具有自校准能力的随机采样技术的研究

为了提高数字存储示波器的可测信号带宽,常采用随机采样技术来获得更高的等效采样率.讨论了随机采样的实现方法,给出了一种具有自校准能力的实现方法,利用该方法来进行采样,可以在采集数据的同时完成校准,精确计算采样数据在波形中的位置,从而降低采样位置的测量误差.     

随机等效采样算法在数字存储示波器上的实现

由于受Nyquist采样定理的制约,数字示波器的测量信号带宽受到一定的限制。文中介绍了一种基于低速器件的高速数据采集技术——随机等效采样在数字示波器上的实现。给出了随机等效排序算法,提出了一次等效采样结束的判断方法。在开发400MHz高速数字存储示波器上,等效采样率达到10GSPS,时间测量分辨率达到100ps。文中给出了实时采样波形图和等效后的波形图。     

基于时间鉴别的随机等效采样短时时间测量方法

针对随机等效采样触发点与下一采样点间的短时时间测量存在测量精度不高、电路复杂问题,提出基于时间鉴别的短时时间测量方法。首先,构建基于边沿检测与窄脉冲扩展的时间鉴别电路,对短时间扩展以满足测量要求;其次,设计测时电路,将时间转化为电压进行测量,以提高测量精度。最后,搭建基于FPGA的随机等效采样短时时间测量实验系统。测试表明:该方法测量精度高且电路简单,采样系统波形重构效果好,满足了随机等效采样短时时间的测量需求。     

一种新型随机等效采样的实现方法

随着现代电子技术的发展,测试手段的提高,开发人员对数字存储示波器的采样率提出了更高要求。为了解决高速数据采集成本高的问题,提出了随机等效采样技术,并利用游标卡尺原理实现对触发时刻与下一采样时钟的时间测量,完成了等效采样率为10 G的采集模块的设计。该模块主要由触发时钟产生模块、采样时钟产生模块、等效采样测时模块与数据存储模块组成。该技术具有较高的实用性,并已应用于产品中。     

用模式匹配的转子振动信号同步整周期重采样方法研究

提出应用模式匹配的转子振动信号同步整周期重采样方法.该方法所用的信号为用等时间间隔同步采集的键相信号和振动信号.文中方法步骤为,先对键相信号进行傅里叶变换,获得大致的基频振动周期,然后根据振动周期提取匹配用波形,再沿着键相信号数据滑动求匹配波形与数据段的相似性来查找周期起止点,相似度大于设定的阈值的数据段存在周期起止点,然后将振动信号用三次样条在起止点间进行等数量插值,即得到同步整周期采样的数据.研究结果表明,该方法能准确地对振动信号进行同步整周期重采样,具有对信号采集设备要求低,相位误差小的优点,可用于转子振动信号整周期采样.     

随机采样技术在数据采集卡中的应用

论述了随机采样的基本原理,提出了利用随机采样技术提高数据采样率的一种方法.讨论了随机采样在数据采集卡中的具体实现并给出了相应的仿真波形.     

数字示波器的系统设计

为了对高速模拟信号进行不失真采集,系统以FPGA与ATMEGA16L单片机为核心,设计并制作了一台具有实时采样方式和等效采样方式的数字示波器。该示波器低频模拟信号采用实时采样方式,波形周期、频率测量准确及时,信号采集与存储方式灵活多样、操作方便;采用等效时间采样原理用较低速的A/D器件实现了高速的数据采集;采用模块化设计方法,使用了多种现代化EDA设计技术,较好地满足了设计要求。     

基于改进m序列的压缩采样观测矩阵设计

为了降低对嵌入式系统数据采集的硬件要求,提出了一种适用于模拟信号采集系统的压缩采样方法,为压缩感知观测矩阵提供了一种低功耗硬件实现方法。介绍了观测矩阵设计的相关要求,并提出了带压缩采样矩阵的高斯随机观测矩阵及基于改进的m序列的压缩采样矩阵硬件实现方法。考虑系统功耗及外围电路复杂度问题,提出利用MSP430微处理器完成压缩采样系统设计,并利用滚珠丝杠动态测试中的振动信号完成对系统的验证。实验结果表明,该系统能以低于亚乃奎斯特采样频率的采样率对振动信号进行压缩采样,能较为精确地重构出原始信号。     

基于FPGA的等效采样存储示波器设计

提出了一种应用于便携式数字存储示波器等效采样的实现方案.详细讲述了FPCA和微处理器LPC2138对高频信号随机等效采样的处理过程,利用一种全新的方法即主要利用FPGA内部逻辑单元完成对触发时刻到与下一采样时刻的时间间隔的测量.给出了FPGA对采样点的处理方法和LPC2138数据的处理及波形还原的软件处理过程.实现一个模拟带宽为1Hz～100MHz的手持式数字存储示波器.     

