Furnace gas waste heat recovery device and method for multi-bottom-electrode energy-saving direct-current submerged arc furnace

Abstract

The invention relates to the technical field of furnace gas waste heat recovery, in particular to a furnace gas waste heat recovery device and method of a multi-bottom-electrode energy-saving direct-current submerged arc furnace. The method comprises the following steps: acquiring a furnace gas intensity index; according to the total amount of the current feeding, the residual amount of the current feeding at the current moment, the actual execution duration of the current feeding at the current moment and the change condition of the furnace gas intensity index at the current moment, predicting the furnace gas intensity index at the next moment at the current moment; obtaining a recovery capability coefficient; and on the basis of the furnace gas strength index and the recovery capacity coefficient at the next moment of the current moment, a parameter correction coefficient at the current moment is obtained, and the working parameters of the furnace gas waste heat recovery device at the current moment are corrected. The working parameters of the furnace gas waste heat recovery device are corrected in real time, the waste heat recovery efficiency of the furnace gas waste heat recovery device is effectively improved, and meanwhile energy loss caused by invalid operation of the furnace gas waste heat recovery device is effectively avoided.

Description

Technical Field

[0001] This invention relates to the field of furnace gas waste heat recovery technology, specifically to a furnace gas waste heat recovery device and method for a multi-bottom electrode energy-saving DC submerged arc furnace. Background Technology

[0002] In the smelting of industrial silicon, ferroalloys (such as ferrosilicon and ferromanganese), and calcium carbide, multi-bottom electrode energy-saving DC submerged arc furnaces have become the mainstream smelting equipment due to their advantages such as low energy consumption, high efficiency, and good environmental performance. This type of equipment uses multiple sets of bottom electrodes to pass DC power, and utilizes the electric arc heat and resistance heat between the electrodes and the furnace charge to achieve high-temperature smelting. During the process, a large amount of high-temperature furnace gas is generated, which contains abundant waste heat resources and has extremely high recycling value.

[0003] Existing methods for recovering waste heat from submerged arc furnace gas mainly employ multi-stage gradient heat exchange devices. A typical process involves: high-temperature furnace gas first undergoing preliminary heat exchange through a high-temperature resistant silicon carbide ceramic heat exchanger to heat cooling water and generate hot water or low-pressure steam; the cooled furnace gas then enters a plate heat exchanger for further cooling, and finally, after purification, it is discharged by an induced draft fan. Such devices typically operate based on fixed parameters (such as preset cooling medium flow rate and induced draft fan power). However, in actual operation of multi-bottom electrode DC submerged arc furnaces, the furnace gas parameters (temperature and flow rate, etc.) are significantly fluctuating due to the influence of the feeding cycle and electrode adjustments. When the waste heat recovery device uses fixed parameter control, it is difficult to adapt to the dynamic changes in furnace gas parameters, which can easily lead to the problem of high-temperature furnace gas not being fully utilized or consuming more energy to recover waste heat, making it impossible to accurately recover the waste heat from the furnace gas. Summary of the Invention

[0004] To address the technical problem that existing waste heat recovery devices for furnace gas use fixed parameter control, which fails to adapt to dynamic changes in furnace gas parameters and thus cannot effectively recover waste heat, the present invention aims to provide a waste heat recovery device and method for a multi-bottom electrode energy-saving DC submerged arc furnace. The specific technical solution adopted is as follows: In a first aspect, one embodiment of the present invention provides a method for recovering waste heat from furnace gas in a multi-bottom electrode energy-saving DC submerged arc furnace, the method comprising the following steps: Based on the current furnace charge consumption rate, furnace temperature and pressure data, furnace gas temperature and dust concentration data, furnace gas outlet flow rate data, and electrode power, temperature, and insertion depth data of the multi-bottom electrode energy-saving DC submerged arc furnace, the furnace gas intensity index at the current moment is obtained. Based on the total amount of material fed in the current feeding, the remaining amount of material fed in the current feeding at the current moment, the actual execution time of the current feeding up to the current moment, and the change of the furnace gas intensity index at the current moment, predict the furnace gas intensity index at the next moment. Based on the current power data of the induced draft fan, the temperature data and flow rate data of the cooling medium, and the heat recovery coefficient of the cooling medium, the recovery capacity coefficient at the current moment is obtained. Based on the furnace gas intensity index and recovery capacity coefficient at the current moment and the next moment, the parameter correction coefficient at the current moment is obtained, and the operating parameters of the furnace gas waste heat recovery device at the current moment are corrected.

[0005] Furthermore, the method for obtaining the furnace gas intensity index is as follows: The product of the current charge consumption rate, furnace temperature data, and gas pressure data is normalized and used as the current charge reaction intensity index. The result of normalizing the product of the negative correlation between the dust concentration data of the furnace gas at the current moment, the temperature data of the furnace gas at the current moment, and the flow rate data of the furnace gas outlet at the current moment is used as the furnace gas state index at the current moment. The normalized product of the electrode's power data, temperature data, and insertion depth at the current moment is used as the electrode's usage intensity index at the current moment. The result of normalizing the sum of the current furnace charge reaction intensity index, furnace gas state index, and electrode usage intensity index is taken as the current furnace gas intensity index.

[0006] Furthermore, the method for predicting the furnace gas intensity index at the current moment and the next moment is as follows: Based on the total amount of material fed in the current feeding, the remaining amount of material fed in the current feeding at the current moment, and the actual execution time of the current feeding up to the current moment, obtain the overall theoretical remaining time and the theoretical remaining time at the current moment; The result of normalizing the difference between the theoretical remaining time at the current moment and the overall theoretical remaining time is taken as the degree of theoretical error at the current moment. Based on the current gas intensity index, theoretical error level, theoretical remaining time, and overall theoretical remaining time, the changes in the current gas intensity index are corrected to obtain the degree of correction at the current moment. The duration between the current moment and the next moment is taken as the first duration; The product of the current degree of change and the first duration is used as the reference change value; The sum of the reference change value and the current gas intensity index is used as the gas intensity index for the next time step.

