Steel plant water system balance regulation and control system and method

Abstract

The invention discloses a steel plant water system balance regulation and control system and method, and belongs to the technical field of industrial water treatment and circular economy. The system comprises a sensing layer, a transmission layer, an intelligent decision platform and an execution layer which are in signal connection in sequence; wherein the sensing layer is used for collecting water quality, water quantity, liquid level and equipment state data of each pool and pipeline of a steel plant; the transmission layer is used for transmitting the data acquired by the sensing layer to the intelligent decision-making platform; the intelligent decision-making platform is used for performing water balance calculation, stepped water consumption optimization decision making, risk early warning and scheduling instruction generation based on the received data; and the execution layer is used for receiving an instruction of the intelligent decision-making platform and driving execution equipment to complete corresponding operation. According to the invention, a water system balance regulation and control technology of water quality grading matching, wastewater gradient utilization, whole-process accurate perception and intelligent optimization scheduling can be realized, so that new water consumption is reduced, wastewater discharge is reduced, and the energy utilization efficiency is improved.

Description

Technical Field

[0001] This invention belongs to the field of industrial water treatment and circular economy technology, specifically relating to a water system balance control system and method for steelmaking plants. Background Technology

[0002] As major water users, steel plants have water systems that supply various water qualities, including demineralized water, soft water, and purified water. These systems also address the water needs of multiple production stages, such as steelmaking, continuous casting, and waste heat recovery, each with significantly different requirements for water quality and quantity. However, current water system management in steel plants generally employs an extensive management model, leading to problems such as low water resource utilization efficiency and serious energy waste, as specifically manifested below:

[0003] Insufficient accuracy in water matching: Due to the lack of a clear water quality classification and supply mechanism, high-quality water (such as demineralized water and soft water) is often used in production processes with lower water quality requirements. For example, soft water is directly used to supply cooling systems with higher salinity tolerance, resulting in serious waste of "high quality used for low-quality purposes" and significantly increasing the cost of new water preparation.

[0004] Low wastewater resource utilization rate: Wastewater generated by various production systems in steelmaking plants, such as flue boiler wastewater (with a certain temperature and low impurity content) and softening system regeneration wastewater (with high salt content but can meet specific low-quality water needs), is mostly discharged directly without treatment. This not only wastes potential secondary water sources but also increases the treatment load of wastewater treatment plants and the cost of discharge.

[0005] The water replacement logic is flawed: When the water quality in the pool deteriorates due to long-term use (e.g., increased salinity, excessive suspended solids), the traditional method usually involves directly replacing it with fresh water (soft water or demineralized water), and the unqualified water is directly discharged. This "one-size-fits-all" replacement model fails to consider the differences in water quality gradients, wasting both fresh water resources and the dissolved substances in the replacement water (such as recyclable salts and heat).

[0006] Inadequate metering and sensing systems: Most steel plants lack high-precision metering equipment at their water replenishment points, drainage points, and user water usage points. Some key locations lack real-time water quality monitoring devices, making it impossible to accurately perform water balance and material balance calculations, making it difficult to grasp the water usage patterns of each subsystem, and consequently, impossible to achieve refined scheduling and optimization.

[0007] The scheduling decision is highly subjective: Current water system scheduling relies heavily on the experience and judgment of operators, lacks intelligent decision support based on real-time data, and is difficult to dynamically adjust water supply strategies according to multiple factors such as water quality, water quantity, and cost, resulting in low scheduling efficiency and poor economic performance.

[0008] To address these issues, the industry urgently needs a water system balance control technology that can achieve water quality classification and matching, cascaded utilization of wastewater, precise sensing throughout the entire process, and intelligent optimization and scheduling. This technology would reduce fresh water consumption, decrease wastewater discharge, improve energy efficiency, and drive steel plants to transform into a green circular economy model. Summary of the Invention

[0009] To address the existing problems in steel plant water system management, such as insufficient accuracy in water use matching, low wastewater resource utilization rate, unreasonable water quality replacement logic, imperfect metering and sensing systems, and strong subjectivity in scheduling decisions, this invention provides a water system balance control system and method for steel plants. This system enables graded water quality matching, cascaded wastewater utilization, precise sensing throughout the entire process, and intelligent optimized scheduling, thereby reducing fresh water consumption, minimizing wastewater discharge, improving energy efficiency, and promoting the transformation of steel plants towards a green circular economy model.

