Harmonic signal extraction from noisy chaotic interference based on synchrosqueezed wavelet transform

For the harmonic signal extraction from chaotic interference, a harmonic signal extraction method is proposed based on synchrosqueezed wavelet transform(SWT). First, the mixed signal of chaotic signal, harmonic signal, and noise is decomposed into a series of intrinsic mode-type functions by synchrosqueezed wavelet transform(SWT) then the instantaneous frequency of intrinsic mode-type functions is analyzed by using of Hilbert transform, and the harmonic extraction is realized. In experiments of harmonic signal extraction, the Duffing and Lorenz chaotic signals are selected as interference signal, and the mixed signal of chaotic signal and harmonic signal is added by Gauss white noises of different intensities.The experimental results show that when the white noise intensity is in a certain range, the extracting harmonic signals measured by the proposed SWT method have higher precision, the harmonic signal extraction effect is obviously superior to the classical empirical mode decomposition method.

WAVELET ALGORITHM FOR INTEGRAL OPERATOR EQUATION AND ITS APPLICATIONS TO ELECTROMAGNETIC PROBLEMS

A brief summary of the basic theory of wavelet is proposed. The properties of wavelet function are discussed. The possible applications of wavelet to electromagnetics are given. Examples show that the wavelet method is feasible and effective for solving electromagnetic problems.

Determination of micro yttrium in an ytterbium matrix by inductively coupled plasma atomic emission spectrometry and wavelet transform

In the determination of trace yttrium (Y) in an ytterbium (Yb) matrix byinductively coupled plasma atomic emission spectrometry (ICP-AES), the most prominent line ofyttrium, Y 371.030 nm line, suffers from strong interference due to an emission line of ytterbium.In mis work, a method based on wavelet transform was proposed for the spectral interferencecorrection. Haar wavelet was selected as the mother wavelet. The discrete detail after the thirddecomposition, D3, was chosen for quantitative analysis based on the consideration of bothseparation degree and peak height. The linear correlation coefficient between the height of the leftpositive peak in D3 and the concentration of Y was calculated to be 0.9926. Six synthetic sampleswere analyzed, and the recovery for yttrium varied from 96.3 percent to 110.0 percent. The amountsof yttrium in three ytterbium metal samples were determined by the proposed approach with an averagerelative standard deviation (RSD) of 2.5 percent, and the detection limit for yttrium was 0.016percent. This novel correction technique is fast and convenient, since neither complicated modelassumption nor time-consuming iteration is required. Furthermore, it is not affected by thewavelength drift inherent in monochromators that will severely reduce the accuracy of resultsobtained by some chemometric methods.

NOVEL ADAPTIVE MULTIUSER DETECTIONALGORITHM BASED ON WAVELET TRANSFORM

The wavelet transform-based adaptive multiuser detection algorithm is presented. The novel adaptive multiuser detection algorithm uses the wavelet transform for the preprocessing, and wavelet-transformed signal uses LMS algorithm to implement the adaptive multiuser detection. The algorithm makes use of wavelet transform to divide the wavelet space, which shows that the wavelet transform has a better decorrelation ability and leads to better convergence. White noise can be wiped off under the wavelet transform according to different characteristics of signal and white noise under the wavelet transform. Theoretical analyses and simulations demonstrate that the algorithm converges faster than the conventional adaptive multiuser detection algorithm, and has the better performance. Simulation results reveal that the algorithm convergence relates to the wavelet base, and show that the algorithm convergence gets better with the increasing of regularity for the same series of the wavelet base. Finally the algorithm shows that it can be easily implemented.

基于Wavelet-CNN的电磁炮过靶信号识别方法

电磁炮测试中,炮口产生强烈的火光信号以及振动等噪声,会严重干扰电枢特征信号的识别处理;为了提升对电枢信号的自动识别率,提出了一种基于小波变换和卷积神经网络(CNN)相结合的电枢信号识别方法;利用小波变换对过靶信号进行小波阈值去噪,进而重构信号,然后利用CNN提取信号的深层次特征,通过CNN的全连接层输出信号的分类结果;当输入信号为电枢信号时,对其作最大值检测获取电枢信号的特征点;实验结果表明,所提方法对比传统小波阈值滤波法在特征点自动拾取准确率上提升了5.88%;该算法对电磁炮电枢过靶信号的滤波、识别具有一定的参考意义。

