Converter waste heat recovery circulating system and oxygen lance intelligent collaborative energy-saving system and method

Abstract

The invention relates to the technical field of converter units of steel works, in particular to a converter waste heat recovery circulating system and oxygen lance intelligent collaborative energy-saving system and method. A feed pump motor; a PLC control end; oxygen blowing equipment; the HMI display unit, the transformer and the frequency converter are electrically connected through a high-voltage isolating switch, the other end of the frequency converter is electrically connected with a water feeding pump motor, one end of the frequency converter is electrically connected with the PLC control end, and one end of the PLC control end is connected with the local control box, the HMI display unit and the oxygen blowing equipment. The monitoring picture also displays the running state of the water feed pump, the rotating speed and current of the motor, the power-on feedback and fault of the frequency converter and various state signals, the alarm picture can provide the alarm function for the fault of the water feed pump, the fault of the frequency converter and the like, and a recording curve is designed for key data. Frequency conversion adjustment of a newly-added frequency converter of a water feeding pump in a converter waste heat recovery circulating system is interlocked with oxygen lance operation.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of converter unit of steelmaking plant, and particularly relates to a system and method for intelligent cooperation of converter waste heat recovery circulating system and oxygen lance. BACKGROUND

[0002] In the converter smelting process, cooling water is needed to supply water cooling for the smoke hood, oxygen lance and other devices of the converter, wherein the smelting cycle of the steelmaking converter is about 35-40 minutes, the oxygen lance time of one furnace of steel is about 12 minutes, the smelting cycle of the vanadium extraction converter is about 20 minutes, and the oxygen lance time of one furnace of steel is about 6 minutes.

[0003] At present, the water supply pumps of the steelmaking converter and the vanadium extraction converter in the steel plant are operated at a high speed in a 50HZ power frequency state, and it is found that the flue gas temperature (low) generated when the converter does not perform oxygen lance is obviously lower than the flue gas temperature (high) generated when the oxygen lance is performed, and the water inlet amount required by the corresponding waste heat boiler is also obviously reduced. In order to better save energy, the existing water pump unit is intelligently controlled to reduce the water inlet amount of the waste heat boiler when the converter stops the oxygen lance, so as to reduce the power consumption.

[0004] Traditional oxygen lance temperature management mainly depends on manual experience or simple threshold control: the operator sets fixed cooling water flow, oxygen lance position and other parameters according to historical data, and adjusts passively when the temperature sensor detects over-limit. This method has obvious defects: the adjustment is triggered only after the temperature is abnormal, which easily leads to local overheating or lag caused by over-adjustment. The composition of the molten iron of different furnace times and the smelting steel grade are quite different, the fixed parameters cannot match the dynamic working conditions, the adaptability is poor, the system is often in full load operation state, and the energy is wasted due to the dynamic optimization according to the actual temperature demand. SUMMARY

[0005] Technical problems solved

[0006] In view of the above-mentioned defects of the prior art, the present application provides a system and method for intelligent cooperation of converter waste heat recovery circulating system and oxygen lance, which can effectively solve the problems in the prior art.

[0007] Technical scheme

[0008] This invention provides a converter waste heat recovery circulation system and an intelligent collaborative energy-saving system for oxygen lances, comprising a transformer, a frequency converter, a feedwater pump motor, a PLC control terminal, an oxygen blowing device, and an HMI display unit. The transformer and the frequency converter are electrically connected via a high-voltage isolating switch. The other end of the frequency converter is electrically connected to the feedwater pump motor, and one end of the frequency converter is electrically connected to the PLC control terminal. One end of the PLC control terminal is connected to a local control box, the HMI display unit, and the oxygen blowing device. The oxygen blowing device includes an outer tube and an inner tube sleeved within the outer tube. A contact probe is fixed to the end of the inner tube.

[0009] Furthermore, the frequency conversion range of the inverter is 20Hz-60Hz.

