Advanced treatment system control method

Abstract

The application provides a deep treatment system control method, which is applied to a deep treatment system. The method comprises the following steps: obtaining the total suspended solid concentration of actual inflow water of the deep treatment system to obtain actual inflow total suspended solid concentration data; predicting the total suspended solid concentration of outflow water of the deep treatment system based on the actual inflow total suspended solid concentration data by using a first prediction model constructed in advance to obtain predicted outflow total suspended solid concentration data; calculating the separation efficiency of a high-efficiency sedimentation tank based on the actual inflow total suspended solid concentration data and the predicted outflow total suspended solid concentration data to obtain a predicted separation efficiency; and adjusting the actual inflow flow of the high-efficiency sedimentation tank based on the predicted separation efficiency to ensure the high-efficiency separation of the high-efficiency sedimentation tank. The deep treatment system control method provided by the application can effectively ensure that the high-efficiency sedimentation tank is always in a high-efficiency separation state, effectively cope with water quality and quantity fluctuation, and ensure the stability of outflow water quality.

Description

Technical Field

[0001] This application relates to the field of wastewater treatment technology, and in particular to a control method for an advanced treatment system. Background Technology

[0002] In the field of existing wastewater treatment technology, although traditional wastewater treatment devices and methods can effectively remove pollutants from water to a certain extent, there are still several significant shortcomings and challenges. For example, there are limitations in improving sludge settling efficiency and accelerating sedimentation, which leads to a longer treatment cycle and difficulty in stabilizing effluent quality to meet standards. In particular, for wastewater containing a lot of complex suspended solids and colloidal substances, traditional sedimentation methods are difficult to efficiently separate these tiny particles, affecting wastewater treatment efficiency and effluent quality. Summary of the Invention

[0003] In view of this, the purpose of this application is to propose a deep processing system control method to solve the above-mentioned technical problems.

[0004] This application provides a control method for an advanced treatment system, which is applied to an advanced treatment system. The advanced treatment system includes a mixing reaction unit and an efficient sedimentation tank connected in sequence. The effluent from the mixing reaction unit enters the efficient sedimentation tank along the tangential direction to form a vortex in the efficient sedimentation tank.

[0005] The method includes:

[0006] The total suspended solids concentration of the actual influent to the deep treatment system is obtained, and the actual total suspended solids concentration data of the influent is obtained.

[0007] Based on the actual influent total suspended solids concentration data, the total suspended solids concentration of the effluent from the deep treatment system is predicted using a pre-built first prediction model, and the predicted effluent total suspended solids concentration data is obtained.

[0008] The separation efficiency of the high-efficiency sedimentation tank is calculated based on the actual influent total suspended solids concentration data and the predicted effluent total suspended solids concentration data, and the predicted separation efficiency is obtained.

[0009] The actual influent flow rate of the high-efficiency sedimentation tank is adjusted based on the predicted separation efficiency to ensure efficient separation in the high-efficiency sedimentation tank.

[0010] Furthermore, adjusting the actual influent flow rate of the high-efficiency sedimentation tank based on the predicted separation efficiency includes:

[0011] In response to the predicted separation efficiency being less than 50%, the actual influent flow rate of the high-efficiency sedimentation tank is adjusted to be greater than or equal to 1.2 times and less than or equal to 1.5 times the design flow rate.

[0012] In response to the predicted separation efficiency being greater than or equal to 50% and less than or equal to 80%, the actual influent flow rate of the high-efficiency sedimentation tank is adjusted to be greater than or equal to 1 and less than 1.2 times the design flow rate.

[0013] In response to the predicted separation efficiency being greater than 80%, the actual influent flow rate of the high-efficiency sedimentation tank is adjusted to be greater than or equal to 0.8 times and less than 1 times the design flow rate.

[0014] And / or, the predicted separation efficiency is calculated using the following formula:

[0015]

[0016] Among them, E sep For the predicted separation efficiency, the The actual total suspended solids concentration data of the influent. The predicted total suspended solids concentration data for the effluent.

