Electric arc furnace steel making intelligent technology development

Electric arc furnace steel making intelligent technology development

Abstract: Based on the application of intelligent technology in EAF steelmaking, the paper analyzes the technology development in power supply, real time monitoring and the global optimization of steelmaking. According to the research status at home and abroad, It’s indicated that intellectualization will matter more in EAF steelmaking and more advanced monitoring means, more reliable global control system and their organic combination will be the important tendency of intelligent steelmaking by EAF.

Electric arc furnace steelmaking as one of the main production methods of the modern steel industry, the use of advanced clean energy – electricity [1]. Electric arc furnace steel production in 2013 accounted for about 30% of global crude steel production (China EAF steel production is only 9% of total domestic steel production). With the rapid development of the world steel industry, a series of new technologies, new processes, new equipment and new materials have been applied in the field of electric arc furnace steelmaking. Many new products have been developed and manufactured to make them efficient, low consumption, intelligent and clean Production. With the increase of electric arc furnace steelmaking raw materials and people’s increasing awareness of energy conservation and environmental protection, electric arc furnace steel production will gradually increase [2].

Looking at the recent progress in electric arc furnace steelmaking technology, we can find that on the basis of the original high-efficiency and energy-saving smelting technology, electric arc furnace steelmaking focuses on intelligent steelmaking and energy saving and environmental protection with ultra-high power supply, Intelligent control, energy saving, environmental protection and other aspects have made great strides, especially in the field of intelligent control to develop a series of advanced monitoring technology and control model, greatly improving the EAF steelmaking process automation level, and promote The development of the steel industry.

Based on the intelligent smelting technology in all aspects of electric arc furnace steelmaking, the development of EAF intelligent steelmaking technology in recent years is introduced and analyzed.

1 、EAF intelligent power supply

Power supply operation is one of the main steps in the electric arc furnace steelmaking process. At the same time, the key to optimizing the power supply is the automatic adjustment of the electrodes. In order to improve the response speed and control accuracy of the electrode adjustment, ensure the balance of the three-phase current of the EAF and the continuous and stable adjustment of the electrode, it is necessary to continuously improve the electrode control system of the EAF so as to achieve the goal of saving energy, reducing the output and improving the quality [3] . Automatically determine the development of scrap melting technology to further enhance the EAF supply of intelligent level.

  • 1.1 electrode intelligent adjustment

The excellent electric arc furnace electrode intelligent regulation is the key to ensure the smooth production and shorten the smelting time [4]. At present, most domestic and foreign researches on adaptive control of electrodeposition of EAF are mainly to identify and control the EAF main circuit as a linear system, and then use the linear system adaptive method to study [5]. The method of piecewise linear self-adaptive control is one of them. The piecewise linear adaptive control strategy is to change the control system of arc furnace electrode from the control of nonlinear system to the control of piecewise linear system The three-phase electric arc furnace system adaptive control problem [6].

With the rapid development of intelligent control theory, researchers widely apply intelligent control algorithm to control the electrodeposition of electric arc furnace. In view of the complex nonlinear and time-varying characteristics of EAF during the two periods, the researchers used neural network and fuzzy control combined with traditional PID respectively to achieve satisfactory control effect in all stages of smelting [7] . US Star Steel uses intelligent control algorithms to improve the electrode control system for 80-t EAFs, resulting in a 10% to 20% increase in productivity, 0.4-0.6 kg / t reduction in electrode consumption, and 18-20 kWh / t reduction in power consumption ]. With the constant impedance neural network, the domestic electric iron electrode system of Wuyue Iron & Steel Co., Ltd, with 100 t arc furnace electrode, has been reduced by 8 min and the power consumption has been reduced by 60 kW · h / t. The actual production effect is remarkable [9].

  • 1.2 automatically determine the scrap melting technology

Modern electric arc furnace steelmaking is generally carried out according to the preset energization diagram of electric adjustment, the smelting process must be repeated (such as 3 times) into the scrap [10]. However, due to frequent changes in the properties of scrap loaded (such as size, volume, weight, shape, etc.) and melting conditions, optimal power supply melting can not be achieved by pre-energizing the chart. Especially in the scrapping additional period and from melting to warming the melting period, mostly by the operator based on experience. Scrap added too early or too late, the electric energy can not be effectively utilized, production efficiency is reduced, and even will damage the furnace refractories; from melting to warming the melting period, the power supply by the general melting period of the power supply diagram changes to the heating period Of the low-voltage high-current energized chart in order to improve heating efficiency of liquid steel heating, melting inaccurate judgment, will increase the smelting time and reduce production efficiency. Therefore, the accurate control of the molten state of scrap in the electric arc furnace has a great influence on the steelmaking operation.