[0010] Furthermore, a heat dissipation pipe is sleeved between the outer tube and the inner tube, and both ends of the heat dissipation pipe are connected to an external cold source through connectors. Both sets of connectors penetrate the outer tube. The inner tube is connected to the oxygen output end. A nozzle structure is fixed at the end of the inner tube, and contact probes are fixed at the four corners of the outer side of the nozzle. The contact probes are all connected to the edge computing module in the PLC control terminal through a communication module. The heat dissipation pipe spirals forward on the outside of the inner tube. The contact probe is a high-temperature K-type thermocouple structure.

[0011] Furthermore, the HMI display unit is a touch-operable LCD screen structure with an operating system.

[0012] To achieve the aforementioned device, this invention also introduces a method for intelligent collaborative energy saving between a converter waste heat recovery and circulation system and an oxygen lance.

[0013] Step 1: Collect raw data from the contact probes, transformers, frequency converters, and feedwater pump motors on the outside of the oxygen blowing equipment, and transmit the raw data to the edge computing module within the PLC control terminal.

[0014] Step 2: Use the PLC data fusion module to calibrate the time-temperature curve of the raw data, establish the temperature rise curve equation, and establish a three-dimensional temperature field distribution model. In advance, adjust the frequency of the inverter to 50Hz and increase the flow rate of the water pump motor to meet the operating requirements of the oxygen blowing equipment. Record the frequency rise data of the water pump motor, oxygen blowing equipment and contact probe at this time.

[0015] Step 3: Feedback signal is sent to the water pump motor to ensure the outflow rate meets the operating requirements of the oxygen blowing equipment, and the signal is digitally displayed on the HMI display unit. The oxygen blowing equipment is then operated.

[0016] Step 4: After the oxygen blowing equipment operation is completed, a completion signal will be sent back;

[0017] Step 5: After receiving the signal, the PLC control terminal automatically reduces the inverter frequency to 30Hz and collects the frequency reduction data;

[0018] Furthermore, in step two, based on the established three-dimensional temperature field distribution model, a preset frequency-cooling process prediction curve is used to calculate the gas supply parameter correction and cooling water flow adjustment of the oxygen blowing equipment nozzle at 50Hz and 30Hz of the frequency converter. The gas supply parameter correction includes the oxygen-inert gas mixing ratio, gas pressure, and blowing rate.

[0019] Furthermore, based on the frequency increase-cooling process curve, a linear relationship is established between the inlet and outlet temperature difference of the cooling water in the vanadium oxygen lance, the converter endpoint temperature, and the outlet temperature of the oxygen blowing equipment. A linear regression prediction model is then established to inversely optimize the current control parameters. After step five, the frequency increase and decrease data at 50Hz and 30Hz are compared with the standard predicted values. If the ratio of the frequency increase / decrease data to the predicted values ​​is less than or equal to the standard range, the requirements are met. If the ratio of the frequency increase / decrease data to the predicted values ​​is greater than the standard range, the predicted values ​​are input.

[0020] Furthermore, the frequency converter of the newly added converter feedwater pump includes the following types of digital and analog signals: digital inputs include start and stop signals; digital outputs include frequency converter high voltage ready, frequency converter running, frequency converter fault, and frequency converter stop signals; analog inputs include frequency adjustment (speed setting); and analog outputs include output frequency and output current.

[0021] Furthermore, a feedback control loop is established through the PLC control terminal of the edge computing module. With the set temperature distribution uniformity index of the oxygen blowing equipment as the optimization target, the dynamic parameters of the control algorithm using a linear regression prediction model are adopted to form a closed-loop adaptive adjustment.

