用红外水分测定仪快速测定食品中的水分

本文采用GB/T5009.3-2003和红外干燥法对三种固体食品样品分别进行了水分检测。结果表明红外干燥法大大缩短了检测时间,且操作简便迅速。经过显著性检验,红外法检测结果与国标中(105±2)℃,(3+1)h的直接干燥法无显著性差异。     

基于改进Prewitt算子的矿井视频图像小波阈值去噪

由于矿井成像环境的复杂性,导致所获取的图像较为模糊且存在一定程度的噪声,有必要采用适当的方法滤除其中的噪声并提高图像的清晰度。为此,提出了一种结合边缘检测的小波域矿井视频图像去噪算法。首先对噪声图像采用均值滤波算法进行预处理;然后对分别从检测模板、自适应阈值设定方法对经典的Prewitt算子进行适当改进,并采用改进的Prewitt算子提取预处理后图像的边缘轮廓信息,从而获得边缘图像和非边缘图像;最后对于非边缘图像,采用一种基于自适应阈值的改进小波阈值函数模型进行去噪处理,该模型充分结合了小波硬、软阈值去噪模型的优势,能够随着小波分解层数的变化自适应调整阈值大小。为了验证该算法的有效性,采用2幅实地获取的山东兖州某煤矿井下视频监控图像进行试验,并与小波硬、软阈值函数模型及2类已有的改进型小波阈值函数模型进行去噪效果对比。结果表明,该算法的去噪效果优于其余几类函数模型,且算法耗时略占优势,对于提高矿井视频监控图像的质量具有一定的参考价值。     

结合小波变换和能量算子的电压暂降检测方法

针对电压暂降扰动的准确定位与精确测量问题,提出结合小波变换与能量算子的暂降检测新方法.该方法通过小波变换将被检测电压暂降扰动分解成近似信号和细节信号两部分.在细节信号部分精确定位扰动发生起止时刻;对近似信号运行能量算子,能快速准确测量到暂降幅值.所提方法中小波变换兼具滤波效果,减弱或去掉低频暂降信号中的高频扰动成分,从...     

Wavelet transform-based stress-time history editing of horizontal axis wind turbine blades

Full scale blade fatigue testing is required to verify that the horizontal axis wind turbine (HAWT) blades posses the strength and service life specified in the design. Unfortunately, fatigue tests must be run for a long time period, which has led blade testing laboratories to seek ways of accelerating fatigue testing time and reducing the costs of tests. The objective of this article is to develop a novel method called a WT-based fatigue damage part extracting method. Based on wavelet transform (WT), this method extracts fatigue damage parts from the stress-time history and generates the edited stress-time history with shorter time length. Also, this article proposes a concept of applying accumulative power spectral density (AccPSD) to identify fatigue damage events contained in the stress-time history of HAWT blades. Wavelet functions used in this study are Morl, Meyr, Dmey, Mexh and DB30. It has been found that Mexh wavelet with an AccPSD level of 9000 Energy/Hz provides the edited stress-time history having a maximum reduction of 20.77% in length with respect to the original length, whilst fatigue damage per repetition can be retained almost the same as the original one. In addition, an existing method, time correlated fatigue damage (TCFD), is used to validate the effectiveness of a WT-based fatigue damage part extracting method. The results suggest that not only does the WT improve the accuracy of fatigue damage retained, but also it provides a shorter length of the edited stress-time history. To conclude, WT is suggested as an alternative technique in fatigue durability study, especially for the field of wind turbine engineering.     

小波包信号提取算法及其在识别磨煤机煤位敏感声频段中的应用

利用小波包将信号按任意时频分辨率（满足测不准原理）分解到不同频段的特点,本文提出了基于“能量——频段”的磨煤机煤位敏感声频段的识别方法——小波包信号特征提取算法、通过对不同煤位时磨煤筒体机声辐射信号的小波包分解和各个频段上分解信号的特征量提取,确定了磨煤机简体煤位敏感声频段。     

Identification of important image features for pork and turkey ham classification using colour and wavelet texture features and genetic selection

A method to discriminate between various grades of pork and turkey ham was developed using colour and wavelet texture features. Image analysis methods originally developed for predicting the palatability of beef were applied to rapidly identify the ham grade. With high quality digital images of 50–94 slices per ham it was possible to identify the greyscale that best expressed the differences between the various ham grades. The best 10 discriminating image features were then found with a genetic algorithm. Using the best 10 image features, simple linear discriminant analysis models produced 100% correct classifications for both pork and turkey on both calibration and validation sets.     

基于WTD-AR谱和MEA-BPNN的轴承故障诊断方法

针对滚动轴承故障诊断模型在噪声干扰下鲁棒性能差的问题,提出一种基于小波阈值去噪（WTD）、AR谱和思维进化算法（MEA）优化反向传播神经网络（BPNN）的轴承故障诊断方法。以原始振动信号为输入,采用小波方法分解重构原始信号滤除高频噪声,然后采用Burg算法估计AR模型参数提取降噪信号功率谱特征,最后将特征向量与对应标签分别作为MEA-BPNN神经网络的输入、输出进行训练,最终实现诊断。将该方法与一些先进的人工神经网络诊断方法作比较,测试该诊断模型的性能。研究结果表明：WTD-AR谱-MEA-BPNN诊断模型能够有效降低轴承振动信号的噪声干扰,实现特征增强,分辨率更高;相较于传统神经网络训练速度更快,在更短时间内甄别故障类型且识别率高。     

Study of Nuclear Physics for Nuclear Fusion

Based on the concept of damp matching [1] and the famous d + t fusion data, a conventional quantum mechanics calculation shows that the plasma fusion, muon-catalyzed fusion, and the low-energy nuclear reaction are essentially same in the sense of resonant tunneling through the Coulomb barrier. The good agreement between theory and experimental data justifies the selectivity in resonant tunneling, which implies the possibility of having fusion energy with no strong neutron and gamma radiation.