基于FPGA的数字Costas环的设计与实现

通过对数字Costas环路原理的分析，提出了新的环路鉴相方式，且环路参数可根据锁定情况及时修改，确保锁相环路稳定工作。详细阐述了环路各部件的参数及电路设计。ChipScopePro实时观测FPGA内部信号和Matlab仿真结果表明．该Costas环路具有十分优良的性能。     

GPS/GLONASS双卫星接收机

本文介绍一种GPS/GLONASS双卫星接收机的设计和制造。该接收机从数字化跟踪的L波段(1.6GHz)-130dBm卫星信号提取数据。利用数字Costas环及全时早一晚码跟踪环跟踪输入信号并对扩频信号解码。对卫星数据解码并将用于定位和时间传递的各种必要参数记录下来。     

基于遗传算法参数优化的变分模态分解结合1.5维谱的轴承故障诊断

为了准确提取轴承的故障特征,提出了一种遗传算法(GA)参数优化的变分模态分解(VMD)结合1.5维谱的轴承故障诊断方法。首先以VMD方法中模态分量的包络熵值最小为优化目标,利用遗传算法对模态分量个数和二次惩罚因子进行优化,确定这两个能使VMD实现最优分解的输入参数。然后利用参数优化的VMD方法对仿真信号和轴承内环故障信号进行分解,并做各模态分量的1.5维谱图。参数优化的VMD分解得到了与仿真信号原始分量相符的4个模态分量,1.5维谱剔除了未参与二次相位耦合的10Hz频率分量。同时在1k Hz频率以下,运用本文方法提取了轴承内环故障特征频率的1至6倍频频率成分以及电机转频对它们的调制频率。由此表明,遗传算法参数优化的VMD可实现复杂信号的正确分解,1.5维谱可有效检测信号的二次相位耦合。同时,遗传算法参数优化的VMD结合1.5维谱能有效提取轴承内环故障特征,从而验证了本文方法的有效性和实用性。     

基于循环统计量的直升机齿轮箱轴承故障早期检测

在分析齿轮箱振动信号的基础上,提出了基于循环统计量的轴承故障早期检测方法,阐述了表征故障的一维和二维循环平稳特征。该方法利用信号与噪声具有不同循环频率的特性实现了信噪分离,能够比较容易地从复杂背景中提取出微弱的特征信息。最后在某型直升机齿轮箱轴承故障的早期检测中进行了实验验证。结果表明,该方法优于功率谱和解调分析,能够提取故障的早期特征。     

基于LMS格型算法的自适应参数谱估计方法

研究了自适应参数谱估计的基本原理,提出了基于最小均方误差（MMSE）准则的LMS格型滤波算法实现自适应参数谱估计的方法。通过对仿真测试信号和线性调频信号的计算表明,该方法能够在改善谱分辨率的同时提高运算效率,满足遥测速变信号的处理和分析计算的要求。     

基于加强谱峭度的航空发动机齿轮毂故障诊断

针对航空发动机减速器一级齿轮毂故障诊断问题,提出了一种基于小波包和CHI-LMD(三次Hermite插值-局部均值分解)的加强谱峭度的故障诊断方法。在用AR(自回归)参数模型对原始信号进行降噪后,首先采用小波包对信号进行分解,并结合谱峭度找出特征频带,继而用CHI-LMD对特征频带进行再分解获得若干PF分量,最后对获得的PF分量计算谱峭度作为故障识别参数。利用此方法对10组待识别信号的诊断结果表明,该方法能有效识别减速器一级齿轮毂故障,在不拆卸发动机的情况下实现了对目标的诊断。     

基于强抗噪威格纳威利分析的滚动轴承故障诊断

为了解决威格纳威利谱(Wigner-Vile spectrum, WVS)时频分析方法对受强背景噪声影响下的滚动轴承冲击性故障信号特征提取难的问题,根据滚动轴承发生故障时呈现出的循环平稳特征,将基于2阶循环统计量的循环谱密度算法(cyclic spectral density, CSD)与WVS相结合,提出基于CSD的WVS分析方法,即循环谱密度威格纳威利谱(CSDWVS)时频分析方法。经仿真及实验验证,相对传统WVS分析方法,该方法能有效提取出强背景噪声影响下的滚动轴承内圈故障特征频率为51.9 Hz及外圈故障特征频率为32.1 Hz。      

