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Using the low-voltage and low-current platform (220 VAC-10 A), this paper selected the Mayr arc theoretical model and the improved control theory model as a theoretical basis and built a single-phase low-voltage AC series arc model based on Simulink. The simulation results showed that arc dissipation power directly determined arc voltage amplitude, arc time constant influenced arc voltage waveform, and arc current was mainly determined by load resistance. Because the arc length parameter can be set by the improved control arc theory model, the arc can be drawn only at the micro-distance of two electrodes, which is more suitable for describing the arc characteristics of low voltage and low current. A scheme of large ratio reducer for permanent magnet brushless DC motor was developed, which was combined with the stepless governor controlled by PWM and the positive and negative switch to realize the adjustment of the two-electrode micro-distance. The collection and analysis of arc voltage and arc current under pure resistance, resistive load, and multi-branch load were completed. The experimental results also verified that the Mayr arc and improved control theory arc have good accuracy in describing low voltage and low current characteristics, which improves data support for later fault identification and removal.

Electric Arc Furnaces (EAFs) are widely used in the steel manufacturing industry to melt scrap steel by employing a large number of electric arcs. EAFs play an important role in ensuring the efficient production of steel. However, their nonlinear and variable load characteristics have a significant impact on power quality. Because the active power of an electric arc depends on its length, a system for controlling the electrode positions is necessary. This paper presents a control system based on a fuzzy logic controller for the active power control of an electric arc furnace. Individual simulation scenarios were chosen with both reference values and the process taken into consideration. The reference, constant value, step variation, and the sequence of step variation were investigated, as well as step disturbances and the sequence of step disturbances from the viewpoint of the process. Furthermore, the procedure of changing the tap on a transformer was investigated. The proposed solution minimizes the time required for charge elaboration, but the main benefit is that there are no additional costs in the implementation process because the installation remains identical, with the only changes being improvements to soft control management.

Purpose. The aim is to build a mathematical model of the electric arc of arc furnace (EAF). The model should clearly show the relationship between the main parameters of the arc. These parameters determine the properties of the arc and the possibility of optimization of melting mode. Methodology. We have built a fairly simple model of the arc, which satisfies the above requirements. The model is designed for the analysis of electromagnetic processes arc of varying length. We have compared the results obtained when testing the model with the results obtained on actual furnaces. Results. During melting in real chipboard under the influence of changes in temperature changes its properties arc plasma. The proposed model takes into account these changes. Adjusting the length of the arc is the main way to regulate the mode of smelting chipboard. The arc length is controlled by the movement of the drive electrode. The model reflects the dynamic changes in the parameters of the arc when changing her length. We got the dynamic current-voltage characteristics (CVC) of the arc for the different stages of melting. We got the arc voltage waveform and identified criteria by which possible identified stage of smelting. Originality. In contrast to the previously known models, this model clearly shows the relationship between the main parameters of the arc EAF: arc voltage Ud, amperage arc id and length arc d. Comparison of the simulation results and experimental data obtained from real particleboard showed the adequacy of the constructed model. It was found that character of change of magnitude Md, helps determine the stage of melting. Practical value. It turned out that the model can be used to simulate smelting in EAF any capacity. Thus, when designing the system of control mechanism for moving the electrode, the model takes into account changes in the parameters of the arc and it can significantly reduce electrode material consumption and energy consumption during smelting.

This paper presents the development of a new bi-arc dynamic numerical model for predicting AC critical flashover voltage (FOV) of ice-covered extra-high voltage (EHV) insulators. The proposed model is based on a generic calculation algorithm coupled with commercial finite element method software designed to solve the Obenaus/Rizk model. The proposed model allows one to implement the Nottingham and Mayr approaches and compare the results obtained as a function of the arcing distance, the freezing water conductivity, and the initial arc length. The validation of the model demonstrated high accuracy in predicting the FOV of ice-covered post-type insulators and its capability to simulate the interaction of the two partial arcs during the flashover process. In particular, the results showed that the Nottingham approach is sensibly more accurate than the Mayr one, especially in simulating the dynamic behavior of the partial arcs during the flashover process. Based on the encouraging results obtained, a multi-arc calculation algorithm was proposed using the bi-arc dynamic numerical model as a basis. The basic idea, which consists in dividing the multi-arc model in several bi-arc modules, was not implemented and validated but will serve as a promising concept for future work.