[0010] The technical solution adopted by the present invention, a water system balance control system and method for steelmaking plants, is as follows:

[0011] A converter tertiary dust removal linkage system includes a sensing layer, a transmission layer, an intelligent decision-making platform, and an execution layer connected in sequence by signals. The sensing layer collects water quality, quantity, level, and equipment status data from various pools and pipelines in the steel plant. The transmission layer transmits the data collected by the sensing layer to the intelligent decision-making platform. The intelligent decision-making platform performs water balance calculations, tiered water use optimization decisions, risk warnings, and generates scheduling instructions based on the received data. The execution layer receives instructions from the intelligent decision-making platform and drives the execution equipment to complete corresponding operations.

[0012] A further improvement of the above technical solution of the present invention is that: the sensing layer includes a liquid level sensor, an electric regulating valve, an electromagnetic flow meter, an automatic sampling port, and an online water quality analyzer; wherein, the liquid level sensor is installed in the production water tank, demineralized water tank, soft water tank, clean circulating water tank, secondary cooling water tank, and slag-steaming water tank; the electric regulating valve and the electromagnetic flow meter are installed on the outlet branch pipes of all water pumps, including water supply branch pipes, drainage branch pipes, and connecting branch pipes; the automatic sampling port is installed at the outlet of key water pumps and is connected to the online water quality analyzer or automatic sampler.

[0013] A further improvement of the above technical solution of the present invention is that: the transmission layer adopts an industrial ring network; the execution layer includes a variable frequency water pump and an electric valve.

[0014] A further improvement of the above technical solution of the present invention is that: the intelligent decision-making platform includes a water balance and material balance calculation engine, a tiered water use optimization model, a prediction and early warning module, and a scheduling instruction generation unit; wherein, the water balance and material balance calculation engine is used to calculate the instantaneous balance and cumulative amount of the entire system and each subsystem based on real-time flow and liquid level data; the tiered water use optimization model is used to convert preset replacement paths and water replenishment rules into digital models and make intelligent decisions; the prediction and early warning module is used to predict water quality change trends and warn of imbalance risks based on real-time and historical data; the scheduling instruction generation unit is used to generate variable frequency pump start / stop and electric valve opening instruction sequences.

[0015] A method for balancing and controlling the water system in a steel plant, using the aforementioned system, includes the following steps.

[0016] S1. The sensing layer collects liquid level data from each pool in the steelmaking plant, flow data from each pipeline, water quality data from key locations, and equipment status data, and transmits them to the intelligent decision-making platform through the transmission layer.

[0017] S2. The intelligent decision-making platform performs water balance and material balance calculations based on the received data through the water balance and material balance calculation engine.

[0018] S3, the tiered water use optimization model generates water replenishment and replacement decisions based on calculation results and preset rules;

[0019] S4. The scheduling instruction generation unit generates scheduling instructions based on the decision results and sends them to the execution layer through the transport layer.

[0020] S5, the execution layer drives the execution device to execute instructions and complete the water replenishment and replacement operations.

[0021] A further improvement of the above technical solution of the present invention is that the preset rules in step S3 include:

[0022] The tiered water quality replacement rule is as follows: when the water quality in the purification pool deteriorates, the replacement wastewater is discharged into the secondary cooling pool; when the water quality in the secondary cooling pool deteriorates, the replacement wastewater is discharged into the slag-suppressing pool; and the wastewater discharged from the slag-suppressing pool enters the plant's wastewater treatment station.

[0023] It also includes high-quality wastewater downgrade and reuse rules: flue boiler wastewater is diverted to the secondary cooling water pool as a supplementary water source, and soft water replacement wastewater from the crystallizer system is recycled to the clean circulating water pool.

[0024] A further improvement of the above technical solution of the present invention is that the stepped water quality replacement rule also includes: during the replacement operation, the liquid level and water quality changes of the relevant water tanks are monitored in real time through the sensing layer, and the data is fed back to the intelligent decision-making platform, which dynamically adjusts the replacement flow rate and replacement duration.

