小波分析及其在时变滤波和信号分离中的应用

利用小波变换具有的多时频分辨率特性，对地震勘探和测井信号这类非平衡信号进行分析，可以充分利用信号的时间－频率特性。文中介绍了小波变换的基本概念及其在地震勘探信号的时变滤波和声波全波列测井信号的信号分离中的应用，实例表明，小波变换在地球物理信号中具有广阔的应用前景。图５参７     

Reaction steady states and stationary states in modelling semi-batch enzyme hydrolysis

Dimensionless material balance equations describing an uninhibited enzyme hydrolysis process in a semi-batch reactor (i.e. fed-batch reactor) are formulated; numerical solution of these equations provided concentration profiles of the enzyme-substrate complex by using published kinetic parameters. The unrestricted values obtained are compared with estimates based separately on the reaction steady state and stationary state assumptions. Results are discussed in terms of the enzyme/substrate inventory used and it is found that the reaction steady state is a satisfactory approximation only when this ratio is sufficiently small. The stationary state may be a better approximation at other values, particularly when enzyme is added to substrate or when an empty tank is being filled. Reaction yields from semi-batch and batch operations are compared. Processing takes longer in the semi-batch operations and complete conversions are only practical in this mode when enzyme is added to substrate.     

一种基于Hough变换的声呐对目标航迹检测算法研究

为提高声呐对目标航迹的检测性能,从单部声呐时间融合的角度出发,提出了一种基于Hough变换的声呐信号检测算法。该算法把航迹上的观测点变换为参数空间的对应曲线,充分利用一段时间内的目标观测数据,在低信噪比下也能从背景噪声中提取目标的航迹特征,提高了声呐的检测概率,且对部分信息和数据的缺失不敏感。仿真试验证明了该算法的有效性。     

A New Image Analysis Based Method for Measuring Electrospun Nanofiber Diameter

In this paper, a new image analysis based method for electrospun nanofiber diameter measurement has been presented. The method was tested by a simulated image with known characteristics and a real web. Mean (M) and standard deviation (STD) of fiber diameter obtained using this method for the simulated image were 15.02 and 4.80 pixels respectively, compared to the true values of 15.35 and 4.47 pixels. For the real web, applying the method resulted in M and STD of 324 and 50.4 nm which are extremely close to the values of 319 and 42 nm obtained using manual method. The results show that this approach is successful in making fast, accurate automated measurements of electrospun fiber diameters.     

三维地震勘探中强声波干扰的压制

在三维地震资料采集中产生的声波为非线性干扰波,能量强,频谱宽,利用常规的分频去噪和线性压噪方法难以将其去除,使后续的资料处理效果受到影响。基于声波具有非常稳定的传播速度这一特点,提出了一种利用非线性变换手段压制强声波干扰的方法。方法原理是,首先对三维地震资料中含声波到达时间的某段记录(时窗)进行转换,将非线性声波时距关系转换为速度趋于无穷、波数趋于零的一组噪声;然后应用f-k滤波对这组噪声进行压制;最后,再通过逆转换得到声波压制后的结果。该方法易于实现,并只对声波到达时间处的小范围数据进行处理,数据量小,计算效率高。对实际三维地震资料的处理结果表明,该方法压制强声波干扰的效果非常明显。     

信号时域积分性质的一个推广应用

对信号进行运算（卷积运算，傅氏变换，拉纸变换）时，应用时域积分性质，得出由函数导数的运算式求取原函数的相应运算结果的一般性计算公式，使时域积分性质的应用得到推广。     

基于地震道时频分析的地层结构解析原理和方法

 地震时频分析是通过对地震信号采用多种数学变换，实现从时频域角度对信号的局部特征进行分解，剖析信号细微特征所对应的地层结构。在应用地震时频分析技术过程中，人们对于这项技术能否真正有效地解决实际地质问题存在许多争论。本文从时频原理综合分析的角度出发，对地震道时频谱中各种频率特性参数和时频旋回直接转化成对地层结构逐级、分步的解析方法进行了较深入的探讨。研究认为时频分析原理不仅是对地震数据进行特殊数学变换，实现对信号的分解，而且充分利用了地层厚度的调谐效应及岩性调谐效应；时频谱与地质结构特征之间的良好响应关系为地震地质精细解释提供了直观的依据。     

利用Hilbert-Huang变换提取地震信号瞬时参数

 通过Hilbert变换求取的信号瞬时参数并非对任何信号都有物理意义，此法通常要求被分析信号是窄带或平稳的，而且对噪声很敏感。而实际地震信号既非平稳又含有噪声，若在实际应用中不加考虑地对地震信号进行Hilbert变换以求取瞬时参数，这种情况下求取的瞬时参数将缺乏物理意义甚至失真。Hilbert-Huang变换是一种新的分析非平稳非线性信号的方法，它先将信号进行经验模态分解（EMD），形成有限个固有模态函数（IMF）之和，再对固有模态函数作Hilbert变换求取时频谱，求取的时频谱在时域和频域都具有较高的分辨率。本文将Hilbert-Huang变换应用于地震瞬时参数的提取，实例表明，对地震剖面做EMD可以得到不同时间尺度上的特征，Hilbert谱比传统的时频谱在时间和频率域上的分辨率都要高，强反射层在第1阶IMF瞬时频率剖面上比原瞬时频率剖面上表现得更为明显。     

Hardware and software architecture for power quality analysis

This paper presents a novel concept for power quality hardware and software architecture. Software tools related to detection, classification and characterization of power quality events can be integrated into a Distribution Control Center in which the interconnection between different subsystems is being carried out through the Internet allowing flexibility to the system. This system is implemented using wavelet analysis applied in all proposed algorithms. Different power quality events are taken as examples to illustrate the capabilities of the proposed method. The obtained results reveal that the proposed architecture is feasible to be implemented as an integral part of a control center system.The proposed system has the property of fast and accurate detection and classification of any power quality disturbance event and introduces a new PQ index determination that allows characterizing any type of disturbance including the non-periodic signals.     

A New Matlab De-noising Algorithm for Signal Extraction

The goal of a de-noising algorithm is to reconstruct a signal from its noise-corrupted observations. Perfect reconstruction is seldom possible and performance is measured under a given fidelity criterion. In a recent work, the authors addressed a new Matlab algorithm for de-noising. A key method of the algorithm is selecting an optimal basis from a library of wavelet bases for ideal de-noising. The algorithm with an optimal basis from a library of wavelet bases for de-noising was created through making use of Matlab＇s Wavelet Toolbox. The experimental results show that the new algorithm is efficient in signal de-nosing.