用多项式模型和自适应滤波估计瞬时频率

本文论述了非平稳信号瞬时频率(IF)的估计方法,包括基干最小均方误差(LMS)算法或递推最小二乘(RLS)算法的自适应IF估计方法和基于信号相位多项式模型的IF估计方法。对各种估计方法的估计方差与理论方差下限进行了比较。说明了,基于互Wigner分布的估计方法所需信噪比(SNR)门限值最低。在低SNR、短信号记录的情况下,用多项式相位模型与最大似然法可以获得比较可靠的IF估计。     

音乐信号的时频分析

对已用于音乐处理上的主要时频（TF）分析方法进行了综述,并描述了它们的应用范围。在Cohen类框架下对技术方法进行检验,有助于新方法的设计和比较。所述内容涵盖了基音同步分析,短时傅立叶变换（STFT）,相位声码器．恒Q变换和小波变换,Wigner分布和模式分布。详细描述了窗函数法的局限性和对稳态假设、无限持续正弦曲线的依赖性。与窗函数法相反,Wigner分布用解析信号定义瞬时频率和功率参数,而模式分布是对优化的Wigner分布的线性变换。应用领域涉及分析、再合成、记谱、分类和识别、可视化。     

基于瞬时频率估计与Vold-Kalman滤波的铣削颤振识别

颤振严重制约了高速铣削加工效率。动态铣削力信号具有非线性、非平稳的特点,常规的信号分解方法难以处理该类信号。提出了一种基于瞬时频率估计和Vold-Kalman滤波的多分量信号分解方法,并运用该信号分解方法识别颤振。基于频谱集中性指标估计信号的瞬时频率参数;用Vold-Kalman滤波器提取对应参数的各信号分量;由于颤振时铣削力信号的能量分布在频域发生变化,由此引入能量熵的定义。采用分解得到的子信号能量熵变化来识别颤振。实验分析表明该方法有效可行。     

基于Crazy Climber的时频分析方法与应用

对于处理频率随时间变化的非平稳信号,传统的时域或者频域表示方法已经不能够满足需要。因此,时频分析成为分析时变非平稳信号的有效工具。基于Crazy Climber的时频分析方法对于一般时频分析方法的结果中出现的时频模糊现象具有明显的改进效果,有利于提高故障诊断过程中瞬时频率估计的准确性。尤其对于带有噪声的时频分布,可以在重新计算时频排列的过程中降低噪声的权值,使瞬时频率估计更加的准确。     

基于LMD结合WVD在瞬时频率测量中的应用

Wigner-Vill分布(WVD)能非常准确地测量单分量信号的瞬时频率,并具有很好的时频聚集性,但在测量多分量信号时会产生严重的交叉干扰项,混淆真实的频率成分。为消除WVD在测量非平稳信号瞬时频率时产生的交叉干扰项,并保存很好的时频聚集性,提出LMD和WVD相结合的方法测量非平稳信号瞬时频率。该方法使WVD同样适用于非平稳信号的瞬时频率测量中,极大地扩展了适用对象。通过实验及仿真分析表明:与直接用WVD测量瞬时频率相比,该改进方法能有效的消除测量过程中产生的交叉干扰项,且有效保留了WVD很高的时频聚集性的优点,从而更加精确的测量出原始信号的瞬时频率。     

时频面上基于瞬频估计的信号提取方法

针对多分量非平稳信号的噪声抑制和信号分离问题,提出了一种新的时频滤波法.采用FMmlet自适应分解将被分析信号在时频空间内展开,得到无交叉项干扰、时频聚集性很强,且能反映信号的线性或非线性结构的时频特性的时频分布.根据时频面内能量脊与瞬时频率的对应关系,采用谱峰检测和时频加窗轮流迭代的方法,估计出信号分量的瞬时频率.在瞬时频率精确估计的基础上,设计适当的时频滤波函数,对被分析信号的Wigner-Ville分布(WVD)进行时频加窗处理,得到单分量信号的修正WVD,然后采用 WVD反变换进行信号分量的时域重构,达到从非平稳信号中分离有用分量的目的.理论分析和仿真实验表明,利用该方法从复杂非线性时变信号中提取出的信号分量失真度小.该方法在非平稳信号的深层特征提取中具有良好的应用前景.     