[0007] Furthermore, the method for obtaining the overall theoretical remaining time and the theoretical remaining time at the current moment is as follows: The total amount of material fed in the current feeding is multiplied by the unit material consumption time of the multi-bottom electrode energy-saving DC submerged arc furnace, which is taken as the overall theoretical time of the current feeding. The difference between the total theoretical duration and the actual execution duration is taken as the total theoretical remaining duration. The theoretical remaining time at the current moment is calculated by multiplying the remaining amount of material from the current feeding by the unit material consumption time of the multi-bottom electrode energy-saving DC submerged arc furnace.

[0008] Furthermore, the method for obtaining the degree of correction change is as follows: Based on the current furnace gas intensity index, theoretical error level, theoretical remaining time, and overall theoretical remaining time, obtain the corrected remaining time at the current moment; The difference between the current time and the previous adjacent time is taken as the first value; The duration between the current moment and its previous adjacent moment is taken as the second duration; The ratio of the first value to the second duration is taken as the degree of change in furnace gas intensity at the current moment; The theoretical reference duration is the product of the theoretical remaining duration at the current moment and the preset reference weight. The hyperbolic tangent of the difference between the current corrected remaining duration and the theoretical reference duration is used as the first correction weight; The product of the first correction weight and the degree of change in furnace gas intensity is used as the correction value for the change in furnace gas intensity at the current moment. The sum of the correction value for the change in furnace gas intensity and the degree of change in furnace gas intensity is taken as the degree of correction at the current moment.

[0009] Furthermore, the formula for calculating the corrected remaining time is as follows: In the formula, The remaining time after correction at the current moment; This refers to the furnace gas intensity index at the current moment; This represents the theoretical remaining time at the current moment. This represents the remaining time of the overall theory. denoted as the theoretical error level at the current moment; e is the natural constant.

[0010] Furthermore, the method for obtaining the recycling capacity coefficient is as follows: The product of the current flow rate of the cooling medium and the heat recovery coefficient of the cooling medium is taken as the total heat recovered by the cooling medium at the current moment. The normalized result of the product of the negative correlation between the temperature data of the cooling medium at the current moment, the total recovered heat, and the power data of the induced draft fan at the current moment is used as the recovery capacity coefficient at the current moment.

[0011] Furthermore, the method for obtaining the parameter correction coefficient at the current moment and correcting the operating parameters of the furnace gas waste heat recovery device at the current moment is as follows: The ratio of the furnace gas intensity index at the current moment to the recovery capacity coefficient at the next moment is used as the parameter correction coefficient at the current moment. The product of each operating parameter at the current moment and the parameter correction coefficient is used as the correction operating parameter to correct the operating parameters of the furnace gas waste heat recovery device at the current moment.

[0012] Furthermore, the method for obtaining the furnace charge consumption rate is as follows: The difference in material height between any two adjacent moments within the current time period is taken as the change in furnace charge height; where the end time of the current time period is the current moment. The ratio of all the changes in furnace charge height to the duration between two adjacent moments is taken as the rate of change of furnace charge height. The average rate of change of all charge heights is taken as the charge consumption rate at the current moment.

[0013] Secondly, another embodiment of the present invention provides a waste heat recovery device for furnace gas of a multi-bottom electrode energy-saving DC submerged arc furnace. The device includes: a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any of the above methods.

[0014] The present invention has the following beneficial effects: This invention first obtains the furnace gas intensity index at the current moment based on the current data of the multi-bottom electrode energy-saving DC submerged arc furnace, including the furnace charge consumption rate, furnace temperature and pressure data, furnace gas temperature and dust concentration data, furnace gas outlet flow rate data, and electrode power, temperature, and insertion depth. This accurately reflects the recoverable waste heat generated by the multi-bottom electrode energy-saving DC submerged arc furnace at the current moment. Further, based on the total amount of the current feed, the remaining amount of the current feed at the current moment, the actual execution time up to the current feed, and the change in the furnace gas intensity index at the current moment, it predicts the furnace gas intensity index at the next moment, accurately predicting the recoverable waste heat generated at the next moment, preparing for subsequent adjustments to the operating parameters of the furnace gas waste heat recovery device. To analyze the waste heat recovery capacity of the furnace gas waste heat recovery device in real time, and further based on the current... By recording the power data of the induced draft fan, the temperature and flow data of the cooling medium, and the heat recovery coefficient of the cooling medium, the current recovery capacity coefficient is obtained, accurately reflecting the current heat recovery capacity of the furnace gas waste heat recovery device. To enable the furnace gas waste heat recovery device to recover the waste heat generated by the submerged arc furnace more accurately and in real time, a parameter correction coefficient is obtained based on the furnace gas intensity index and recovery capacity coefficient at the current and next time points. This accurately reflects the need to adjust the operating parameters of the furnace gas waste heat recovery device at the current time, allowing for precise correction of the device's operating parameters. This ensures more accurate and reasonable heat recovery, effectively improving the waste heat recovery efficiency of the device and preventing energy loss caused by ineffective operation. This achieves the dual goals of precise waste heat recovery and energy-saving operation. Attached Figure Description

[0015] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 A schematic flowchart of a waste heat recovery method for a multi-bottom electrode energy-saving DC submerged arc furnace provided in an embodiment of the present invention; Figure 2 A flowchart illustrating a method for obtaining furnace gas intensity indicators according to an embodiment of the present invention; Figure 3 This is a flowchart of a method for predicting the furnace gas intensity index at the current moment and the next moment, provided by an embodiment of the present invention. Figure 4A structural diagram of a waste heat recovery system for a multi-bottom electrode energy-saving DC submerged arc furnace provided in one embodiment of the present invention; Figure 5 This is a schematic diagram of a computer device provided according to an embodiment of the present invention. Detailed Implementation

[0017] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a waste heat recovery device and method for a multi-bottom electrode energy-saving DC submerged arc furnace according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0019] The following description, in conjunction with the accompanying drawings, details the specific scheme of the waste heat recovery device and method for a multi-bottom electrode energy-saving DC submerged arc furnace provided by the present invention.

[0020] Example 1: This invention proposes a method for recovering waste heat from furnace gas in a multi-bottom electrode energy-saving DC submerged arc furnace. Please refer to [link / reference]. Figure 1 The diagram illustrates a schematic flowchart of a waste heat recovery method for a multi-bottom electrode energy-saving DC submerged arc furnace according to an embodiment of the present invention. The method includes the following steps: Step S1: Based on the current furnace charge consumption rate, furnace temperature and pressure data, furnace gas temperature and dust concentration data, furnace gas outlet flow rate data, and electrode power, temperature, and insertion depth of the multi-bottom electrode energy-saving DC submerged arc furnace, obtain the furnace gas intensity index at the current moment.

