基于ESPRIT的谐波和间谐波参数估计方法

为了准确地获得信号中谐波、间谐波成分的频率和幅值等参数,提出了一种新的检测算法,即ESPRIT(Estimation of Signal Parameters via Rotational Invariance Techniques)。此算法是一种基于子空间技术的高分辨率检测方法,它把信号分解为信号子空间和噪声子空间,能够精确地估计出被噪声污染的正弦信号的频率,幅值等信息,克服了传统FFT算法分辨率的限制。仿真结果表明此算法能够在较短的信号长度内准确检测出信号各个谐波和间谐波成分,证明了此算法的正确性。     

基于实值MUSIC算法的电力谐波分析方法

现代谱估计方法逐渐被应用于电力谐波及间谐波的超分辨率检测与分析,其中的多重信号分类方法(MUSIC)算法最具代表性.然而,常规谱MUSIC算法在分析电力谐波时必须将实值信号转换为复频率信号,因而计算复杂度较高;此外,其伪频谱的峰值搜索过程也存在着类似栅栏效应,导致其频率分析精度有限.为了改善谱MUSIC算法对电力谐波的分析精度,本文基于子空间分析理论提出了针对实值周期信号的谱MUSIC频率检测方法,推导并给出了其伪谱函数的表达式.在此基础上,还利用Newton-Raphson算法对伪谱峰值进行迭代求精,进一步提高了谐波频率的估计精度.仿真结果表明:实值MUSIC伪谱更能有效区分真实谐波谱峰与噪声伪峰,同时本文方法的计算复杂度远远低于原有复值谱MUSIC算法,而频率估计精度与求根MUSIC算法接近,非常有利于电力谐波参数的准确获取.     

近场声源三维定位MUSIC算法研究

信号到达方向(DOA)估计是阵列信号处理的最主要目的之一,基于语音阵列的DOA估计与传统的窄带远场信号的DOA估计在信号模型和处理方法上有很大区别.本文把经典的MUSIC算法推广到语音阵列处理中,实现了声源三维定位.该算法的基本思想是:把宽带语音信号通过短时傅立叶变换转换为独立离散频率点,利用MUSIC算法求出每个/部分频率点的空间谱矩阵,然后加权平均这些空间谱矩阵.通过搜索该平均空间谱矩阵,找到信号源的位置.最后,在16元均匀圆环阵的情况下,选用双语音信号源进行了仿真.仿真结果表明,该算法定位性能优良.     

扩展Prony算法在电力系统非整次谐波检测中的应用研究

准确有效地检测出电力系统中各次谐波及间谐波,对于提高电能质量是至关重要的。传统的快速傅里叶变换由于频谱泄漏等原因,无法准确检测出系统中的非整次谐波。为解决这一问题,文章提出应用扩展Prony算法检测系统的非整次谐波。首先利用小波去除噪声,很好的克服Prony算法对噪声敏感这一弱点;然后通过线性预测得到模型的特征矩阵,运用奇异值分解法求解特征矩阵得到模型的特征多项式;最后运用最小二乘法求出特征多项式的根,得到非整次谐波各参数。针对信号频带宽窄可能影响算法精度这一问题,文章对不同带宽信号进行扩展Prony分析,验证算法精度。实验分析说明了该算法的可行性和有效性。     

Parameter estimation for MIMO system based on MUSIC and ML methods

The frequency offset and channel gain estimation problem for multiple-input multiple-output (MIMO) systems in the case of flat-fading channels is addressed. Based on the multiple signal classification (MUSIC) and the maximum likelihood (ML) methods, a new joint estimation algorithm of frequency offsets and channel gains is proposed. The new algorithm has three steps. A subset of frequency offsets is first estimated with the MUSIC algorithm. All frequency offsets in the subset are then identified with the ML method. Finally, channel gains are calculated with the ML estimator. The algorithm is a one-dimensional search scheme and therefore greatly decreases the complexity of joint ML estimation, which is essentially a multi-dimensional search scheme. __________ Translated from Journal of Electronics and Information Technology, 2008, 30(7): 1552–1556 [译自: 电子与信息学报]     