Against this background, Daido Steel [11] developed the E-adjust (Electronic arc furnace-Automatic Dynamic Judgment System of Scrap Meltdown Timing) system for the automatic determination of scrap melting in an electric arc furnace (Fig. 1). The main use of electric arc furnace smelting process occurred in the high-order harmonic current (or higher harmonic voltage) and electric arc furnace two elements to determine the melting state of the furnace scrap, and then automatic control.

The researchers determined the thresholds that could be used as criteria by analyzing the correlation data of the higher harmonics over time in the melting process and the sounding law in the even times of the power frequency at the end of melting, and developed a fusion determination system based on the intelligent algorithm. In actual production, the melting determination system uses the current value measured by the current transformer to perform the arithmetic processing to obtain the higher harmonic components, and utilizes the noise variation measured by the noise meter to analyze the frequency of the furnace noise. Then, using the intelligent module of the system, Scrap melting state to determine.

Daido Steel collected a large amount of actual production data of E-adjust and compared it with the traditional manual judgment of production mode. Table 1 compares the operation parameters before and after the introduction of the purification system. The results show that the average power consumption of the electric arc furnace is reduced by 7.1kW · h / furnace and the operating time is reduced by 0.4min. After the introduction of the E-adjust system, the operation is stable and the invalidation of the electric power is eliminated, the electric energy is saved and the electric arc furnace Productivity.

1 - Electric arc furnace steel making intelligent technology development

Table 1 Determination of clear system before and after the introduction of operating parameters comparison


In recent years, based on adaptive technology, neural network and fuzzy control electrode automatic adjustment model gradually introduced into the domestic electric arc furnace control system, the actual production effect is remarkable. Due to the extensive use of molten iron hot charging technology in domestic electric arc furnace steelmaking, the automatic determination of scrap melting technology needs to be further improved to meet the EAF steelmaking process with different scrap ratios and improve its reliability.

2 、EAF steelmaking furnace real-time monitoring technology

Electric arc furnace smelting process at high temperatures, smelting environment is poor, there are many parameters in the actual production can not be accurately obtained. However, with the development of science and technology, researchers at home and abroad have developed a series of monitoring techniques for electric arc furnace smelting process, laying the foundation for the intelligent control of EAF steelmaking process.

  • 2.1 temperature sampling new technology

The temperature measurement and sampling of molten steel in the electric arc furnace steelmaking process has been one of the key links restricting the electric energy consumption and production efficiency of electric arc furnace [12]. Aiming at the problems of poor safety and high cost of traditional artificial temperature sampling, a series of new technologies of automatic temperature sampling are developed and popularized.

       2.1.1 automatic temperature sampling

Commonly used sampling and temperature measurement is done by manually inserting the sampler or thermocouple from the oven door into the molten steel. SIEMENS VAI Simetal LiquiRob automatic temperature measurement sampling robot (Figure 2), the outer layer coated with special dust-proof insulation fibers, with 6 degrees of freedom of movement, automatic replacement of samplers and temperature probes, detection of invalid temperature probe And other functions, can be fully automatic control through the man-machine interface. Compared with robotic sampling, the service life is longer and the maintenance cost is lower. The use of automatic sample temperature robot to improve the working environment and improve the accuracy of temperature sampling [13].

The PTI TempBoxTM Automatic Temperature Sampling System (Figure 3) developed by the United States PTI Company enters the molten pool temperature sampling through the furnace wall. The drive mechanism and cooling system of the device are specially designed to meet the harsh environment and process requirements of electric arc furnace smelting. Due to the working position and characteristics of PTI TempBoxTM, the temperature sampling is not limited by the system power supply, and the furnace door can be kept closed in the smelting process, which increases the residence time and thickness of foam slag in the furnace and improves the heat transfer efficiency in the furnace. Reduce the energy consumption of the smelting process.


