Modeling and control of the hydraulic actuator in a ladle furnace.

The dynamic behavior of the hydraulic actuator in a system for regulating the electrode's position is crucial for the operation of a Ladle Furnace. This work aims to identify, model, and control the hydraulic actuator in the Ladle Furnace of ACINOX Las Tunas. For identifying the system, input signals of Pseudo-Random Binary type and black box models were used. As a result, three models were obtained, two reflecting the process's asymmetric behavior according to the upward or downward movement. The third model approximates the process dynamic behavior around the operating point and includes the uncertainty caused by the weight variation during the electrode wear. The models obtained, with a fit greater than 85%, allow a better understanding of the study case behavior. In addition, these allowed the evaluation of the electrode's weight variation and tuning of several controllers. The optimal one was a novel non-linear PI controller of guaranteed robustness. In future works, the use of a non-linear function could be evaluated to compensate for the asymmetric behavior of the process.

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

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.