An engine fault diagnosis system using intake manifold pressure signal and Wigner–Ville distribution technique

This paper proposed an engine fault diagnosis system based on intake manifold pressure signal and artificial neural network with the Wigner–Ville distribution technique. Traditionally, the engine diagnostic method depends on the experience of the technician, but some faults might be inaccurately judged by the technician’s experience when the engine is operating. In the present study, an engine platform diagnosis system using intake manifold pressure was developed. The algorithm of the proposed system consisted of Wigner–Ville distribution (WVD) for feature extraction and the neural network technique for fault classification. In previous work, the Wigner–Ville distribution was often used to analyze the non-stationary signal, because it provides a simple and clear energy spectrum diagram both in the time and frequency domains. This instantaneous energy diagram presented the magnitude of each engine fault under various operating conditions. The Wigner–Ville distribution extracts these features as database input to a neural network and the neural network is used to develop the training and testing modules. To prove the efficiency of the neural network, both the radial basis function neural network and generalized regression neural network are used and compared. The experimental results demonstrated the proposed system is effective and the performance is satisfactory.     

A review of time–frequency matched filter design with application to seizure detection in multichannel newborn EEG

This paper presents a novel design of a time–frequency (t–f) matched filter as a solution to the problem of detecting a non-stationary signal in the presence of additive noise, for application to the detection of newborn seizure using multichannel EEG signals. The solution reduces to two possible t–f approaches that use a general formulation of t–f matched filters (TFMFs) based on the Wigner–Ville and cross Wigner–Ville distributions, and a third new approach based on the signal ambiguity domain representation; referred to as Radon-ambiguity detector. This contribution defines a general design formulation and then implements it for newborn seizure detection using multichannel EEG signals. Finally, the performance of different TFMFs is evaluated for different t–f kernels in terms of classification accuracy using real newborn EEG signals.Experimental results show that the detection method which uses TFMFs based on the cross Wigner–Ville distribution outperforms other approaches including the existing TFMF-based ones. The results also show that TFMFs which use high-resolution kernels such as the modified B-distribution, achieve higher detection accuracies compared to the ones which use other reduced-interference t–f kernels.     

Wigner分布中互谱项特征及其消除方法的探讨

Ｗｉｎｇｅｒ分布中互谱项严重影响了其物理解释及其应用。本文在分析Ｗｉｇｎｅｒ分布互谱项的特征后，讨论了消减互谱项的方法，并应用于机械状态监测实际信号分析中，机械特征相当明显，且得到了较为理想的时一频分布结果。     

卫星非线性信道下非对称MAPSK优化设计

为了克服非线性失真对卫星通信系统的影响,首先论述了卫星非线性信道的特性,提出了在调制端对MAPSK映射星座进行非对称设计,在解调端采用标准的解映射星座进行解调的方法。通过仿真试验验证了此方法能够补偿非线性失真对MAPSK调制信号带来的相位和幅度的影响。     

Geometric attack resistant image watermarking based on MSER

Geometric distortions are simple and effective attacks rendering many watermarking methods useless. They make detection and extraction of the embedded watermark difficult or even impossible by destroying the synchronization between the watermark reader and the embedded watermark. In this paper, we propose a blind content-based image watermarking scheme against geometric distortions. Firstly, the MSER detector is adopted to extract a set of maximally stable extremal regions which are affine covariant and robust to geometric distortions and common signal processing. Secondly, every original MSER is fitted into an elliptical region that was proved to be affine invariant. In order to achieve rotation invariance, an image normalization process is performed to transform the elliptical regions into circular ones. Finally, watermarks are repeatedly embedded into every circular disk by modifying the wavelet transform coefficients. Experimental results on standard benchmark demonstrate that the proposed scheme is robust to geometric distortions as well as common signal processing.     

基于奇异值分解的、抗几何失真的数字水印算法

许多现有的适用于图像的数字水印对几何失真都是很敏感的。尤其是此类失真会严重妨碍对水印的盲提取。为此，提出了一种基于奇异值分解的数字水印算法，它对常见的几何失真是稳健的。此水印是被嵌入到图像分解后的奇异值之中。根据奇异值分解的代数性质，严格证明了嵌入了水印的图像在受到转置、镜像、旋转、放大和平移等几何失真后，其奇异值是不变的。在经过了上述的几何失真、一般的信号处理操作或JPEG压缩以后，嵌入的水印能够被可靠地提取和检测。实验结果表明本算法具有很好的稳健性。     

