A signal processing module for power system applications

This paper presents a unified power signal processor (PSP) for use in various applications in power systems. The introduced PSP is capable of providing a large number of signals and pieces of information which are frequently required for control, protection, status evaluation, and power quality monitoring of power systems. The PSP receives a set of locally measured three-phase voltage and current signals and provides their fundamental components, amplitudes, phase angles, frequency, harmonics, instantaneous and stationary symmetrical components, active and reactive currents and powers, power factor, and the total harmonic distortion. Simplicity and integrity of its structure as well as its robustness with respect to internal parameters and external disturbances and noise render the proposed scheme very attractive for practical implementations.     

An efficient hardware realization of EMD for real-time signal processing applications

This paper presents a field-programmable gate array (FPGA) and application-specific integrated circuit (ASIC) based design for the real-time implementation of empirical mode decomposition (EMD) algorithm. Here, at the beginning, register-transfer-level (RTL) design of EMD algorithm is developed in the form of verilog-HDL code. Then, simulation-based testing of the RTL design is done. In this paper, two envelope computation methods are proposed: one using linear Bezier curve (LBC) and the other using cubic spline interpolation (CSI). For ASIC, the verilog-HDL code of EMD is synthesized using Genus tool of Cadence using SCL 180-nm technology library and Innovus tool of Cadence is used for the layout design. The core area of the proposed EMD ASIC is 1.16 mm² and can be operated at 62.5 MHz clock rate. The developed FPGA-based EMD architecture can be operated at 50 MHz clock rate and up to 50 MHz sampling rate. Here, an effort is also made to classify the normal and seizure/ictal electroencephalogram (EEG) signals, which are used as an input to EMD, with the help of a support vector machine (SVM). The classification accuracy obtained is above 99%, and here, MATLAB is used for feature calculation and classification purposes.     

An analog cell and its applications in analog signal processing

This paper presents a straightforward current‐mode CMOS squarer circuit. The proposed circuit exploits the square‐law characteristic of MOS transistor in saturation region. The squarer circuit is then used to implement multiplier and exponential functions. To demonstrate the method, circuits are designed in 0.35 µm CMOS process, using single 3.3 V supply. HSPICE simulations, with level 49 model parameters, confirm the operation of the proposed CMOS circuits. Copyright © 2010 John Wiley & Sons, Ltd.     

A .NET solution for distributed computing applications

Distributed computing is used to solve computational complexity problems. This paper explores the suitability of the .NET platform and XML Web services for distributed computing applications. This study demonstrates the practical feasibility of a .NET Web-services application in distributed computing and it also exposes APIs on the Internet. Thus from the experimental results, the speed of the algorithm introduced by Web services are determined and the cluster performance is achieved by scheduling algorithm, which properly selects the size of the work slice for each client to assign.     

小波分析在滚动轴承故障信号处理中的应用

在旋转机械中,当轴承发生故障时,振动信号比较复杂,相对其它振动信号太弱,基于傅立叶变换的谱分析技术对滚动轴承的故障特征的提取不太理想。提出采用小波变换和傅立叶变换相结合的方法来处理滚动轴承的故障振动信号,通过对某航空发动机滚动轴承的外环故障信号处理,结果验证了该方法对提取滚动轴承故障特征的有效性。     

基于DAQ-2005的虚拟信号发生和数据处理系统

为实现非线性电介质测试,基于LabVIEW平台采用凌华DAQ-2005采集卡构建了虚拟信号发生器和数据处理系统。该系统可以实现信号发生、数据采集、信号滤波和响应电流分解。首先给出了系统总体方框图,其次介绍了硬件选型过程和详细的软件设计,最后给出了实测数据和信号处理结果。这种基于虚拟仪器的设计方案在非线性电介质测试领域具有重要的实用价值。     

Design of integrated all-pass filters with linear group delay for analog signal processing applications

This article describes the design of integrated linear group delay filters for analog signal processing (ASP) applications and their implementation through constant-resistance lattice and bridged-T networks. Unlike previously published works, our design method uses a recursive procedure as the basis for the synthesis of a suitable transfer function. Thanks to this method, filters with a more linear group delay characteristic and flat magnitude response can be obtained. Two filters are designed in a 0.13-μm BiCMOS technology to demonstrate the method: a balanced lattice with a negative slope and an unbalanced bridged-T of positive slope.     

Digital signal processors for a signal processing laboratory

An undergraduate level laboratory course on digital signal processors and their use in real-time digital signal processing (DSP) systems is described. Special emphasis is put on some practical issues such as execution time optimization, finite wordlength effects and a pipelined strategy as a suitable way to improve the performance of a real-time DSP system. The primary purpose of the laboratory is a better understanding of the theoretical concepts and a more active participation of the students in the course. The authors think that this paper will be of interest to those teaching related courses such as Introduction to DSP, Digital Signal Processing, Real-time DSP, Microprocessors and Hardware/Softmare Interaction. The well-known Texas Instruments' TMS320C2x and TMS320C5x fixed-point processors are used as the fundamental tool in the lab experiments and the TMS320C3x is suggested as a low-cost floating-point alternative. Enough detail is provided in the paper to duplicate certain parts of the experiments     

基于ARM9分布信号同步数据采集系统设计

针对分布信号的同步数据采集,给出了1种基于ARM9的同步数据采集系统的设计方法和过程,并对设计中遇到的主要问题进行了分析和解决.本文从系统的硬件组成、软件设计进行了说明.本系统主要功能是对分布在各个点的各种物理量(如温度、压力、声音)进行同步数据采集,将采集后的数据进行模数转换.系统最大的优点是利用GPS信号控制ADC...     