Electric arc furnace smelting process, due to difficult to control the status of slag, to be cleaned furnace slag and other sampling channels to ensure the normal working sampling probe. At present, most domestic EAF steelmaking enterprises still adopt the traditional artificial sampling and temperature measurement method. The advanced automatic temperature sampling device has been introduced into the domestic EAF production in recent years.

2.1.2 non-contact continuous temperature measurement

Electric arc furnace steelmaking requires accurate temperature control at any given time – not only the bath’s surface temperature but also the bath’s internal temperature [14]. Traditional electric arc furnace steelmaking manual temperature measurement, not only high temperature measurement costs, labor-intensive, poor safety performance, and the need to stop power supply, extend the hot downtime, so the operator is generally only in the sampling and tapping temperature. However, accurate and real-time monitoring of molten steel temperature can guide the optimization of foaming slag, molten steel dephosphorization, optimization of power supply and other related processes [15]. Due to the harsh high-temperature smelting environment in EAF steelmaking, it has been difficult to continuously monitor the temperature of molten steel.

SIEMENS VAI has developed an innovative solution – the Simetal RCB Temp, a non-contact, continuous molten steel temperature measurement system based on a combined supersonic gun. Different from the traditional temperature measurement method, Simetal RCB Temp can accurately measure the molten steel temperature in a short time, accurately determine the tapping time, so that the electric arc furnace steelmaking process, the power-on time and power-off time are the best.

2 - Electric arc furnace steel making intelligent technology development

Simetal RCB Temp temperature measurement device schematic.

The device includes a combination of supersonic gun and optical sensor in two parts. Supersonic gun functions are: (1) oxygen injection to the molten pool to decarburization of steel; (2) temperature, the temperature is injected into the gas instead of oxygen. The optical sensor is installed at the lower end of the gun to receive the signal under test. The signal is amplified and processed by the analyzer, and then through the relevant algorithm model to calculate the measured temperature. The Simetal RCB Temp temperature measurement system accurately measures the temperature of the electric arc furnace with the furnace door closed. When the molten steel reaches tapping temperature, the electric arc furnace without delay power off, tapping.

Simetal RCB Temp realizes the continuous temperature measurement of non-contact molten steel and enhances the production capacity of EAF steelmaking. However, the reliability and service life of this system must be further verified and improved.

  • 2.2   foam slag monitoring and control technology

Foaming slag operation in electric arc furnace steelmaking can isolate the molten steel from the air, cover the arc, reduce the heat loss to the furnace wall and the furnace lid, effectively convert the electric energy into the heat energy to be transported to the molten pool, improve the heating efficiency and shorten the smelting cycle. Making molten slag during smelting and keeping it low is the key to EAF with low consumption and high productivity. In recent years, foam slag operation monitoring and control technology has been studied and applied with good results [16-17].

SIEMENS has developed the Simelt FSM (Foaming Slag Manager) Foam Slag Monitoring System (Figure 5). Simelt FSM is capable of qualitatively determining the presence of foaming slag in the furnace in response to the influence of the height and distribution of foamed slag on the sound propagation in the furnace. Specially designed sound sensor installed in a specific location on the furnace wall, the sound signal acquisition furnace, signal analysis system based on the collected signal analysis foam height and distribution status. Based on this, the FSM system can automatically regulate the power supply and the input of charcoal powder in various regions of the furnace, adjust the foam slag operation and stabilize the arc to improve the energy supply of the electric arc furnace and improve the production efficiency.

PTI SwingDoorTM (Figure 6), an electric arc furnace door cleaning and foam slag control system developed by PTI Company of the United States, reduced the entry of outside air and improved the sealing of the steelmaking process. An integrated oxygen lance system is installed on the oven door to automatically clean the oven door area instead of the oven door cleaning gun or the oven door lance. The system controls the flow slag by controlling the closing of the furnace door instead of the furnace body tilting device and can also control the foam slag level and the existence time in the furnace so as to ensure the thickness of the slag layer in the furnace during the smelting process and reduce the additional consumption of energy and the arc transmission Thermal efficiency, improve energy efficiency.

3 - Electric arc furnace steel making intelligent technology development

At present, most domestic steel mills still employ artificial means to control the production of foam slag. Some mills have adopted the electric arc furnace door system to optimize their energy utilization efficiency. However, due to the complexity of EAF steelmaking furnaces, the reliability of foam slag monitoring system based on sounding in the furnace remains to be verified.