Low-voltage AC power lines are prone to arc faults, and an arc current presents as a random and complicated signal. The amplitude of the line current remains relatively unchanged during the occurrence of series arcs, hence complicating the detection of series arc faults. In this work, we developed a low-voltage series arc fault test platform to analyze the digital features of low-voltage series arc currents and the morphology of arc combustion, as the current model fails to capture the high-frequency and randomness of arc currents. An analysis of the physical causes and influencing factors of the random distribution of AC arc zero-crossing times was conducted. A time-domain simulation model for arc fault currents was developed by enhancing the time constant of the Cassie arc model, while the high-frequency features of arc currents were simulated using a segmented noise model. The measured arc current data were utilized to validate the model through the analysis of the zero-crossing time distribution of arc current, the correlation coefficient of the arc current frequency-domain signal, and the similarity of the time-domain waveforms. When comparing the similarity of the simulated waveforms of the arc model presented in this research and those of other traditional arc models, it was found that the suggested model effectively characterizes the time-/frequency-domain features of low-voltage AC series arc fault currents. The suggested model enhances the features of randomness in low-voltage AC series arc faults and is important in extracting essential aspects and reliably recognizing low-voltage series arc faults.

Accurate electrical arc modeling with physically meaningful parameters is essential for the assessment of medium-voltage DC circuit breakers in industrial and railway applications. Laboratory testing and characterization, as outlined in the IEC 61992 standard series for railway applications, typically provide data to asses the operational behavior of the componentsin the power distribution system, including recorded waveforms of terminal voltage and current but not the insights and inputs needed for inner behavior analysis and design optimization. This paper introduces lumped-parameter multi-physics models to describe different phases of arc behavior and outlines a methodology for model–data assimilation. Using experimental test data, the approach enables performance evaluation and supports non-invasive diagnostics and potential condition monitoring of circuit breakers.

The arc behaviour of short, low current switching arcs is not well understood and lacks a reliable model. In this work, the behaviour of an arc in the air is studied during contact separation at low DC currents (0.5 A to 20 A) and for small gap lengths (0 mm to 6 mm). The experiments are performed on a low voltage relay with two different electrode configurations. The arc voltage is measured during the opening of the contacts at constant current. The arc length is determined optically by tracing the mean path of the arc over time from a series of high-speed images. From the synchronised data of voltage vs. distance, first a sudden jump of the voltage at the start of contact opening is observed. Secondly, a sudden change in the voltage gradient occurs as the arc is elongated. Short arcs with a length up to approximately 1.25 mm show an intense radiation in the overall gap region and high voltage gradients. An unexpected behaviour never reported before was observed for longer arcs at low current: Two characteristic regions occur, a region in front of the cathode, with a length of approximately 1.25 mm, having an intense radiation and a high voltage gradient as well as a region of much lower radiation intensity and a comparatively lower voltage gradient in the remaining gap area despite a small anode spot region. The characteristic border of approximately 1.25 mm is almost independent of the current. A generalised arc voltage model is proposed based on the assumption that a constant sheath voltage and two discrete field regions exist, which are modelled as two independent linear functions of voltage vs. length. The data for various currents is combined to yield a general non-linear function for predicting the arc voltage vs. arc length and current.

It is essential to understand the power-arc model and the relationship of various parameters in pulsed gas metal arc welding (P-GMAW) process, in order to obtain stable arc length and droplet transfer. In this study, we analyzed the linear model of the GMAW process with some reasonable assumptions. A mathematical power-arc model of P-GMAW was established through an experimental statistical method by using a commercial welding power supply. Then, the mathematical model was applied combined with the adaptive arc length control strategy in the P-GMAW process of Al–Mg alloy by using the self-developed welding power supply. The experimental results indicated that the arc length of P-GMAW process for Al–Mg alloy kept uniform when using the experimental mathematical model and adaptive arc length control strategy. One drop per pulse (ODPP) droplet transfer mode was observed without spatters and cracks by carefully designing the preset parameters. The adaptive arc length control strategy showed good feasibility in Al–Mg alloy welding.

Due to high unit capacities, electric arc furnaces are among the receivers that significantly affect the power system from which they are supplied. Arc furnaces generate a number of disturbances to the power grid, including fast-changing voltage fluctuations causing the phenomenon of flickering light, asymmetry, and deformation of the voltage curve. The main issues discussed in the article are problems related to the distortion of current and voltage waveforms, resulting from the operation of electric arc furnaces. An analysis of the indices characterizing the voltage distortion recorded in the supply network of the arc furnaces is presented. The changes in the range of current and voltage waveform deformation in individual smelting phases in the arc furnace are also presented. Furthermore, the changes in the degree of deformation of the current and voltage waveforms in the individual smelting phases in an arc furnace are presented. A multi-voltage electric arc model used in computer simulations is proposed.