工程实践背景下的周期性方波信号分解与合成

在分析了周期性信号的傅里叶级数分解的意义和方法的基础上,设计了方波信号分解与合成的硬件电路系统,整个电路由方波振荡电路、分频与滤波电路、信号调理电路、移相电路、信号叠加电路等电路构成。本电路系统实现了由基波、三次谐波和五次谐波合成近似的方波,效果良好。实践证明,学生通过动手操作加深了对周期性信号分解与合成的理解,培养了学生的工程实践能力。     

一种直接利用连续时间非周期信号的频谱计算相应周期序列的频谱的方法

提出了直接利用连续时间非周期信号频谱计算相应周期序列频谱的方法。利用函数逼近冲激函数时,其曲线下的面积保持不变的特性,证明了周期冲激信号的频谱具有离散性、谐波性和均匀性。以此为基础,首先导出了连续时间非周期信号频域分解的表达式及其频谱计算公式,然后导出了非周期序列的频域分解表达式及其频谱计算公式,周期序列的频域分解表达式及其频谱的计算公式,最后给出了利用连续时间非周期信号的频谱来计算相应周期序列的频谱的方法。     

一种新的随机共振模型的电路设计与信号检测实验研究

基于一种新的分段混合随机共振模型,设计实现了信号检测硬件电路;对不同噪声强度背景下的微弱周期信号进行了随机共振信号检测实验研究和分析;在相同参数和相同输入信号条件下,将该电路和连续双稳系统电路进行了信号检测效果对比实验。结果表明,该电路可以实现噪声背景下的微弱信号检测,在强噪声背景下,检测效果优于连续双稳系统。     

谱跟踪和噪声模型语音信号分析/合成方法

把语音信号分解为确定和随机两部分是非常典型的语音信号分析与合成方法。针对目前主流研究的谐波加噪声模型(Harmonic plus Noise Model, HNM)和准谐波模型(Quasi-Harmonic Model, QHM)法等存在冗余大的问题,提出了一种基于谱跟踪和噪声模型的语音信号分析/合成方法。以音素为基本单元进行编解码,用谱跟踪法提取时变特征合成语音信号的确定部分,用AR模型合成语音信号的随机部分。实验发现,合成语音与原语音波形上比较接近,MOS分约为3.24,冗余也明显减少。     

基于MSP430F499的波形合成器

以MSP430F499为核心,主要由方波振荡电路、分频与滤波模块、移相电路、放大电路、加法器等组成。将方波振荡器的信号分频滤波产生不同频率的正弦波,经移相放大等处理后,分别根据方波三角波谐波组成关系,再合成方波和三角波。滤波模块对同一信号进行二次滤波,先用开关电容滤波器滤波,再经三阶巴特沃斯低通滤波器滤波,降低了高次谐波对信号的影响同时保证了通带内信号的平坦。可通过按键进行波形切换以及合成阶数切换,人机交互灵活,界面友好,操作简单。     

基于MSP432E401Y的信号失真度测量系统

信号的总谐波失真度(THD)是衡量放大器性能的重要指标,本文设计了一种针对低频信号的总谐波失真度测量系统,能够对输入的周期信号进行采集分析,并测得输入信号的总谐波失真THD。本系统的硬件主要由放大电路系统和MSP-EXP432E401Y主控芯片构成,外接ESP32通讯模块与Android studio制作的手机app进行交互。周期输入信号首先通过AD603增益可控制放大器放大,随后接入加法电路滤去负压,然后由MSP432板载AD模块采入信号并进行数据处理,最后经由串口屏进行本地显示。本系统的软件设计是基于MSP432的FFT,处理得到输入信号的基波幅值及二至五次谐波幅值,通过ESP32将计算结果上传至服务器,手机端从服务器上下载数据。     