[0017] Further, the step of predicting the total suspended solids concentration of the effluent from the advanced treatment system using a pre-built first prediction model based on the actual influent total suspended solids concentration data, to obtain predicted effluent total suspended solids concentration data, includes:

[0018] Based on the actual total suspended solids concentration data of the influent, the total suspended solids concentration of the effluent from the deep treatment system is predicted using a prediction sub-model trained based on historical data, thus obtaining the first prediction data.

[0019] Based on the actual influent total suspended solids concentration data, the total suspended solids concentration of the effluent from the advanced treatment system is predicted using an expert model to obtain second prediction data.

[0020] In response to the fact that the deviation between the first predicted data and the second predicted data is within a preset deviation threshold range, the average value of the first predicted data and the second predicted data is determined as the predicted total suspended solids concentration data of the effluent.

[0021] Furthermore, the method also includes:

[0022] Obtain the total suspended solids concentration of the actual effluent from the deep treatment system to obtain the actual effluent total suspended solids concentration data.

[0023] In response to the actual effluent total suspended solids concentration exceeding a preset first warning value, the real-time influent flow rate of the high-efficiency sedimentation tank is dynamically adjusted within a flow range determined based on the predicted separation efficiency, until the actual effluent total suspended solids concentration does not exceed the preset first warning value or reaches the adjustment limit of the corresponding flow range.

[0024] Furthermore, the method also includes:

[0025] Obtain the actual influent flow rate and actual total phosphorus concentration of the biochemical treatment system at the front end of the deep treatment system to obtain actual influent water volume data and actual influent total phosphorus concentration data.

[0026] Based on the actual biochemical influent volume data and the actual biochemical influent total phosphorus concentration data, the influent flow rate and total phosphorus concentration of the deep treatment system are predicted using a pre-built second prediction model, thereby obtaining predicted influent flow rate data and predicted influent total phosphorus concentration data.

[0027] The amount of coagulant used in the mixing reaction unit is calculated using the predicted influent flow rate data and the predicted total phosphorus concentration data, and the appropriate amount of coagulant is added to the mixing reaction unit.

[0028] Further, the step of calculating the amount of coagulant used in the mixing reaction unit using the predicted influent flow rate data and the predicted influent total phosphorus concentration data includes:

[0029] Obtain the upper limit standard value of total phosphorus concentration in the effluent of the advanced treatment system;

[0030] The coagulant dosage ratio is calculated using the predicted influent total phosphorus concentration data and the upper limit standard value of the effluent total phosphorus concentration of the advanced treatment system.

[0031] The amount of coagulant used in the mixing reaction unit is calculated using the dosage ratio and the predicted influent flow rate data.

[0032] Furthermore, the method also includes:

[0033] Obtain the total phosphorus concentration of the actual effluent from the deep treatment system to obtain the actual effluent total phosphorus concentration data.

[0034] In response to the actual effluent total phosphorus concentration data exceeding the preset second warning value, a correction coefficient is used to correct the coagulant dosage calculated based on the predicted influent flow rate data and the predicted influent total phosphorus concentration data, and the corrected dosage of coagulant is added to the mixing reaction unit.

[0035] The correction coefficient is determined based on the actual total phosphorus concentration data of the effluent and the preset second warning value.

[0036] Furthermore, a heavy medium is added to the deep processing system to improve the separation effect;

[0037] The advanced treatment system also includes a heavy media recovery device connected to the bottom of the high-efficiency sedimentation tank, which is used to screen the mixed sludge in the high-efficiency sedimentation tank to recover the heavy media, and to re-input the recovered heavy media into the mixing reaction unit.

[0038] The method further includes:

[0039] Obtain the total suspended solids concentration of the actual effluent from the deep treatment system to obtain the actual effluent total suspended solids concentration data.

[0040] In response to the actual effluent total suspended solids concentration data exceeding a preset first warning value, the heavy media recovery device is activated, the recovery efficiency of the heavy media is monitored, and the operating parameters of the heavy media recovery device are adjusted based on the recovery efficiency to ensure efficient recovery of the heavy media.

[0041] Furthermore, the heavy media recovery device includes a feed inlet on the side wall, an underflow outlet at the bottom, and an overflow outlet at the top; the feed inlet is connected to the bottom of the high-efficiency sedimentation tank, the underflow outlet is connected to the mixing reaction unit, and the overflow outlet is used to discharge the overflow product to the outside of the system.

