基于高阶滤波的闪电电场测量与波形校正

为提高对闪电辐射电场瞬态高频分量的探测能力,抑制环境工频噪声影响,本文设计了一种基于高阶滤波的闪电电场测量系统,对于高频通带内信号,其灵敏度为12.11 V/(m/V),最小可以识别0.1 V/m的脉冲电场信号,对工频噪声的抑制可达41 dB.另一方面,为克服高阶滤波作用带来的测量电场低频失真问题,提出了一种直接根据传感器电路参数构造系统函数的波形校正方法,对失真的低频信号进行补偿.通过模拟数值和实测数据的验证分析可知,利用提出的高阶快天线测量系统以及重构方法,既可以观测得到微弱的闪电电场变化事件,又能够在一定程度上补偿波形的低频失真成分,可应用于多站闪电定位以及雷电放电参数的反演估计.     

高精度非接触测量转速新方法研究

本文研究一种高精度非接触测量转速的新方法,用激光CCD位移传感器采集数据,用小波多频分析方法对信号的低频信号和高频噪声进行分离,依据奈奎斯特采样定理将分离后的低频信号进行频率提取,得到要测量的转速.实验证明该测量方法有很好的实用价值.     

基于SVD的涡街流量计信号处理方法

针对涡街信号处理中振动干扰及噪声信号难以分离的问题,提出一种基于奇异值分解(SVD)的信号处理方法。在获取涡街传感器输出的两路差分信号的基础上,利用噪声系数对两路信号进行合成,并采用SVD对信号的主要频率成分进行分解。通过对涡街信号幅频关系的分析,将有效信号分量从分解出来的频率成分中提取出来,进而计算出信号的频率。测试结果表明利用SVD可以有效提取信号中的主要频率成分,滤除杂乱噪声及振动干扰信号,提高涡街流量计信号处理的准确度与抗干扰性。     

基于HHT的多MEMS陀螺信号融合算法研究

基于经验模态分解方法将多MEMS陀螺信号分解为一列本征模态函数和残差函数,并采用希尔伯特变换求取其瞬时频率和瞬时能量.首先,通过本征模态函数与原信号的非线性相关系数分析来实现MEMS陀螺信号噪声的滤波处理;然后,以非线性相关信息熵作为优化指标,通过选取不同本征模态函数的组合进行加权融合,优化结果能有效地提高信号的测量精度;最后,通过仿真结果验证了所提出方法的有效性.     

基于特征向量盲分离的多频微弱信号检测方法

研究了低信噪比条件下混合信号的盲分离,针对实际探测的微弱信号常常是多个频率微弱信号共存的情形, 进行了利用特征向量盲分离检测多个频率周期性微弱信号的研究, 以便把利用特征向量盲分离的微弱信号检测应用于信号处理中微弱信号的提取.该方法首先建立混合信号阵元接收模型,利用多路传感器信号盲分离提取有用信号,达到微弱信号检测的目的.仿真和实测数据试验结果表明,此方法可检测出湮没在强噪声环境中的微弱信号的幅度和频率,在-30dB极低信噪比下恢复出了多个弱信号,具有很高的可靠性.     

小波阈值消噪在管道漏点检测定位中的应用

为了提取管道漏声信号中的有用成分,消除和减弱环境干扰噪声,使定位结果更加准确,使用CA - YD - 103压电传感器和HS801五合一虚拟综合测试仪进行实验,采集铸钢管道漏声振动信号,分析其时域波形和频率特征,确定了信号的频率分布.由于小波变换具有“变焦距”的性质,适合处理非平稳信号,选用小波阈值去噪算法,对信号进行滤波去噪,并与ⅡR滤波效果对比.实验结果表明,选用小波阈值消噪能有效滤除高频干扰,保留中低频中的有用信号,漏声振动信号波形更加清晰,消嗓效果明显优于傅里叶算法.该方法为管道漏点具体定位奠定了基础,具有一定的实用意义与应用价值.     