[0022] Beneficial effects

[0023] In use, this invention allows operators to start and stop the feedwater pumps, set the motor speed, and perform manual / automatic operation on the screen within the converter waste heat recovery circulation system. Simultaneously, the monitoring screen displays the feedwater pump operating status, motor speed and current, inverter power-on feedback and faults, and various status signals. The alarm screen provides alarm functions for pump and inverter faults and records key data using curves. Therefore, in operation, the frequency conversion adjustment of the newly added inverter for the feedwater pump in the converter waste heat recovery circulation system is interlocked with the oxygen lance operation. To meet the smelting requirements of the converter waste heat boiler, the inverter frequency must be pre-adjusted to 50Hz, and the pump flow rate must be increased to meet the oxygen lance operation requirements. A signal indicating that the pump flow rate has reached the oxygen lance operation requirements is displayed on the HMI screen, and the operator then operates the oxygen lance. After the oxygen lance operation is completed, an oxygen lance completion signal is received. Upon receiving this signal, the program automatically reduces the inverter frequency to 30Hz to maximize energy savings.

[0024] Furthermore, in this invention, the linear regression model quantifies the linear relationship between parameters such as oxygen flow rate, cooling water temperature difference, and lance position and oxygen lance temperature. For every 10 m³ / h increase in cooling water flow rate, the oxygen lance temperature decreases by 5°C, and the model can predict temperature change trends 5-10 seconds in advance. When the model predicts that the temperature will exceed the safety threshold, the system can actively adjust the cooling system or oxygen lance position to avoid equipment damage caused by lag, reducing the oxygen lance overheating failure rate by more than 30%. Compared to traditional cooling systems that often operate at full load, the linear regression model can dynamically match the cooling intensity based on the predicted temperature: automatically reducing the cooling water flow rate in the low-temperature range and precisely increasing cooling efficiency in the high-temperature range. Practice shows that this method can reduce cooling water consumption per ton of steel by 8-12%, while also reducing the energy consumption of the oxygen lance drive motor, saving approximately 50,000-80,000 RMB per converter per year in production costs. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0026] Figure 1 This is a schematic diagram of the structure of the present invention;

[0027] Figure 2 This is a schematic diagram of the oxygen blowing device of the present invention;

[0028] Figure 3 This is a cross-sectional view of the oxygen blowing equipment in this invention;

[0029] Figure 4 This is a schematic diagram of the converter waste heat recovery cycle system in this invention;

[0030] Figure 5 This is a flowchart of the system method in this invention.

[0031] The labels in the diagram represent: 1. Converter; 2. High-pressure pump set; 3. Deaerator; 4. PLC control terminal; 5. Oxygen blowing equipment; 51. Outer pipe; 52. Contact probe; 53. Heat dissipation pipe; 54. Inner pipe; 55. Connector; 6. HMI display unit; 7. Control box; 8. Transformer; 9. Frequency converter; 10. Feed water pump motor. Detailed Implementation

[0032] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0033] The present invention will be further described below with reference to embodiments.

[0034] Example: A converter waste heat recovery and circulation system and an intelligent energy-saving system for oxygen lances, as shown in the attached figure. Figure 1 - Appendix Figure 3 The system includes a transformer 8, a frequency converter 9, a water pump motor 10, a PLC control terminal 4, an oxygen blowing device 5, and an HMI display unit 6. The transformer 8 and the frequency converter 9 are electrically connected through a high-voltage disconnect switch. The other end of the frequency converter 9 is electrically connected to the water pump motor 10. One end of the frequency converter 9 is electrically connected to the PLC control terminal 4. One end of the PLC control terminal 4 is connected to the local control box 7, the HMI display unit 6, and the oxygen blowing device 5. The oxygen blowing device 5 includes an outer tube 51 and an inner tube 54 sleeved inside the outer tube 51. A contact probe 52 is fixed at the end of the inner tube 54.