[0025] A further improvement of the above technical solution of the present invention is that: the generation logic of the water replenishment and replacement decision in step S3 is as follows:

[0026] The intelligent decision-making platform prioritizes cascaded recycled water as a source of replenishment water based on the source water quality, quantity, cost, and water quality and level requirements of the target water tank. It then selects low-cost fresh water and finally high-quality soft water or demineralized water.

[0027] A further improvement of the above technical solution of the present invention is that: the cost includes water price and electricity cost; the intelligent decision-making platform calculates the comprehensive cost of different water replenishment schemes by establishing a cost accounting model, and selects the water replenishment scheme with the lowest comprehensive cost as the optimal decision.

[0028] A further improvement of the above technical solution of the present invention is that: step S3 further includes a prediction and early warning module that predicts the trend of water quality change based on real-time and historical data, and when an imbalance risk is detected, sends an early warning signal to the scheduling instruction generation unit, and the scheduling instruction generation unit generates risk control instructions first.

[0029] Due to the adoption of the above technical solution, the technical progress achieved by this invention includes:

[0030] This invention establishes a water use model of "high-quality wastewater downgraded and reused + cascade replacement chain," transforming previously directly discharged wastewater such as flue boiler exhaust and soft water replacement wastewater from crystallizers into secondary water sources, thus achieving cascade utilization of water resources. Simultaneously, it avoids the wasteful phenomenon of traditional "high-quality waste used in a low-quality manner," thereby reducing fresh water consumption.

[0031] This invention utilizes a tiered replacement path to transfer the deteriorated water quality from the purification pool and the secondary cooling pool to the lower-level pool with lower water quality requirements. Only the final wastewater from the slag-steaming pool is sent to the wastewater treatment plant, significantly reducing the amount of wastewater entering the treatment plant and lowering wastewater treatment costs and environmental risks associated with external discharge.

[0032] This invention utilizes devices such as level sensors in the sensing layer, electromagnetic flow meters, and online water quality analyzers to achieve real-time acquisition and accurate measurement of water levels in various pools, flow rates in pipelines, and water quality parameters, solving the problem of incomplete measurement and sensing systems in traditional management. Based on real-time data-driven water balance calculations, managers can comprehensively grasp the operating status of the water system, realizing a shift from "experience-based management" to "data-driven management."

[0033] The intelligent decision-making platform of this invention uses a tiered water use optimization model and a cost accounting model to comprehensively consider factors such as source water quality, water quantity, water price, and electricity costs. It dynamically selects the optimal water supply source and route, prioritizes the use of low-cost tiered recycled water, reduces the use of high-quality soft water and demineralized water, and lowers the overall operating cost of the water system.

[0034] The prediction and early warning module of this invention is based on real-time and historical data. It can predict water quality change trends and water system imbalance risks in advance, and generate early warning signals and control instructions in a timely manner to avoid production interruptions or equipment damage caused by system imbalance, thereby improving the continuity and stability of steel plant production. Detailed Implementation

[0035] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments. In the following description, descriptions of well-known structures and technologies are omitted to avoid unnecessarily obscuring the concepts of this invention.

[0036] Example 1

[0037] The existing water system of the steel plant used in this embodiment includes 200m 3 Demineralized water tank, 300m 3 Soft water pool, 500m 3 Clean circular water tank, 400m 3 Second cooling water tank, 600m 3 Sludge-curing pool and 800m 3 Production water tank.

[0038] This embodiment provides a water system balance control system for a steel plant, comprising a sensing layer, a transmission layer, an intelligent decision-making platform, and an execution layer connected in sequence by signals.

[0039] Specifically, the sensing layer is equipped with submersible level sensors in the demineralized water tank, soft water tank, clean circulating water tank, secondary cooling water tank, slag-curing water tank, and production water tank to collect the level data of each tank in real time and convert it into real-time water volume; DN50-DN200 electric regulating valves with a measurement range of 0-500m are installed on the outlet branch pipes of all water pumps, including water supply branch pipes, drainage branch pipes, and connecting branch pipes. 3 The system features a high-precision electromagnetic flowmeter with a flow rate of [number] h. An electric regulating valve controls the water flow opening, while the electromagnetic flowmeter measures the flow rate and direction. Automatic sampling ports are installed at key pump outlets, including the flue boiler drain, the crystallizer soft water replacement drain, the clean circulating water tank outlet, the secondary cooling water tank outlet, and the slag-curing water tank outlet. These ports are connected to an online water quality analyzer via pipelines. The online analyzer detects parameters such as pH, conductivity, suspended solids concentration, and hardness. Additionally, the automatic sampling ports are connected to an automatic sampler for offline verification via pipelines.