[0021] Specifically, this embodiment uses a multi-bottom electrode energy-saving DC submerged arc furnace and its residual heat recovery device as an example for analysis. The term "multi-bottom electrode energy-saving DC submerged arc furnace and its residual heat recovery device" will be used in the following descriptions. To achieve real-time monitoring of the operating status of the multi-bottom electrode energy-saving DC submerged arc furnace and its residual heat recovery device, sensors are deployed at key locations within the furnace and device. These sensors at key locations include a charge reaction progress monitoring unit, a furnace gas status monitoring unit, an electrode status monitoring unit, and a residual heat recovery device monitoring unit.

[0022] It should be noted that the furnace charge reaction progress monitoring unit is deployed inside or near the furnace to monitor the core smelting process within the furnace. It includes a microwave particle level sensor, a pressure sensor, and a thermocouple temperature sensor. Among them, the microwave particle level sensor can penetrate the high-temperature environment and monitor the changes in the furnace charge height in real time to calculate the material consumption rate. The pressure sensor is used to monitor the gas pressure inside the furnace in real time. The gas pressure change is an important indicator of the reaction intensity and the rate of furnace gas generation. The thermocouple temperature sensor is used to directly measure the temperature of the reaction zone inside the furnace, indirectly reflecting the real-time intensity of the chemical reaction. The furnace gas status monitoring unit is deployed in the furnace gas outlet pipeline to quantify the status of raw materials for waste heat recovery. It includes a temperature sensor, an ultrasonic flow meter, and a microwave dust concentration data meter. The temperature sensor is used to accurately measure the temperature of the high-temperature furnace gas in real time, which is a key parameter for calculating the total amount of waste heat. The ultrasonic flow meter is used to measure the volumetric flow rate of the furnace gas in real time. The microwave dust concentration data meter is used to monitor the dust concentration data in the furnace gas in real time. High dust concentration can affect heat exchange efficiency and may clog the equipment. The electrode status monitoring unit is deployed in the electrode system to directly monitor the status of the energy input core. It includes current and voltage sensors, laser displacement sensors, and infrared temperature sensors. Among them, the current and voltage sensors are used to monitor the working power of the electric arc in real time, which is the direct basis for calculating energy input and reaction intensity. The laser displacement sensor is used to measure the insertion depth of the electrode in real time and accurately. This parameter directly affects the arc length and the position of the reaction zone. The infrared temperature sensor is used to measure the surface temperature of the electrode in a non-contact manner. The waste heat recovery device monitoring unit is integrated into the waste heat recovery system itself to evaluate its performance and status. It includes an electromagnetic flow meter, a cooling medium temperature sensor, and a power sensor. The electromagnetic flow meter is installed on the circulating water pipeline to accurately measure the flow rate of the cooling medium used for heat exchange, and is a direct control variable for adjusting the recovery intensity. The cooling medium temperature sensor measures the water temperature at the inlet and outlet of the heat exchanger to calculate the instantaneous heat exchange and recovery efficiency. The power sensor monitors the operating power of the induced draft fan in real time to evaluate the energy consumption of the device and indirectly reflect changes in system resistance.

[0023] In addition, to accurately monitor the transfer and loss of heat in the recovery device, temperature sensors are installed in stages at the furnace gas outlet and the outlets of each heat exchange unit in the waste heat recovery device.

[0024] To ensure data reliability and availability, all sensors utilize high-temperature resistant materials and designs, guaranteeing long-term stable operation in harsh high-temperature environments of 500℃-1000℃, preventing data distortion or equipment failure. This embodiment uses a uniform frequency of 20Hz for synchronous data acquisition, capturing rapid parameter changes caused by arc fluctuations, feeding actions, etc., providing a high-fidelity data foundation for subsequent real-time analysis and predictive control. Implementers can set the data acquisition frequency according to actual conditions; no limitation is imposed here. Furthermore, the acquired raw data requires preprocessing, including but not limited to signal filtering, unit conversion, and invalid value removal, to improve data quality. The processed valid data is transmitted in real-time and stored in a designated database, providing accurate data support for subsequent analysis.

[0025] To analyze the energy generated by material reactions in a multi-bottom electrode energy-saving DC submerged arc furnace in real time, enabling accurate adaptive control of the waste heat recovery device's operating parameters and maximizing energy saving and recovery, this embodiment obtains the furnace gas intensity index based on the furnace charge consumption rate, furnace temperature and pressure data, furnace gas temperature and dust concentration data, furnace gas outlet flow rate data, and electrode power, temperature, and insertion depth at the current moment. A higher furnace gas intensity index indicates a greater total amount of recoverable waste heat generated at the current moment.

[0026] Preferably, in one feasible embodiment, the method for obtaining the furnace gas intensity index is described in [reference needed]. Figure 2 The document presents a flowchart of a method for obtaining a furnace gas intensity index provided in this embodiment. The method includes the following steps: Step S201: The normalized result of the product of the current furnace charge consumption rate, furnace temperature data and gas pressure data is used as the furnace charge reaction intensity index at the current moment.

[0027] A higher charge consumption rate at the current moment, along with higher temperature and pressure data within the furnace, indicates a more intense material reaction within the furnace. Therefore, this embodiment normalizes the product of the charge consumption rate, temperature, and pressure data at the current moment as an indicator of the charge reaction intensity. A higher charge reaction intensity indicator indicates a more intense material reaction within the furnace, indirectly indicating a greater amount of recoverable energy generated at that moment. This embodiment normalizes the product of the charge consumption rate, temperature, and pressure data at the current moment using a normalization function.