一种基于匹配跟踪的谐波和独立谱线正弦模型实现方案

该文基于匹配跟踪的谐波和独立谱线正弦模型提出了一种用于参数音频编码的实现方案,输入音频信号的正弦成分由谐波联合独立谱线共同表示,分析合成过程采用50%叠接相加(OLA)消除帧间不连续,匹配跟踪(MP)算法在频域提取模型参数(幅度、频率和相位)大大降低运算复杂度。谐波谱线基频由谐波积谱法(SHS)获得,各次谐波频点确切位置借助MP迭代过程推出,并进行二次曲线拟合,对应的谐波幅度采用LPC谱包络近似。独立谱线的提取有效弥补了谐波提取不足。实验证明该文提出的正弦模型实现方案可以很好地表示出音频信号中的平稳成分,并对低比特率的参数音频编码有一定的借鉴性。     

基波相减的电力谐波有源滤波器

在详细分析了谐波合成原理的基础上,根据谐波合成可逆原理,提出了基于基波相减的谐波分离和消除方法。通过对实现电路的具体分析,给出了谐波分离的关键电路原理图,并详细说明了其工作原理。实测证明,所提出的滤波器简单有效,可作为一种新的全频谱谐波消除手段。     

基于ARMA谐波分解和相干检测的非线性电路故障诊断

针对非线性模拟动态电路故障诊断,提出一种基于谐波分解的故障诊断方法.通过激励设计使电路响应的Volterra谱具有可分离性,通过ARMA谐波分解方法提取Voherra线性子电路响应;然后利用相干检测提取动态电路相位切片上的静态参数;最后,根据线性电路的频响叠加性原理建立故障诊断方程.仿真实例说明,该方法具有软故障、多故障诊断能力.     

一种基于AT89C51的正弦信号产生电路

由方波信号通过滤波电路产生正弦信号的方法,因谐波分量大而常不被设计者所采用。为消除谐波分量,提出了一种谐波分量超前消除的解决方案,并给出了相应的电路和实验数据。实验表明,针对不同的精度要求设计合适的谐波分量超前消除级数能很好地消除谐波分量,使低通滤波器输出的正弦信号精度得到明显提高。     

Séquences anharmoniquespremière partie: Analyse et synthèse

A simple geometric drawing able to bind a periodic binary signal to its spectrum is used to see whether there is a harmonic line or not. From the results of this analysis, a general synthesis procedure is developped with the object of forming binary periodic signals which do not show certain harmonic lines. Later on, this procedure will be transposed algebraïcally, which will lead to the synthesis of binary sequences approaching the sine signal. Some examples are shown with their results.     

A Lossy Dielectric-Ring Loaded Waveguide With Suppressed Periodicity for Gyro-TWTs Applications

A dielectric-loaded (DL) waveguide is an attractive possibility for interaction circuits with high-power sources in the millimeter-wave regime down to tenths of millimeters, particularly for gyrotron-traveling-wave-tube amplifiers (gyro-TWTs). We present results on a systematic investigation of the influence of the periodically loaded lossy dielectric on the propagation characteristics of the operating modes, which reveals that a complex mode in the periodic system can be mapped to a corresponding mode in an empty waveguide or a uniform DL waveguide. Dielectric losses not only induce modal transitions between different modes with similar field structures and close phase velocities in the uniform system but also unify the discrete mode spectrum into a continuous spectrum in the periodic system. Since the lossy dielectric functions as a power sink, the higher order Bloch harmonic components arising from the structural periodicity are suppressed, and the mode spectrum of the lossy periodic system degenerates into that of an empty waveguide. This alleviates the potential danger of spurious oscillations induced by the higher order harmonic components, making the periodic lossy DL waveguide promising in a high-power millimeter-wave gyro-TWT.     

An Orthogonal Design of Experiments for Accurately Estimating Harmonics of Periodic Signals at Low Frequencies

The lack of synchronization between the sampling rate and the signal frequency is the main source of leakage errors in the harmonic analysis of periodic signals performed by means of digital techniques. An algorithm for accurately measuring the harmonic parameters of low-frequency, arbitrary voltage signals without using synchronization circuits was published recently. It is shown that the algorithm is an alternative orthogonal design of experiments for the problem of fitting a linear trigonometric model to integrating digital voltmeter data. This was experimentally confirmed in recent comparison of the proposed method with a synchronous synthesizing and sampling system. The harmonic magnitudes as a percentage of the fundamental measured by both methods differ by less than one part in 10^{6}. The algorithm can be advantageously used in almost any kind of low-frequency ac applications where two arbitrary voltage signals measured by two voltmeters are to be compared for harmonic magnitude and phase shift.     

