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。     

A Filtering Technique for Three-Phase Power Systems

A novel filter for use in three-phase power systems is introduced. When the input to the filter is a balanced three-phase set of signals, the filter suppresses noise and distortions and extracts a smooth three-phase fundamental component. When the input signal to the filter is unbalanced, it extracts the fundamental positive-sequence component of the input signal. The filter also estimates the magnitude, phase angle, and frequency of the signal and adaptively follows the variations in all these three variables. The characteristics of the filter, including its mathematical equations, stability analysis, steady state, and dynamic responses, are discussed in this paper. The filter highly attenuates the harmonics, unknown interharmonics, and distortions. However, an extension of the filter for full removal of harmonics and unknown interharmonics is also presented, and its operating principles are discussed. The structural simplicity and robustness of the filter make it desirable for power system applications. In addition to the wide applications in power systems, it can specifically be used as an adaptive antialiasing filter for three-phase applications.     

时频域滤波及在飞机颤振试飞试验中的应用

针对飞机颤振试飞试验信号噪声过大的问题，提出了一种时频域滤波算法。采用Modet小波对扫频激励及其响应进行时频分析，利用该类信号聚焦于时频域特定区域的特性，有效地提取真实响应信号，达到信噪分离的目的。给出了具体的滤波算法，并研究了信号的重构问题。最后将上述方法应用于仿真算例和实际试飞数据，结果表明该方法显著的提高了频响函数的估计精度。     

An Adaptive Estimation Algorithm

An adaptive approach for sequential parameter-change detection and revision of the moving average parameter in the first-order integrated-moving average time series model is presented. Derivation of recursive formulas based on least squares estimation theory is given. Simulation experiments of this study indicate its validity for on-line parameter tracking applications. Practical considerations in implementing the proposed adaptive estimation system and its extensions to higher-order models are discussed.     

基于自适应均值的图像滤波算法

目的为了提高激光三维成像系统中的图像质量,有效滤除图像中噪声,提出一种自适应均值漂移的图像滤波算法。方法在传统算法基础上对均值漂移滤波算法进行改进,选取领域内像素的均方差为控制参量对带宽矩阵h大小进行自适应调控。根据宽带矩阵h的大小,选择合适的像元值参与到计算均值过程中,以提高结果的计算精度。结果实验结果表明改进后的算法能够有效滤除图像中的噪声,提高图像清晰度。结论该算法具有良好的保边去噪特性。     

脉宽调制式三相功率源的研制

三相精密功率源在工频仪器仪表校验中得到广泛应用。本文对功率源采用线性功率放大器的功率损耗问题进行了分析，提出了采用脉宽调制式功率放大器的技术方案，并对该功率源的构成及工作原理进行了论述。测试结果表明，该功率源具有输出波形失真度小（≤０．８％）、输出电压（电流、功率）稳定度高（在１００秒内相对变化率≤０．０２％）、效率高、输出功率大和可靠性高等特点。     

一种激光多普勒信号的频率估计算法

分析了激光多普勒回波信号的特征,提出了一种激光多普勒信号的频率估计算法.用FFT(Fast Fourier Transform)技术求得信号的自相关函数,并由功率谱得到信号频率的粗估计,然后用粗估计值对自相关函数移频,并根据移频信号自相关函数在一点的相位,估计频偏,对粗估计进行频率校正得到频率估计值.在进行信号频率粗估计和求相位时,利用计算过程中得到的结果和FFT因子的对称性,减少运算量.仿真结果表明,本算法有较小的均方根误差和平均绝对误差,应用于激光多普勒测速实验,结果与仿真一致.     

利用自适应阵对空间信号测向

给出一种基于Gram Schmidt正交 (GSO)结构的自适应测向方法 ,分辨力与特征值分解类算法相当。在测向的过程中 ,不需要事先知道或估计信号源的个数 ,算法简单 ,实时性好     

一种变步长LMS自适应滤波算法研究

为了解决最小均方(LMS)算法的稳定性及收敛速度(自适应速度)和稳态误差(自适应滤波器的精度)之间的矛盾,本文提出了一种自适应变步长的LMS算法,它的权系数的调整取决于误差曲面在新权值点上的梯度.分析了新算法的收敛特性以及参数选择对算法性能的影响.该算法具有较快的收敛速度、鲁棒稳定性且运算小易于实现的特点.计算机仿真的结果证实了该算法的收敛性能优于标准的LMS算法并且具有较好的实用性.     

Optimization of Adaptive Fuzzy Controller for Maximum Power Point Tracking Using Whale Algorithm

The advantage of fuzzy controllers in working with inaccurate and nonlinear inputs is that there is no need for an accurate mathematical model and fast convergence and minimal fluctuations in the maximum power point detector. The capability of online fuzzy tracking systems is maximum power, resistance to radiation and temperature changes, and no need for external sensors to measure radiation intensity and temperature. However, the most important issue is the constant changes in the amount of sunlight that cause the maximum power point to be constantly changing. The controller used in the maximum power point tracking (MPPT) circuit must be able to adapt to the new radiation conditions. Therefore, in this paper, to more accurately track the maximum power point of the solar system and receive more electrical power at its output, an adaptive fuzzy control was proposed, the parameters of which are optimized by the whale algorithm. The studies have repeated under different irradiation conditions and the proposed controller performance has been compared with perturb and observe algorithm (P&O) method, which is a practical and high-performance method. To evaluate the performance of the proposed algorithm, the particle swarm algorithm optimized the adaptive fuzzy controller. The simulation results show that the adaptive fuzzy control system performs better than the P&O tracking system. Higher accuracy and consequently more production power at the output of the solar panel is one of the salient features of the proposed control method, which distinguishes it from other methods. On the other hand, the adaptive fuzzy controller optimized by the whale algorithm has been able to perform relatively better than the controller designed by the particle swarm algorithm, which confirms the higher accuracy of the proposed algorithm.     