[0028] The method for obtaining the furnace charge consumption rate is as follows: Considering that the consumption of furnace charge is a continuous process, this embodiment sets the duration of the current time period to 0.1 seconds. The implementer can set the size of the current time period according to the actual situation; no limitation is made here. The end time of the current time period is always the current time. The absolute value of the difference between the material heights at any two adjacent moments within the current time period is obtained and used as the furnace charge height change value. The ratio of each furnace charge height change value to the duration between the corresponding two adjacent moments is used as the furnace charge height change rate. The average of all furnace charge height change rates is used as the furnace charge consumption rate at the current moment. It should be noted that the current time period must be the time period corresponding to the same charge feeding in the furnace; that is, there must be no charge feeding activity within the current time period.

[0029] Step S202: The normalized result of the product of the negative correlation between the dust concentration data of the furnace gas at the current moment, the temperature data of the furnace gas at the current moment, and the flow rate data of the furnace gas outlet is used as the furnace gas state index at the current moment.

[0030] The higher the furnace gas temperature, the larger the furnace gas outlet flow rate, and the smaller the furnace gas dust concentration at the current moment, the more energy can be recovered at that moment. Therefore, in this embodiment, the negative correlation result of the furnace gas dust concentration data at the current moment, the product of the furnace gas temperature data and the furnace gas outlet flow rate data at the current moment, is normalized and used as the furnace gas state index at the current moment. The larger the furnace gas state index, the more energy can be recovered at the current moment. In this embodiment, the negative of the furnace gas dust concentration data at the current moment is used as the power of an exponential function with the natural constant as the base. The output of this exponential function is the negative correlation result of the dust concentration data. In this embodiment, the negative correlation result of the furnace gas dust concentration data at the current moment, the product of the furnace gas temperature data and the furnace gas outlet flow rate data at the current moment is normalized using the norm normalization function.

[0031] Step S203: The normalized result of the product of the current electrode power data, temperature data and insertion depth is used as the electrode usage intensity index at the current moment.

[0032] A higher electrode power, temperature, and insertion depth at the current moment indicate a stronger arc intensity between the electrode and the furnace charge, and consequently, a greater electrode operating intensity. This indirectly suggests a stronger reaction in the furnace charge, resulting in a greater amount of recoverable energy. Therefore, this embodiment uses the normalized product of the electrode power, temperature, and insertion depth at the current moment as the electrode operating intensity index. A higher electrode operating intensity index indicates a stronger reaction in the furnace charge at the current moment. Specifically, this embodiment uses a normalization function to normalize the product of the electrode power, temperature, and insertion depth at the current moment.

[0033] Step S204: Add the current furnace charge reaction intensity index, furnace gas state index and electrode usage intensity index and normalize the result to obtain the current furnace gas intensity index.

[0034] It is known that the higher the current-time charge reaction intensity index, furnace gas state index, and electrode usage intensity index, the greater the recoverable energy generated at that time. Therefore, in this embodiment, the sum of the current-time charge reaction intensity index, furnace gas state index, and electrode usage intensity index, followed by normalization, is taken as the current-time furnace gas intensity index. This embodiment uses a normalization function to normalize the sum of the current-time charge reaction intensity index, furnace gas state index, and electrode usage intensity index.

[0035] Step S2: Based on the total amount of material fed in the current feeding, the remaining amount of material fed in the current feeding at the current moment, the actual execution time of the current feeding up to the current moment, and the change of the furnace gas intensity index at the current moment, predict the furnace gas intensity index at the next moment.

[0036] Specifically, it is known that the charging runtime of a multi-bottom electrode energy-saving DC submerged arc furnace is significantly correlated with its internal operating conditions in practice. When the equipment's workload is higher (e.g., faster charge reaction rate, increased electrode power), the charge consumption rate increases accordingly, and the charging runtime shortens. Conversely, when the equipment's workload decreases (e.g., slower charge reaction, reduced electrode power), charge consumption slows down, and the charging runtime lengthens. Simultaneously, it is known that the furnace gas intensity index is strongly coupled with the equipment's operating conditions. Changes in equipment conditions directly lead to changes in furnace gas generation efficiency, temperature, and flow rate. Therefore, the furnace gas intensity index can serve as a reference indicator for characterizing the equipment's real-time operating status. Based on these characteristics, by integrating existing patterns of furnace gas intensity index changes during equipment operation (e.g., fluctuation curves and stage characteristics of furnace gas intensity index during historical charging operations) and combining them with real-time charging progress, a dynamic prediction model for changes in charging runtime can be constructed. This model can further predict subsequent changes in furnace gas intensity index, providing a forward-looking basis for adjusting the operating parameters of the furnace gas waste heat recovery device. Therefore, this embodiment predicts the furnace gas intensity index for the next moment based on the total amount of material fed in the current feeding, the remaining amount of material fed in the current feeding at the current moment, the actual execution time of the current feeding up to the current moment, and the change in the furnace gas intensity index at the current moment. This is done to prepare for adjusting the operating parameters of the furnace gas waste heat recovery device to improve the waste heat recovery rate. It should be noted that the total amount of material fed in the current feeding refers to the total volume of the material fed in the current feeding, and the remaining amount of material fed in the current feeding at the current moment refers to the volume of the material remaining at the current moment.

[0037] Preferably, in one feasible embodiment, the method for predicting the furnace gas intensity index at the current moment and the next moment can be found in [reference needed]. Figure 3 The document presents a flowchart of a method for predicting the furnace gas intensity index at the current moment and the next moment, as provided in this embodiment. The method includes the following steps: Step S301: Obtain the theoretical error level at the current moment.

[0038] First, based on the total amount of material fed in the current operation, the remaining amount of material fed in the current operation at the current moment, and the actual execution time of the current operation up to the current moment, the overall theoretical remaining time and the theoretical remaining time at the current moment are obtained. The closer the overall theoretical remaining time and the theoretical remaining time at the current moment are to each other, the more accurate the analyzed theoretical remaining time is. Then, the absolute value of the difference between the theoretical remaining time at the current moment and the overall theoretical remaining time is normalized, and the result is used as the theoretical error level at the current moment. The smaller the theoretical error level, the smaller the error of the relevant theoretical information on the furnace charge running time. In this embodiment, the absolute value of the difference between the theoretical remaining time at the current moment and the overall theoretical remaining time is normalized using the norm normalization function.