基于正交匹配追踪的周期非均匀采样研究

结合正交匹配追踪算法,提出了一种针对稀疏信号的周期非均匀采样与重构方法。根据周期非均匀采样的系统模型,基于联合子空间理论将采样与重构过程转换为矩阵向量运算;再借助正交匹配追踪算法确定采样数据矩阵中非零元素的位置,并分析了该算法在周期非均匀采样系统中的完整重构条件,通过插值器实现信号完整重构。最后,以多带正弦信号为例验证了可完整重构概率,系统实验证明:对于稀疏信号的采样与重构,该方法满足完整重构条件。     

浅表层伪随机编码超宽带探地雷达研制

伪随机编码信号因为有着较大的时间带宽积和良好的自相关特性,在探地雷达设计中有着广阔的应用前景。介绍了一套伪随机编码超宽带探地雷达的原理和具体实现方法。基于数字芯片的超宽带信号产生和采样方法,极大地降低了系统设计复杂程度,易于调试。串并转换技术实现了FPGA和高速DAC的数据速率转换。混合采样技术降低了实时采样率,从而降低了采样芯片成本。现场实验结果表明,伪随机编码超宽带信号可以有效地应用于探地雷达,可以在极低功率下实现对地下目标的探测识别。增加编码长度可以在分辨率不变的情况下增加发射能量,从而提高探测性能。     

Measuring displacement signal with an accelerometer

An effective and simple way to reconstruct displacement signal from a measured acceleration signal is proposed in this paper. To reconstruct displacement signal by means of double-integrating the time domain acceleration signal, the Nyquist frequency of the digital sampling of the acceleration signal should be much higher than the highest frequency component of the signal. On the other hand, to reconstruct displacement signal by taking the inverse Fourier transform, the magnitude of the significant frequency components of the Fourier transform of the acceleration signal should be greater than the 6 dB increment line along the frequency axis. With a predetermined resolution in time and frequency domain, determined by the sampling rate to measure and record the original signal, reconstructing high-frequency signals in the time domain and reconstructing low-frequency signals in the frequency domain will produce biased errors. Furthermore, because of the DC components inevitably included in the sampling process, low-frequency components of the signals are overestimated when displacement signals are reconstructed from the Fourier transform of the acceleration signal. The proposed method utilizes curve-fitting around the significant frequency components of the Fourier transform of the acceleration signal before it is inverse-Fourier transformed. Curve-fitting around the dominant frequency components provides much better results than simply ignoring the insignificant frequency components of the signal.     

A simple and efficient alternative to implementing systematic random sampling in stereological designs without a motorized microscope stage

When properly applied, stereology is a very robust and efficient method to quantify a variety of parameters from biological material. A common sampling strategy in stereology is systematic random sampling, which involves choosing a random sampling relevant objects start point outside the structure of interest, and sampling at sites that are placed at pre‐determined, equidistant intervals. This has proven to be a very efficient sampling strategy, and is used widely in stereological designs. At the microscopic level, this is most often achieved through the use of a motorized stage that facilitates the systematic random stepping across the structure of interest. Here, we report a simple, precise and cost‐effective software‐based alternative to accomplishing systematic random sampling under the microscope. We believe that this approach will facilitate the use of stereological designs that employ systematic random sampling in laboratories that lack the resources to acquire costly, fully automated systems.     

Automatic sampling for unbiased and efficient stereological estimation using the proportionator in biological studies

Quantification of tissue properties is improved using the general proportionator sampling and estimation procedure: automatic image analysis and non-uniform sampling with probability proportional to size (PPS). The complete region of interest is partitioned into fields of view, and every field of view is given a weight (the size) proportional to the total amount of requested image analysis features in it. The fields of view sampled with known probabilities proportional to individual weight are the only ones seen by the observer who provides the correct count. Even though the image analysis and feature detection is clearly biased, the estimator is strictly unbiased. The proportionator is compared to the commonly applied sampling technique (systematic uniform random sampling in 2D space or so-called meander sampling) using three biological examples: estimating total number of granule cells in rat cerebellum, total number of orexin positive neurons in transgenic mice brain, and estimating the absolute area and the areal fraction of β islet cells in dog pancreas. The proportionator was at least eight times more efficient (precision and time combined) than traditional computer controlled sampling.     