[0042] The method of adjusting the operating parameters of the heavy medium recovery device based on the recovery efficiency includes:

[0043] In response to the recovery efficiency being less than 50%, the diameter of the underflow outlet is adjusted to be greater than or equal to 0.3 times and less than or equal to 0.5 times the design diameter value;

[0044] In response to a recovery efficiency greater than or equal to 50% and less than or equal to 80%, the diameter of the underflow outlet is adjusted to be greater than 0.5 times and less than 0.8 times the design diameter value;

[0045] In response to the recovery efficiency being greater than 80%, the diameter of the underflow outlet is adjusted to be greater than or equal to 0.8 times and less than or equal to 1 times the design diameter value;

[0046] And / or, the formula for calculating the recovery efficiency is as follows:

[0047] R recovery =M recovered / M total

[0048] M recovered =C recovered ×Q O

[0049] M total =C total ×Q E

[0050] Among them, R recovery M represents the recovery efficiency. recovered M represents the mass of the heavy medium flowing out of the underflow outlet. total C represents the total mass of heavy media entering the heavy media recovery device. recovered C represents the concentration of the heavy medium in the effluent from the underflow outlet. total Q is the concentration of the heavy medium at the feed inlet. O Q is the flow rate of the overflow outlet. E The flow rate at the feed inlet is denoted as .

[0051] Furthermore, the bottom of the high-efficiency sedimentation tank is provided with a first sludge discharge port, which is connected to the feed inlet;

[0052] A second sludge discharge port is provided on the side wall of the high-efficiency sedimentation tank at a height of 1 / 5 to 1 / 3 of the distance from the first sludge discharge port. The second sludge discharge port is connected to the outside of the system through a sludge discharge pipeline.

[0053] The method further includes:

[0054] Monitor the real-time sludge level in the high-efficiency sedimentation tank;

[0055] In response to the real-time sludge level height being greater than a preset sludge level height threshold, the second sludge discharge port is opened to discharge a portion of the sludge in the high-efficiency sedimentation tank to the outside of the system through the sludge discharge pipeline.

[0056] As can be seen from the above, this application provides a deep treatment system control method. The effluent from the mixing reaction unit enters the high-efficiency sedimentation tank tangentially, forming a vortex within the tank. Due to the vortex, heavier particles are thrown to the periphery and gradually settle to the bottom, while lighter water rises from the center, promoting the sedimentation of suspended solids and effectively improving sedimentation separation efficiency. Simultaneously, the actual influent flow rate of the high-efficiency sedimentation tank is adjusted using predicted separation efficiency. When the influent flow rate changes, the inlet velocity of the high-efficiency sedimentation tank also changes. This velocity change further alters the rotational speed and centrifugal force of the vortex within the tank. Increased rotational speed and centrifugal force further enhance the sedimentation velocity of suspended solids, thereby improving the sedimentation separation efficiency in the high-efficiency sedimentation tank. Furthermore, the predicted separation efficiency is calculated based on the predicted total suspended solids concentration data of the effluent from the first prediction model. This allows for advance prediction of the separation efficiency of the high-efficiency sedimentation tank, enabling timely adjustment of the actual influent flow rate to ensure efficient separation. Attached Figure Description

[0057] To more clearly illustrate the technical solutions in this application or related technologies, the drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0058] Figure 1 This is a schematic diagram of a deep processing system control method in an embodiment of this application;

[0059] Figure 2 This is a schematic diagram of a deep processing system according to an embodiment of this application;

[0060] Figure 3 This is a schematic diagram of an electronic device according to an embodiment of this application. Detailed Implementation

[0061] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with specific embodiments and the accompanying drawings.