[0039] The methods for obtaining the overall theoretical remaining time and the theoretical remaining time at the current moment are as follows: the product of the total amount of material fed in the current feeding and the unit material consumption time of the multi-bottom electrode energy-saving DC submerged arc furnace is used as the overall theoretical remaining time of the current feeding; the difference between the overall theoretical time and the actual execution time of the current feeding up to the current moment is used as the overall theoretical remaining time; and the product of the remaining amount of material fed in the current feeding and the unit material consumption time of the multi-bottom electrode energy-saving DC submerged arc furnace is used as the theoretical remaining time at the current moment.

[0040] Furthermore, the method for obtaining the unit material consumption time of the multi-bottom electrode energy-saving DC submerged arc furnace is as follows: A preset number of feeding cycles that are prior to and adjacent to the current feeding cycle are all used as reference feeding cycles; the average of the total amount of all reference feeding cycles is used as the average feeding amount; the average of the overall running time of all reference feeding cycles is used as the average feeding running time; and the ratio of the average feeding running time to the average feeding amount is used as the unit material consumption time of the multi-bottom electrode energy-saving DC submerged arc furnace. In this embodiment, the preset number is set to 5. Implementers can set the size of the preset number according to actual conditions, and this is not limited here.

[0041] Step S302: Obtain the degree of correction change at the current moment.

[0042] In order to accurately analyze the changes in the furnace gas intensity index at the current moment and accurately predict the furnace gas intensity index at the next moment, this embodiment further corrects the changes in the furnace gas intensity index at the current moment based on the furnace gas intensity index at the current moment, the theoretical error level, the theoretical remaining time, and the overall theoretical remaining time, and obtains the correction change level at the current moment, accurately characterizing the change trend of the furnace gas intensity index at the current moment, so as to prepare for predicting the furnace gas intensity index at the next moment. The method for obtaining the degree of correction is as follows: First, based on the furnace gas intensity index, theoretical error level, theoretical remaining time, and overall theoretical remaining time at the current moment, the corrected remaining time at the current moment is obtained. This is because accurately analyzing the remaining running time of the current feeding operation requires a comprehensive correction based on the theoretical remaining time at the current moment and the overall theoretical remaining time, combined with the furnace gas intensity index and theoretical error level at the current moment. Specifically, since the furnace gas intensity index characterizes the equipment's current operating intensity, a higher furnace gas intensity index indicates a more intense internal reaction and higher operating intensity, thus requiring a further shortening of the current feeding operation. The remaining time is used to match the rapid consumption of furnace charge caused by high-intensity operation of the equipment. The degree of theoretical error reflects the degree of deviation between the actual furnace charge consumption and the theoretical model. Its magnitude directly affects the weighting of the theoretical remaining time at the current moment and the overall theoretical remaining time. When the degree of theoretical error is smaller, it indicates that the deviation between the actual consumption and the theoretical model is smaller, and the reference value of the overall theoretical remaining time and the theoretical remaining time at the current moment should be similar. When the degree of theoretical error is larger, it indicates that the theoretical model deviates further from the actual working conditions, the credibility of the overall theoretical remaining time decreases, and the correction process will rely more on the theoretical remaining time at the current moment to improve the accuracy of the prediction results. Therefore, the formula for calculating the remaining time is: In the formula, The remaining time after correction at the current moment; This refers to the furnace gas intensity index at the current moment; This represents the theoretical remaining time at the current moment. This represents the remaining time of the overall theory. The theoretical error level at the current moment; e is the natural constant; The difference between the current moment and its adjacent moment is taken as the first value; the duration between the current moment and its adjacent moment is taken as the second duration; and the ratio of the first value to the second duration is taken as the degree of change of the gas intensity at the current moment, thus initially determining the trend of the gas intensity index at the current moment. When the degree of change of the gas intensity is greater than 0, the gas intensity index at the current moment shows an increasing trend. In this case, if the remaining time after correction is larger, the increasing trend of the gas intensity index at the next moment should be larger; conversely, if the remaining time after correction is smaller, the increasing trend of the gas intensity index at the next moment should be smaller. When the degree of change of the gas intensity is less than 0, the gas intensity index at the current moment shows a decreasing trend. In this case, if the remaining time after correction is larger, the decreasing trend of the gas intensity index at the next moment may be larger; conversely, if the remaining time after correction is smaller, the decreasing trend of the gas intensity index at the next moment should be smaller, because at this time, the remaining burden is less, the gas intensity is already in its final stage, so the decreasing trend should be slow. Based on the consideration of correcting the remaining time, to more accurately predict the subsequent changes in the furnace gas intensity index at the current moment, the theoretical remaining time at the current moment is multiplied by a preset reference weight, which is then used as the theoretical reference time. In this embodiment, the preset reference weight is set to... The implementer can set the size of the preset reference weight according to the actual situation, which is not limited here, but the preset reference weight must be greater than 0 and less than 1. The hyperbolic tangent of the difference between the current correction remaining time and the theoretical reference time is used as the first correction weight. The smaller the first correction weight, the smaller the correction remaining time, and the weaker the growth trend or decrease trend of the gas intensity index should be. Then, the product of the first correction weight and the degree of change of gas intensity is used as the correction value of the gas intensity change at the current time. Then, the sum of the correction value of the gas intensity change and the degree of change of gas intensity is used as the degree of correction change at the current time.

[0043] Step S303: Predict the furnace gas intensity index at the current moment and the next moment.

[0044] Given that the degree of correction change at the current moment is essentially the predicted trend of the furnace gas intensity index at the next moment, we obtain the duration between the current moment and the next moment as the first duration; then we multiply the degree of correction change at the current moment by the first duration as the reference change value; finally, we add the reference change value to the furnace gas intensity index at the current moment as the furnace gas intensity index at the next moment.

[0045] Step S3: Based on the power data of the induced draft fan, the temperature data and flow rate data of the cooling medium at the current moment, and the heat recovery coefficient of the cooling medium, obtain the recovery capacity coefficient at the current moment.