Performance analysis of velocity–pressure smoothing for direction‐of‐arrival estimation of coherent signals

In this paper, we consider the problem of direction‐of‐arrival (DOA) estimation of coherent signals by using a number of identically oriented acoustic vector‐sensors, wherein source decorrelation can be achieved by velocity–pressure smoothing. We examine the effect of velocity–pressure smoothing on the performance of MUSIC‐type methods in terms of the overall root mean‐square errors (RMSE) of DOA estimates. The closed‐form expression for the overall RMSE is derived and analyzed. We also compare velocity–pressure smoothing with the conventional spatial smoothing technique. Simulation results are given to confirm the analyses. Copyright © 2009 John Wiley & Sons, Ltd.     

电力系统状态估计算法的研究现状和展望

为了保证电力系统的安全性和经济性,状态估计是能量管理系统(EMS)中不可或缺的组成部分。状态估计算法是状态估计的核心部分。综述了电力系统状态估计的研究现状。简要介绍了电力系统状态估计的基本概念及功能,描述了状态估计的数学模型。介绍了几种目前常用的估计算法,即加权最小二乘法、快速分解法、基于量测变换的状态估计算法等,并对这些算法作了简明的对比,指出各个算法的优缺点。最后,对状态估计算法中值得研究的方面进行展望。     

Real‐time frequency estimation for sinusoidal signals with application to robust fault detection

This paper has investigated the problem of estimating unknown frequencies of a given sinusoidal signal with disturbances and noises, as well as its usages for fault detection. On the basis of a parametric linear model of the signal, a gradient estimator with leakage is adopted to identify the frequencies. The estimation mechanism is applied to fault detection, as it achieves not only the tolerance to disturbances but also the sensitivity to faults. Simulations verify the feasibility and capability of the frequency identifier for estimating frequencies and detecting faults. Copyright © 2012 John Wiley & Sons, Ltd.     

Behavior of the least mean square algorithm with a periodically time‐varying input power

The paper analyzes the transient and steady‐state performances of a least mean square algorithm in the rarely‐studied situation of a time‐varying input power. A scenario of periodic pulsed variation of the input power is considered. The analysis is carried out in the context of tracking a Markov plant with a white Gaussian input. It is shown that the mean square deviation (MSD) converges to a periodic sequence having the same period as that of the variation of the input power. Expressions are derived for the convergence time and the steady‐state peak MSD. Surprisingly, it is found that neither the transient performance nor the steady‐state performance degrades with rapid variation of the input power. On the other hand, slow input power variation causes degradation in both the transient and steady‐state performances for given amplitude of variation of the input power. In the case of a time‐invariant plant, neither rapid nor slow variation of the input power causes degradation in the steady‐state performance. On the other hand, there is degradation in the transient performance for slow variation of the input power. Copyright © 2012 John Wiley & Sons, Ltd.     

Real‐time spectral analysis

For signal analysis, the Fourier transform and the linear prediction methods are the main approaches. In recent years, the wavelet transform, which gives an expression in the time–frequency domain, has been attracting attention. In the wavelet transform, scale and shift operations are used to analyze regional waves in the signal. In this paper, we propose a new method for signal analysis. Instead of the wavelet, short sine waves and cosine waves which have slightly different frequencies and phases established beforehand are used. These frequencies and phases play the same role as wavelets in analyzing regional waves in the signal. However, our proposed method is different from the wavelet transform because it does not use multiresolution analysis. In conventional spectral analysis methods, all data are prepared beforehand and calculations are performed by using these data. In the proposed method, the spectrum is updated whenever new signal data come in. We show that the amount of calculation is markedly reduced and that real‐time spectral analysis can be achieved. Finally, we present an analysis of Japanese vocal sounds using the proposed method. © 2007 Wiley Periodicals, Inc. Electr Eng Jpn, 161(1): 43–50, 2007; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20504     