  • 2.3 flue gas continuous analysis system

Modern EAF steelmaking combines high efficiency, safety and environmental protection, and is increasingly demanding for flue gas detection, control and process optimization in the steelmaking process [18]. Modern electric arc furnace flue gas analysis system can accurately measure the flue gas temperature, flow and flue gas CO, CO2, H2, O2, H2O and CH4 and other ingredients. The flue gas analysis system uses the collected information and its own control model to analyze, determine and control the smelting process. The flue gas on-line detection sensor is generally installed in the fourth hole of the EAF and must be specially designed to meet the harsh high temperature and dust environment of the fourth hole to increase its reliability and service life [19].

The EFSOP flue gas analysis system developed by TENOVA in Italy includes a high temperature exhaust gas sampling system, a control computer with dedicated simulation and control software and data sampling [20]. Based on real-time detection of the composition and temperature of flue gas, the system is able to determine the utilization of chemical energy in the furnace, the degree of imbalance between carbon and oxygen, the danger of explosion in the flue gas system, and whether the ventilation system is excessively aspirated , At the same time can achieve the dynamic input control of oxygen and gas in order to ensure the full combustion of the gas. The system uses the infrared gas pyrometer, pressure detector and flow sensor to measure the temperature of arc furnace excluding flue gas, the static pressure of gas in the pipeline and the flue gas velocity, respectively, and to calculate the carbon potential balance of the sampling points according to the flue gas flow rate. The Simetal Lomas Flue Gas Continuous Analysis System, developed by SIEMENS, has a special design for the gas sampling probe, equipped with a water-cooled device and an automatic cleaning device (Figure 7). The system is equipped with two gas sampling detectors: two detectors can automatically cycle switching, a detector work, the other detector clean correction, so as to ensure the continuous measurement and analysis of flue gas smelting process. Domestic Jiangsu Huai Steel developed a secondary combustion system based on furnace gas analysis developed by the United States Praxair with oxygen control for secondary combustion, and achieved significant energy saving effect. The electricity consumption per ton of steel decreased by 28 kW · h, and the smelting time was shortened by 7.5 minutes [21 ].

Modern EAF steelmaking also uses flue gas analysis to monitor leaks in the furnace to prevent excessive moisture from entering the EAF causing an explosion, leading to a major safety incident [22]. The EFSOP flue gas analysis system uses the relevant intelligent algorithm model module to process the detected flue gas composition signals and monitor the water infiltration in the EAF. At the same time, experimental and historical data analysis is used to define the water level in the furnace, forecast the leaking situation in the furnace and take the automatic Measures to avoid causing harm.

Flue gas analysis system has been widely used in electric arc furnace at home and abroad, the effect is good. For the current practical application, high temperature and dust gas detection sensors need to continue to research and development to further reduce the cost and improve the accuracy of gas analysis.

3 、arc furnace smelting process optimization control

With the development of electric arc furnace steelmaking technology, the production of electric arc furnace by controlling the production of electric arc furnace only by the operator’s experience has severely restricted the production pace of modern electric arc furnace steelmaking. Through the exchange of data and process control, the cost control and reasonable energy supply of EAF steelmaking process are optimized to reduce costs and increase efficiency [23].

  • 3.1 cost control optimization system

Traditional electric arc furnace smelting operation, electric arc furnace technical indicators by the operator proficiency. The development of modern computer technology makes it possible to optimize the operation of electric arc furnaces by using the computer’s memory and calculation functions. Beijing University of Science and Technology developed the electric arc furnace smelting process control cost optimization system through the electric arc furnace smelting process historical data records, the establishment of a database; according to the cost, minimum energy consumption or the principle of the shortest smelting time, the choice and the current smelting furnace charge structure, smelting environment And other similar optimal historical data, and then smelting according to the optimal furnace smelting process, in order to achieve the optimal smelting effect [24-25]. The system developed by the University of Science and Technology Beijing has been in the trial operation of electric furnace at home and abroad.