[0035] The frequency converter 9 has a frequency adjustment range of 20Hz-60Hz. This system, with PLC control terminal 4 as its core, constructs a linkage control network connecting transformer 8, frequency converter 9, feedwater pump motor 10, oxygen blowing equipment 5, and HMI display unit 6. A high-voltage isolating switch ensures the safety of the electrical connection between transformer 8 and frequency converter 9. Simultaneously, relying on the wide frequency adjustment range of frequency converter 9 (20Hz-60Hz), the operating parameters of feedwater pump motor 10 can be flexibly adjusted to adapt to different converter operating conditions. The high-temperature K-type thermocouple contact probes at the four corners of the inner tube end of the oxygen blowing equipment can collect real-time temperature data of the working area of ​​the oxygen lance (oxygen blowing equipment 5) and transmit it to the edge computing module of PLC control terminal 4 via a communication module. This enables rapid analysis and feedback of temperature information, thereby accurately controlling the operating status of oxygen blowing equipment 5, significantly reducing manual intervention, improving the overall automation and precise control capabilities of the system, and avoiding energy waste or decreased production efficiency due to human error.

[0036] A heat dissipation pipe 53 is sleeved between the outer pipe 51 and the inner pipe 54, and both ends of the heat dissipation pipe 53 are connected to an external cold source through connectors 55. Both sets of connectors 55 pass through the outer pipe 51. The inner pipe 54 is connected to the oxygen output end. A nozzle structure is fixed at the end of the inner pipe 54, and contact probes 52 are fixed at the four corners of the nozzle. The contact probes 52 are all connected to the edge computing module in the PLC control terminal 4 through a communication module. The heat dissipation pipe 53 spirals forward on the outside of the inner pipe 54. The contact probes 52 are high-temperature K-type thermocouple structures. The oxygen blowing equipment 5 innovatively adopts a three-layer nested structure of "outer pipe 51-heat dissipation pipe 53-inner pipe 54". The heat dissipation pipe 53 spirals forward on the outside of the inner pipe 54, and both ends are connected to an external cold source through connectors 55 that pass through the outer pipe 51, forming an efficient annular heat dissipation channel. During oxygen lance operation, an external cold source continuously cools the heat dissipation tube 53. Through a spiral winding design, the contact area between the heat dissipation tube 53 and the inner tube 54 is maximized, quickly dissipating the heat generated by the inner tube 54 due to oxygen transport and the high-temperature environment, effectively reducing the operating temperature of the inner tube 54 and the nozzle structure. This design not only prevents material aging and performance degradation caused by long-term high-temperature operation of the oxygen lance, extending the equipment's service life, but also ensures the stability of oxygen delivery, preventing the impact of thermal expansion and contraction of the pipeline on oxygen supply pressure and flow rate, thus ensuring the stable operation of the oxygen blowing process in converter 1.

[0037] The HMI display unit 6 is a touch-operated LCD screen with an operating system. On one hand, the coordinated operation of the frequency converter 9 and the feedwater pump motor 10 dynamically adjusts the operating frequency of the feedwater pump motor 10 according to the actual needs of the converter 1 waste heat recovery circulation system (such as waste heat recovery water volume and water temperature control requirements), avoiding the energy waste of traditional fixed-frequency motors and ensuring precise matching between the feedwater pump output power and system requirements, significantly reducing pump operating energy consumption. On the other hand, the system achieves intelligent linkage between the oxygen blowing equipment 5 and the waste heat recovery circulation system through the PLC4 control terminal. Combined with temperature data collected by the contact probe 52, it rationally adjusts the oxygen blowing parameters and waste heat recovery rhythm, ensuring efficient recovery and utilization of waste heat resources and reducing energy waste.

[0038] Meanwhile, the touch-operable LCD screen of the HMI display unit can display the operating parameters of various system components in real time (such as inverter frequency, feedwater pump speed, oxygen lance temperature, waste heat recovery, etc.), which makes it easy for staff to intuitively grasp the system's operating status, promptly identify and optimize abnormal energy consumption links, further improve the system's energy efficiency, and provide strong support for enterprises to reduce production costs and achieve green production.