采用匹配滤波和ICA消除sEMG的工频干扰

设计了一种采用匹配滤波和独立分量分析消除表面肌电信号中工频干扰的新方法。采用匹配滤波可以有效判断表面肌电信号中是否含有工频噪声,从而避免不加区分地对表面肌电信号进行工频去噪。在确定含有工频噪声的前提下,采用独立分量分析,该方法不但能够有效地消除表面肌电信号中的工频噪声,且不会对表面肌电信号的其它频率成分造成明显的影响,取得了良好的工频去噪效果。这一设计思想在实际的表面肌电信号检测时取得了较好的实验结果。     

Harmonic Estimation Base on Center Frequency Shift Algorithm

Harmonic pollution has been a key issue affecting the safe operation of power system. But the traditional harmonic analysis methods are easy to be affected by the environmental factors. In order to reduce the impact of these disturbances, a novel harmonic analysis method based on center frequency shift is presented. The harmonic spectral lines located at the half frequency points is need for frequency shift in time domain. However, to considering the harmonic spectral lines after frequency shift will not be just in the ideal position, an offset factor is proposed for modifying the position of the harmonic spectral lines. At the same time, the corresponding formulas to estimate the magnitude, phase angle and frequency are deduced. The simulation results show that the FFT harmonic parameter estimation algorithm based on center frequency shift is effective. The parameters of harmonic signals can be accurately estimated by the algorithm. And the interference factors can also be suppressed.     

交互式多模型集自适应协同滤波目标跟踪算法研究

为了解决传统交互式多模型算法静态模型集带来的精度低等局限问题,提出了一种多模型集自适应协同滤波算法.通过比较目标与当前模型集中不同模型之间的模型匹配概率,自动确定当前模型匹配中的最好模型与最坏模型,利用激活、保留和剔除策略改变固定模型集的结构以达到模型集自适应的过程.通过与其他已经提出的交互式多模型算法进行比较,实验结...     

An Adaptive Estimation Procedure Using the LaPlace Transformation

An adaptive parameter estimation procedure based upon the Laplace transformation is investigated. The parameter estimates are shown to be strongly consistent and asymptotically normally distributed when properly normalized. In the case that the parameters are the mixing parameters of a mixture of distributions, the parameter estimates are shown to be unbiased for any sample size. Computational experience and potential applications are included to demonstrate how this estimation procedure is especially useful to the reliability engineer.     

基于当前统计模型的一种双自适应模糊滤波算法

在当前统计模型的基础上,提出一种双自适应模糊滤波算法.该算法利用模糊推理机制及结合升半正态形模糊分布函数,对最大加速度和过程噪声协方差矩阵进行双自适应调整.针对阶跃机动,引入强跟滤波器达到增强跟踪机动目标的能力.仿真结果表明,该算法提高了机动模型与目标实际机动模型的匹配程度以及对强机动目标跟踪的精度,改善了滤波器的跟踪性能,克服了对弱机动目标跟踪性能的不足.     

A Simple Recursive Algorithm for Simultaneous Magnitude and Frequency Estimation

A new approach in the design of digital algorithms for simultaneous local system magnitude and frequency estimation of a signal with time-varying frequency is presented. The algorithm is derived using the maximum likelihood method. The pure sinusoidal voltage model was assumed. The investigation has been simplified because the total similarity to the state of the problem of dc offset and frequency estimation has been noticed. Finite impulse response (FIR) digital filters are used to minimize the noise effect and to eliminate the presence of harmonic effects. The algorithm showed a very high level of robustness, as well as high measurement accuracy over a wide range of frequency changes. The algorithm convergence provided fast response and adaptability. This technique provides accurate estimates in about 25 ms and requires modest computations. The theoretical bases of the technique are described. To demonstrate the performance of the developed algorithm, computer-simulated data records are processed. The proposed algorithm has been tested in a laboratory to establish its feasibility in a real-time environment.     

动态定量称量包装系统滤波算法

目的为了提高动态定量称量包装精度,提升数据采集和信号测量的准确性。方法分析定量称量系统的组成以及工作原理,并针对系统中存在的噪声,提出一种基于小波包滤波的称量包装滤波算法。通过塔式分解方法实现快速离散小波包变换,由离散卷积方程得到小波包分解系数,进而完成滤波算法的重组。结果通过仿真和实验结果可知,小波包滤波方法能够很好地滤除动态称量信号中的噪声,提升了有用信号的品质。结论该滤波算法提升了动态定量称量系统的稳定性,提高了称量包装精度。     

进化论自适应滤波算法及降噪特性研究

基于生物进化论策略的自适应滤波算法，利用其有性繁殖和无性繁殖的随机搜索能力实现全局最优搜索，可克服最小均方法（Least Mean Square，简称：LMS）对于多峰特性问题有可能收敛于某一局部最小值，无法实现全局最优的缺点。提出峰值系数指标PR（Peak Ratio）概念解决进化论自适应滤波器的性能评估问题，提出收敛速度CS（Converge Speed）指标和峰值系数指标PR高度的方法解决最优滤波参数的选取问题，并列进化论自适应滤波器的降噪进行模拟仿真，讨论了滤波长度和进化系数对进化论自适应算法消噪效果的影响及最优滤波参数。