基于电流分解的单相无功功率定义及测量方法

周期非正弦激励电路中的无功功率定义是一个颇具争议的问题。本文提出了一种基于Fryze时域电流分解的单相无功功率定义方法,给出了这种定义下正弦激励下各种线性元件和非线性元件的无功功率表达式,以及非直线激励下线性电阻元件的无功功率表达式。推导结果表明,这种无功定义能更加直接地准确定位系统中的谐波源,更加有利于谐波治理和无功的实时补偿,文章最后给出了基于Matlab的电流分解算法,为无功实时补偿和无功电能计量奠定了基础。     

A method of analysis of periodic processes in nonautonomous discrete-time systems with quantization

A method of analysis of stationary processes in systems with an arbitrary number of quantization levels in the presence of periodic external signals is proposed. The method is based on the representation of stationary oscillations in the form of an invariant set of nonlinear discrete point mappings. The spectral composition of the response of a system with an arbitrary period coupled with the discretization period through a rational relationship is calculated with the use of the discrete Fourier transform. The discrete Fourier transform is applied also to calculate nonlinear distortions. It is suggested to use the dependence of the ratio of the first-harmonic amplitude of the system’s steady-state response to the amplitude of the input-signal harmonic on the frequency of the input harmonic signal as the amplitude-frequency characteristic of a nonlinear system. In addition, it is suggested to use the dependence of the difference between the argument of the first harmonic of the system’s response and the initial phase of the input signal on the frequency of the input harmonic signal as the phase-frequency characteristic of the system. The usage of the method is illustrated by its application for the analysis of processes in first-and second-order circuits.     

一种基于微弱周期信号的自适应处理算法

在传感器,特别是分布式光纤传感器领域,原始信号通常具有微弱性、周期性等特点,在经过接收电路后会出现不可避免的失真,对后续的信号处理带来极大的影响。在对微弱周期信号接收电路进行理论分析的基础上,提出一种基于微弱周期信号的自适应处理算法,采用该算法对接收信号进行数据处理可以显著降低输出信号的失真度,实现了对输出信号进行优化、补偿的一种通用处理方法。     

模型法与分离塞入比法的改进

本文介绍了模型法与分离塞入比法由于采用了模拟电路，而具有的缺点。提出了改进模型法与改进分离塞入比法，可以利用全数字电路实现。同时，文章分析了改进模型法与改进分离塞入比法的性能，以说明它们克服了原方法的不足，而又保持了原方法的优良性能，并给出了对比实验结果。     

Efficient calculation of finite Gabor transforms

The Gabor transform may be viewed as a collection of localized Fourier transforms and as such is useful for analysis of nonstationary signals and images. We present a new approach to analyzing the Gabor transform and use it to study the various critically sampled discretizations that form the infinite-discrete, periodic finite-discrete, and nonperiodic finite-discrete versions of the transform. In particular, we distinguish between the analysis and synthesis forms of the transform, and introduce an intermediate operation that decomposes both forms into collections of independent Toeplitz operators. In the continuous, the infinite-discrete, and the periodic finite-discrete cases, this decomposition allows us to show that, for appropriate windows, the analysis and synthesis transforms are inverses of each other. In the nonperiodic finite-discrete case this relation no longer holds, but we are still able to use the decomposition and results on Toeplitz matrices to show that both the transform and the inverse transform of P discrete samples are computable in O(P log P) operations (after a setup cost of O(Plog²P)). Furthermore, we use the decomposition to study in detail the differences between the periodic and nonperiodic versions of the transform and to compare their conditioning