简化的Wigner分布及其在笔迹鉴别中的应用

本文提出了简化的Ｗｉｇｎｅｒ分布纹理分析方法并用于笔迹鉴别．Ｗｉｇｎｅｒ分布是图像的局部频谱表示，但计算量和存储量太大，我们证明Ｗｉｇｎｅｒ分布是信号的冗余表示，然后对它进行了简化．简化的Ｗｉｇｎｅｒ分布是信息保持的，且仍保持较好的纹理度量性能．该方法在笔迹鉴别实验中比以往的笔迹纹理分析方法取得了更好的结果。     

Revealing quantum correlation by negativity of the Wigner function

We analyze two two-mode continuous variable separable states with the same marginal states. We adopt the definition of classicality in the form of well-defined positive Wigner function describing the state and find that although the states possess positive local Wigner functions, they exhibit negative Wigner functions for the global states. Using the negativity of Wigner function as an indicator of nonclassicality, we show that despite these states possess different negativities of the Wigner function, they do not reveal this difference as phase space nonclassicalities such as negativity of the Mandel Q parameter or quadrature squeezing. We then concentrate on quantum correlation of these states and show that quantum discord and local quantum uncertainty, as two well-defined measures of quantum correlation, manifest the difference between negativity of the Wigner functions. The non-Gaussianity of these states is also examined and show that the difference in behavior of their non-Gaussianity is the same as the difference between negativity of their Wigner functions. We also investigate the influence of correlation rank criterion and find that when the states can be produced locally from classical states, the Wigner functions cannot reveal their quantum correlations.     

发电机励磁碳刷运行故障检测方法

针对发电机励磁系统中碳刷结构故障检测困难,故障定位不准确的问题,本文根据实际碳刷运行过程建立碳刷结构检测系统。通过建立组件对象模型(Component Object Model COM)动态检测方案将碳刷结构模型化,使系统能够更为精确的检测到故障原因。设计数字式光纤传感器(BF5R)检测电路将碳刷故障过程图像化,缩短系统检测时间。通过改进维格纳威尔分布(Wigner Ville distribution WVD)故障定位算法精准定位碳刷故障位置,采用合理方式进行维修。通过Proteus软件仿真检测系统运行过程,实验表明本设计对碳刷故障检测具有明显效果,在15KW发电机环境中,碳刷故障定位时间为3.5min,信号幅值为13V,结果精确度为96.4%,证实了本设计的可行性;通过仿真对比三种不同系统信号检测幅值电压和检测准确度曲线,由此验证了本研究的优越性。     

小波变换结合盲源分离的EEG情感识别

由于脑电信号独立源数目的不确定性以及其他噪声的干扰,使得采集的脑电信号各导信号之间产生串扰、源信号难以估计以及噪声混杂等问题,严重影响了对脑电信号的分析研究。将小波变换与盲源分离算法相结合,并对盲源分离算法中维格纳分布存在的交叉项干扰现象进行重排处理。主要思路是首先将每一导信号进行小波变换,提取出特征波β波,然后对这些β波信号进行基于重排光滑伪维格纳分布的盲源分离,分离出关联性极大的β波成分。实验结果表明,所用方法分离出了各导信号中关联性大的脑电信号成分,并在一定程度上解决了源信号难以估计等问题,使识别结果有明显的提升。     

一种基于小波和时频分解的端点检测方法

提出了一种新的基于小波和时频分解的语音端点检测方法。首先通过小渡分解对舍噪信号进行增强，然后采用Matching pursuits算法对去噪信号进行时频分解．使得信号在时频平面上具有较明显的魏格纳能量分布．最后利用该特点设定合适的门限来进行语音端点检测。实验结果表明，该方法对低信噪比的语音端点检测仍有效。     

一种基于奇异值分解的稳健数字水印算法

提出了一种基于奇异值分解的数字水印算法，它对常见的失真是稳健的。由服从标准正态分布的随机数组成的水印被嵌入到图像分解后的奇异值中。实验结果表明本算法具有很好的稳健性。在经过了一般的信号处理操作和JPEG压缩以后，嵌入的水印能够被可靠地提取和检测。特别地，本算法对转置、行(列)镜像、直角旋转、行(列)整数倍放大和有填充平移等几何失真具有不变性。     

加性噪声抵消的对称相关函数法

提出了一种新的噪声抵消方法－对称相关函数法,它利用时频分析中的WVD分布分析实信号时零频处的交叉项包含有原信号的所有信息这一特性,定义了对称相关函数,并从理论上分析了它抵消平稳随机过程中与信号不相关的加性随机噪声的机理。仿真结果证明了该方法的有效性。     