[0040] The transmission layer adopts an industrial Ethernet ring network architecture, connecting the control modules of all sensors, analyzers, and actuators in the perception layer to the industrial switch via optical fiber.

[0041] The intelligent decision-making platform is built on an industrial control computer, and its core algorithm modules are developed using the C++ language, specifically including:

[0042] Water balance and material balance calculation engine: Receives flow data from each flow meter and liquid level change data from the liquid level sensor in real time. Calculates the instantaneous water balance state of the entire system and each subsystem using the material balance formula "Inflow = Outflow + Liquid Level Change × Water Tank Cross-sectional Area". Simultaneously, it combines the concentration data from the water quality analyzer to calculate the balance of dissolved substances and generate a balance report.

[0043] The tiered water use optimization model transforms the preset replacement paths and water replenishment rules into a digital model. The input parameters of the model include water quality parameters (such as pH, conductivity, etc.) of each water source, water volume data, cost parameters (such as fresh water price, soft water price, demineralized water price, electricity cost, etc.) and the water quality and water level requirements of the target water tank. The model solves the optimal solution through a linear programming algorithm and outputs the water source, water replenishment volume, and water replenishment path decisions.

[0044] Prediction and Early Warning Module: Employing an LSTM neural network algorithm, this module trains a water quality prediction model based on historical water quality data (such as conductivity and suspended solids concentration), water volume data, and production load data from the past three months. The model predicts the water quality change trend of each pool within the next two hours. When the predicted value approaches the water quality threshold (such as conductivity reaching 480 μS / cm) or the liquid level is below 1.5m or above 4.5m, the module triggers an early warning signal and pushes the risk level (divided into three levels: general, moderate, and severe).

[0045] Dispatch instruction generation unit: Based on the decision results of the tiered water use optimization model and the signals from the prediction and early warning module, it generates specific dispatch instructions. The instruction format adopts the Modbus-RTU protocol, including pump start and stop instructions and electric valve opening instructions. After the instructions are generated, they are sent to the execution layer through the transmission layer.

[0046] The execution layer includes variable frequency water pumps and electric valves (the same equipment as the electric regulating valves in the sensing layer). All equipment is equipped with a PLC control module. After receiving instructions from the intelligent decision-making platform, it drives the water pump to adjust its speed or the valve to adjust its opening, performs the corresponding operation, and feeds back the equipment operating status (such as water pump running / stopping, valve opening value) to the intelligent decision-making platform through the transmission layer to form a closed-loop control.

[0047] This embodiment also provides a method for balancing and regulating the water system of a steel plant, including the following steps:

[0048] S1. Data Acquisition and Transmission: The liquid level sensor, electromagnetic flow meter, and online water quality analyzer in the sensing layer acquire data in real time. The acquired data is transmitted to the intelligent decision-making platform through the industrial ring network. The platform filters the data (removing outliers, such as when the instantaneous value of the flow meter suddenly exceeds the range) to ensure data accuracy.

[0049] S2. Water and Material Balance Calculation: The water and material balance calculation engine performs water and material balance calculations based on the received data.

[0050] S3. The tiered water use optimization model generates water replenishment and replacement decisions based on calculation results and preset rules. The generation logic of the water replenishment and replacement decisions is as follows: the intelligent decision-making platform prioritizes tiered recycled water as the water source for replenishment based on the source water quality, quantity, cost, and water quality and level requirements of the target water tank. Secondly, it selects low-cost fresh water and finally high-quality soft water or demineralized water. The above costs include water price and electricity cost. The intelligent decision-making platform calculates the comprehensive cost of different water replenishment schemes by establishing a cost accounting model and selects the water replenishment scheme with the lowest comprehensive cost as the optimal decision.