基于小波变换的锚杆锚索测力仪设计

针对井下存在的电磁干扰,会对测力仪采集到的运放端的电压信号存在较大的干扰,进而对传感器测得的压力值准确性产生影响的问题;设计了基于小波变换的锚杆锚索测力仪。以国产HC32L176单片机作为主控芯片,对运放端的电压信号进行AD采集;选用合适的小波基函数、分解层数、阈值规则及阈值函数,对含噪信号进行分解,滤除不同层的高频成分,再对信号重构,得到去噪后的信号。Matlab仿真与实际测试结果表明:小波变换可以对采集的电压信号实现很好去噪,提高了锚杆锚索测力仪的可靠性与稳定性。

Common-mode Electromagnetic Interference Mitigation for Solid-state Transformers

Solid-state transformers(SSTs)have been widely used in many areas owing to their advantages of high-frequency isolation and high power density.However,high-frequency switching causes severe electromagnetic interference(EMI)problems.Particularly,the common-mode(CM)EMI caused by the switching of the dual active bridge(DAB)converter is conducted through the parasitic capacitances in the high-frequency transformer and impacts the system reliability.With the understanding of the CM EMI model in SSTs,CM EMI mitigation methods have been studied.For passive mitigation,the coupled inductor can be integrated with the phase-shift inductor function to reduce CM EMI.For active mitigation,variations in the DAB switching frequency can help reduce the CM EMI peak.An active EMI filter can also be designed to sample and compensate for CM EMI.Using these methods,CM EMI can be reduced in SSTs.

突发脉冲干扰下的白鲸哨声端点检测方法

针对圈养条件下大量突发脉冲干扰影响白鲸哨声检测的问题,提出了一种可调Q因子小波变换(TQWT)结合自适应谱聚类的无监督哨声信号检测方法。对原始信号做高Q因子的小波分解,并以平均小波系数作为检验统计量完成哨声端点粗检测,排除静默时间段与低强度脉冲干扰;在此基础上使用局部密度自适应谱聚类进一步区分哨声与强脉冲干扰,完成白鲸哨声检测。使用实采的白鲸信号测试该检测器性能并计算其F_(1)分数。该检测器在两段测试信号下分别获得了0.9487和0.9429的F_(1)分数,且在大数据量情况下明显优于由k-means聚类或传统谱聚类构成的检测器,具有更高的鲁棒性。

开放式超低场移动磁共振系统的电磁干扰抑制方法

为了发挥超低场磁共振成像可移动化的优势,传统的被动电磁屏蔽方法应该被主动电磁干扰抑制方法所替代。该文首先分析了电磁干扰传输路径并发现人体耦合为主要传输路径。针对性地设计了用以采集人体耦合电磁干扰的“戒指”型电磁干扰检测线圈,并配合平面及螺线管型线圈共同构成了电磁干扰参考通道。该文提出相关窗口概念:一定采集间隔内的参考电磁干扰信号仍有助于更加精确地估计某一时刻核磁通道电磁干扰信号。选定各通道K空间外围数据为校准数据,由核磁通道校准数据构建校准目标矩阵;由相关窗口内参考通道校准数据构建校准源矩阵。对上述两个矩阵进行小波分解后并通过最小二乘法求得各层转移系数。由参考电磁干扰信号在相关窗口内构建重构源矩阵,并由各层转移系数求得核磁通道电磁干扰拟合值。最后从受污染的核磁信号减去求得的拟合值,实现主动降噪。一维信号以及人体成像实验表明,该主动电磁干扰系统可大幅降低外界电磁干扰对图像质量的影响,使得磁共振扫描仪可在无屏蔽的开放环境中工作。

高频变压器传导共模干扰分析与评估

为了搭建适合工程批量应用的高频变压器共模抑制特性评估平台,分析变压器的共模噪声传导机理,研究变压器通道上共模噪声的传导特性,评估变压器对共模噪声的抑制能力。首先,通过函数发生器产生高频跳变电位信号,将其施加于变压器原边绕组以模拟变压器的共模噪声传输特性;其次,采用示波器捕捉共模信号在采样电阻上产生的电压降的值,判断变压器对共模噪声的抑制效果,分析评估平台中采样电阻的阻值选取对评估结果的影响;最后,对比评估结果与传导电磁干扰频谱的测试结果,验证所提变压器共模抑制特性评估方法的有效性。

