M.M. Morcos

Artificial Intelligence and Advanced Mathematical Tools for Power Quality Applications: A Survey

Increasing interest in power quality has evolved in the past decade. This article surveys the literature for current applications of advanced artificial intelligence techniques in power quality. Applications of some advanced mathematical tools in general, and wavelet transform in particular, in power quality are also reviewed. An extensive collection of literature covering applications of fuzzy logic, expert systems, neural networks, and genetic algorithms in power quality is included. Literature exposing the use of wavelets in power quality analysis as well as data compression is also cited.

Application of AI tools in fault diagnosis of electrical machines and drives-an overview

Condition monitoring leading to fault diagnosis and prediction of electrical machines and drives has recently become of importance. The topic has attracted researchers to work in during the past few years because of its great influence on the operational continuation of many industrial processes. Correct diagnosis and early detection of incipient faults result in fast unscheduled maintenance and short down time for the machine under consideration. It also avoids harmful, sometimes devastative, consequences and helps reduce financial loss. Reduction of the human experts involvement in the diagnosis process has gradually taken place upon the recent developments in the modern artificial intelligence (AI) tools. Artificial neural networks (ANNs), fuzzy and adaptive fuzzy systems, and expert systems are good candidates for the automation of the diagnostic procedures. This present work surveys the principles and criteria of the diagnosis process. It introduces the current research achievements to apply AI techniques in the diagnostic systems of electrical machines and drives.

A neuro-fuzzy approach to automatic diagnosis and location of stator inter-turn faults in CSI-fed PM brushless DC motors

The paper presents a neuro-fuzzy-based perspective to the automation of diagnosis and location of stator-winding interturn short circuits in CSI-fed brushless dc motors. Performance of the drive under normal and short-circuit conditions are obtained through classical lumped-parameter network models. Waveforms of the electromagnetic torque and summation of phase voltages are monitored to develop two independent diagnostic algorithms. Diagnostic indices derived from the characteristic waveforms using discrete Fourier transform (DFT) lead to identifying the number of shorted turns. Fault location is achieved through a different set of indices extracted by the short-time Fourier transform (STFT). Adaptive neuro-fuzzy inference systems (ANFIS) are trained based on simulation results to automate the diagnostic process. ANFIS testing along with the good agreement between simulated and measured waveforms show the effectiveness of the proposed techniques.

Behavior of induction motor due to voltage sags and short interruptions

An experimental study and some calculations on induction motor behavior were carried out. The effects due to short interruptions and voltage sags were investigated. A standard three-phase squirrel-cage motor of 5.5 kW, 1500 r/min, and 380 V was used. The presence of induction motor changes the voltage sag waveform and duration. Protection characteristic curves and contactor ride-through capability together with their improvement are also studied. The interaction between motor load, system hot-load pickup, and voltage sag magnitude determine the motor re-acceleration duration and magnitudes. Besides, on-sag and post-sag currents can reach levels higher than the direct start values. Post-sag overcurrent duration can last more than twice the normal start time period, having specific energies in the same order of magnitude.

Dynamics of metallic particle contaminants in GIS with dielectric-coated electrodes

Electrical insulation performance of compressed gas insulated switchgear (GIS) and gas insulated transmission line (GITL) systems is adversely affected by metallic particle contaminants. Dielectric coatings applied to the inside surface of the outer enclosure of a coaxial GIS/GITL system improve the insulation performance in several ways. Coating has the effect of smoothing the electrode surface and reducing the prebreakdown current in the gas gap. Also, the electrostatic charge acquired by a particle is reduced and hence the range of its motion under an applied power frequency field is inhibited. The movement of such particles is complex and dependent on several parameters. In this paper the dynamics of wire particles in a coaxial system under AC voltage is studied when the inside surface of the outer enclosure of a coaxial GIS/GITL system is coated with a high resistance material. Suggestions for reducing the particle excursion in GIS/GITL systems are discussed.

Battery chargers for electric vehicles

This article presents a comparative study of the performance of two types of battery chargers being developed for electric vehicles. The first charger is a microprocessor-based ferroresonant battery charger, referred to as the ferroresonant charger. The power delivery section of this charger is a ferroresonant transformer, which exploits the saturation of magnetic materials through its capacitor winding to produce a well-regulated output that resembles a square wave. The control section periodically places a resistive load across the battery under charge that allows this change in resistance to be detected. A microprocessor controls the timing and executes the gating of the needed switches in the circuit and then gathers and analyzes data from the battery charge monitor circuit. The monitor circuit measures the voltage drop across the battery, which is proportional to the battery internal resistance when the load is introduced. The second charger is a multiphase AC-to-DC converter that employs two three-phase transformers to create twelve phases and is called the twelve-phase charger. One transformer primary is in the delta configuration, and the other transformer primary is in the wye configuration. The center-tapped secondaries create the twelve phases. Thyristors are used to control the output voltage of the charger through digital control of the firing angle. A microprocessor controls the charging profile of the battery. A motor-generator set is used to simulate the load to the charger for test conditions.

Detection of stator short circuits in VSI-fed brushless DC motors using wavelet transform

The paper presents methodologies to detect and locate short-circuit faults on the stator winding of VSI-fed PM brushless dc motors. Normal performance characteristics of the motor are obtained through a discrete-time lumped-parameter network model. The model is modified to accommodate short-circuit faults in order to simulate faulty operation. Fault signatures are extracted from the waveforms of electromagnetic torque and phase-voltage summation using wavelet transform. Three independent detection techniques are introduced. Experimental measurements agree acceptably with simulation results, and validate the proposed methods. This work sets forth the fundamentals of an automatic fault detector and locator, which can be used in a fault-tolerant drive.

Flicker Sources and Mitigation

Flicker is a power quality problem that affects our daily lives. In this paper, the authors describe how voltage fluctuations may originate in the power system, but most frequently they are generated by the equipment or load connected to it, for example, arc furnaces, welders, etc.

A power quality monitoring system: a case study in DSP-based solutions for power electronics

Programmable digital signal processors (DSPs) are emerging as the processors of choice in monitoring and control of high-end power electronics systems. This paper adopts a case study approach to illustrate a development methodology for DSP-based solutions. The unique features of DSP chips that make them ideal for real-time applications are highlighted. Power electronics systems where DSPs have been used are indicated. A case study in which a DSP-based solution was developed for a power quality monitoring application is presented. Through the case study, the issues involved in adopting a system architecture, selecting a DSP, and developing software for an application are discussed. The methodology described in this paper presents broad guidelines which can be intelligently applied to develop DSP-based solutions to meet specific requirements.

Automatic diagnosis and location of open-switch fault in brushless DC motor drives using wavelets and neuro-fuzzy systems

The faulty performance of permanent-magnet (PM) brushless dc motor drives is studied under open-switch conditions. The wavelet transform is used to extract diagnostic indices from the current waveform of the motor dc link. An intelligent agent based on adaptive neuro-fuzzy inference systems (ANFIS) is developed to automate the fault identification and location process. ANFIS is trained offline using simulation results under various healthy and faulty conditions obtained from a lumped-parameter, network model. ANFIS testing shows that the system could not only detect the open-switch fault, but also identify the faulty switch. Good agreement between simulation results and measured waveforms confirms the effectiveness of the proposed methodology.