[0051] Specifically, the aforementioned preset rules include

[0052] The tiered water quality replacement rule is as follows: when the water quality in the purification pool deteriorates, the replacement wastewater is discharged into the secondary cooling pool; when the water quality in the secondary cooling pool deteriorates, the replacement wastewater is discharged into the slag-suppressing pool; the wastewater discharged from the slag-suppressing pool enters the plant's wastewater treatment station; the tiered water quality replacement rule also includes: during the replacement operation, the liquid level and water quality changes of the relevant pools are monitored in real time through the sensing layer, and the data is fed back to the intelligent decision-making platform, which dynamically adjusts the replacement flow rate and replacement duration;

[0053] It also includes high-quality wastewater downgrade and reuse rules: flue boiler wastewater is diverted to the secondary cooling water pool as a supplementary water source, and soft water replacement wastewater from the crystallizer system is recycled to the clean circulating water pool.

[0054] It also includes a prediction and early warning module that predicts water quality change trends based on real-time and historical data. When an imbalance risk is detected, it sends an early warning signal to the scheduling instruction generation unit, which then prioritizes generating risk control instructions.

[0055] S4. The scheduling instruction generation unit generates scheduling instructions based on the decision results and sends them to the execution layer through the transport layer.

[0056] S5, the execution layer drives the execution device to execute instructions and complete the water replenishment and replacement operations.

[0057] When this embodiment is applied to a scenario of high-quality wastewater degradation and reuse in steel plants:

[0058] When the flue gas boiler is operating normally, its wastewater discharge flow rate is stable at 40-60 m³ / h. 3The online water quality analyzer showed that the wastewater had a pH of 7.5-8.0, a conductivity of 250-350 μS / cm, and a suspended solids concentration of <10 mg / L, meeting the requirements for makeup water quality in the secondary cooling water tank. The intelligent decision-making platform, using a tiered water use optimization model, determined that the wastewater could be used as a makeup water source for the secondary cooling water tank and generated the instruction: "Close the new water supply valve for the secondary cooling water tank, open the valve for the flue boiler to discharge water into the secondary cooling water tank, and dynamically adjust the opening degree according to the liquid level in the secondary cooling water tank (i.e., adjust the opening degree to 60% when the liquid level is below 2m, and adjust the opening degree to 30%-40% when the liquid level is 2-4m)."

[0059] During the operation of the crystallizer system, soft water replacement is required 1-2 times per month, with a replacement drainage flow rate of approximately 80m³. 3 The water was discharged at a rate of / h for 4 hours. Water quality testing showed that its conductivity was <100μS / cm and hardness was <0.03mmol / L, meeting the water replenishment requirements of the clean circulation water tank. After detecting the start of crystallizer replacement, the intelligent decision-making platform automatically generated the instruction: "Open the valve for draining the crystallizer water to the clean circulation water tank, opening to 100%, and simultaneously close the soft water replenishment valve of the clean circulation water tank."

[0060] When this embodiment is applied to a cascade replacement scenario in a steel plant:

[0061] Due to long-term operation, the conductivity of the circulating water tank gradually increased to 490 μS / cm (approaching the threshold), triggering a "general" warning from the prediction and early warning module. The intelligent decision-making platform's tiered water use optimization model initiated the replacement process, generating the instruction: "Open the circulating water tank replacement valve to 30% to discharge the replacement wastewater into the secondary cooling water tank; simultaneously open the flue boiler drain valve to 20% to replenish the circulating water tank with tiered recycled water." During the replacement process, the online water quality analyzer monitored the conductivity changes of the circulating water tank and the secondary cooling water tank in real time. When the conductivity of the circulating water tank dropped to 400 μS / cm, the platform generated the instruction: "Close the circulating water tank replacement valve and adjust the flue boiler drain valve opening to 10% to maintain a stable level in the circulating water tank." This replacement did not use fresh water or soft water, reducing costs compared to the traditional method of replacing with soft water.

[0062] After receiving the replacement drainage from the circulating water tank, the conductivity of the secondary cooling water tank gradually increased to 2900 μS / cm (close to the threshold). The intelligent decision-making platform initiated a secondary replacement, generating the instruction: "Open the replacement valve of the secondary cooling water tank to 40% to discharge the replacement drainage into the slag-suppressing water tank; simultaneously increase the opening of the flue boiler drain valve to 50% to replenish the secondary cooling water tank with wastewater." After 3 hours of replacement, the conductivity of the secondary cooling water tank dropped to 2000 μS / cm, and the platform closed the replacement valve, completing the secondary replacement. After receiving the replacement drainage, the conductivity of the slag-suppressing water tank increased to 4500 μS / cm. Further replacement is not required at this time; the wastewater will be sent to the wastewater treatment plant when the conductivity approaches the threshold.