用于强非线性负荷的瞬时无功与谐波电流检测算法研究

为解决强非线性与类随机性负荷下的瞬时无功与谐波补偿问题,综合应用ip-iq法和p-q法,提出了一种有效的瞬时无功与谐波电流检测算法。该算法适用于任意工况的三相电路,包括三相四线制电路、电压非对称正弦或含有谐波等情况。理论推导和仿真证明了该算法的正确性和有效性。同时,将该算法进行推广,可实现对任意次谐波正序或负序有功、无功电流的有效提取。     

Experimental proof of voltage‐current waveform sensor output of resin molded type for measurement of power factor and harmonics in general power distribution system

We have proposed a voltage‐current sensor of resin molded type for measurement of the power factor and harmonics. To understand the characteristics of the conventional prototype sensor and the problems of its practical use, we conducted a finite element analysis. Problems involving the cost and practical usage of the sensor were identified. Therefore, we have redesigned the prototype sensor, incorporating the current sensor designed on the basis of the FEM and a ready‐made voltage sensor. In this paper, we describe feasibility field experiments with the present sensor in a practical 6.6‐kV distribution system and show that the sensor can measure the power factor and harmonics of horizontal and vertical power line systems successfully. © 2011 Wiley Periodicals, Inc. Electr Eng Jpn, 178(3): 1–10, 2012; Published online in Wiley Online Library ( wileyonlinelibrary.com ). DOI 10.1002/eej.21213     

一种新的分布式电力系统状态估计算法

随着电力系统的发展,区域电网互联,形成了规模更大的系统。为了适应这一趋势,电力系统状态估计应采用分布式算法。在配置少量PMU的基础上,将分区后的边界等式约束条件通过拉格朗日乘子计入整体目标函数,将分布式状态估计的问题转化为一个带等式约束的最优化问题,实现了电力系统状态估计的分布式计算。该算法不仅提高了状态估计的速度,而且可在不必改动原有状态估计模块的基础上,很容易地加入等式约束的修正模块。最后通过IEEE14节点和IEEE30节点系统的模拟仿真,验证了该算法的有效性和优越性。     

基于VSS-CDFE的三相非平衡电力系统频率无偏估计

为了实现含噪三相非平衡电力系统高精度频率无偏估计,引入了复数域直接频率估计(CDFE)算法,分析其原理并对其进行了改进。CDFE算法基于正弦信号的线性预测,求取误差函数的瞬时平方值关于频率的偏导数,并以该值作为频率估计的更新值。在此基础上,进一步提出变步长CDFE(VSS-CDFE)算法,根据最速下降法则动态更新步长因子来代替CDFE算法的固定步长。仿真分析及实验结果表明,在噪声干扰下,VSS-CDFE算法可以准确地对基于复数建模的三相非平衡电力系统进行频率追踪,其估计均方误差和理论值相吻合。相比CDFE算法,VSS-CDFE算法在相同的收敛速度下,估计均方误差更小,在相同的估计均方误差下,收敛速度更快。     

Speed estimation of induction motor drive using d‐axis slot harmonics and parameter identification method

This paper describes a rotor speed estimation technique of an induction motor, which utlizes slot harmonics on the d‐axis caused by permeance variation across the air gap. The frequency of the slot harmonics is a multiple of the actual rotor speed, and is proportional to the number of rotor slots. In order to extract the slot harmonics, a novel adaptive bandpass filter incorporating coordinate transformation is proposed, which is effective to estimate the rotor speed from 400 to 2000 rpm. This rotor speed estimation is applied to a field‐oriented controller as well as a speed controller. In addition, performance improvement is carried out by compensating a motor parameter mismatch. Feasibility of the proposed technique is confirmed through several tests, using a prototype experimental setup. © 2010 Wiley Periodicals, Inc. Electr Eng Jpn, 171(2): 50–58, 2010; Published online in Wiley InterScience ( www. interscience.wiley.com ). DOI 10.1002/eej.20901     