基于虚拟仪器的直接频率合成器相位噪声测量

相位噪声是DDS（直接频率合成器）的一个重要测量指标。介绍了基于虚拟仪器技术,把各个测量仪器有机地组建成DDS相位噪声的自动测量平台。通过高速数字DIO卡对DDS内部各个控制寄存器进行配置,调节DDS输出波形的频率,利用信号分析仪的相位噪声测量软件对DDS输出波形的相位噪声进行测量,最后基于Labview语言和NI公司的Digital Waveform Editor数字波形编辑软件开发了DDS相位噪声的自动测量软件。该方案也可用于DDS其它特性参数的测试。     

滤波技术在地震次声波信号研究中的应用

次声波可以通过专门的仪器接收、转换并最终以二进制文件的形式存储,通过对其进行读取就可以获得次声波声压与时间的关系。根据显示出来的波形特征来判断是否包含跟地震相关的信号信息。但同时,次声波传感器所接收到的数据中会包含一定量甚至是大量的噪声干扰,影响了与地震相关的次声波信号的研究。本文将总结介绍噪声消除的一些常用方法及处理效果。     

基于MISEP算法的瞬时混合模型非线性电路的信噪盲分离

针对非线性电路信噪分离问题,提出基于互信息的信噪盲分离算法,用以对非线性电路的测量信号进行补偿.首先面向瞬时混合模型下的非线性电路,将用于计算分离信号的模块与用于调整参数的模块进行反馈级联,构造多层感知机网络;然后采用含随机噪声的电路测量数据,以最小互信息为目标对该网络进行训练,直至代价函数值收敛于预设的误差范围;最后利用训练好的网络进行非线性电路盲源分离问题的解算.对前非线性电路、后非线性电路和单级放大器的实验结果表明,该算法分离出的信号和噪声在时域波形和功率谱特征方面均与输入相符.     

利用小波分析检测航空发动机传感器故障

该文比较了傅立叶变换与小波分析的基本理论并研究了它们在航空发动机传感器故障检测应用中的特点,提出了一种基于小波变换的故障检测方法.该方法针对噪声和故障信号均具有呈现非平稳瞬态特性的特点,利用小波多分辨分析将量测信号分解到不同的频率通道中去,因此它就可以在一定的频率区间内,将故障信号成分和正常信号输出成分区分开来,提高传感器故障检测的准确度.仿真结果表明,该方法借助小波变换强大的时频分析能力,可以准确判定传感器软、硬故障,有效降低误报率和漏报率,具有良好的应用价值.     

The perceived urgency of speech warnings: semantics versus acoustics

The relationship between the semantics of words and the acoustics of the way they are spoken is explored. Actors spoke warning signal words in an urgent, nonurgent and monotone style, and participants rated the urgency of the words. Results showed effects for signal word and style of presentation. Acoustic analysis showed that the urgent words were spoken at higher frequency with a broader pitch range and were louder than the nonurgent or monotone words. These acoustic differences were used to synthesize artificial versions of signal words in urgent and nonurgent formats. The urgent words were rated as more urgent than the nonurgent words, a finding attributable to their differing acoustics. Within each speaking style the words were acoustically the same, yet effects for signal word were found, suggesting that semantics is also important in urgency perception. This research has implications for the design and implementation of speech warning systems, particularly those in which urgency mapping is required.     

解耦的声表面波波动方程的求解􀀂

由于压电材料对称性的存在,当一些压电材料取某些特殊切型时,声表面波存在着解耦现象,解耦波常有几种固定的模式.本文对解耦的声表面波波动方程的求解进行了研究.并以PZT-5H材料为例,用编制的程序对解耦的纯Rayleigh波和B-G波进行了计算机数值求解,其结果与文献[3]的值一致.说明这一求解原理和方法普遍适用于对各种解耦的声表面波波动方程的求解.对于全面分析SAW的传播特性具有一定的参考价值.     

基于神经网络方法的水声信号预测

由于海洋环境的复杂性和水声信道复杂的时变、空变特性，使得舰船辐射噪声是一种非平稳、非高斯过程。如能提前预测敌方舰船的辐射噪声，并有效地对敌进行水下对抗，先敌使用武器攻击，是克敌制胜的前提，也是我海军目前各型潜艇和水面舰艇急需解决的关键技术。文章根据水声信号的特点建立了预测模型和网络结构参数的设计。并分别采用BP神经网络和RBF神经网络对仿真信号和实际舰船水声信号进行预测。结果表明，利用神经网络预测水声信号达到了一定的效果，为今后进一步开展水声信号预测研究奠定了基础。     

HDD seeking acoustics analysis by a transfer function approach

A new approach to analyze HDD seeking acoustics is proposed. An acoustic transfer function was derived that has seeking current as input and seeking acoustics as response. The derivation and the advantage and limitation of this acoustic transfer function approach is discussed in details in this paper. HDD seeking acoustics is mainly determined by the seeking current spectrum and the mechanical design. The acoustics transfer function represents the mechanical design, and was used to diagnose trouble mechanical modes and to guide servo design to reduce specific seeking current frequency content. The acoustic transfer function approach also enables quick performance prediction of combination of different mechanical designs and seeking currents. Various HDDs with different seeking current profiles and mechanical designs were evaluated experimentally and numerically. Finally, a new seeking servo algorithm was evaluated, and good agreement was shown between the numerical prediction using the acoustics transfer function approach and the measured seeking acoustics.     