[0063] When this embodiment is applied to an emergency water replenishment scenario in a steel plant:

[0064] During the summer, due to excessively high temperatures, the evaporation rate in the circulating water tank increased sharply, with the water level dropping from 3.5m to 1.8m within one hour, triggering a "critical" warning from the prediction and early warning module. The intelligent decision-making platform prioritized monitoring the cascaded recycled water source, determining that it could not meet the rapid water replenishment demand. It then activated the emergency water replenishment mechanism, generating the instruction: "Open the soft water replenishment valve of the circulating water tank to 100% opening, and simultaneously open the fresh water replenishment valve to 80% opening." After 30 minutes, the water level in the circulating water tank rose back to 2.5m, and the platform gradually closed the soft water replenishment valve, maintaining the fresh water replenishment valve at 50% opening. One hour later, the water level recovered to 3.0m, and the platform closed the soft water replenishment valve, maintaining a stable water level solely through wastewater from the flue boiler and fresh water. This ensured the normal operation of the continuous casting machine's cooling system and prevented production interruptions.

[0065] In the above embodiments, the present invention provides a water system balance control system and method for steelmaking plants. By establishing a water use model of "high-quality wastewater degradation and reuse + cascade replacement chain," the present invention transforms wastewater previously directly discharged, such as flue boiler wastewater and crystallizer soft water replacement wastewater, into secondary water sources, achieving cascade utilization of water resources. Simultaneously, it avoids the wasteful phenomenon of traditional "high-quality, low-use" and reduces fresh water consumption. Through a cascade replacement path, the present invention transfers the deteriorating water quality from the purification pool and secondary cooling pool sequentially to lower-level pools with lower water quality requirements, sending only the final wastewater from the slag-steaming pool to the wastewater treatment plant, significantly reducing the amount of wastewater entering the treatment plant and lowering wastewater treatment costs and environmental risks associated with discharge. Furthermore, through devices such as level sensors, electromagnetic flow meters, and online water quality analyzers in the sensing layer, the present invention achieves real-time acquisition and accurate measurement of liquid levels in each pool, pipeline flow rates, and water quality parameters, solving the problem of incomplete measurement and sensing systems in traditional management. Based on real-time data-driven water balance calculations, managers can gain a comprehensive understanding of the water system's operational status, enabling a shift from "experience-based management" to "data-driven management." The intelligent decision-making platform of this invention, through a tiered water use optimization model and cost accounting model, comprehensively considers factors such as source water quality, quantity, price, and electricity costs to dynamically select the optimal water source and pathway for replenishment. It prioritizes the use of low-cost tiered recycled water, reducing the consumption of high-quality soft water and demineralized water, thereby lowering the overall operating cost of the water system. Simultaneously, the prediction and early warning module of this invention, based on real-time and historical data, can predict water quality trends and the risk of water system imbalance in advance, generating timely early warning signals and control commands to prevent production interruptions or equipment damage caused by system imbalances, thus improving the continuity and stability of steel plant production.

[0066] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the concept and scope of the present invention. Various modifications and improvements made to the technical solutions of the present invention by those skilled in the art without departing from the inventive concept should fall within the protection scope of the present invention. All technical contents for which protection is sought in this invention are fully described in the claims.

Claims

1. A water system balance control system for a steel plant, characterized in that: The system comprises a sensing layer, a transmission layer, an intelligent decision-making platform, and an execution layer, which are sequentially connected by signals. The sensing layer collects data on water quality, quantity, level, and equipment status from various pools and pipelines in the steel plant. The transmission layer transmits the data collected by the sensing layer to the intelligent decision-making platform. The intelligent decision-making platform performs water balance calculations, tiered water use optimization decisions, risk warnings, and generates scheduling instructions based on the received data. The execution layer receives instructions from the intelligent decision-making platform and drives the execution equipment to complete corresponding operations.

