基于小波系数变换的小波阈值去噪算法改进

小波阈值去噪是近年兴起的一种较好的去噪算法,其一关键点在于准确的选取阈值将细节信号和噪声信号区分开来。提出了一种算法对小波系数进行变换,将难以区分信号和噪声的区域放大,以利于阈值的选取,从而达到改进小波阈值去噪的目的。通过使用传统阈值去噪算法和该改进算法进行仿真,结果表明改进算法对去噪指标SNR、SME（平均方差）都有所改善。另外本文实验也表明改进算法可以更好的去除噪声,且较好的重现原信号的细节特征。     

一种新的小波阈值函数及其在振动信号去噪分析中的应用

摘要：研究一种新的小波收缩阈值函数用于信号的去噪分析,对比分析了硬阈值、软阈值和新收缩阈值函数的优缺点,给出了收缩阈值函数法中的阈值计算详细过程,基于虚拟仪器LabVIEW构建检测齿轮箱系统的振动与噪音检测系统,在MATLAB平台上利用收缩阈值方法开发了对齿轮箱振动和噪声信号进行去噪处理的软件,试验数据的分析表明：基于新的小波阈值函数的信号降噪分析方法去噪效果明显,且保留了原始信号的细节特征,是一种较传统经典去噪手段更为优越的方法,具有较高的实用价值。
     

基于小波改进阈值去噪和HHT的滚动轴承故障诊断

利用Hilbert-Huang变换（Hilbert-Huang Transformation,简称HHT）对滚动轴承进行故障诊断时,发现振动信号中包含的噪声对诊断结果影响较大。为克服此不足,提出了一种小波改进阈值法与HHT相结合的信号分析方法。该方法首先应用小波改进阈值方法对滚动轴承故障信号进行预处理,然后对去噪后的信号进行经验模态分解（Empirical Mode Decomposition,简称EMD）,接着选取含有故障信息的本征模函数（Intrinsic Mode Function,简称IMF）分量进行边际谱分析,从而提取出故障特征频率,并判断故障类型。仿真和实验结果验证了该方法的有效性。     

果蝇优化小波阈值超声检测信号去噪

由于材料结构的复杂性,超声检测回波信号往往存在很多干扰噪声。针对钢制结构中平底孔的超声检测信号传统小波去噪方法中小波阈值难确定的问题,结合小波良好时频特性和果蝇的全局优化能力,提出基于果蝇算法(FOA)优化小波阈值函数的超声检测信号去噪方法。对原始信号叠加5d B高斯白噪声,通过测试最大信噪比改善量获得最佳小波基和分解层数,采用sym5小波对超声检测信号进行6层分解后,利用果蝇算法对小波阈值进行参数优化,对比传统4种阈值确定方法,提高小波阈值的精度。验证结果表明:该方法对超声检测信号去噪后信噪比、均方根误差和相关性等参数具有满意的效果,去噪效果明显。     

检测技术中新的小波阈值函数的信号去噪

在信号检测技术中,构造了一个新的阈值函数,与传统的软硬阈值函数相比,连续性好,高阶可导,便于进行各种信号处理和检测。实验仿真结果表明,采用新的阈值函数的去噪效果在信噪比增益和均方误差意义上均优于传统的软硬阈值方法,给检测技术带来了新的发展。     

一种改进的小波阈值去噪算法研究

研究小波去噪算法中软阈值函数与硬阈值函数的方法,针对一些可变阈值函数的运算复杂的问题,提出一种新的阈值函数。经仿真测试,改进的小波阈值去噪算法的信噪比为20.103,去噪后,数据的均方误差为0.1152。     

基于小波影响锥分析的小波域阈值去噪方法

分析了传统的小波域阈值去噪方法在信号的奇异点附近产生震荡的一方面原因.基于尽可能的保留携带奇异点信息的小波系数的思想,提出了一种基于小波影响锥分析的小波阈值去噪方法首先通过阈值确定重要小波系数的时间位置,然后在小波影响锥分析的基础上保留所有影响锥内的小波系数.试验表明,本文方法与传统的阈值去噪方法相比在抑制震荡的同时能显著地提高信噪比.     

基于小波影响锥分析的小波域阈值去噪方法

分析了传统的小波域阈值去噪方法在信号的奇异点附近产生震荡的一方面原因。基于尽可能的保留携带奇异点信息的小波系数的思想,提出了一种基于小波影响锥分析的小波阈值去噪方法:首先通过阈值确定重要小波系数的时间位置,然后在小波影响锥分析的基础上保留所有影响锥内的小波系数。试验表明,本文方法与传统的阈值去噪方法相比在抑制震荡的同时能显著地提高信噪比。     

小波阈值去噪法的改进算法

基于小波变换的阈值去噪法是去除数字信号中白噪声的有效算法.其中阈值函数关系着重构信号的连续性和精度,硬阈值函数的不连续性和软阈值函数中估计的小波系数与信号的小波信号间存在恒定偏差的缺陷,也限制了它的进一步应用.本文通过数学方法的引入,对阈值函数进行了改进.仿真结果表明,该方法具有较好的去噪效果.     