[0039] like Figure 5 As shown in Example 2: In this example, based on Example 1, a method for implementing the above examples is introduced:

[0040] A method for intelligent collaborative energy saving of a converter waste heat recovery and circulation system and an oxygen lance.

[0041] Step 1: Collect raw data from the contact probe 52, transformer 8, frequency converter 9, and feedwater pump motor 10 on the outside of the oxygen blowing equipment 5, and transmit the raw data to the edge computing module inside the PLC control terminal 4.

[0042] Step 2: Use the PLC data fusion module to calibrate the time-temperature curve of the raw data, establish the temperature rise curve equation, and establish a three-dimensional temperature field distribution model. In advance, adjust the frequency of inverter 1 to 50Hz and increase the flow rate of water pump motor 10 to meet the operation requirements of oxygen blowing equipment. Record the frequency rise data of water pump motor 10, oxygen blowing equipment 5 and contact probe 52 at this time.

[0043] Step 3: Feedback signal is sent to the water pump motor 10 to ensure the outflow rate meets the operating requirements of the oxygen blowing equipment 5, and the signal is digitally displayed on the HMI display unit 6. The oxygen blowing equipment 5 is then operated.

[0044] Step 4: After the oxygen blowing equipment 5 has completed operation, a completion signal will be sent back;

[0045] Step 5: After receiving the signal, the PLC control terminal 4 automatically reduces the frequency of the inverter 9 to 30Hz and collects the frequency reduction data;

[0046] A feedback control loop is established through the PLC control terminal of the edge computing module. The set temperature distribution uniformity index of the oxygen blowing equipment 5 is used as the optimization target. The dynamic parameters of the control algorithm are controlled by a linear regression prediction model to form a closed-loop adaptive adjustment.

[0047] In this invention, a linear regression model quantifies the linear relationship between parameters such as oxygen flow rate, cooling water temperature difference, and lance position and oxygen lance temperature. For every 10 m³ / h increase in cooling water flow rate, the oxygen lance temperature decreases by 5°C, and the model can predict temperature change trends 5-10 seconds in advance. When the model predicts that the temperature will exceed the safety threshold, the system can actively adjust the cooling system or oxygen lance position to avoid equipment damage caused by lag, reducing the oxygen lance overheating failure rate by more than 30%. Compared to traditional cooling systems that often operate at full load, the linear regression model can dynamically match the cooling intensity based on the predicted temperature: automatically reducing the cooling water flow rate in the low-temperature range and precisely increasing cooling efficiency in the high-temperature range. Practice shows that this method can reduce cooling water consumption per ton of steel by 8-12%, while also reducing the energy consumption of the oxygen lance drive motor, saving approximately 50,000-80,000 RMB per converter per year in production costs.

[0048] Example 3:

[0049] Based on the established three-dimensional temperature field distribution model, the frequency increase-cooling process prediction curve is preset, and the gas supply parameter correction and cooling water flow adjustment of the nozzle of the oxygen blowing equipment 5 at 50Hz and 30Hz of the frequency converter 9 are calculated. The gas supply parameter correction includes the oxygen-inert gas mixing ratio, gas pressure and blowing rate.

[0050] Based on the frequency increase-cooling process curve, a linear functional relationship was established by incorporating the inlet and outlet temperature difference of the cooling water in the vanadium-oxygen lance, the converter endpoint temperature, and the outlet temperature of oxygen blowing equipment 5. A linear regression prediction model was then established, and the specific steps are as follows:

[0051] ①: Prediction target (dependent variable, i.e., oxygen lance nozzle temperature y), characteristic variables, i.e., a series of process parameters strongly correlated with the oxygen lance, smelting operation parameters: oxygen flow rate, oxygen lance position (height from the molten pool surface), oxygen blowing time, and the weight of molten steel in the current heat; cooling system parameters: cooling water inlet temperature and cooling water flow rate; raw materials and previous conditions: molten iron temperature entering the furnace, molten iron composition (carbon and silicon content), and the peak oxygen lance temperature of the previous heat; environmental and equipment parameters: converter furnace age (degree of furnace lining wear) and ambient temperature;

[0052] ②: Collect and preprocess the above data. Preprocessing eliminates noise and fills in missing values. Export historical production data from PLC, including the above "characteristic variables" and "target variables". The time granularity matches the smelting rhythm, the time unit is s, and it contains complete data of at least 1000 heats, covering different working conditions (such as different steel grades and different furnace ages).