Order and parameter estimation of time‐varying system by subspace method

This paper proposes an identification algorithm for time‐varying systems. We apply subspace method for estimation, since it is known to be useful when the input–output (I/O) data are observed by multi‐input multi‐output (MIMO) systems. Among many proposed techniques of subspace methods, we use MOESP (MIMO Output‐Error State Space model identification) in this paper, which assures arithmetic stability by RQ factorization and singular value decomposition (SVD). Generally, subspace methods can be applied after I/O data collection, so that we introduce updated steps of matrices for PI‐MOESP, which uses past inputs for instrumental variables. We propose a recursive update algorithm of PI‐MOESP, including estimation step of the system order, and consider some parameters inherent to the algorithm, namely, initial number of data, estimation step of the order, and forgetting factor. A numerical example shows the usefulness of the proposed method. © 2006 Wiley Periodicals, Inc. Electr Eng Jpn, 157(2): 57–64, 2006; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20169     

A noise‐constrained algorithm for estimation over distributed networks

Much research has been devoted recently to the development of algorithms to utilize the distributed structure of an ad hoc wireless sensor network for the estimation of a certain parameter of interest. A successful solution is the algorithm called the diffusion least mean squares algorithm. The algorithm estimates the parameter of interest by employing cooperation between neighboring sensor nodes within the network. The present work derives a new algorithm by using the noise constraint that is based on and improves the diffusion least mean squares algorithm. In this work, first the derivation of the noise constraint‐based algorithm is given. Second, detailed convergence and steady‐state analyses are carried out, including analyses for the case where there is mismatch in the noise variance estimate. Finally, extensive simulations are carried out to test the robustness of the proposed algorithm under different scenarios, especially the mismatch scenario. Moreover, the simulation results are found to corroborate the theoretical results very well. Copyright © 2012 John Wiley & Sons, Ltd.     

A cascade‐connected neural model for improved 2D DOA estimation of an EM signal

This article proposes a neural network‐based approach to increase accuracy of two‐dimensional direction of arrival (DOA) estimation of an electromagnetic signal. The proposed method combines two neural networks developed using simulated and small amount of empirical data, respectively. The output of the simulation‐based neural network represents approximate information on DOAs. It is then considered as a priori knowledge for the small empirical network that is crucial for obtaining more accurate DOA estimates. The developed cascade‐connected model is validated using real data from a rectangular antenna array. Improvements in terms of accuracy and reliability are obtained and compared with the MUSIC algorithm. Copyright © 2015 John Wiley & Sons, Ltd.     

Decentralized unscented Kalman filter based on a consensus algorithm for multi-area dynamic state estimation in power systems

A decentralized unscented Kalman filter (UKF) method based on a consensus algorithm for multi-area power system dynamic state estimation is presented in this paper. The overall system is split into a certain number of non-overlapping areas. Firstly, each area executes its own dynamic state estimation based on local measurements by using the UKF. Next, the consensus algorithm is required to perform only local communications between neighboring areas to diffuse local state information. Finally, according to the global state information obtained by the consensus algorithm, the UKF is run again for each area. Its performance is compared with the distributed UKF without consensus algorithm on the IEEE 14-bus and 118-bus systems. The low communication requirements and high estimation accuracy of the decentralized UKF make it an alternative solution to the multi-area power system dynamic state estimation.     

三相四线制变频电网的谐波及无功电流检测

为了满足变频电网提高电能质量的需要,提出一种基于通用瞬时无功理论和正序基波滤波器的谐波、无功及不平衡电流检测方法.针对基于传统通用瞬时无功理论的方法在电源电压畸变或不对称时检测不准确的问题,提出了改进算法.详细分析了正序基波滤波器的特性,采用带有自适应参数的正序基波滤波器提取正序基波电压,采用平均值法获得平均功率,同时应用到改进算法中,适应了电网基频的各种变化,克服了低通滤波器在变频工况下使用的缺陷.在飞机交流变频电网并联APF系统中对所提方法进行了仿真验证,并与Ip-Iq改进法和PHC法进行了对比.研究表明所提方法在电网基频处于不同稳态值或在稳态值间快速变化时均能实现准确,快速地检测.与传统方法相比,具有检测精度高,受变频环境影响小的优点.