorthogonal这4种不同小波函数的实验数据分析和对传统小波阈值选取方式的改进,最终确定了基于rigisure阈值的小波阈值去噪的信号处理方法,并提出一种新的信噪比量来衡量信号处理的效果。这种方法可以快速可靠地处理光谱信号,处理后所得的监测浓度准确度基本控制在1.5%以内。在实验室环境下和工业现场环境下的大量实验结果表明本方法能有效的减小噪声对SO₂浓度监测带来的影响。     

基于小波和小波包变换的苯丙酮尿症傅里叶变换衰减全反射红外光谱筛查模型的研究

应用小波和小波包变换对傅里叶变换衰减全反射红外光谱(FTIR/ATR)进行去噪处理,以提高苯丙酮尿症(PKU)筛查模型的性能。首先优化小波和小波包变换的参数,然后分别对原始光谱(OS)、9点平滑光谱(9S)和一阶微分9点平滑光谱(1D9S)进行去噪处理,以均方根误差(RMSE)、平均相对误差(MRE)、预测准确率(Acc)等为指标,考察小波和小波包变换对模型性能的影响。结果与变换前相比,模型性能均有所提高,其中小波变换以1D9S+sym12处理结果为最优,而小波包变换以1D9S+sym1为最优;Acc全部提高为100%。     

Fractal analysis of polyethylene catalysts surface morphologies based on wavelet transform modulus maxima method

Surface morphologies of supported polyethylene (PE) catalysts are investigated by an approach combining fractal with wavelet. The multiscale edge (detail) pictures of catalyst surface are extracted by wavelet transform modulus maxima (WTMM) method. And, the distribution of edge points on the edge image at every scale is studied with fractal and multifractal method. Furthermore, the singularity intensity distribution of edge points in the PE catalyst is analyzed by multifractal spectrum based on WTMM. The results reveal that the fractal dimension values and multifractal spectrums of edge images at small scales have a good relation with the activity and surface morphology of PE catalyst. Meanwhile the catalyst exhibiting the higher activity shows the wider singular strength span of multifractal spectrum based on WTMM, as well as the more edge points with the higher singular intensity. The research on catalyst surface morphology with hybrid fractal and wavelet method exerts the superiorities of wavelet and fractal theories and offers a thought for studying solid surfaces morphologies. Supported by the Chinese Petroleum & Chemical Corporation Development Department (Grant No. x504024)     

End-point detection in potentiometric titration by continuous wavelet transform

The aim of this work was construction of the new wavelet function and verification that a continuous wavelet transform with a specially defined dedicated mother wavelet is a useful tool for precise detection of end-point in a potentiometric titration. The proposed algorithm does not require any initial information about the nature or the type of analyte and/or the shape of the titration curve. The signal imperfection, as well as random noise or spikes has no influence on the operation of the procedure.The optimization of the new algorithm was done using simulated curves and next experimental data were considered. In the case of well-shaped and noise-free titration data, the proposed method gives the same accuracy and precision as commonly used algorithms. But, in the case of noisy or badly shaped curves, the presented approach works good (relative error mainly below 2% and coefficients of variability below 5%) while traditional procedures fail. Therefore, the proposed algorithm may be useful in interpretation of the experimental data and also in automation of the typical titration analysis, specially in the case when random noise interfere with analytical signal.     

连续样条小波变换用于分解重叠峰的研究

以B-样条小波为分析小波，提出了用于分析化学重叠信号解析的新方法——连续样条小波变换，结果表明：连续样条小波变换应用于分析化学信号的处理，能使峰变窄同时还能提高信号的信噪比，是一种新型有效的重叠信号解析方法，能从含噪声重叠信号中直接得到重叠峰的峰数目及其相应的峰位置。     

利用二进样条小波模极大方法消除毛细管电泳信号噪声的研究

根据毛细管电泳信号中噪声与真实信号的模极大值特性之间存在较大差异的特点，提出了一种利用二进样条小波模极大值法去噪的方法研究了信号的半峰宽、不同信噪比以及阈值的选取对去噪结果的影响，并对模拟含噪信号和含噪毛经电泳信号去噪前后的结果进行了比较，实验结果表明，该法能效地消除谱带较宽的毛细管电泳等信号中存在的噪声。     

The application of spline wavelet transform to the determination of electroosmotic mobility in capillary electrophoresis

The rule of current change was studied during capillary electrophoresis (CE) separation process while the conductivity of the sample solution was different from that of the buffer. Using a quadratic spline wavelet of compact support, the wavelet transforms (WTs) of capillary electrophoretic currents were performed. The time corresponding to the maximum of WT coefficients was chosen as the time of current inflection to calculate electroosmotic mobility. The proposed method was suitable for different CE modes, including capillary zone electrophoresis, nonaqueous CE and micellar electrokinetic chromatography. Compared with the neutral marker method, the relative errors of the developed method for the determination of electroosmotic mobility were all below 2.5%.     

去卷积伏安法中离散数据处理的方法研究(Ⅰ)──正交小波变换平滑

一系列的离散数据处理方法已成为化学计量学的重要组成部分[1],去卷和伏安法就是结合计算机技术的新一代电分析方法,其激励信号与输出信号均为计算机发生和采集的数字信号,对采集到的信号一般采用移动平均法[2]和Fourier变换处理法[3]进行平滑处理．但是,Fourier变换在电分析化学领域的难度较大,运算复杂,为此,Aubarel等[4]提出了不用FFT的Fourier变换平滑算法,但是该法要先对信号进行预处理,并且对Fourier的和式要反复进行折叠,计算量较大．80年代末发展起来的小波变换引起了人们广泛的关注[5],被称为数学“显微镜”,具有…     

一种有效提取微弱信号的新方法

根据小波变换能进行时频局部化分析的特性,本文提出一种用小波分段分析处理信号的方法。对任意长度的信号数据,在不增减信号点的情况下,提高分析信号的信噪比,有效地从信号中提取有用信息。将它应用于微弱信号检测,效果满意。