Comparison of Nonactive Powers for the Detection of Dominant Harmonic Sources in Power Systems

This paper deals with an innovative technique for the detection of disturbing loads in distorted power systems. The technique is a single-point strategy based on a comparison among different “nonactive” power quantities already proposed in the literature, which are measured at the same metering section. In this paper, the effectiveness of the strategy is discussed, which also considered the errors of the measurement transducers; the analysis is supported by simulation tests, which were carried out on both a simple single-phase system and an IEEE standard three-phase test power system. The latter was used by other authors as a benchmark system for the analysis of multipoint measurement techniques for harmonic pollution monitoring.      

Particle Filtering for State Estimation in Nonlinear Industrial Systems

State estimation is a major problem in industrial systems, particularly in industrial robotics. To this end, Gaussian and nonparametric filters have been developed. In this paper, the extended Kalman filter, which assumes Gaussian measurement noise, is compared with the particle filter, which does not make any assumption on the measurement noise distribution. As a case study, the estimation of the state vector of an industrial robot is used when measurements are available from an accelerometer that was mounted on the end effector of the robotic manipulator and from the encoders of the joints' motors. It is shown that, in this kind of sensor fusion problem, the particle filter outperforms the extended Kalman filter, at the cost of more demanding computations.     

Optimal Allocation of Multichannel Measurement Devices for Distribution State Estimation

This paper proposes an optimization algorithm that is suitable for choosing the optimal number and position of the measurement devices in distribution state estimation (DSE) procedures used in modern electric distribution networks. The algorithm is based on the techniques of dynamic programming, and its goal is to guarantee both the minimum cost and the accuracy required for the measured data needed to operate management and control issues, such as energy dispatch and protection coordination. Both the uncertainty introduced by the measurement devices and the tolerance in the knowledge of the network parameters (line impedances) are taken into account in the proposed approach. The aggregation of the quantities to be measured in a few measurement points has been favored to reduce the overall cost of the measurement system. Random changes in the loads are considered to establish adequate reference conditions for the tests. Tests relevant to real distribution networks are presented to show the validity of the proposed approach. The results emphasize how both the influence of the tolerance on the network parameters and the cost of the measurement system can dramatically be minimized by suitably choosing the algorithm to be implemented to solve the DSE problem.      

电气化铁路的谐波电能计量技术研究

分析了电气化铁路对电力系统电压电流信号测量和电能计量的影响,建立了针对电气化铁路电能计量的基于离散傅里叶变换的非正弦信号电能计量算法,给出了算法模型、实现机理和依据谐波有功功率判据谐波潮流的方法,利用MATLAB对电气化铁路的谐波电能计量方法进行了仿真实验,在此基础上研制的三相多功能谐波电能表的有功电能计量准确度达到0.2 S,谐波测量准确度满足我国A类谐波测量仪器的要求,符合我国现行电网运行需要.     

基于状态估计的分布式离散事件系统可诊断性研究

针对分布式离散事件系统,提出了一种验证基于状态估计的分布式离散事件系统可诊断性的方法。首先对离散事件系统的可诊断性进行形式化定义,然后提出一种基于状态估计的分布式离散事件系统的可诊断性验证算法,进而推导出分布式离散事件系统可诊断的充分必要条件,最后结合实际算例对该算法的可行性进行验证分析。相比现有算法,本文提出的算法无需各站点进行实时同步,仅要求在有限时延内各站点间能进行通信即可,且算法的时间复杂度也明显降低。     

Time Reversal for the Polarization State in Optical Systems

Abstract

The time-reversal operator for the polarization state can be successfully implemented in any optical system where a beam retraces its path. A Faraday rotator followed by a mirror realizes a device whose representative matrix is similar to the quantum mechanics time-reversal operator for the spin. Any effect of the medium birefringence is cancelled and, for linear polarization, the beam always returns opposite polarized with respect to the entrance state. Analogies with the operation of a phase-conjugation mirror are pointed out and suggested consequences of the novel optical configuration are given.     

Feature Selection for Robust Localization of Acoustic Emission Sources in Ship-Hull Structures

In this article, a novel feature selection method based on the Fisher ratio (F-ratio) and k-means clustering algorithm is presented and evaluated for nondestructive monitoring of acoustic mission (AE) sources in ship-hull structures. Avoiding complex and time-consuming implementations, the proposed approach use the advantages of the discrimination measure of the F-ratio and the fast convergence rate of a k-means algorithm in the feature selection problem. An extremely efficient set of only four features per sensor is selected for AE sources localization using a radial basis function (RBF) neural network (NN) giving error-free localization accuracy.

In the presence of additive white Gaussian noise, different type of information has been selected from the original set of 90 features. Extensive experiments show that even in the very noisy environment of 0 dB SNR, a small set of four features can be used for robust neural localization of AE sources giving localization rates better than 94%.     

Estimation of Parameters in the Weibdl Distribution

A new method of estimation is used to obtain two simple estimators of the parameters in a Weibull distribution. These estimators are similar to the estimators given by Gumbel, Miller and Freund, and Menon. Some useful properties of these estimators are developed which make it practical to use Monte Carlo methods to determine the variances and biases of the estimators for various sample sizes. Comparisons of the estimators can be made and unbiasing factors calculated in some cases. The variances of the estimators are also compared to the Cramer-Rao lower bounds for regular unbiased estimators.     