[0046] In the waste heat recovery device of multi-bottom electrode energy-saving DC submerged arc furnace, the dynamic matching of the furnace gas intensity index and the recovery capacity coefficient is the core prerequisite for achieving efficient energy-saving recovery. The furnace gas intensity index is used to comprehensively quantify the furnace gas temperature, flow rate, and equipment operating conditions, reflecting the total amount of waste heat that can be recovered per unit time. The recovery capacity coefficient, on the other hand, characterizes the maximum waste heat absorption capacity of the furnace gas waste heat recovery device through the cooling medium flow rate, temperature, and induced draft fan power. The comparison between the two directly determines the recovery status: when the furnace gas intensity index is greater than the recovery capacity coefficient, it indicates that the actual total amount of waste heat from the furnace gas exceeds the current recovery capacity of the device. A large amount of high-temperature furnace gas is discharged without being fully utilized, resulting in under-recovery. This not only wastes usable energy but may also cause thermal damage to subsequent equipment due to excessively high exhaust temperature. When the furnace gas intensity index is less than the recovery capacity coefficient, it means that the device's recovery capacity exceeds the actual waste heat demand. Excessive consumption of the cooling medium and ineffective energy consumption of the induced draft fan lead to over-recovery. Although waste heat can be fully recovered, additional energy is wasted due to redundant equipment operation.

[0047] To avoid the aforementioned problems, a parameter adjustment mechanism based on the comparison between the furnace gas intensity index and the recovery capacity coefficient needs to be established. When under-recovery is detected, the recovery capacity of the device is enhanced by increasing the cooling medium flow rate or increasing the induced draft fan power, so that the recovery capacity coefficient approaches the furnace gas intensity index. When over-recovery is detected, the cooling medium flow rate or the induced draft fan power is reduced to weaken the recovery capacity to match the actual waste heat load. Through this dynamic adjustment, the recovery capacity coefficient and the furnace gas intensity index are ensured to be matched in real time, maximizing waste heat recovery efficiency while avoiding energy loss caused by ineffective equipment operation, achieving the dual goals of precise recovery and energy-saving operation. Therefore, this embodiment first obtains the recovery capacity coefficient at the current moment based on the induced draft fan power data, cooling medium temperature data, flow rate data, and the heat recovery coefficient of the cooling medium, preparing for subsequent adjustment of the operating parameters of the furnace gas waste heat recovery device. The heat recovery coefficient of the cooling medium can be directly obtained through experiments, and its essence is the heat that can be carried away by a unit flow rate through the equipment's cooling pipe.

[0048] Preferably, in one feasible embodiment, the recovery capacity coefficient is obtained by multiplying the flow rate data of the cooling medium at the current moment by the heat recovery coefficient of the cooling medium, which is taken as the total recovered heat of the cooling medium at the current moment. The larger the total recovered heat, the stronger the recovery capacity of the furnace gas waste heat recovery device at the current moment. When the power data of the induced draft fan at the current moment is larger and the temperature data of the cooling medium at the current moment is lower, it also indicates that the recovery capacity of the furnace gas waste heat recovery device at the current moment is stronger. Furthermore, in this embodiment, the normalized result of the negative correlation of the temperature data of the cooling medium at the current moment, the total recovered heat, and the power data of the induced draft fan at the current moment is taken as the recovery capacity coefficient at the current moment. In this embodiment, the negative number of the temperature data of the cooling medium is taken as the power of an exponential function with the natural constant as the base, and the output of the exponential function is the negative correlation result of the temperature data of the cooling medium. In this embodiment, the negative correlation of the temperature data of the cooling medium at the current moment, the total recovered heat, and the power data of the induced draft fan at the current moment are normalized by the norm normalization function.

[0049] Step S4: Based on the furnace gas intensity index and recovery capacity coefficient at the current time and the next time, obtain the parameter correction coefficient at the current time, and correct the working parameters of the furnace gas waste heat recovery device at the current time.

[0050] Specifically, as shown in step S3, when the furnace gas intensity index at the current moment is greater than the recovery capacity coefficient at the current moment, the various operating parameters of the furnace gas waste heat recovery device at the current moment should be adjusted upwards to improve the heat absorption capacity of the furnace gas waste heat recovery device and avoid under-recovery. When the furnace gas intensity index at the current moment is less than the recovery capacity coefficient at the current moment, the various operating parameters of the furnace gas waste heat recovery device at the current moment should be adjusted downwards to avoid redundant operation of the equipment leading to additional energy waste. Therefore, this embodiment obtains the parameter correction coefficient at the current moment based on the furnace gas intensity index at the current moment and the recovery capacity coefficient at the next moment, and corrects the operating parameters of the furnace gas waste heat recovery device at the current moment. It should be noted that the operating parameters refer to the flow rate data of the cooling medium and the power data of the induced draft fan in the furnace gas waste heat recovery device.

[0051] Preferably, in one feasible method of this embodiment, the method for obtaining the parameter correction coefficient at the current moment and correcting the operating parameters of the furnace gas waste heat recovery device at the current moment is as follows: the ratio of the furnace gas intensity index to the recovery capacity coefficient at the next moment is used as the parameter correction coefficient at the current moment. It should be noted that this embodiment does not consider the case where the furnace gas intensity index and the recovery capacity coefficient are 0, because the case where the furnace gas intensity index and the recovery capacity coefficient are 0 will not occur during the operation of the multi-bottom electrode energy-saving DC submerged arc furnace and its furnace gas waste heat recovery device. Then, the product of each operating parameter of the furnace gas waste heat recovery device at the current moment and the parameter correction coefficient is used as the correction operating parameter to accurately correct the operating parameters of the furnace gas waste heat recovery device at the current moment. This ensures in real time that the furnace gas waste heat recovery device maximizes waste heat recovery efficiency while effectively avoiding energy loss caused by ineffective operation of the furnace gas waste heat recovery device, achieving the dual goals of accurate recovery and energy-saving operation.