抽样定理在周期性非连续信号的压电泵气穴现象中的应用方法

抽样时间间隔由抽样定理来决定.压电泵气穴现象所摄取的连续画像也应遵从该定理来抽取得到不连续的静止画像.可是,作为由振动形式驱动的压电泵,气穴现象只发生在吸入工程,了解其气穴现象统计特性时,如果按着抽样定理,在吐出工程的半周期,即使是不发生气穴现象也必须依次抽样.若利用这样的数据系统,数据的样本将过大,对其解析的时间性与经济性均不利.而且,在吐出工程的半周期,是与气穴无关系的信号.因此对于气穴现象数据系统,可以说是输入了错误情报信号.为此,开发了适用于压电泵气穴现象周期性非连续信号的抽样定理的方法;同时,利用这个方法,以有阀压电泵为例,调查了该泵的气穴现象特性之一的中心多发性,发现里利用新方法测得的中心多发几率高于原方法.     

Using biased image analysis for improving unbiased stereological number estimation – a pilot simulation study of the smooth fractionator

The smooth fractionator was introduced in 2002. The combination of a smoothing protocol with a computer‐aided stereology tool provides better precision and a lighter workload. This study uses simulation to compare fractionator sampling based on the smooth design, the commonly used systematic uniformly random sampling design and the ordinary simple random sampling design. The smooth protocol is performed using biased information from crude (but fully automatic) image analysis of the fields of view. The different design paradigms are compared using simulation in three different cell distributions with reference to sample size, noise and counting frame position. Regardless of clustering, sample size or noise, the fractionator based on a smooth design is more efficient than the fractionator based on a systematic uniform random design, which is more efficient than a fractionator based on simple random design. The fractionator based on a smooth design is up to four times more efficient than a simple random design.     

液压系统压力信号无线数据传输优化

针对现有系统数据吞吐量低、采样频率低而无法满足液压系统压力测量要求的问题,通过详细分析其采样传输过程的原理,提出对采样数据打包、改进SimpliciTI协议、提高微控制器时钟频率和合理调整采样时间等方法来提高系统数据吞吐量。最后,分别用标准三角波信号和实际液压系统的压力信号对优化后的系统进行了性能测试。结果表明,系统的数据吞吐量可达76.8kbit/s,且数据采样均匀性良好。     

基于神经网络代数算法的电子罗盘的标定

为了标定KVH-C100型电子罗盘,分析了电子罗盘产生误差的原因,设计了电子罗盘信号采集的软硬件系统;为了减少随机因素的干扰,对采样数据进行了中值滤波;在此基础上,采用神经网络代数算法建立了电子罗盘的误差补偿模型,该模型能实现在样本空间的精确映射,具有较高的非线性逼近精度。通过实验证明该补偿模型比中值正弦误差补偿精度高,使得误差范围由标定前的-5.468 15°～1.457 96°减小到-0.492 8°～0.517 8°,重复性实验也证明该补偿模型一致性好,满足控制要求。     

采样定理的拓展--一种新的非均匀采样规则

由于采样定量用来指导采样时段内信号的均匀采样（或重采样），但在实际中需要进行磋均匀采样，因此提出了一种新的非均匀采样规则，即让短时采样频率大于等于2倍的信号短时最大频率，以指导非均匀采样（或重采样）。经用两个仿真信号验证说明，非均匀采样的数据用样条插值恢复只有很小的数值误差，说明该规则是可行的，并将它与传统的非均匀采样定理做了比较，指出了它面向时变信号采样的特点。     

基于压缩感知的新型声信号采集方法

介绍了一种基于压缩感知的声音信号采集方法,特别适合于无线传感器网络的声学监控应用,能够大大降低采样过程中对硬件采样速率和能量的需求,同时减轻了无线通信的负担,从而实现无线传感器的低成本化和实用化.利用声学信号在频域中的稀疏性质,在压缩感知相关理论的指导下设计了一种新型的随机压缩采样方法,实现了信号有用信息的高效获取;同时,利用加权L1 -magic算法对信号进行重构,完成完整的信号采集过程.仿真及实验表明,该方法能够实现在1/10以下标准采样频率下的声信号采集.