Modeling of the AC Arc Discharge on Snow-covered Insulators

A mathematical model for predicting the ac flashover voltage of snow-covered insulators is presented. The arc constant parameters in air gaps and inside snow, as well as the arc reignition condition are determined using a cylindrical model. The effects of the arc length on the arc constants parameters are also investigated. The model is then applied to an EPDM insulator artificially covered with natural snow. There is good concordance between the flashover results determined from the mathematical model and those obtained experimentally.     

Dynamic modeling of DC arc discharge on ice surfaces

A dynamic model for predicting DC arc behavior and critical flashover voltage of ice-covered insulating surfaces is presented. The model takes into consideration insulating geometry, pre-contamination level, and characteristics of ice layers. Assuming arc behavior as a time dependant impedance, it is possible to determine various arc characteristics such as time histories of leakage currents, potential gradient, channel radius, trajectory, propagation velocity and the energy injected into the zones free of ice (also called air gaps). The simulated results provided by the model are in agreement with those obtained experimentally using a simplified ice-covered cylinder as well as a short string of five IEEE standard porcelain suspension units covered with artificial ice.     

Nonlinear regenerative chatter in turning

Chatter is a topic of immense engineering importance because its occurrence in machining results in poor surface finish, promotes tool wear and hampers productivity. In this paper, a single degree of freedom, delay differential equation model is presented. The central idea of the model is the study of regenerative chatter effect, which qualitatively explains the nonlinear dynamics in machining. Stability charts are derived for the linearized case in a two dimensional phase plane (μ, Ω) with the bifurcation parameter μ representing the dynamic variation of the chip thickness, and the critical rotational speed Ω. The governing nonlinear equations are integrated in time by Adams Predictor corrector Method. Phase portraits are drawn between the instantaneous tool position x₁ and the relative tangential velocity x₂. It has been shown that in the absence of a cubic nonlinearity, the chatter response appears to be more chaotic.     

Effects of temperature and impurities on the DC conductivity of snow

Several major parameters affecting the electrical behavior of natural snow, namely volume conductivity and density, liquid water content and conductivity of water melted from snow, are crucial for the characterization of the electrical performance of snow-covered HV insulators. However, little study has been devoted to this subject, despite of its importance. These parameters are found to vary significantly with snow composition and purity as well as with other parameters, such as temperature, airborne pollutants, electric field strength and polarity. From laboratory experiments carried out on a large number of snow samples, it was found that DC conductivity of snow shows a peak at about -2degC. This apparently curious behavior near the melting temperature is attributed to important changes to the microstructure of snow. A correlation between DC conductivity and snow temperature was established     

Dielectric spectroscopy techniques as quality control tool: a feasibility study - [feature article]

In this article, the feasibility of using time- and frequency-domain dielectric spectroscopy measurements to monitor the condition of oil-impregnated paper (OIP) condenser bushings is discussed.     

Water in oil-filled high-voltage equipment part II: water content as physicochemical tools for insulation condition diagnostic

In the first part of this investigations, we examined the current state of knowledge of the effect of water on paper and liquid-insulating materials. Demonstrated that the scientific representation of the states of water in insulating liquids has a direct practical application as a diagnostic tool for electrical equipment, at least for the dielectric properties of the insulation. The work presented in this second part of these investigations is divided into four sections. The first section deals with the influence of water on the electrical characteristics of the oil/paper insulating materials, followed by a critical review of up-to-date water quantification methods. Based on the physicochemical criteria of the limiting state discussed in the third section, this article proposes some analytical expressions that can help electrical engineers monitor and/or diagnose oil-filled, high-voltage equipment. Our investigations show the advantage of diverse methods for measuring humidity in insulating liquids, and a variety of analytical expressions for calculating the condition of liquid/ solid insulation systems.     

Specific investigations to quantify heavy damage causes on loading resistor modules

In this paper, premature damage to some static inverter loading resistor modules is analyzed. Furthermore, investigations were carried out to determine the origins and causes of this serious damage occurring on the resistor modules in service. Investigations were preformed on the insulating liquid samples as well as new resistor modules. From the results obtained, it seems that the origin of the damage is from a long-standing, free-burning arc between two resistor windings, following mechanical breakdown.     

The prevalence of diabetes mellitus in three population groups in the Republic of Mali

A new method of estimating intracranial decompensation in man is described. An on-line computer system is connected to an intracranial pressure (ICP) monitoring system to compute regression plots of mean ICP vs standard deviation; standard deviation is used as a measure of ICP instability. Two zones with distinctly different slopes are a characteristic feature of these plots. It is thought that the changes of slope signify intracranial decompensation.     

M‐RPSS: A modified RPSS for path scheduling of mobile sink in wireless sensor network

In wireless sensor networks (WSNs), data gathering is the main concern, since it directly affects the network lifetime and data latency. Rendezvous Point Selection Scheme (RPSS) is a mobile sink node approach; it offers superior performance than its preceding mobile sink schemes like Rendezvous Design for Variable Track (RD‐VT), RD‐VT with Steiner Minimum Tree (RD‐VT‐SMT), and Weight Rendezvous Planning with Steiner Minimum Tree (WRP‐SMT). However, a more uniform distribution of the rendezvous node leads to less energy consumption in WSNs. The more optimum path offers less data latency. In the proposed approach, we use particle swarm optimization (PSO) to find the optimum rendezvous point and adaptive PSO (APSO) to find an optimum path by solving the travelling salesman problem. By rigorous simulation, we prove that modified RPSS (M‐RPSS) increases the network lifetime by more than 10% and decreases the data latency.