[0052] To further quantify and evaluate the recovery efficiency of the waste heat recovery device and ensure its stable operation, it is necessary to monitor the waste heat recovery effect in real time by measuring the temperature difference between the inlet and outlet of the device. This embodiment uses the normalized result of the difference between the inlet and outlet furnace gas temperatures at each moment as the waste heat recovery effect coefficient for that moment. Specifically, the difference between the inlet and outlet furnace gas temperatures is normalized using a normalization function. A larger waste heat recovery effect coefficient indicates a larger temperature difference between the inlet and outlet furnace gas temperatures at the corresponding moment, indirectly indicating a higher proportion of waste heat recovery and a better recovery effect. Conversely, a smaller coefficient indicates a decrease in waste heat recovery efficiency, suggesting potential problems such as poor heat exchange in the waste heat recovery device. Furthermore, if the waste heat recovery efficiency coefficient is consistently lower than the preset waste heat recovery efficiency coefficient threshold within a preset time period, an anomaly is determined in the furnace gas waste heat recovery device. In this case, a protection mechanism will be automatically triggered, stopping the operation of the submerged arc furnace and the waste heat recovery device. Simultaneously, a maintenance warning will be issued, prompting a comprehensive overhaul of the waste heat recovery device (such as cleaning the heat exchange surfaces, calibrating sensors, and checking pipeline patency) to restore its normal waste heat recovery capacity and ensure its long-term stable operation in a highly efficient and energy-saving state. In this embodiment, the preset time period is set to 10 minutes, and the preset waste heat recovery efficiency coefficient threshold is set to 0.6. Implementers can adjust the preset time period and the preset waste heat recovery efficiency coefficient threshold according to actual conditions; no limitation is imposed here.

[0053] In summary, this embodiment obtains the furnace gas intensity index; based on the total amount of material fed in the current operation, the remaining amount of material fed in the current operation at the current moment, the actual execution time of the current operation up to the current moment, and the change in the furnace gas intensity index at the current moment, it predicts the furnace gas intensity index at the next moment; it obtains the recovery capacity coefficient; and based on the furnace gas intensity index and recovery capacity coefficient at the next moment, it obtains the parameter correction coefficient at the current moment, and corrects the operating parameters of the furnace gas waste heat recovery device at the current moment. This invention effectively improves the waste heat recovery efficiency of the furnace gas waste heat recovery device by real-time correction of its operating parameters, while effectively avoiding energy loss caused by ineffective operation of the furnace gas waste heat recovery device.

[0054] Example 2: This invention also proposes a waste heat recovery system for a multi-bottom electrode energy-saving DC submerged arc furnace. Please refer to [link to relevant documentation]. Figure 4 The diagram shows a structural diagram of a waste heat recovery system for a multi-bottom electrode energy-saving DC submerged arc furnace according to an embodiment of the present invention. The system includes: a furnace gas intensity index acquisition module 10, a furnace gas intensity index prediction module 20, a recovery capacity coefficient acquisition module 30, and a correction module 40.

[0055] The furnace gas intensity index acquisition module 10 is used to acquire the furnace gas intensity index at the current moment based on the furnace charge consumption rate, furnace temperature and pressure data, furnace gas temperature and dust concentration data, furnace gas outlet flow rate data, and electrode power data, temperature data, and insertion depth of the multi-bottom electrode energy-saving DC submerged arc furnace.

[0056] The furnace gas intensity index prediction module 20 is used to predict the furnace gas intensity index at the next moment based on the total amount of the current feeding, the remaining amount of the current feeding at the current moment, the actual execution time of the current feeding up to the current moment, and the change of the furnace gas intensity index at the current moment.

[0057] The recovery capacity coefficient acquisition module 30 is used to acquire the recovery capacity coefficient at the current moment based on the power data of the induced draft fan, the temperature data and flow data of the cooling medium, and the heat recovery coefficient of the cooling medium.

[0058] The correction module 40 is used to obtain the parameter correction coefficient at the current moment based on the furnace gas intensity index and recovery capacity coefficient at the next moment, and to correct the working parameters of the furnace gas waste heat recovery device at the current moment.

[0059] It should be noted that the system provided in the above embodiments is only an example of the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the computer equipment can be divided into different functional modules to complete all or part of the functions described above. In addition, the waste heat recovery system for multi-bottom electrode energy-saving DC submerged arc furnace and the waste heat recovery method for multi-bottom electrode energy-saving DC submerged arc furnace provided in the above embodiments belong to the same concept. The specific implementation process is detailed in the method embodiments and will not be repeated here.

[0060] Example 3: This invention also proposes a waste heat recovery device for a multi-bottom electrode energy-saving DC submerged arc furnace. The device includes a memory and a processor. The memory stores executable program code, and the processor calls and executes the executable program code to perform a waste heat recovery method for a multi-bottom electrode energy-saving DC submerged arc furnace provided in this application. Specifically, the device may be a chip, component, or module. The chip may include a connected processor and memory; the memory stores instructions, and when the processor calls and executes the instructions, the chip can perform the waste heat recovery method for a multi-bottom electrode energy-saving DC submerged arc furnace provided in the above embodiment.

[0061] Furthermore, this application also protects a computer device; please refer to [link to relevant documentation]. Figure 5 The computer device includes a memory 401, a processor 402, and a computer program 403 stored in the memory 401 and running on the processor 402. When the processor 402 executes the computer program 403, the computer device can perform any of the aforementioned methods for recovering waste heat from furnace gas in a multi-bottom electrode energy-saving DC submerged arc furnace.

[0062] Example 4: This embodiment also provides a computer-readable storage medium storing computer program code. When the computer program code is run on a computer, the computer executes the above-mentioned related method steps to realize the waste heat recovery method of the furnace gas of the multi-bottom electrode energy-saving DC submerged arc furnace provided in the above embodiment.

[0063] Example 5: This embodiment also provides a computer program product. When the computer program product is run on a computer, it causes the computer to perform the above-mentioned related steps to realize the waste heat recovery method of the furnace gas of the multi-bottom electrode energy-saving DC submerged arc furnace provided in the above embodiment.

[0064] In this embodiment, the device, computer-readable storage medium, computer program product, or chip are all used to execute the corresponding methods provided above. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects in the corresponding methods provided above, and will not be repeated here.

[0065] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0066] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A method for recovering waste heat from furnace gas in a multi-bottom electrode energy-saving DC submerged arc furnace, characterized in that, The method includes the following steps: Based on the current furnace charge consumption rate, furnace temperature and pressure data, furnace gas temperature and dust concentration data, furnace gas outlet flow rate data, and electrode power, temperature, and insertion depth data of the multi-bottom electrode energy-saving DC submerged arc furnace, the furnace gas intensity index at the current moment is obtained. Based on the total amount of material fed in the current feeding, the remaining amount of material fed in the current feeding at the current moment, the actual execution time of the current feeding up to the current moment, and the change of the furnace gas intensity index at the current moment, predict the furnace gas intensity index at the next moment. Based on the current power data of the induced draft fan, the temperature data and flow rate data of the cooling medium, and the heat recovery coefficient of the cooling medium, the recovery capacity coefficient at the current moment is obtained. Based on the furnace gas intensity index and recovery capacity coefficient at the current moment and the next moment, the parameter correction coefficient at the current moment is obtained, and the operating parameters of the furnace gas waste heat recovery device at the current moment are corrected.

