New algorithm for controlling electric arc furnaces using their vibrational and acoustic characteristics

Cherednichenko, V. S.; Bikeev, R. A.; Serikov, V. A.; Rechkalov, A. V.; Чередниченко, А. В.

doi:10.1134/s0036029516120053

Cited by 3 publications

(4 citation statements)

References 2 publications

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“…During the initial phase, the interaction between the arcs generated instability and therefore an alteration in the pressure levels within the EAF. As stated by Cherednichenko et al [9], these instabilities generated acoustic waveforms with great variability and maximum sound pressure levels caused by the discharges of the arc column and the circulation of the electric current through the fragments of the furnace charge. Figure 6b shows the spectrograms of the signals in the different stages of the process.…”

Section: Proposal For a New Arc Stability Indexmentioning

confidence: 92%

“…During the operation of the EAF, electric arcs generate changes in sound pressure causing a high level of noise. EAFs are a source of noise pollution with a negative impact on the health of the personnel operating the furnace [8,9]. Usually, during furnace operation, the experienced operators determine the operation of the EAF, the stages of the melting process, and the quality of the foamy slag from the sound generated by the EAF.…”

Section: Introductionmentioning

confidence: 99%

“…Usually, during furnace operation, the experienced operators determine the operation of the EAF, the stages of the melting process, and the quality of the foamy slag from the sound generated by the EAF. Although, in practice, measurements of voltage and current signals are mostly used for monitoring, control, and modeling of the EAF [10], previous studies [8,9,11,12] have shown that the acoustic emission (AE) signal can be used to characterize the operation of the EAF.…”

Section: Introductionmentioning

confidence: 99%

“…The high relationship between the arc power derivative waveforms and the sound pressure signal was also demonstrated. Cherednichenko et al [9] made a simulation of the process in the EAF from a mathematical model with the aim of describing the acoustic characteristics of sound in the EAF and its energy. The authors of this paper proposed to keep the highest amplitudes of the AE signals in the frequency range of 5-150 Hz.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

New Arc Stability Index for Industrial AC Three-Phase Electric Arc Furnaces Based on Acoustic Signals

Guerra-Serrano

Roca

González-Yero

et al. 2020

Sensors

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This research proposes a new index to evaluate the stability of the melting process, in three-phase electric arc furnaces (EAFs), based on the acoustic signals generated during the different stages of the casting. The proposed stability index is obtained by characterizing the time and frequency domain of the acoustic signals. During EAF monitoring, acoustic signals were acquired using a microphone coupled to an NI USB-9234 acquisition system. To validate the results, the voltage and current signals were measured with the aid of a Circutor AR6 power analyzer for three-phase electrical networks. The results showed that the acoustic signal energy in the frequency range of 1 to 12 kHz can be used as an indicator of the process stability in the EAF. Finally, the validity of the proposed stability index is evaluated from the process characterization using the harmonic distortion analysis methods and the dynamic U-I characteristics of the arc voltage and current signals. The results obtained demonstrated the effectiveness of the proposal and constitute a starting point for advances in the automatic control of the process in the EAF, from the acoustic signals.

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Section: Proposal For a New Arc Stability Indexmentioning

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

New Arc Stability Index for Industrial AC Three-Phase Electric Arc Furnaces Based on Acoustic Signals

Guerra-Serrano

Roca

González-Yero

et al. 2020

Sensors

View full text Add to dashboard Cite

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Physical modelling of particle transport phenomenon and vibration behavior of converter with bottom powder injection

Zhang

Lou

Zhu

2022

J. Iron Steel Res. Int.

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Ferroalloy industry waste processing

Cherednichenko

Zuev

2019

IOP Conf. Ser.: Mater. Sci. Eng.

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In order to develop a technology and equipment for remelting waste from the ferroalloy industry, the Yurga ferroalloy plant gives 1500 kg of ferrosilicon waste to “Sibelektroterm” for experimental smelts and formulation of technical requirements for new remelting equipment. The findings of these operations are presented in this article. The results of experimental ferroalloy waste processing smelts in a direct-current furnace with the power of 140 kW are examined; parameters of three-phase electric furnaces of alternating current with power 0.63-6.3 MV·A and technologies of ferroalloy waste processing are examined. In addition, original characteristics of the waste are considered. Remelting of ferrosilicon waste in three-phase alternating current furnaces is considered.

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New algorithm for controlling electric arc furnaces using their vibrational and acoustic characteristics

Cited by 3 publications

References 2 publications

New Arc Stability Index for Industrial AC Three-Phase Electric Arc Furnaces Based on Acoustic Signals

New Arc Stability Index for Industrial AC Three-Phase Electric Arc Furnaces Based on Acoustic Signals

Physical modelling of particle transport phenomenon and vibration behavior of converter with bottom powder injection

Ferroalloy industry waste processing

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