Image, Signal, and Distributed Data Processing for Networked eHealth Applications [A View from the Guest Editors]

In this era of distributed computing the trend in medical informatics is toward achieving two goals: the availability of software applications and medical information anywhere and anytime and the invisibility of computing. The six papers in this special issue provide an overview of the most promising prospects for the state-of-the-art and emerging field of image, signal, and distributed data processing for networked eHealth applications.     

Digital signal processing with applications: a new and successfulapproach to undergraduate DSP education

The new approach to undergraduate digital signal processing education at Purdue is based on a simple idea: emphasize applications. Students are assumed to have a significant exposure to sampling and discrete-time signals, systems, and transforms at the junior level. In the senior course, the traditional digital signal processing topics of digital filter design, the discrete Fourier transform (DFT), radix-2 fast Fourier transforms (FFTs), and quantization are covered in the first five weeks of the semester. Coverage of these topics is augmented by treatment in the laboratory component of the course using diverse software tools and by Matlab-based homework assignments. The remainder of the course is devoted to treating the topics of speech processing and image processing in substantial depth and involves a design project. The course has been very successful in terms of increasing enrolment and outstanding student evaluations     

The SIVA Demonstration Gallery for signal, image, and video processing education

The techniques of digital signal processing (DSP) and digital image processing (DIP) have found a myriad of applications in diverse fields of scientific, commercial, and technical endeavor. DSP and DIP education needs to cater to a wide spectrum of people from different educational backgrounds. This paper describes tools and techniques that facilitate a gentle introduction to fascinating concepts in signal and image processing. Novel LabVIEW- and MATLAB-based demonstrations are presented, which, when supplemented with Web-based class lectures, help to illustrate the power and beauty of signal and image-processing algorithms. Equipped with informative visualizations and a user-friendly interface, these modules are currently being used effectively in a classroom environment for teaching DSP and DIP at the University of Texas at Austin (UT-Austin). Most demonstrations use audio and image signals to give students a flavor of real-world applications of signal and image processing. This paper is also intended to provide a library of more than 50 visualization modules that accentuate the intuitive aspects of DSP algorithms as a free didactic tool to the broad signal and image-processing community.     

基于分布式并行计算框架的海量数据增量处理方法研究

随着大数据时代的到来,各大企业已经陆续建设数据仓库,如何提升海量数据处理的效率逐渐成为数仓应用中的重要问题。分析了企业大数据平台现状,提出了基于分布式并行计算框架的数据增量处理方法,并基于此方法对海量增量数据处理进行了实践,验证结果表明,该方法提升了数据处理效率,增强了企业数据仓库数据处理的准确性。     

On distributed computing for on-line power system applications

This paper reviews the state-of-the-art of distributed computing (also called coarse-grained parallel computing) technology, which has rapidly evolved over the last two decades, with emphasis on the trend towards standardization that has occurred in the last few years. The review is focused on on-line power system applications, and excludes fine-grained parallel applications and planning applications. The applications are divided into two categories. The first category consists of applications where the motivation for distributed processing stems from geographical distribution. The second category is the rest of the on-line applications where the parallelism stems from the easily decomposable abstract (mathematical) model of the problem as opposed to being ‘physically based’. Some of the issues in such distributed computing are illustrated using the example of security-constrained optimal power flows. The paper concludes with some projections on the use of this technology in energy management systems (EMS) in the near future.     

Limits of control performance for distributed networked control systems in presence of communication delays

In terms of computational complexity and fault tolerance, distributed networked control systems (DNCSs) is favorable for large‐scale processes. However, it poses additional limitations on the achievable control performance, especially when communication delay is present. The conventional minimum variance (MV) benchmarks mainly consider the limitations caused by the system itself and can give overly estimates of achievable performance when applied to the systems under distributed networked control. This paper proposes a solution to the MV benchmark for DNCSs considering both system time delays and time‐invariant communication delays. Furthermore, lower and upper bounds of the MV benchmark are proposed to assess the performance of DNCSs when there are time‐varying communication delays. These results are useful for evaluating the potential performance improvement if a DNCS is implemented to replace a decentralized control system. The proposed results are illustrated by a simulation example.     

IIR filter scaling for real-time signal processing

Students generally have difficulty implementing infinite impulse response filters (IIR) using fixed-point arithmetic. Most of the trouble is with amplitude scaling the filter and representing the coefficients in the fixed-point format. The authors present a systematic procedure for scaling a second-order IIR filter which is used as the basic building block of higher-order filters. A simple simulation program is used to estimate the size of the signals at the summing nodes of the filter section. Once the estimates are known, the filter section can he reliably scaled. The procedure is clarified by implementing a second-order resonant filter on a digital signal processor: the TMS320C25