基于改进小波系数奇异值分解和小波去噪的低频振荡时变模式辨识

提出了一种基于连续小波变换(continuous walelet t r a n s f o r m , C W T )和奇异值分解( s i n g u l a r v a l u e decomposition,SVD)相结合的提升小波系数 SVD 辨识信号振荡频率和模式信息提取及信号去噪的新方法.克服了噪声较大或者密集模态时,小波脊线不清晰甚至会出现混叠和交叉难以提取频率的情况,根据提升的小波系数奇异值分解频率向量识别各阶振荡模式的频率.同时选用小波能量系数来识别主导振荡模式,用小波软阈值去噪和 SVD 分解后矩阵重构来进行信号去噪.CWT 可以处理含时变振荡模式的低频振荡信号,且对模式参数具有较高的辨识精度.仿真算例验证了算法的有效性和适用性     

2013—2017年邯郸市PM2.5浓度变化特征及污染源区研究

为探索邯郸地区PM_2.5浓度长期变化特征及污染潜在源区,对邯郸2012年12月—2018年2月河北工程大学站点在线监测的PM_2.5质量浓度进行统计分析,并结合HYSPLIT模型、潜在源贡献因子法（PSCF）和浓度权重轨迹分析法（CWT）对PM_2.5进行来源解析。结果表明：邯郸市2013—2017年PM_2.5年均值为108.4、98.3、92.2、81.2、66.3 μg·m^-3;整体呈逐年下降趋势;秋冬季污染最为严重,春、夏季次之;月均值呈单峰型分布,1月最高（167.4 μg·m^-3）,7月最低（59.2 μg·m^-3）。后向轨迹结果显示,近地层大气污染气团输送路径以近距离轨迹为主,轨迹较短的路径占比在40%以上。除冬季外,近距离输送路径均存在螺旋转向,轨迹方向转为南向和东向路径;邯郸主要污染源区范围较大,其中河北中南部、河南北部、山西中南部、陕西北部、内蒙古南部地区的轨迹对邯郸PM_2.5质量浓度贡献较大。     

基于小波的搜索量聚类及在变量选择中的应用

针对使用网络购物搜索量数据建立预测模型时的变量选择问题,提出一种基于连续小波变换(CWT)及其逆变换的聚类方法。算法充分考虑了搜索量的数据特征,将原始序列分解成为不同时间尺度下的周期成分,并重构为输入向量。在此基础上通过加权模糊C均值(FCM)方法进行聚类。变量选择是根据聚类后每个分类中的关键词隶属度函数值确定的,选择效果通过我国居民消费价格指数(CPI)的预测模型进行验证。结果表明,搜索量序列具有不同长度的周期成分,聚类后同组关键词具有明显的商品类型一致性。与其他变量选择方法相比,基于小波重构序列聚类的预测模型具有更高的预测精度,单步和三步预测相对误差仅为0.3891%和0.5437%,预测变量也具有清晰的经济含义,因此特别适用于解决大数据背景下高维预测模型的变量选择问题。     

基于小波熵的低误报率人体热释电红外信号识别

提出一种基于双密度双树复小波变换小波熵特征的热释电红外(PIR)信号人体识别方法.首先对人体和狗的PIR探测器输出信号进行去噪预处理,然后提取信号的双密度双树复小波变换的小波熵作为特征,最后采用最小二乘支持向量机对特征进行分类.实验结果表明:所提取的特征及分类方法对人体与狗的热释电红外信号的识别率可达93.6%.因此该识别方法能大大降低PIR探测器的误报率,并可进一步提升PIR探测器在安防和智能家居系统中应用.     

基于时频分析的Lamb波散射源定位方法研究

针对Lamb波损伤定位中频散效应对定位精度的影响,提出了基于时频曲线和椭圆定位法的Lamb波散射源定位法.利用经验模态分解(EMD)法把散射信号分解成有限个窄带信号分量,再采用改进的连续小波变换(CWT)求出每个信号分量的时频曲线,叠加形成整个信号的时频曲线,实现对不同频率成分波达时刻的准确判别.利用椭圆定位法获得对应于散射信号中一系列频率成分的定位结果,最终由这些多组定位的综合判定损伤位置.在铝板结构上的测试结果表明,在频散较严重的A0模式低频段,该方法求出的时频曲线较细致,损伤位置定位较精确,能有效排除偶然因素对最终结果的影响.     