[0053] ③ Feature Optimization: Calculate the Pearson correlation coefficient between each feature and the target variable, which measures linear correlation. The value range is [-1, 1]. Determine the correlation between the absolute value of each feature data and 1; the closer to 1, the stronger the correlation. Finally, retain feature data with an absolute correlation coefficient > 0.3. Standardize the feature data: scale the features to the same order of magnitude using Z-score standardization: X′=(X-μ) / σ), reducing model coefficient bias.

[0054] ④: Linear regression model training and parameter solving, the formula is as follows: ,in For the intercept term, ... Let Y be the predicted temperature and Y be the feature parameter. 1: Divide the preprocessed dataset into a training set (for model fitting) and a test set (for evaluating generalization ability) in a 7:3 or 8:2 ratio, maintaining temporal continuity during the partition. The datasets are partitioned according to the furnace order. 2: Model training: Solve for the coefficients using the least squares method: calculate the optimal value by minimizing the sum of squares between the predicted and actual values ​​(loss function). ... The formula is: (where X is the feature matrix, Y is the actual temperature vector, 3. According to the positive and negative values ​​of w obtained, it represents the correlation between the feature and the target variable. Specifically: positive coefficient: the feature increases, the temperature increases; negative coefficient: the feature increases, the temperature decreases, and the absolute value of the coefficient reflects the degree of influence: if the coefficient of "cooling water flow rate" is -0.8, it means that increasing the cooling water flow rate has a significant effect on reducing the oxygen gun temperature. Finally, the model performance is verified through the test set. If the accuracy is insufficient, iterative optimization is required. 4. The evaluation standard adopts the coefficient of determination method: that is: The value ranges from [0,1]. The closer it is to 1, the stronger the model's explanatory power. ≥0.7, if <0.6, additional features (including but not limited to process parameters such as "slag oxidizability" and "oxygen lance nozzle wear") are required, or higher-order terms of nonlinear features are transformed (including but not limited to the "oxygen flow rate × lance position" interaction term). 5. Integrate the optimized model into the converter control system to realize real-time prediction and feedback of oxygen lance temperature.

[0055] Linear regression models offer fast calculation speed and strong interpretability (clearly defining the influence weight of each process parameter on temperature) for converter oxygen lance temperature prediction, making them suitable for real-time control scenarios. The model can automatically output adjustment suggestions for each parameter (e.g., "Oxygen flow rate needs to be reduced by 200 m³ / h to control temperature"), allowing for self-judgment based on previously collected data, reducing reliance on human experience. Furthermore, the output linear coefficients (such as feature weights) can assist engineers in understanding the process mechanism. In addition, the lightweight nature of linear regression allows it to be embedded in PLC real-time control systems with a response latency of <1 second, meeting the real-time requirements of high-intensity converter smelting.

[0056] The current control parameters are optimized in reverse. After step five, the up-frequency data and down-frequency data at 50Hz and 30Hz are compared with the standard predicted values. If the ratio of the up-frequency data and the predicted value is less than or equal to the standard range, the requirement is met. If the ratio of the up-frequency data and the predicted value is greater than the standard range, the predicted value is input.

[0057] The newly added converter feed water pump's frequency converter 9 includes the following types of digital and analog signals: digital inputs include start and stop signals; digital outputs include frequency converter high voltage ready, frequency converter running, frequency converter fault, and frequency converter stop signals; analog inputs include frequency adjustment (speed setting); and analog outputs include output frequency and output current.