[0062] It should be noted that, unless otherwise defined, the technical or scientific terms used in the embodiments of this application should have the ordinary meaning understood by one of ordinary skill in the art to which this application pertains. The terms "first," "second," and similar terms used in the embodiments of this application do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed after the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are only used to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0063] Biological treatment is a common wastewater treatment method and a core component of wastewater treatment, belonging to the secondary treatment stage. It mainly relies on the metabolic activities of microorganisms to decompose and transform organic pollutants and some inorganic substances (such as ammonia nitrogen and phosphate) in wastewater. The principle of biological treatment is to utilize microbial communities such as bacteria, fungi, and protozoa in aerobic, anoxic, or anaerobic environments to degrade organic matter into carbon dioxide, water, and biomass, while simultaneously achieving nitrogen and phosphorus removal. Common biological treatment processes include activated sludge processes, biofilm processes, and anaerobic treatment. In the wastewater treatment process, although biological treatment can efficiently remove most biodegradable pollutants (such as organic matter and ammonia nitrogen), its purification capacity still has limitations, thus requiring supplementary advanced treatment.

[0064] Advanced treatment, a tertiary treatment stage, is an enhanced purification phase designed to remove residual recalcitrant pollutants, nutrients, pathogens, and emerging pollutants (such as pharmaceuticals and microplastics) to meet high standards for reuse or discharge. Coagulation-flocculation-sedimentation is one method of achieving advanced treatment. By adding chemical agents during the coagulation and flocculation stages, the stability of pollutants is disrupted, forming large flocs. Finally, sedimentation separation achieves water purification, effectively removing residual colloids, suspended solids (SS), phosphorus, and some difficult-to-sediment organic matter after biological treatment. Sedimentation efficiency is one of the key indicators in the coagulation-flocculation-sedimentation system. Higher sedimentation efficiency leads to higher treatment efficiency for suspended solids, phosphorus, and other pollutants in wastewater, better effluent quality, shorter treatment time, and a higher total wastewater volume that can be treated per unit time. Sedimentation efficiency is influenced by sludge settling performance, as well as the properties, particle size, and density of suspended particles and colloidal substances in the wastewater. Solid-liquid separation mainly occurs during the sedimentation stage, and the operation mode and equipment structure of the sedimentation stage also affect sedimentation efficiency to some extent.

[0065] In existing technologies, increasing the dosage of chemicals and sedimentation time is necessary to improve sedimentation efficiency. However, these methods also increase costs and processing time, impacting overall wastewater treatment efficiency. Therefore, limited by factors such as cost and treatment efficiency, the current coagulation-flocculation-sedimentation system has significant limitations in improving sedimentation efficiency, especially for wastewater containing a large amount of complex suspended solids and colloidal substances. Traditional sedimentation methods struggle to efficiently separate these tiny particles, affecting wastewater treatment efficiency and effluent quality. Furthermore, the quality and quantity of influent in the upstream biological treatment stage often fluctuate. Existing coagulation-flocculation-sedimentation systems cannot effectively handle these fluctuations, lacking sufficient flexibility and response speed. Frequent water quality fluctuations make it difficult to maintain stable effluent quality, affecting subsequent treatment and wastewater discharge. They also make it difficult to accurately adjust key parameters such as chemical dosage, impacting sedimentation efficiency and further affecting effluent quality.

[0066] In view of this, this application provides a control method for a deep processing system, which, when applied to a deep processing system, can effectively improve the precipitation separation efficiency of the deep processing system and achieve efficient precipitation separation; such as Figure 2 As shown, the deep treatment system includes a mixing reaction unit 10 and a high-efficiency sedimentation tank 20 connected in sequence. The effluent from the mixing reaction unit 10 enters the high-efficiency sedimentation tank 20 along the tangential direction to form a vortex in the high-efficiency sedimentation tank 20.

[0067] like Figure 1 As shown, the method includes:

[0068] S101. Obtain the total suspended solids concentration of the actual influent to the deep treatment system, and obtain the actual total suspended solids concentration data of the influent.

[0069] S102. Based on the actual influent total suspended solids concentration data, the total suspended solids concentration of the effluent from the deep treatment system is predicted using a pre-built first prediction model to obtain the predicted effluent total suspended solids concentration data.

[0070] S103. Based on the actual influent total suspended solids concentration data and the predicted effluent total suspended solids concentration data, the separation efficiency of the high-efficiency sedimentation tank 20 is calculated, and the predicted separation efficiency is obtained.