Minimum Distance Estimation for the Generalized Pareto Distribution

The generalized Pareto distribution (GPD) is widely used for extreme values over a threshold. Most existing methods for parameter estimation either perform unsatisfactorily when the shape parameter k is larger than 0.5, or they suffer from heavy computation as the sample size increases. In view of the fact that k > 0.5 is occasionally seen in numerous applications, including two illustrative examples used in this study, we remedy the deficiencies of existing methods by proposing two new estimators for the GPD parameters. The new estimators are inspired by the minimum distance estimation and the M-estimation in the linear regression. Through comprehensive simulation, the estimators are shown to perform well for all values of k under small and moderate sample sizes. They are comparable to the existing methods for k < 0.5 while perform much better for k > 0.5.     

Estimation of the Utility's and Consumer's Contribution to Harmonic Distortion

A method for the allocation of responsibilities between a utility and a consumer, with reference to the distortion of three-phase voltage waveforms at the point of common coupling (PCC), has been presented. The input data required for applying this method are the measured voltage and current waveforms at the PCC. The frequencies in the measured waveforms are estimated, and a Kalman filter is used to estimate the phasors at these frequencies. Subsequently, the parameters of the electrical system of the industrial load have been estimated using the recursive least-squares technique. With these estimated data, the individual contributions to the distortion of the three-phase voltage waveforms have been calculated. The proposed method has been illustrated using practical examples.     

Review of Second Harmonic Generation Measurement Techniques for Material State Determination in Metals

This paper presents a comprehensive review of the current state of knowledge of second harmonic generation (SHG) measurements, a subset of nonlinear ultrasonic nondestructive evaluation techniques. These SHG techniques exploit the material nonlinearity of metals in order to measure the acoustic nonlinearity parameter, \(\beta \). In these measurements, a second harmonic wave is generated from a propagating monochromatic elastic wave, due to the anharmonicity of the crystal lattice, as well as the presence of microstructural features such as dislocations and precipitates. This article provides a summary of models that relate the different microstructural contributions to \(\beta \), and provides details of the different SHG measurement and analysis techniques available, focusing on longitudinal and Rayleigh wave methods. The main focus of this paper is a critical review of the literature that utilizes these SHG methods for the nondestructive evaluation of plasticity, fatigue, thermal aging, creep, and radiation damage in metals.     

Estimation of Electric Charge Output for Piezoelectric Energy Harvesting

Abstract: Piezoelectric materials (PZT) can be used as mechanisms to transfer mechanical energy, usually ambient vibration, into electrical energy that can be stored and used to power other devices. With the recent advances in wireless and micro‐electro‐mechanical‐systems (MEMS) technology, sensors can be placed in exotic and remote locations. As these devices are wireless it becomes necessary that they have their own power supply. The power supply in most cases is the conventional battery; however, problems can occur when using batteries because of their finite life span. Because most sensors are being developed so that they can be placed in remote locations such as structural sensors on a bridge or global positioning service (GPS) tracking devices on animals in the wild, obtaining the sensor simply to replace the battery can become a very expensive task. Furthermore, in the case of sensors located on civil structures, it is often advantageous to embed them, making access impossible. Therefore, if a method of obtaining the untapped energy surrounding these sensors was implemented, significant life could be added to the power supply. One method is to use PZT materials to obtain ambient energy surrounding the test specimen. This captured energy could then be used to prolong the power supply or in the ideal case provide endless energy for the sensors lifespan. The goal of this study is to develop a model of the PZT power harvesting device. This model would simplify the design procedure necessary for determining the appropriate size and vibration levels necessary for sufficient energy to be produced and supplied to the electronic devices. An experimental verification of the model is also performed to ensure its accuracy.     

加窗插值FFT谐波分析算法的误差估计

非同步采样的情况下，快速傅里叶变换用于谐波分析存在较大的误差，很难获得准确的谐波参数。加窗插值FFT谐波分析算法能够减小谐波分析误差。针对该算法，借助计算机仿真研究了谐波分析时误差的变化规律以及最大的误差限。最后给出了谐波分析应用中的若干重要结论。     

Maximum Likelihood Parameter Estimation for the Quartic Exponential Distribution

The quartic exponential (QE) distribution defined by the probability density function of the type

is examined in detail.

The problem of obtaining maximum likelihood point estimates of the population parameters reduces to that of identifying the α as functions of the population moments μ _r ′, r = 1, 2.3.4.

The invalidity is explained of methods proposed by previous authors to deal with the nonlinear relationships involved, and a new algorithm is developed which overcomes these objections. The new algorithm is applied to practical data, and the resulting distributions fitted to observed frequencies are shown to compare favourably with those obtained by previous Methods.     

Parameter and Quantile Estimation for the Generalized Pareto Distribution

The generalized Pareto distribution is a two-parameter distribution that contains uniform, exponential, and Pareto distributions as special cases. It has applications in a number of fields, including reliability studies and the analysis of environmental extreme events. Maximum likelihood estimation of the generalized Pareto distribution has previously been considered in the literature, but we show, using computer simulation, that, unless the sample size is 500 or more, estimators derived by the method of moments or the method of probability-weighted moments are more reliable. We also use computer simulation to assess the accuracy of confidence intervals for the parameters and quantiles of the generalized Pareto distribution.     

负二项分布可靠度的经验Bayes估计

本文在平方损失下,给出了负二项分布可靠度θ的Bayes估计、Bayes置信下限,同时构造了θ的渐近最优的经验Bayes（EB）估计,并证明了该EB估计的收敛速度为O（n^-1）.     

电动器具绕组温升测试的不确定度评定

本文利用A类和B类评估方法,对绕组温升测试过程中产生的不确定度各分量进行了评估,并对类似电动器具的温升测试的不确定度主要影响因素进行了探讨.