[0058] When the converter is preparing the oxygen lance, the centralized control system sends a signal to the PLC to adjust the frequency converter to 50Hz. Once the water pump flow rate reaches the level required for the converter's oxygen lance operation, a signal authorizing oxygen lance operation is sent back and displayed on the HMI display unit. Only then can the operator authorize the oxygen lance operation. After the oxygen lance operation is completed, the converter requires a lower volume of circulating water. A signal is then sent back to the centralized control system. Upon receiving this signal, the PLC program automatically reduces the frequency converter to 30Hz, allowing the converter feedwater pump to operate in energy-saving mode.

[0059] Please refer to Figure 4 Specific Implementation Example: Taking an implemented project as an example, a steel plant installed electricity meters on the 355kW frequency converters (8 operational and 4 standby) of the 12 circulating high-pressure water pump groups 2 in the waste heat boilers of No. 1 steelmaking converter 1 and No. 2 vanadium extraction converter 1 to measure the actual power consumption. The hot air generated in each converter 1 can be introduced into the deaerator 3. One end of the deaerator 3 is connected to the high-pressure water pump group 2. The actual power of the motors in each circulating high-pressure water pump group 2 is measured. The actual power of the motors in each circulating high-pressure water pump group 2 is approximately 298kW. The frequency converters in the 12 circulating high-pressure water pump groups 2 maintain a low frequency of 30Hz during non-oxygen blowing time. The energy saving calculation is as follows:

[0060] The pump frequency and speed are linearly proportional. ;

[0061] Where: n - pump speed (r / min); f - power supply frequency (Hz); P - number of motor pole pairs (fixed value); s - slip (~5%)

[0062] The power of a water pump is directly proportional to the cube of its rotational speed. Right now ;

[0063] Therefore, the 12 circulating high-pressure water pump sets save energy: ,

[0064] Where: 4320 - is the low-speed energy-saving operation time of the water pump (hours); 298 - is the actual power of the water pump motor (kW); 12 - is the number of water pumps in operation (units).

[0065] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions will not cause the essence of the corresponding technical solutions to deviate from the protection scope of the technical solutions of the embodiments of the present invention.

Claims

1. A converter waste heat recovery and circulation system and an intelligent collaborative energy-saving system for oxygen lances, characterized in that, The equipment includes a transformer (8), a frequency converter (9), a water pump motor (10), a PLC control terminal (4), an oxygen blowing device (5), and an HMI display unit (6). The transformer (8) and the frequency converter (9) are electrically connected through a high-voltage disconnect switch. The other end of the frequency converter (9) is electrically connected to the water pump motor (10). One end of the frequency converter (9) is electrically connected to the PLC control terminal (4). One end of the PLC control terminal (4) is connected to the local control box (7), the HMI display unit (6), and the oxygen blowing device (5). The oxygen blowing device (5) includes an outer tube (51) and an inner tube (54) sleeved inside the outer tube (51). A contact probe (52) is fixed at the end of the inner tube (54).

2. The converter waste heat recovery and circulation system and the intelligent collaborative energy-saving system with the oxygen lance as described in claim 1, characterized in that, The frequency converter (9) has a frequency adjustment range of 20HZ-60HZ.

3. The converter waste heat recovery and circulation system and the intelligent collaborative energy-saving system with the oxygen lance as described in claim 1, characterized in that, A heat dissipation pipe (53) is sleeved between the outer tube (51) and the inner tube (54), and the two ends of the heat dissipation pipe (53) are connected to an external cold source through connectors (55). Both sets of connectors (55) pass through the outer tube (51). The inner tube (54) is connected to the oxygen output end. A nozzle structure is fixed at the end of the inner tube (54), and contact probes (52) are fixed at the four corners of the nozzle. The contact probes (52) are all connected to the edge computing module in the PLC control terminal (4) through a communication module. The heat dissipation pipe (53) spirals forward on the outside of the inner tube (54). The contact probes (52) are high-temperature K-type thermocouple structures.