2. The method for recovering waste heat from furnace gas in a multi-bottom electrode energy-saving DC submerged arc furnace as described in claim 1, characterized in that, The method for obtaining the furnace gas intensity index is as follows: The product of the current charge consumption rate, furnace temperature data, and gas pressure data is normalized and used as the current charge reaction intensity index. The result of normalizing the product of the negative correlation between the dust concentration data of the furnace gas at the current moment, the temperature data of the furnace gas at the current moment, and the flow rate data of the furnace gas outlet at the current moment is used as the furnace gas state index at the current moment. The normalized product of the electrode's power data, temperature data, and insertion depth at the current moment is used as the electrode's usage intensity index at the current moment. The result of normalizing the sum of the current furnace charge reaction intensity index, furnace gas state index, and electrode usage intensity index is taken as the current furnace gas intensity index.

3. The method for recovering waste heat from furnace gas in a multi-bottom electrode energy-saving DC submerged arc furnace as described in claim 1, characterized in that, The method for predicting the furnace gas intensity index at the current moment and the next moment is as follows: Based on the total amount of material fed in the current feeding, the remaining amount of material fed in the current feeding at the current moment, and the actual execution time of the current feeding up to the current moment, obtain the overall theoretical remaining time and the theoretical remaining time at the current moment; The result of normalizing the difference between the theoretical remaining time at the current moment and the overall theoretical remaining time is taken as the degree of theoretical error at the current moment. Based on the current gas intensity index, theoretical error level, theoretical remaining time, and overall theoretical remaining time, the changes in the current gas intensity index are corrected to obtain the degree of correction at the current moment. The duration between the current moment and the next moment is taken as the first duration; The product of the current degree of change and the first duration is used as the reference change value; The sum of the reference change value and the current gas intensity index is used as the gas intensity index for the next time step.

4. The method for recovering waste heat from furnace gas in a multi-bottom electrode energy-saving DC submerged arc furnace as described in claim 3, characterized in that, The methods for obtaining the overall theoretical remaining time and the theoretical remaining time at the current moment are as follows: The total amount of material fed in the current feeding is multiplied by the unit material consumption time of the multi-bottom electrode energy-saving DC submerged arc furnace, which is taken as the overall theoretical time of the current feeding. The difference between the total theoretical duration and the actual execution duration is taken as the total theoretical remaining duration. The theoretical remaining time at the current moment is calculated by multiplying the remaining amount of material from the current feeding by the unit material consumption time of the multi-bottom electrode energy-saving DC submerged arc furnace.

5. The method for recovering waste heat from furnace gas in a multi-bottom electrode energy-saving DC submerged arc furnace as described in claim 3, characterized in that, The method for obtaining the degree of correction change is as follows: Based on the current furnace gas intensity index, theoretical error level, theoretical remaining time, and overall theoretical remaining time, obtain the corrected remaining time at the current moment; The difference between the current time and the previous adjacent time is taken as the first value; The duration between the current moment and its previous adjacent moment is taken as the second duration; The ratio of the first value to the second duration is taken as the degree of change in furnace gas intensity at the current moment; The theoretical reference duration is the product of the theoretical remaining duration at the current moment and the preset reference weight. The hyperbolic tangent of the difference between the current corrected remaining duration and the theoretical reference duration is used as the first correction weight; The product of the first correction weight and the degree of change in furnace gas intensity is used as the correction value for the change in furnace gas intensity at the current moment. The sum of the correction value for the change in furnace gas intensity and the degree of change in furnace gas intensity is taken as the degree of correction at the current moment.

6. The method for recovering waste heat from furnace gas in a multi-bottom electrode energy-saving DC submerged arc furnace as described in claim 5, characterized in that, The formula for calculating the corrected remaining time is: In the formula, The remaining time after correction at the current moment; This refers to the furnace gas intensity index at the current moment; This represents the theoretical remaining time at the current moment. This represents the remaining time of the overall theory. denoted as the theoretical error level at the current moment; e is the natural constant.

7. The method for recovering waste heat from furnace gas in a multi-bottom electrode energy-saving DC submerged arc furnace as described in claim 1, characterized in that, The method for obtaining the recycling capacity coefficient is as follows: The product of the current flow rate of the cooling medium and the heat recovery coefficient of the cooling medium is taken as the total heat recovered by the cooling medium at the current moment. The normalized result of the product of the negative correlation between the temperature data of the cooling medium at the current moment, the total recovered heat, and the power data of the induced draft fan at the current moment is used as the recovery capacity coefficient at the current moment.

8. The method for recovering waste heat from furnace gas in a multi-bottom electrode energy-saving DC submerged arc furnace as described in claim 1, characterized in that, The method for obtaining the parameter correction coefficient at the current moment and correcting the operating parameters of the furnace gas waste heat recovery device at the current moment is as follows: The ratio of the furnace gas intensity index at the current moment to the recovery capacity coefficient at the next moment is used as the parameter correction coefficient at the current moment. The product of each operating parameter at the current moment and the parameter correction coefficient is used as the correction operating parameter to correct the operating parameters of the furnace gas waste heat recovery device at the current moment.

9. The method for recovering waste heat from furnace gas in a multi-bottom electrode energy-saving DC submerged arc furnace as described in claim 1, characterized in that, The method for obtaining the furnace charge consumption rate is as follows: The difference in material height between any two adjacent moments within the current time period is taken as the change in furnace charge height; where the end time of the current time period is the current moment. The ratio of all the changes in furnace charge height to the duration between two adjacent moments is taken as the rate of change of furnace charge height. The average rate of change of all charge heights is taken as the charge consumption rate at the current moment.

10. A waste heat recovery device for a multi-bottom electrode energy-saving DC submerged arc furnace, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the waste heat recovery method of the multi-bottom electrode energy-saving DC submerged arc furnace as described in any one of claims 1-9.

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