2. The water system balance control system for a steel plant according to claim 1, characterized in that: The sensing layer includes a level sensor, an electric regulating valve, an electromagnetic flow meter, an automatic sampling port, and an online water quality analyzer. The level sensor is installed in the production water tank, demineralized water tank, soft water tank, clean circulating water tank, secondary cooling water tank, and sludge-containing water tank. The electric regulating valve and electromagnetic flow meter are installed on the outlet branch pipes of all water pumps, including the water supply branch pipe, drainage branch pipe, and connecting branch pipe. The automatic sampling port is installed at the outlet of key water pumps and is connected to the online water quality analyzer or an automatic sampler.

3. The water system balance control system for a steel plant according to claim 1, characterized in that: The transmission layer adopts an industrial ring network; the execution layer includes variable frequency water pumps and electric valves.

4. The water system balance control system for a steel plant according to claim 3, characterized in that: The intelligent decision-making platform includes a water balance and material balance calculation engine, a tiered water use optimization model, a prediction and early warning module, and a scheduling instruction generation unit. The water balance and material balance calculation engine calculates the instantaneous balance and cumulative volume of the entire system and each subsystem based on real-time flow and level data. The tiered water use optimization model converts preset replacement paths and water replenishment rules into digital models for intelligent decision-making. The prediction and early warning module predicts water quality change trends and warns of imbalance risks based on real-time and historical data. The scheduling instruction generation unit generates sequences of commands for starting and stopping variable frequency pumps and opening electric valves.

5. A method for balancing and regulating the water system of a steel plant, characterized in that: Using the system according to any one of claims 1-4 includes the following steps: S1. The sensing layer collects liquid level data from each pool in the steelmaking plant, flow data from each pipeline, water quality data from key locations, and equipment status data, and transmits them to the intelligent decision-making platform through the transmission layer. S2. The intelligent decision-making platform performs water balance and material balance calculations based on the received data through the water balance and material balance calculation engine. S3, the tiered water use optimization model generates water replenishment and replacement decisions based on calculation results and preset rules; S4. The scheduling instruction generation unit generates scheduling instructions based on the decision results and sends them to the execution layer through the transport layer. S5, the execution layer drives the execution device to execute instructions and complete the water replenishment and replacement operations.

6. The method for balancing and regulating a steel plant water system according to claim 5, characterized in that: The preset rules in step S3 include The tiered water quality replacement rule is as follows: when the water quality in the purification pool deteriorates, the replacement wastewater is discharged into the secondary cooling pool; when the water quality in the secondary cooling pool deteriorates, the replacement wastewater is discharged into the slag-suppressing pool; and the wastewater discharged from the slag-suppressing pool enters the plant's wastewater treatment station. It also includes high-quality wastewater downgrade and reuse rules: flue boiler wastewater is diverted to the secondary cooling water pool as a supplementary water source, and soft water replacement wastewater from the crystallizer system is recycled to the clean circulating water pool.

7. The method for balancing and regulating a steel plant water system according to claim 6, characterized in that: The stepped water quality replacement rule also includes: during the replacement operation, the liquid level and water quality changes of the relevant water tanks are monitored in real time through the sensing layer, and the data is fed back to the intelligent decision-making platform, which dynamically adjusts the replacement flow rate and replacement duration.

8. The method for balancing and regulating a steel plant water system according to claim 5, characterized in that: The logic for generating the water replenishment and replacement decisions in step S3 is as follows: The intelligent decision-making platform prioritizes cascaded recycled water as a source of replenishment water based on the source water quality, quantity, cost, and water quality and level requirements of the target water tank. It then selects low-cost fresh water and finally high-quality soft water or demineralized water.

9. A method for balancing and regulating a steel plant water system according to claim 8, characterized in that: The costs include water prices and electricity costs; the intelligent decision-making platform calculates the comprehensive cost of different water replenishment schemes by establishing a cost accounting model, and selects the water replenishment scheme with the lowest comprehensive cost as the optimal decision.

10. A method for balancing and regulating a water system in a steel plant according to claim 5, characterized in that: Step S3 further includes a prediction and early warning module that predicts water quality change trends based on real-time and historical data. When an imbalance risk is detected, an early warning signal is sent to the scheduling instruction generation unit, which then generates risk control instructions first.