In recent years, Beijing University of Science and Technology [26] adopted the theory of spatio-temporal multi-scale structure to study the EAF steel making process, pointing out that there are many time-space scales such as micro scale, mesoscopic scale, unit operation scale and worksite scale Scale structure (Figure 8). On the basis of fully absorbing the existing process control models of domestic and foreign steel companies and combining with the EAF cost control model and the expert guidance model of electric arc furnace steelmaking process, a set of technical standards including EAF, refining and continuous casting, cost monitoring, process Optimization guidance in one of the online EAF steelmaking process model multi-scale model [27]. The multi-scale integration model brings together expert guidance models (including composition and temperature prediction of molten steel, endpoint prediction of EAF and optimization of alloy for refining process) of EAF steelmaking cost control model and EAF steelmaking process.

The multi-scale model of the on-line electric arc furnace steelmaking process has been successfully developed for EAF production in Xinyu Xinliang Special Steel, Hengyang Steel Pipe, Malaysia AnYu Iron and Steel, Taiwan YiSheng Steel, Xining Special Steel and Tianjin Steel Pipe [28]. The average tonne of steel oxygen consumption reduced 2Nm3, power consumption decreased 2kW · h, the metal material consumption decreased 10kg, steel cost per ton lower than 30 yuan, significant economic and social benefits.

  • 3.2 EAF steel control endpoint

Electric furnace tapping, the molten steel temperature and O, C, P and other elements of the content of the subsequent refining and continuous casting production have an important part. Precise prediction and control of the endpoint parameters of EAF steelmaking are the key to reduce production costs and speed up the smelting rhythm [29].

Early researchers based on EAF steelmaking material balance, energy balance and various stages of chemical reaction mechanism model, and because EAF steelmaking process is high temperature, heterogeneous, rapid reaction process, complex and varied, harsh conditions, many parameters in the The actual production is difficult to obtain, the accuracy of the mechanism model prediction is difficult to be guaranteed [30]. In recent years, with the development of intelligent algorithms, researchers introduced intelligent algorithms such as artificial neural networks, support vector machines and genetic algorithms into electric arc furnace steelmaking, developed a series of end-point prediction models and achieved good application effects in practical applications . Yuan Ping et al. [31] and other models based on SVM models obtained that the end-point hit rate was obtained when the end temperature range of the EAF was ± 10 ℃, the end point [C] range was ± 0.05 and the end point [P] Respectively, 93%, 93%, 87% of the forecast effect. Based on the BP neural network modeling, all the predictions of hit rate were 91% and 100% respectively when the final temperature range was ± 8 ℃ and ± 10 ℃. He Chunlai and Dong Kai [33] established the C-control model of EAF based on flue gas analysis and obtained better forecasting results.

Due to the overreliance on data by the “black box model” based on the intelligent algorithm and the lack of guidance on the production process, a mixed end-point prediction model combining the reaction mechanism and the intelligent algorithm has been gradually developed in recent years [34]. It can be foreseen that in the field of arc furnace steelmaking end control, more effective monitoring technology and high reliability intelligent model research and development and the combination of the two will be the hotspot of research.

  • 3.3 smelting process overall intelligent control

With the development of monitoring methods and computer technology, intelligent control of electric arc furnace steelmaking is no longer limited to the monitoring and control of a certain link. From the overall process, the information collected in the smelting process should be combined with the basic mechanism of the process to analyze and make decisions And control, the pursuit of the overall EAF steelmaking process optimization [36-37].

SIEMENS VAI developed the overall control scheme for the Simental EAF Heatopt (Holistic process control) (Figure 8), which provides real-time overall control of the EAF steelmaking process and greatly improves energy efficiency, production efficiency and safety of the manufacturing process [38]. The system uses the latest detection technology and condition monitoring and control program to optimize the control of EAF steelmaking process. The program integrates a variety of measurement techniques and information analysis and processing systems, including Simetal EAF Lomas, Simetal EAF SAM, Simetal RCB Temp Simetal FSD, Simetal CSM for electrode control, Simetal SlagMon and others. The use of these technologies enables real-time monitoring and control of the steelmaking process. The electric arc furnace steel overall control system to ensure the maximum production efficiency, the best energy conversion rate and the minimum production costs.

The system achieved good results in practical use at SDI Roanok Steel Plant in Virginia, USA: a 15% reduction in gas and oxygen consumption, a 15% reduction in toner consumption, a 3.6% increase in production efficiency and a significant reduction in production costs. [38]

The overall intelligent control of electric arc furnace steelmaking process depends on the intelligent control of all aspects of the research is still in its infancy. The continuous optimization of monitoring methods and control models in the smelting process will promote the further development of the overall intelligent control of EAF steelmaking.


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