基于EMD小波阈值去噪和时频分析的齿轮故障模式识别与诊断

建立了齿轮故障系统试验装置,对齿轮传动系统在各种转速与故障状态下进行测试分析,获取了有关振动信号,对齿轮系统的无故障、齿根裂纹、分度圆裂纹、齿面磨损四种状态信号进行特征提取,并对提取的信号进行基于经验模态EMD分解的小波阈值去噪处理,然后对预处理后的信号进行时频分析与诊断。结果表明,采用基于EMD的小波阈值去噪方法比单纯采用小波阈值去噪对测试信号进行预处理,能提高信噪比,并更加有效的提取出故障特征,而在EMD的小波阈值去噪的基础上,再与时频分析方法相结合能够较好的识别不同运转状况下不同种类的故障,如齿根裂纹、分度圆裂纹、齿面磨损等,可用于对实际工程工作的齿轮系统进行故障诊断。     

6σ方法的选择与分析

6σ改进主要应用于现有的过程或产品, 而6σ设计主要应用于设计或重新设计过程或产品;何时优先采用6σ设计方法一直是一个备受争议的问题.为解决这一问题,比较了6σ改进和6σ设计方法的差异;进而从系统论的观点,分析了选择6σ方法时需要考虑的要素并建立了相应的指标体系;在此基础上,引入了多目标决策的层次分析方法,并对一个6σ项目进行了分析.结果表明,选择6σ方法受到许多因素的影响,从而替代了6σ文献中"只有达到4.8σ,才能实施6σ设计"的准则.结论是任何实施6σ管理的组织可以根据技术、顾客需求、成本、复杂性、风险等因素,选择适应于自身发展的6σ方法.     

上海电信话费异议的精确化管理——基于精益六西格玛的方法

分析了精益生产和六西格玛管理的精髓,结合两者思路,指出精益六西格玛是实现精确化管理的有效工具,并提出了基于精益六西格玛的精确化管理的技术路线,包括界定问题、细化问题、确定原因、制定措施、监控结果等五阶段.以上海电信降低话费异议率为例,验证所提出观点和方法的有效性.     

对基于6 sigma体系的包装生产管理的实践探讨

简要介绍了6 sigma的管理体系,及其定义、目的和实施步骤.主要针对6 sigma 在包装生产管理上的具体运用作了一系列探讨.     

Crossover Effects in the Nonlinear σ-Model with Damping

We study the behavior of the nonzero temperature quantum nonlinear sigma model in d = 2 dimensions at finite temperatures in the presence of the damping term. Using the renormalization group (RG) method we calculated the effect of the finite temperature on the magnetic coherence length and the damping of the fluctuations. The results have been used to calculate the relaxation rates from nuclear magnetic resonance, which have been analyzed phenomenologically by different authors in order to get the phase diagram in the doped cuprate superconductors. Our calculations showed a good agreement with the experimental data, but we also evaluated the corrections which appear due to a more accurate analysis performed using the RG method.     

Quantum Nonlinear Sigma Model with a Damping Term; Finite Temperature Renormalization Group Analysis

We study the behavior of the finite temperature quantum nonlinear sigma model in two dimensions in the presence of the damping of the formf (|θ _n |) = γ|ω _n |^α, whereα satisfiesα ≥ 1. The analytical calculations will be performed usingα=2 and the results will be compared with the standard results obtained for the standard quantum nonlinear sigma model. The behavior of such a system is connected with the pseudogap which appears in the normal state of the cuprate superconductors.     

Disentangling causal relationships of a manufacturing process using genetic algorithms and six-sigma techniques

The manufacturing of hard disk drive storage is a highly competitive industry due to ever changing technology and the introduction of solid-state storage. Therefore manufacturers have introduced business improvement techniques to help leverage manufacturing advantages over competitors. This paper aims to investigate the integration of business improvement methodologies with intelligent techniques for the improvement of manufacturing efficiency. The authors use a case study based on the disentangling of causal relationships during the manufacturing of hard disk drive components. This paper reports on the application of intelligent system techniques to aid implementation of business improvement methodologies within this manufacturing environment. The results reported highlight that significant gains may be made when utilizing such a hybrid approach. The approach is validated by determining the secondary effects that degraded a previously implemented six-sigma project and also by identifying areas of investigation that enabled engineers to improve process yield.     

A graphical approach to obtaining confidence limits of Cpk

The process capability index C_pk has been widely used as a process performance measure. In practice this index is estimated using sample data. Hence it is of great interest to obtain confidence limits for the actual index given a sample estimate. In this paper we depict graphically the relationship between process potential index (C_p), process shift index (k) and percentage non-conforming (p). Based on the monotone properties of the relationship, we derive two-sided confidence limits for k and C_pk under two different scenarios. These two limits are combined using the Bonferroni inequality to generate a third type of confidence limit. The performance of these limits of C_pk in terms of their coverage probability and average width is evaluated by simulation. The most suitable type of confidence limit for each specific range of k is then determined. The usage of these confidence limits is illustrated via examples. Finally a performance comparison is done between the proposed confidence limits and three non-parametric bootstrap confidence limits. The results show that the proposed method consistently gives the smallest width and yet provides the intended coverage probability. © 1997 John Wiley & Sons, Ltd.     

Six sigma-based approach to optimize deep drawing operation variables

The six sigma approach has been increasingly adopted worldwide in the manufacturing sector in order to enhance the productivity and quality performance and to make the process robust to quality variations. This paper deals with one such application of six sigma methodology to improve the yield of deep drawing operations. The deep drawing operation has found extensive application in producing automotive components and many household items. The main issue of concern of the deep drawn products involves different critical process parameters and governing responses, which influences the yield of the operation. The effects of these parameters are analysed by the DMAIC (Define, Measurement, Analyse, Improve, Control)-based six sigma approach. A multiple response optimization model is formulated using the fuzzy-rule-based system. The functional relationship between the process variables and the responses is established, and thereafter their optimum setting is explored with the aid of response surface methodology (RSM). Rigorous experimentations have been carried out, and it is observed that the process capability of processes is enhanced significantly, after the successful deployment of the six sigma methodology.