Feature extraction using wavelets and classification through decision tree algorithm for fault diagnosis of mono-block centrifugal pump

Monoblock centrifugal pumps are employed in variety of critical engineering applications. Continuous monitoring of such machines becomes essential in order to reduce the unnecessary break downs. Vibration based approaches are widely used to carry out the condition monitoring tasks. Decision tree, fuzzy logic, support vector machine and artificial neural networks are some of the classification algorithms employed for condition monitoring and fault diagnosis. In the present study, fault discriminating capability of wavelets in its continuous form with the application of J48 algorithm is analyzed. Vibration signals are extracted from the experimental setup. The continuous wavelet transform (CWT) is calculated for different families and at different levels which form the feature set. The features are then fed as an input to the classifier (J48 algorithm, a WEKA implementation) and the classification accuracies are calculated. Then, the results are validated to find classification capability of CWT features for monoblock centrifugal pump. The different faults considered for this study are cavitation (CAV), impeller fault, bearing fault (FB) and both bearing and impeller fault.     

国产亚临界直流炉给水加氧处理工艺的应用

介绍了国产亚临界直流炉给水加氧处理工艺应用的经验,对加氧处理转换过程中的影响因素和凝结水精处理的运行方式进行了讨论,并评估了给水加氧处理的效果.     

Detection of chipping in ceramic cutting inserts from workpiece profile during turning using fast Fourier transform (FFT) and continuous wavelet transform (CWT)

Ceramic cutting tool inserts are prone to premature failure by chipping instead of gradual wear due to their low impact toughness. Thus, in-process detection of failure of ceramic tools is important to prevent workpiece surface deterioration. The objective of this study is to develop a method of detection of the onset of chipping in ceramic cutting tool inserts during dry finish turning from the workpiece profile signature. The profile of the workpiece surface opposite the cutting side was captured using an 18-MP DSLR camera at a shutter speed of 0.25 ms during the turning of AISI01 oil-hardening tool steel. The edge profile was extracted to sub-pixel accuracy from the 2-D image of the workpiece surface using the invariant moment method. The effect of chipping in the ceramic insert on the surface profile signature of the workpiece was investigated using the fast Fourier transform (FFT) and continuous wavelet transform (CWT). The results show that the stochastic behavior of the cutting process after tool chipping manifest as sharp increase in the amplitude of spatial frequencies below the fundamental feed frequency. The proposed sub-window FFT method is effective in resolving the time resolution by detecting tool chipping at cutting time duration of around 17.13 s. Compared to the sub-window FFT method the CWT method is able to detect the exact onset of chipping in the cutting tool insert.     

基于广义S变换的地震资料谱分解技术研究

谱分解技术一般采用短时Fourier变换和连续小波变换。短时Fourier变换的分析时窗是恒定的,不随频率的变化而自动调节,连续小波变换的尺度与频率的关系并不确定。广义S变换具有优良的时频聚集性和时频分辨率,它综合了短时Fourier变换和连续小波变换的一些优点,而克服了它们的不足,同时通过调节时窗宽度因子可以获得更好的时频分辨率。研究将其应用于地震资料的谱分解中,给出了基于广义S变换的谱分解业务流程,并对实际地震资料进行了分析。结果表明该方法是可行的。     

给水加氨、加氧联合处理工况(CWT)在600MW超临界燃煤机组中的应用

本文针对广东汕尾电厂两台60万超临界燃煤机组在给水、凝结水中加氧和不加氧的处理工况进行全面的介绍和对比,总结出给水、凝结水加氧处理在水汽质量控制、加药成本、机组运行经济性方面的效果和优势。以期对同类型参数的机组有关加氧可行性、经济性方面提供参考和依据。