基于DP83640的秒脉冲移相器设计与实现

使用DP83640 IEEE 1588精密时间协议（PTP）收发芯片设计实现了一款秒脉冲精密移相器,它能与外部的标准秒脉冲（1 PPS）进行同步并进行精密相位微调,可应用于高精度相位微跃器。秒脉冲移相器采用DP83640芯片进行级联实现秒脉冲精密移相：利用ARM微处理器控制第二级DP83640实现与外部标准秒脉冲的相位粗调,控制第一级DP83640实现相位微调。相位调整时将外部输入的相位偏移量换算为8 ns整周期倍数的相位粗调值,以及不同时间长度档位的相位微调值,分别写入第二级和第一级DP83640共同实现高精度相位微跃。由于硬件电路特性和器件综合噪声的影响,经测试平均相位微跃准确度可以达到0.1 fs。     

超声振动载荷下合金的疲劳裂纹扩展性能研究

本文应用超声共振试验技术研究了4种工程常用合金(Astroloy, 17-4PH, Ti-6Al-4V, Al-Li8090)在超声振动载荷(f=20kHz, R=-1)下的疲劳裂纹扩展性能, 并与常规疲劳载荷(f≤50Hz, R=0.7)下材料的有关性能做了对比分析。对超声疲劳载荷下材料损伤及裂纹扩展机理的特点做了研究, 给出了这种特定载荷形式下应力强度因子的计算方法。研究结果表明, 超声疲劳载荷下各种合金的裂纹扩展性能与常规疲劳试验中确定的有效应力强度因子△Keff类同。      

基于dSPACE的频率特性测试与模型辨识研究

为了满足伺服控制系统设计需要,提出了一种利用dSPACE系统对被测对象进行频率特性测试与模型辨识的方法,对该方法所使用的激励信号与响应数据处理进行了研究。利用dSPACE硬件平台产生离散正弦扫频信号,利用软件合成的方法实现相关分析运算,使用Matlab进行数据处理,完成被测对象频率特性曲线绘制,采用Levy方法进行了模型辨识。应用结果表明,该方法使用方便,对传递函数具有较高的辨识精度,可以为控制算法设计提供理论依据。     

光纤频标传递的稳定性分析

光纤是进行长距离、高精度频标传递的理想介质,为达到更好的传递效果,分析了光纤频标传递系统的稳定性能,找出了影响频标稳定度的主要因素,进行了稳定性的仿真计算,并得出了与相关精密测算一致的结果。结果表明,几种主要因素的影响大小均与频标的中心频率无关,强度噪声是影响频标稳定性的最大因素,控制信噪比是提高稳定性的关键所在。     

高动态跳频信号时钟同步设计与实现

由于跳频信号各跳之间的符号速率和符号数量不一致,特别是低速跳只含少量符号,导致时钟误差提取困难。针对高动态下的跳频信号时钟同步难题,提出基于频偏估计的钟偏反馈调整方法。该方法通过同步序列进行频率估计和钟偏估计,并结合反馈方法调整钟偏和时钟跟踪,实现了高精度时钟同步。仿真结果表明：该方法适应飞行速度7.9 km/s、加速度0.2 km/s²的超高动态,定时同步性能优越,定时精度满足高速跳频信号解调要求,且解调损失小于0.1 dB。     

用相位计测量群时延的方法和技巧

介绍用相位计测量群时延的方法和技巧。通过分析和实验,给出了两种便于操作的测量方法,特别是利用第二种方法的测试技巧,把对时延的测量转换为对频率的测量,提高了测量准确度,使测量过程简便可行。     

利用小波方差进行原子钟频率稳定度的估计

离散小波变换可以在不同尺度上分解时间序列,而不同尺度的波动性可用小波方差来表征。从小波方差的定义入手,系统地归纳了基于极大重叠离散小波变换(MODWT)的小波方差估计方法,及其等效自由度(EDF)的实用计算方法。最后利用一个实测算例进行计算分析,并与相应的重叠阿伦方差、重叠哈达玛方差进行比较,通过实验分析可以看出小波方差可有效消除原子钟信号非线性和非平稳性的影响,通过选择适当的小波基函数,如D4、D6小波,其方差可以像哈达玛方差一样,减少调频闪变噪声和调频随机游走噪声的泄露,适用于原子钟频率稳定度的表征。     

Force measurement using strain-gauge balance in shock tunnel based on deep learning

When a force test is conducted in a shock tunnel, vibration of the Force Measurement System (FMS) is excited under the strong flow impact, and it cannot be attenuated rapidly within the extremely short test duration of milliseconds order. The output signal of the force balance is coupled with the aerodynamic force and the inertial vibration. This interference can result in inaccurate force measurements, which can negatively impact the accuracy of the test results. To eliminate inertial vibration interference from the output signal, proposed here is a dynamic calibration modeling method for an FMS based on deep learning. The signal is processed using an intelligent Recurrent Neural Network (RNN) model in the time domain and an intelligent Convolutional Neural Network (CNN) model in the frequency domain. Results processed with the intelligent models show that the inertial vibration characteristics of the FMS can be identified efficiently and its main frequency is about 380 Hz. After processed by the intelligent models, the inertial vibration is mostly eliminated from the output signal. Also, the data processing results are subjected to error analysis. The relative error of each component is about 1%, which verifies that the modeling method based on deep learning has considerable engineering application value in data processing for pulse-type strain-gauge balances. Overall, the proposed dynamic calibration modeling method has the potential to improve the accuracy and reliability of force measurements in shock tunnel tests, which could have significant implications for the field of aerospace engineering.     

核磁共振陀螺中内嵌碱金属磁力仪研究

核磁共振陀螺利用核自旋的闭环磁共振实现角速度的测量,其磁共振信号一般由内嵌碱金属磁力仪测出。为了提高磁力仪性能,对描述磁力仪的Bloch方程,采用微扰迭代法和级数展开法,求出了各磁矩分量的近似解,然后讨论了线性测量范围随纵向与横向弛豫时间的变化规律以及频率响应特性。利用数值仿真,对上述近似解析解进行了验证。结果表明,磁力仪的线性测量范围随纵向、横向弛豫时间的增大而减小,其频率响应为一阶低通,截止频率仅与横向弛豫时间有关。上述研究对核磁共振陀螺的优化有一定的参考意义。     

Oblique shock train motion based on schlieren image processing

In this paper, shock train motion in a Mach number 2.7 duct is studied experimentally, and large numbers of schlieren images are obtained by a high-speed camera. An image processing method based on Maximum Correlation Detection (MCD) is proposed to detect shock train motion from the schlieren images, based on which the key structures, e.g., separation positions and separation shock angles on the top and bottom walls, can be analysed in detail. The oscillations of the shock train are generated by rhombus and ellipse shafts at various excitation frequencies. According to the analysis of MCD results, the distributions of the frequency components of shock train oscillation generated by the two shafts are distinctly different, in which the motion generated by the ellipse shaft is much smoother; shock train motion is mainly characterized by the oscillation of separation position while the separation shock strength is not so sensitive to downstream disturbance; there is a hysteresis loop relation between the downstream pressure and separation position.