仿真数据驱动的起重机钢丝绳断丝定量识别方法

针对工程应用中起重机钢丝绳损伤检测由于故障样本不足导致检测效果较差的问题,提出了一种仿真数据驱动的、基于卷积神经网络(CNN)模型的钢丝绳断丝定量识别方法。首先,使用有限元软件COMSOL对直径24 mm的6×37结构钢丝绳不同损伤类型进行了建模与仿真,并将提离值为5 mm处仿真漏磁场减去背景磁场,得到了仿真损伤信号;其次,搭建了钢丝绳漏磁检测试验台,采集了与仿真参数一致的钢丝绳断丝实测信号,并进行了小波去噪处理,解决了实测信号中由于存在噪声干扰导致与仿真信号不匹配的问题;最后,建立了卷积神经网络模型,采用仿真数据辅助模型训练,并使用早停法抑制了模型对训练集中仿真数据的过拟合问题。以仿真数据作为训练集和仿真数据辅助小样本实测数据作为训练集,进行了实验验证。研究结果表明:仿真数据驱动、小波去噪能够较大幅度地提高断丝识别率;早停法能够较好地抑制实验中的过拟合问题;该方法在两种实验形式下的准确率分别达到了84.5%和97.5%,证明该方法能够有效识别钢丝绳损伤,具有一定的理论研究价值和工程应用前景。

多定频干扰下准随机跳频信号检测仿真

多定频干扰环境的复杂性会对准随机跳频信号产生影响,导致跳频信号检测效果不佳。为了提升检测性能,提出多定频干扰下准随机跳频信号检测方法。对多定频干扰下的准随机跳频信号开展分析,获取跳频信号,并对信号实行小波阈值去噪处理;根据去噪处理结果,对准随机跳频信号开展傅里叶变换,求解跳频信号的局部自适应阈值,以此消除定频干扰,完成跳频信号提取;检测提取信号在时域的驻留连续性,区分跳频信号及可疑目标信号,实现多定频干扰下准随机跳频信号的检测。实验结果表明,通过开展信噪比测试、检测误差测试,验证了该方法的检测效果较好,说明其具有实用性和有效性。

基于小波能量熵的电磁式电压互感器绕组故障检测

电磁式电压互感器高压绕组层数多,绕组端部电场变化剧烈,长期运行极易导致绕组层间绝缘故障。为进一步提高绕组层间故障诊断的可靠性,提出一种基于冲击响应电压小波能量熵的电磁式电压互感器绕组绝缘检测方法。该方法采用高压脉冲波对正常电压互感器和故障电压互感器原边分别进行冲击实验,利用sym4小波对高压绕组冲击响应电压信号进行离散小波分解和重构以消除噪声信号的干扰,并用重构的信号计算小波能量熵,作为绕组层间故障诊断的特征参量。实验结果表明正常绕组与放电故障和短路故障绕组的小波能量熵区分度为86.5%和28.3%,可以有效判别绕组层间绝缘状态,根据故障绕组的小波能量熵值大小可以较好地区分故障类型。

信号峭度不定干扰下的电缆局部放电模式识别研究

电缆不同类型缺陷引发的放电故障受信号偏斜度、峭度的影响,造成电缆的局部放电信号模式识别效果较差。为此,在信号峭度不定干扰下,提出基于卷积神经网络的电缆局部放电模式识别方法。采用小波阈值去噪方法预处理电缆局部放电信号。运用双树复小波变换提取局部放电信号特征。通过提取偏斜度和峭度刻画信号的分布特征,可以解决信号峭度不定干扰问题。采用卷积神经网络训练提取的特征,并将该特征作为分类器完成电缆局部放电模式识别。试验结果表明,该方法的识别准确率高于95%、识别时间低于5.4 s。该方法应用后具有较好的电缆局部放电模式识别性能。