天然气压气机械设备故障信号时频分析特征提纯

天然气压气站压气机械设备工作环境恶劣,故障多发,而机械设备的故障状态下的振动噪声信号是研究机械设备故障诊断的有效载体。为有效进行故障诊断,需要对机械设备的故障信号进行提纯分析和特征提取等研究。提出基于时频分析技术的WVD和Hough变换结合的方法对低信噪比的故障信号进行提纯算法。首先分析了非平稳信号处理技术的基本原理,对原始信号的滤波和检测、频谱分析等处理,分析了时频分析特性和对应的条件,提出采用时间均值、频率均值、时间散布和频率散布四个特征值作为时频分析的特征提取量。仿真实验以某天然气压气站某型压缩机故障振动下采集信号样本为研究对象,进行提纯滤波和特征提取仿真,仿真实验得到降噪滤波和WVD及Hough变换算法下的检测结果,表明在强干扰背景SNR为-8dB下,有卓越的滤波降噪和检测性能,特征提纯检测性能相比传统算法提高18％以上。为天然气压缩机故障诊断奠定了可靠的理论基础。     

基于图像正则化的抗几何变换的感知哈希算法

图像哈希在内容认证、数据库搜索和水印等领域有广泛的应用。该文提出的新的抗几何变换的感知哈希方法包括三个主要阶段：第一阶段通过图像正则化过程获得一个对任意仿射变换具有不变性的正则图像;第二阶段对随机选择的多个子图像进行小波变换产生一个包括图像主要特征的副图像;第三阶段采用奇异值分解捕获图像的局部感知成分并生成最终哈希。仿真实验表明算法有效抵抗了几何变换、压缩等感知保持操作,内容篡改也被正确检测。批量实验也证明算法有较好的稳健性和抗误分类能力。     

Segmentation of textured images and Gestalt organization usingspatial/spatial-frequency representations

The generic issue of clustering/grouping is addressed. Recent research, both in computer and human vision, suggests the use of joint spatial/spatial-frequency (s/sf) representations. The spectrogram, the difference of Gaussians representation, the Gabor representation, and the Wigner distribution are discussed and compared. It is noted that the Wigner distribution gives superior joint resolution. Experimental results in the area of texture segmentation and Gestalt grouping using the Wigner distribution are presented, proving the feasibility of using s/sf representations for low-level (early, preattentive) vision     

基于时变AR预白滤波处理的水雷非水雷识别算法

基于时变AR预白化滤波器处理方法采用图象模式识别技术设计开发了一个水雷/非水雷的自动识别系统.数据预处理完成后截取有效数据段并提取信号特征由分类器对真假水雷目标进行识别.时变AR预白滤波器方法在一定程度上将背景混响预白化,提高了匹配滤波的检测性能.本文基于实际湖试和海试数据对该识别算法进行验证,结果表明此算法识别效果较好.     

L_p shape deformation

Shape deformation is a fundamental tool in geometric modeling.Existing methods consider preserving local details by minimizing some energy functional measuring local distortions in the L 2 norm.This strategy distributes distortions quite uniformly to all the vertices and penalizes outliers.However,there is no unique answer for a natural deformation as it depends on the nature of the objects.Inspired by recent sparse signal reconstruction work with non L 2 norm,we introduce general L p norms to shape deformation;the positive parameter p provides the user with a flexible control over the distribution of unavoidable distortions.Compared with the traditional L 2 norm,using smaller p,distortions tend to be distributed to a sparse set of vertices,typically in feature regions,thus making most areas less distorted and structures better preserved.On the other hand,using larger p tends to distribute distortions more evenly across the whole model.This flexibility is often desirable as it mimics objects made up with different materials.By specifying varying p over the shape,more flexible control can be achieved.We demonstrate the effectiveness of the proposed algorithm with various examples.     

Signal distortions in comparator pulse gate transformation using the statistical method for a low number of samples

Distortions during comparator pulse gate transformation of noisy signals are analyzed using the statistical method and its variants. The distortions are characterized with a systemic error in measuring the input signal??s amplitude. The studies are carried out for a low number of operations of comparing a signal with a constant threshold. Systemic errors of the main statistical method and error correction methods are compared. It is shown that the correction ensured using the combined approach is almost ideal. The results of the studies can be used in ultrawideband radio detection (UWB).     

锥形核广义类时-频分布及其对语音的描述

语音的传统短时傅立叶分析方法不仅要假设语音具有准稳定性,而且其时间分辨率和频率分辨率存在着折衷。本文采用具有锥形核的广义类时-频分布(CK-GTFD)描述方法,并重点考察了它的瞬态响应和压缩交叉项的能力,结果表明,它不仅能同时获得好的时间分辨率和频率分辨率,对多分量信号也能精确地描述。最后,通过对语音的爆破音-元音转换段,以及元音-鼻辅音转换段的描述,表明了它在语音共振峰频谱描述、声门关闭时间确定,以及辅音-元音划分等方面的优势,为语音特征提取和识别打下了基础。