基于改进峰值搜索法的旋转机械瞬时频率估计

提出了一种用于提取转子瞬时频率的改进峰值搜索法,并将该方法应用于旋转机械阶比跟踪。改进的峰值搜索法将瞬时频率中相邻两点一阶导数的差值作为搜索峰值是否合理的判别条件,避免了传统峰值搜索法在干扰信号作用下提取到的虚假峰值,提高了瞬时频率的估计精度。仿真实验表明,改进的峰值搜索法能够降低干扰信号对瞬时频率提取的影响,效果优于传统的峰值搜索法。用该方法对实测转子升速振动信号进行阶比分析,取得了良好的效果。     

基于瞬时频率转速提取算法的汽车排气噪声分析

对某卡车发动机排气噪声信号分帧处理,由短时自相关分析得到去除非转速相关随机噪声的信号序列,对该序列进行短时傅里叶变换得出时间-频率能量分布图;基于瞬时频率转速提取算法,利用改进谱峰值搜索法估计发动机瞬时频率进而得到转速曲线。利用该转速信息对原发动机排气噪声信号按等转速间隔切片进行谱阵图分析,确定发动机排气噪声与转速之间的对应关系,分析出主要阶次信息、敏感频率和转速,实现了基于瞬时频率估计转速提取算法的排气噪声分析,为排气系统的设计与优化提供理论参考。     

基于自动搜峰瞬时频率估计的自适应多阶比分析技术研究

提出一种利用自动搜峰的瞬时频率估计技术来实现旋转机械自适应多阶比分析(Adaptive Multiple Order Tracking,AMOT)的新方法。首先,通过时频分析得到振动信号的时频分布,根据频率峰值坐标自动选取搜峰起始点,自适应搜索出不同阶比分量的时频峰值。其次,利用最小二乘法将不同频率分量进行拟合实现瞬时频率估计,然后根据参考分量计算出重采样的鉴相时标对原始信号进行重采样,最后通过FFT变换实现阶比分析。该方法通过瞬时频率估计能够自动识别出所有阶比分量,实现优中选优,避免了传统算法中人为直观选取一个分量进行遮掩滤波提取分量的方法,减少了人为选取分量及起始点造成的误差,具有自适应性。并且无需同步采集转速信号,大大简化了应用条件,同时减少了人为因素,提高了分析精度,为旋转机械故障诊断提供了新方法。仿真实验和应用实例验证了方法的有效性。     

一种新的估计多项式相位信号瞬时频率的参数化时频分析方法

通过多项式非线性核函数取代线性调频小波变换中的线性核函数,提出一种新的参数化时频分析方法：非线性调频小波变换。对瞬时频率是时间任意连续函数的信号而言,选择合适的多项式核特征参数,非线性调频小波变换的时频分布有良好的时频聚集性。应用非线性调频小波变换分析任意阶次多项式相位信号。由于非线性调频小波变换的性能取决于多项式核特征参数,本文还给出非线性调频小波变换的核特征参数估计算法,进一步可实现多项式相位信号的瞬时频率和参量估计。仿真信号验证算法的有效性。     

Automatic Heart Disease Detection by Classification of Ventricular Arrhythmias on ECG Using Machine Learning

This paper focuses on detecting diseased signals and arrhythmias classification into two classes: ventricular tachycardia and premature ventricular contraction. The sole purpose of the signal detection is used to determine if a signal has been collected from a healthy or sick person. The proposed research approach presents a mathematical model for the signal detector based on calculating the instantaneous frequency (IF). Once a signal taken from a patient is detected, then the classifier takes that signal as input and classifies the target disease by predicting the class label. While applying the classifier, templates are designed separately for ventricular tachycardia and premature ventricular contraction. Similarities of a given signal with both the templates are computed in the spectral domain. The empirical analysis reveals precisions for the detector and the applied classifier are 100% and 77.27%, respectively. Moreover, instantaneous frequency analysis provides a benchmark that IF of a normal signal ranges from 0.8 to 1.1 Hz whereas IF range for ventricular tachycardia and premature ventricular contraction is 0.08–0.6 Hz. This indicates a serious loss of high-frequency contents in the spectrum, implying that the heart’s overall activity is slowed down. This study may help medical practitioners in detecting the heart disease type based on signal analysis.     

Measuring metastability and its effect on communication signalprocessing systems

New digital communication receivers often oversample an intermediate frequency (IF) or baseband signal at a very high rate (16 to 32 times the IF frequency or bit rate) as a means to demodulate the encoded data and synchronize the recovered clock. Unfortunately, an asynchronous data source can result in metastable errors and its effect on communications system performance has not been analyzed before now. Fortunately, our results demonstrate the vitality of 1-bit quantized IF high-speed digital signal processing. We review a practical measurement technique using a digital sampling oscilloscope that can be easily applied to today's digital signal processing systems. This method is used to collect data on a high-speed digital gate array technology used for a digital communication receiver, and the statistics of packet error rate are calculated. The analysis shows the substantial robustness of fast gate array logic and the importance of selecting the right technology. The technique and analysis presented can be applied to other digital systems     

基于全相位HHT的瞬时频率测量

全相位谱分析能够很好地抑制频谱泄漏、优化系统性能,其关键技术在于对数据进行全相位预处理。将这一技术运用于HHT求解瞬时频率中,提出了一种全相位HHT的瞬时频率测量算法,分析了全相位预处理和HHT求解瞬时频率的算法,将信号首先进行全相位预处理,然后用HHT算法求解信号的瞬时频率。这种算法是一种优化算法性能的算法,不会过多增加系统的计算量。通过对一非平稳信号分析,验证了基于全相位HHT的瞬时频率方差更小,具有更高的精确性。     