Helmholtz共振腔气动噪声数值仿真

为探究出一套完整、准确的气动噪声仿真方法,用FLUENT和Actran仿真Helmholtz共振腔旁接管道系统模型.针对流场仿真,采用六面体网格建模,分析选择合适的网格密度,明确网格及边界条件的影响,以获得准确的声源信息;运用Lighthill声类比方法对声场进行仿真,采用数值计算、传声损失仿真和气动噪声仿真计算等3种方法提取管道内部场点声压级频谱曲线,分析曲线峰值频率特征,包括共振频率分析和声模态分析等.采用CFD软件与声学仿真软件相结合的方法,可以有效进行流场和声场的仿真.     

Sound Tracing: Rendering Listener Specific Acoustic Room Properties

We present an acoustic rendering approach visualizing the listener‐specific contribution of frequency‐dependent pressure fields on a scene geometry with acoustic reflection and scattering properties. Our method facilitates the evaluation of simulated acoustics showing the effect of simulation parameters like absorption and scattering. The image‐based spatial localization of acoustic properties is complementary to the auditive evaluation by means of auralization. Our core contribution is a pressure‐based acoustic rendering equation and a corresponding raytracing method applying techniques from photorealistic rendering to the field of simulated room acoustics. Applications are directed at the visualization of interference patterns and analyzing the impact of acoustic reflection parameters.     

Fast method of interpolation for frequency estimation of sinusoidal and spindle data

Estimating the frequency of one or more sinusoidal waves is a problem belonging to the field of signal analysis. The frequency characteristics of sinusoidal waves can be measured by peaks or troughs of the waves. Because of (he limit of the sampling frequency, the peaks or troughs of sinusoidal and EEG waves in the sampling usually deviate from their original ones in the time domain. Starting from a sinusoidal wave analysis, we present a correction formula with which the deviation time t_d can be calculated so as to detect the position of the real peak or trough of the data as fast and as accurately as possible on the time axis. The wave of the sleep spindle in the EEG can be considered as an asymmetrical sinusoid. Then after the waves have been filtered, the formula can also be applied to analyse the spindle of EEG waves and it is shown to be useful in the measurement of the frequency of the spindle wave. Error analysis and practical examples are presented.     

Acoustic signal separation of mechanical devices using ICA with band-pass filters

We propose a method of separating the acoustic signals of motors and the gears of mechanical devices by using independent component analysis (ICA) with band-pass filters. The frequency distribution of a recorded acoustic signal from the operating mechanical device can be divided into three fields, the low-frequency field, which corresponds to the frequency characteristics of the gear, the medium-frequency field, which is mixed with the frequency characteristics of the gear and the motor, and the high-frequency field, which corresponds to the frequency characteristics of the motor. Since only the medium-frequency components are a mixture of the acoustic signals of gears and motors, ICA with band-pass filters is expected to separate the acoustic signals of motors and gears more accurately than conventional ICA. The simulation and experimental results show that the proposed method can separate the acoustic signals of motors and gears of mechanical devices successfully.This work was presented, in part, at the 9th International Symposium on Artificial Life and Robotics, Oita, Japan, January 28–30, 2004     

Finite-difference time-domain simulation of acoustic propagation in dispersive medium: An application to bubble clouds in the ocean

Accurate modeling of pulse propagation and scattering is a problem in many disciplines (i.e. electromagnetics and acoustics). For the case of an acoustic wave propagating in a two-dimensional non-dispersive medium, a routine 2nd order in time and space Finite-Difference Time-Domain (FDTD) scheme representation of the linear wave equation can be used to solve for the acoustic pressure. However when the medium is dispersive, one is required to take into account the frequency dependent attenuation and phase speed. Until recently to include the dispersive effects one typically solved the problem in the frequency domain and not in the time domain. The frequency domain solutions were Fourier transformed into the time domain. However by using a theory first proposed by Blackstock [D.T. Blackstock, J. Acoust. Soc. Am. 77 (1985) 2050. [1]], the linear wave equation has been modified by adding an additional term (the derivative of the convolution between the causal time-domain propagation factor and the acoustic pressure) that takes into account the dispersive nature of the medium. In the case of acoustic propagation through water, the water environment becomes strongly dispersive due to the presence of air bubbles that are present below the air-water interface.