用于地下金属浅层探测的便携式频域电磁探测系统降噪方法研究

浅地表电磁探测的接收信号是十分微弱的,其受宇宙辐射电磁噪声、电源频率、谐波干扰以及工业电器噪声等环境因素影响,采用电磁感应法时不可避免地会受到线圈耦合的影响,会导致频域电磁系统信噪比低、一次场干扰严重且接收信号很容易淹没在噪声中。因此本文通过对差分模型的互感建模分析,提出了一种收-发线圈水平共轴差分式组合设计方案来去除一次场干扰;在系统采集模块提出了一种二次场数字正交矢量解调算法,用来提取电磁信号中的幅值和相位;在数据处理模块提出了一种小波阈值去噪技术,利用信噪比、均方根误差对实测数据与小波变换的去噪效果对比分析,最后基于上述技术设计相应的便携式频率域电磁地下金属探测原理样机系统。实验结果表明,水平共轴差分方案可以有效抑制一次场的干扰,数字正交矢量解调算法可以有效地从噪声信号中提取出有用信号的幅值和相位,通过对比分析小波变换,将系统信噪比提高了27.32 dB。本文研究成果对频率域电磁法探测系统提取二次场信号和对采集信号进行噪声去除具有实际应用价值。

变电站无人机自动化巡检系统抗电磁干扰设计

针对变电站无人机自动化巡检系统抗电磁干扰性能较差的问题,提出变电站无人机自动化巡检系统抗电磁干扰设计方法。该系统的抗电磁干扰总体框架包含抗电磁干扰子系统、无人机自动化巡检子系统,抗电磁干扰子系统能够自主感知巡检子系统遭受的电磁干扰程度、实时判定电磁干扰等级,达到预警线之上则控制地面发射功率,保障巡检数据被实时、完整回传至地面站;当机载接收器遭受电磁干扰时,采用小波阈值降噪法处理电磁干扰信号噪声,并搭建清除等效电流磁扰补偿模型,实现抗电磁干扰。实验结果表明,该方法能够将电磁干扰信号控制在安全范围之内,降噪处理后误差明显缩小,能够较好补偿电磁干扰信号,且信息传输性能极佳。

互感器检定装置整体检定技术综述

文章提出了一种互感器检定装置整体检定技术,从二次回路状态评估、电源校验技术、环境电磁干扰试验3个方面展开说明。该技术克服了传统单独检验部件的局限性,实现了测量用互感器检定装置整体性能的有效评估,在国内企业的推广应用中显著提高了产品质量,为电力系统的安全稳定经济运行提供了有力保障。

Wavelet diagnosis of ECG signals with kaiser based noise diminution

The evaluation of distortion diagnosis using Wavelet function for Electrocardiogram (ECG), Electroencephalogram (EEG) and Phonocardiography (PCG) is not novel. However, some of the technological and economic issues remain challenging. The work in this paper is focusing on the reduction of the noise interferences and analyzes different kinds of ECG signals. Furthermore, a physiological monitoring system with a programming model for the filtration of ECG is presented. Kaiser based Finite Impulse Response (FIR) filter is used for noise reduction and identification of R peaks based on Peak Detection Algorithm (PDA). Two approaches are implemented for detecting the R peaks;Amplitude Threshold Value (ATV) and Peak Prediction Technique (PPT). Daubechies wavelet transform is applied to analyze the ECG of driver under stress, arrhythmia and sudden cardiac arrest signals. From the obtained results, it was found that the PPT is an effective and efficient technique in detecting the R peaks compared to ATV.

Research on EMI Noise Measurement Technology Based on Wavelet Analysis

Aiming at the problem that it is difficult to measure the electromagnetic radiation produced by the equipment at present,this paper presents a method for measuring the noise of electromagnetic interference(EMI)based on wavelet analysis.The technique uses time frequency localization features of the wavelet transform,based on threshold function filtering method to filter the test signal,which makes it possible in open space or noisy environment for measurement of electromagnetic interference of equipment.Simulation and experimental results show that the technique is able to eliminate or attenuate the noise in the frequency band of 30Hz^1000MHz.

基于模糊小波的光照干扰图像对比度增强方法

为了增强在光照干扰环境下图像清晰度,提出基于模糊小波的光照干扰图像对比度增强方法。提取处于光线变化和干扰状态下的图像特征,根据特征提取结果,利用小波变换对光照干扰图像去噪后,分离图像高频与低频部分,采用双边滤波器去除照射分量的低频带,采用模糊增强算法对高频带上的图像纹理边缘进行增强,结合并非完全曲线归一化方法对处理后的图像对比度增强。实验结果表明,所提方法得到的图像边缘细节丰富清晰,直方图分布更均匀,在数字图像技术方面具有极高的应用价值。