Extending the Bandwidth and Dynamic Range of Old RF Instruments to Meet State-of-the-Art Performance, Using a Synthetic Instrument Approach

A decrease in life cycle cost is a key issue for testing mobile communication systems. The rapid development and edge technology requires high-performance instruments and state-of-the-art measurement technology. New investments are expensive, but even older generation instruments are capable of extending their bandwidth and dynamic range to meet even the latest third-generation partnership project (3GPP) cellular measurement requirements by the addition of external hardware using a synthetic instrument approach. The novelty of this paper is the high performance on the most crucial parameters, i.e., the dynamic range and bandwidth achieved by only replacing some parts of the legacy instrument. Moreover, the demonstrated direct IF synthesis has a high degree of novelty at wide modulation bandwidths. It is desired to use virtual/synthetic instruments and make the signal processing in the software independent of the hardware, i.e., software-defined measurements (SDMs). In this paper, a state-of-the-art experimental setup for signal generation and signal analysis is demonstrated. A direct IF synthesis is used to generate a wideband code-division multiple-access (WCDMA) carrier with more than 72-dB adjacent carrier leakage ratio (ACLR) up to 12 parallel carriers with more than 68-dBc ACLR over a total bandwidth of 100 MHz. The signal analysis capabilities (e.g., ACLR performance) for a WCDMA carrier is better than -70 dBc and for a continuous wave better than -85 dBc over a bandwidth of 42.5 MHz. The critical RF downconverter in the setup is carefully designed not to degrade the dynamic range performance.     

Power Measurement in DVB-T Systems: On the Suitability of Parametric Spectral Estimation in DSP-Based Meters

Performance assessment and large-scale monitoring of terrestrial digital video broadcasting (DVB-T) transmission apparatuses are currently a pressing need due to the rapid growth of related broadcasting networks in many countries. Power measurements, in particular, play a very important role since RF and IF signal power, RF channel power, RF and IF power spectrum, noise (or unwanted) power, and power efficiency are relevant parameters to be measured as accurately as possible. Although modern spectrum analyzers and high-performance vector signal analyzers exhibit satisfying accuracy and repeatability, their cost, weight, and size make them unsuitable for the purpose. This paper is focused on the design and realization of a digital signal processing-based meter for power measurement in DVB-T systems that is capable of granting good accuracy, satisfying repeatability, reduced measurement time, and cost effectiveness. This paper deals with the digital signal processing algorithm to be implemented in the meter, paying attention to parametric power spectral density (PSD) estimators for their reduced memory requirement and potentially limited computational burden. In particular, a parametric estimation algorithm that is capable of assuring a fast measurement rate is implemented and made operative. The simulation and emulation stages are properly designed to regulate the most relevant parameters of the adopted PSD estimators according to the specific features of the signals involved; a number of experiments on actual DVB-T signals are conducted, the results of which are compared to those provided by competitive measurement solutions.      

基于能量重心法的列车轴承多普勒畸变故障声信号校正诊断研究

由麦克风采集的运动声源信号存在多普勒畸变现象,这极大的增加了对信号分析的难度,针对这一问题,本文提出了一种基于能量重心法的多普勒畸变校正方法,并将其应用在列车轴承故障诊断中。首先由基于能量重心法的瞬时频率（IF）估计（IFE）来获取IF向量,在莫尔斯声学理论的基础上,对IF向量进行非线性拟合,进而得到在时域进行重采样的时间间隔序列,再对原信号进行重采样处理,即可实现多普勒畸变的消除。最后本文做了一个仿真和列车轴承内外圈故障声信号的实验,分析的结果验证了此种方法的有效性。     

正弦扫描振动响应的时频分析

以一个正弦扫描振动响应信号为例,分别应用常用的正弦约减法与短时Fourier变换和Wigner分布进行了对比分析,讨论了在正弦扫描振动激励下结构响应的时频分析问题。结果表明,时频分析方法可以更好地揭示结构的非线性特性或由于层间间隙、连接不牢引起的碰撞等动力学行为,是一种更为有效的正弦扫描振动响应分析方法。     

宽带声学多普勒流速剖面仪的中频正交采样算法

宽带声学多普勒流速剖面仪(Broadband Acoustic Doppler Current Profile,BBADCP)发射由伪随机编码调制的正弦信号,信号带宽在频域上产生展宽,成为带通信号。宽带回波信号的处理多采用正交解调的方法,但此方法对采样率的要求较高,硬件较难实现。利用数字中频正交采样法来实现,大大降低了采样频率,并且针对BBADCP解模糊速度的要求,进行了宽带回波信号的仿真试验,结果证明插值的数字中频正交采样法适合于BBADCP的信号处理。     

大气湍流引起的特种激光外差通信系统相位起伏的研究

本文对特种激光外差通信系统接收中频信号相位受大气湍流随机起伏进行了实验测试。实验结果表明:该系统有助于克服大气湍流对接受中频信号相位的随机起伏,由大气湍流带来的随机相位噪声可以不予考虑。