随机载荷谱下基于声发射的耳片接头疲劳裂纹识别方法

作为航空结构中传递集中载荷的关键部件,耳片接头的失效将会带来灾难性的后果,因此需要通过疲劳试验来验证其是否满足设计要求。声发射（AE）作为一种在线监测手段,能够及时捕捉接头裂纹萌生扩展进程,提升试验质量。然而,在随机载荷谱下,会产生大量极其复杂且毫无规律的声发射信号,致使传统的基于特征提取及参数滤波的声发射数据分析方法难以发挥作用,无法有效识别接头裂纹的萌生。因此,本文提出了一种随机载荷谱下疲劳裂纹的声发射识别方法,该方法利用随机载荷谱的分布特点,通过分析不同载荷谱块下相同循环时段所对应的声发射信号表象差异来发现、锁定异常,并结合定位分析与干扰排除分析,确定裂纹的发生时间及位置。通过疲劳试验,该方法的有效性得到了证实,因而可为随机载荷谱下的相关航空结构试验提供参考。     

基于线调频小波路径追踪阶比循环平稳解调的滚动轴承故障诊断

针对变转速工况下滚动轴承的故障诊断问题,提出一种将线调频小波路径追踪算法与阶比循环平稳解调方法相结合的滚动轴承故障诊断方法.该方法先利用线调频小波路径追踪算法提取轴承的故障特征频率,再根据轴承的故障特征频率对变转速下时域振动信号的包络在角域等角度重采样,并对获取的角域平稳信号进行循环平稳解调,计算得到切片解调谱;最后根据切片解调谱识别滚动轴承故障.仿真分析和应用实例表明:该方法能准确提取变转速工况下滚动轴承的外圈与内圈故障故障特征,提取效果明显优于基于Wigner-Ville峰值跟踪法的包络阶次谱方法.      

连续变速颤振试验信号处理的递推时频分析方法

针对连续变速颤振试验信号的非平稳特点及在线分析需求,提出了一种递推时频分析方法。该方法利用自适应算法跟踪一个时变系统,从而获得具有时变系数的参数化数学模型,进而可得到信号的时变参数谱。数值仿真结果证明了该方法的可行性与优越性,低速风洞气弹模型的连续变速颤振试验验证了该方法的工程应用前景。     

Staggered Costas Signals

A radar signal, based on coherent processing of a train of staggered Costas bursts, is suggested and investigated. The selection of sequences of each burst is based on a minimum number of collocation of their individual ambiguity function sidelobe peaks. The resulting ambiguity function combines qualities of both "thumbtack" and "bed of nails" signals. Comparison with linear-FM, V-FM, and complementary phase coded (CPC) signals is given, as well as comparison with hybrid signals consisting of both phase and frequency coding.     

Cross-correlation properties of algebraically constructed Costasarrays

The problem of determining the cross-correlation properties of signals based on algebraically constructed Costas arrays is addressed by examining the discrete cross-correlation of the algebraically constructed Costas arrays for a given construction and dimension. Finding two arrays that minimally correlate implies that the signals based on these arrays also minimally correlate. The properties of finite fields are reviewed, and the major algebraic constructions for Costas arrays are presented, i.e. the Welch construction and the Golomb construction. The discrete cross-correlation properties of the Costas arrays are derived for arrays of the same dimension derived from the same construction. The use of Costas arrays in the signal design problem is discussed, and examples are given to show the cross-correlation of the signals based on the algebraically constructed arrays     

基于Birge-Massart阈值降噪与EEMD及谱峭度的滚动轴承故障特征提取

针对传统共振解调方法易受噪声干扰导致故障特征提取效果不佳的问题,提出了一种基于Birge-Massart策略的阈值降噪与集成经验模态分解(EEMD)和快速谱峭度算法相结合的滚动轴承故障特征提取方法。对原始故障信号进行EEMD并采用峭度准则筛选出含有故障信息的本征模态函数(IMF)分量;采用Birge-Massart策略和快速谱峭度对故障信号进行滤波降噪;对滤波后信号进行Hilbert包络解调,提取轴承故障特征。采用该方法分别对仿真信号和实验信号进行特征提取,结果表明该方法可以有效提高故障信号信噪比,清晰准确地获取轴承内、外圈故障的频率特征。利用峭度因子准则筛选IMF分量能有效保留原始故障信号中的冲击特征,去除无关IMF分量的影响。      

