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A study for the sensor system based on the spatio-temporal gradient analysis

基于时空梯度分析的传感器系统研究

基本信息

批准号：
17560375
负责人：
TERAMOTO Kenbu
金额：
$ 2.18万
依托单位：
Saga University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
2005
资助国家：
日本
起止时间：
2005 至 2007
项目状态：
已结题

项目摘要

1: The first result presents an autonomous directivity microphone system based on the newly proposed spatio-temporal blind source separation. The blind source separation principally uses no a priori knowledge about parameters of convolution, filtering and mixing. In the simplest case of the blind source separation problems, observed mixed signals are linear combinations of unknown mutually statistically independent, zero-mean source signals. The blind signal separation algorithm utilizes the linearity among the four signals: (1) the sound pressure, (2) x, (3) y, and (4) z-directional particle velocities, all of which are governed by the wave equation and the equation of motion. The proposed method, therefore, has an ability to simplify the convolution blind source separation problems into the instantaneous blind source separation over the spatiotemporal gradient space. 2. The second result presents an opt-acoustical measurement of non-invasive measurement over the acoustic wave-field. … More In this study, a novel method for grading vector measurement of the sound pressure-field is proposed. The proposed method has an ability to capture the projection of the gradient vector of acoustic wave-field through the eccentricity of the 0th-order Fraunhofer diffraction. In this study, the theoretical analysis of the process of the above projection is discussed and their physical meanings are investigated through numerical experiments and acousto-optical experiments. 3. The third result presents the eigenvalue imaging method to be independent of frequency and phase velocity and to characterize the wave field where incident and scattered waves overlap each other. For detecting the defects, spatio-temporal gradient analysis based on the linear dependency among the vertical displacement, the vertical particle velocity, and a pair of shear strains is used. The following conclusions and remarks are conducted: (1) Eigenvalue Imaging based on the spatio-temporal gradient analysis is proposed as a novel NDE method. (2) The third eigenvalue detects a wave scattered by defects. (3) The fourth eigenvalue has an ability to localize defects. Less

1：第一个结果提出了一个自主指向性麦克风系统的基础上新提出的时空盲源分离。盲源分离主要是利用卷积、滤波和混频参数的先验知识。在盲源分离问题的最简单情况下，观测到的混合信号是未知的相互统计独立的零均值源信号的线性组合。盲信号分离算法利用四个信号之间的线性：（1）声压，（2）x，（3）y和（4）z方向粒子速度，所有这些都由波动方程和运动方程控制。因此，所提出的方法，有能力简化卷积盲源分离问题的时空梯度空间上的瞬时盲源分离。2.第二个结果提出了一种在声波场上进行无创测量的光声测量。 ...更多信息在这项研究中，提出了一种新的声压场的分级矢量测量方法。该方法能够通过0阶夫琅和费衍射的偏心率来捕捉声波场梯度矢量的投影。本文对上述投影过程进行了理论分析，并通过数值实验和声光实验研究了它们的物理意义。3.第三个结果提出了本征值成像方法是独立的频率和相速度和入射波和散射波相互重叠的波场的特征。对于检测的缺陷，时空梯度分析的基础上的线性依赖之间的垂直位移，垂直粒子速度，和一对剪切应变。本文的主要工作和结论如下：（1）提出了一种基于时空梯度分析的特征值成像无损检测方法。(2)第三特征值检测由缺陷散射的波。(3)第四特征值具有定位缺陷的能力。少