4. The converter waste heat recovery and circulation system and the intelligent collaborative energy-saving system with the oxygen lance as described in claim 1, characterized in that, The HMI display unit (6) is a touch-operable LCD screen structure with an operating system.

5. A method for intelligent coordinated energy saving of a converter waste heat recovery circulation system and an oxygen lance, used to realize the intelligent coordinated energy saving of a converter waste heat recovery circulation system and an oxygen lance according to any one of claims 1-4, characterized in that, Step 1: Collect raw data from the contact probe (52), transformer (8), frequency converter (9), and feedwater pump motor (10) on the outside of the oxygen blowing equipment (5), and transmit the raw data to the edge computing module inside the PLC control terminal (4). Step 2: Use the PLC data fusion module to calibrate the time-temperature curve of the original data, establish the temperature rise curve equation, and establish a three-dimensional temperature field distribution model. In advance, adjust the frequency of the inverter (1) to 50Hz and increase the flow rate of the water pump motor (10) to meet the operation requirements of the oxygen blowing equipment. Record the frequency rise data of the water pump motor (10), oxygen blowing equipment (5) and contact probe (53) at this time. Step 3: Feedback signal to the water pump motor (10) to ensure the outflow rate meets the operating requirements of the oxygen blowing equipment (5), and display the signal digitally on the HMI display unit (6). Operate the oxygen blowing equipment (5). Step 4: After the oxygen blowing equipment (5) has been operated, a completion signal is sent back; Step 5: After receiving the signal, the PLC control terminal (4) automatically reduces the frequency of the inverter (9) to 30Hz and collects the frequency reduction data.

6. The method for intelligent coordinated energy saving of a converter waste heat recovery circulation system and an oxygen lance according to claim 1, characterized in that, In step two, based on the established three-dimensional temperature field distribution model, the frequency increase-cooling process prediction curve is preset, and the gas supply parameter correction and cooling water flow adjustment of the nozzle of the oxygen blowing equipment (5) at 50Hz and 30Hz of the frequency converter (9) are calculated. The gas supply parameter correction includes the oxygen-inert gas mixing ratio, gas pressure and blowing rate.

7. The method for intelligent coordinated energy saving of a converter waste heat recovery circulation system and an oxygen lance according to claim 6, characterized in that, Based on the frequency increase-temperature decrease process curve, the inlet and outlet water temperature difference of the cooling water in the vanadium oxygen lance, the converter end temperature and the outlet temperature of the oxygen blowing equipment (5) are used to establish a linear function relationship, establish a linear regression prediction model, optimize the current control parameters in reverse, and after step five, compare the frequency increase data and frequency decrease data at 50Hz and 30Hz with the standard predicted values. If the ratio of the frequency increase and frequency decrease data to the predicted values ​​is less than or equal to the standard range, the requirements are met. If the ratio of the frequency increase and frequency decrease data to the predicted values ​​is greater than the standard range, the predicted values ​​are input.

8. The method for intelligent coordinated energy saving of a converter waste heat recovery circulation system and an oxygen lance according to claim 7, characterized in that, The frequency converter (9) for the newly added converter feed water pump includes the following types of digital and analog signals: digital inputs include start, stop and other signals; digital outputs include frequency converter high voltage ready, frequency converter running, frequency converter fault, frequency converter stop and other signals; analog inputs include frequency adjustment (speed setting); analog outputs: output frequency, output current.

9. A method for intelligent coordinated energy saving of a converter waste heat recovery circulation system and an oxygen lance according to claim 8, characterized in that, A feedback control loop is established through the PLC control terminal of the edge computing module. The set temperature distribution uniformity index of the oxygen blowing equipment (5) is used as the optimization target. The dynamic parameters of the linear regression prediction model control algorithm are used to form a closed-loop adaptive adjustment.

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