Research on Feature Extraction of Remnant Particles of Aerospace Relays

The existence of remnant particles, which significantly reduce the reliability of relays, is a serious problem for aerospace relays. The traditional method for detecting remnant particles—particle impact noise detection (PIND)—can be used merely to detect the existence of the particle; it is not able to provide any information about the particles’ material. However, information on the material of the particles is very helpful for analyzing the causes of remnants. By analyzing the output acoustic signals from a PIND tester, this paper proposes three feature extraction methods: unit energy average pulse durative time, shape parameter of signal power spectral density (PSD), and pulse linear predictive coding coefficient sequence. These methods allow identified remnants to be classified into four categories based on their material. Furthermore, we prove the validity of this new method by processing PIND signals from actual tests.     

基于时频脊线和阶次分析的转子故障诊断

为解决采用在转子升降速过程中产生的非平稳信号难以进行故障诊断的问题,提出一种基于2维时频脊线和阶次分析的转子故障诊断方法。采集转子升降速信号,采用2维时频分布的峰值脊线提取法获得信号脊线特征,结合脊线特征与等角度重采样技术依次获得信号角度域、角-阶域和阶次域图像,将信号阶次域内的特征参数作为故障敏感特征,输入人工神经网络诊断模型,对转子信号的故障类型进行分类。利用实测信号验证所提方法的实际应用效果,并与传统特征提取法的结果进行对比。结果表明：阶次分析方法的测试准确率约为99.8%,标准差小于0.09%,均优于传统特征提取法。基于时频脊线和阶次分析的转子故障诊断方法具有更高的诊断准确率,在非平稳信号特征提取过程中具有很好的可行性和准确性。     

基于经验模态分解的航空器结构模态参数识别

介绍了一种基于经验模式分解（Empirical Mode Decomposition,EMD）与粒子群优化算法相结合的飞机结构模态参数辨识方法。一个复杂的脉冲响应信号利用EMD方法使得耦合在一起的多阶模态响应信号分解为与各单阶模态响应信号一一对应的分量,得到前几阶主要的内禀模式函数（Intrinsic Mode Function,IMF）,再对分解得到的每一单阶IMF利用粒子群算法辨识得到各阶模态参数。试验仿真结果表明该方法有较高的计算精度,可应用于结构运行模态分析,为飞机等结构设计、运行检测提供有力保障。     

基于稀疏表示的多雷达信号二维融合处理

多雷达信号融合通过对多视角和多频带雷达信号进行相干融合,可以提高图像的距离和方位向分辨率.为了克服基于谱估计的多雷达信号融合方法稳健性严重依赖于散射点个数估计精度和二维极点配对精度的问题,在深入研究逆合成孔径雷达(ISAR)信号的基础上,构造了多雷达信号二维融合的线性表示模型,将融合处理转化为一个信号表示问题;充分挖掘...     

Family of multicarrier bi-phase radar signals represented by ternary arrays

A K times L ternary array, comprised of the elements {0, 1, - 1}, with some unique features, represents a multicarrier radar signal with favorable autocorrelation and ambiguity functions. Constructing such an array using Galois fields is described. As in a Costas binary array, only one frequency is transmitted at any time slot, but in our array the same frequency is repeated in several time slots, yielding a signal with considerably larger pulse compression than a Costas signal that uses the same number of frequencies     

Carrier-Tracking Loop Performance for Quaternary and Binary PSK Signals

By expressing the open-loop response voltage as a Fourier series in terms of the phase-tracking error and then utilizing a very useful mean-value expression, we assess the performance of loops suited to recovering the carrier of four-phase (quaternary) and two-phase (binary) phase-shift-keyed (QPSK and BPSK) signals. At high signal to noise ratios (SNRs) they perform comparably, but at low SNRs the former's performance deteriorates much more rapidly. The loop's ability to maintain the carrier frequency despite the noise accompanying the PSK signal is measured by the mean and the variance of the oscillator's control voltage. In particular, Spilker's loop for QPSK and the Costas loop for BPSK signals are discussed.