[0071] S104. Adjust the actual influent flow rate of the high-efficiency sedimentation tank 20 based on the predicted separation efficiency to ensure the high-efficiency separation of the high-efficiency sedimentation tank 20.

[0072] In this application, the effluent from the mixing reaction unit 10 enters the high-efficiency sedimentation tank 20 tangentially, creating a swirling flow within the tank. Due to this swirling flow, heavier particles are thrown to the periphery of the sedimentation tank 20 and gradually settle to the bottom, while lighter water rises and flows out from the center, thus promoting the sedimentation of suspended solids and effectively improving sedimentation separation efficiency. Simultaneously, the actual influent flow rate of the high-efficiency sedimentation tank 20 is adjusted using predicted separation efficiency. When the influent flow rate changes, the inlet velocity of the high-efficiency sedimentation tank 20 also changes. When the flow rate changes, the rotation speed and centrifugal force of the swirling flow within the high-efficiency sedimentation tank 20 can be further altered. When the swirling speed increases and the centrifugal force strengthens, the settling velocity of suspended solid particles can be further enhanced, thereby improving the sedimentation and separation efficiency in the high-efficiency sedimentation tank 20. Furthermore, the predicted separation efficiency is calculated based on the predicted total suspended solids concentration data of the effluent from the first prediction model. This allows for advance prediction of the separation efficiency of the high-efficiency sedimentation tank 20, enabling timely adjustment of the actual influent flow rate to ensure efficient separation within the high-efficiency sedimentation tank 20.

[0073] Total Suspended Solids (TSS) concentration refers to the concentration of suspended solid particles in water, including silt, organic matter, microorganisms, and other solid particles. TSS includes not only inorganic particles (such as silt) but also organic flocs (such as microbial aggregates and recalcitrant organic matter), thus reflecting the sedimentation removal efficiency of different types of suspended solids in a sedimentation process.

[0074] In some embodiments, adjusting the actual influent flow rate of the high-efficiency sedimentation tank 20 based on the predicted separation efficiency includes:

[0075] In response to the predicted separation efficiency being less than 50%, the actual influent flow rate of the high-efficiency sedimentation tank 20 is adjusted to be greater than or equal to 1.2 times and less than or equal to 1.5 times the design flow rate.

[0076] In response to the predicted separation efficiency being greater than or equal to 50% and less than or equal to 80%, the actual influent flow rate of the high-efficiency sedimentation tank 20 is adjusted to be greater than or equal to 1 and less than 1.2 times the design flow rate.

[0077] In response to the predicted separation efficiency being greater than 80%, the actual influent flow rate of the high-efficiency sedimentation tank 20 is adjusted to be greater than or equal to 0.8 times and less than 1 times the design flow rate.

[0078] In this application, the actual influent flow rate of the high-efficiency sedimentation tank 20 is further adjusted based on the predicted separation efficiency. When the predicted separation efficiency is less than 50%, it indicates that after the current sewage enters the high-efficiency sedimentation tank 20, there will be problems such as insufficient settling capacity, ineffective solid-liquid separation, and a significant increase in the content of solid particles in the supernatant, which will lead to unstable effluent quality and failure to meet standards. Therefore, at this time, the actual influent flow rate of sewage entering the high-efficiency sedimentation tank 20 is controlled to be greater than or equal to 1.2 times and less than or equal to 1.5 times the design flow rate value. That is, the actual influent flow rate is controlled to be significantly higher than the design flow rate value, which increases the pressure when sewage enters the high-efficiency sedimentation tank 20 and increases the influent flow velocity, thereby increasing the vortex speed and centrifugal force of sewage in the high-efficiency sedimentation tank 20, and promoting the settling of solid particles in sewage, so as to quickly improve the current separation efficiency of the high-efficiency sedimentation tank 20. When the predicted separation efficiency is between 50% and 80%, it indicates that the separation efficiency cannot meet the current water quality requirements after the wastewater enters the high-efficiency sedimentation tank 20, and fluctuations in effluent quality are likely to occur. Therefore, the actual influent flow rate of the high-efficiency sedimentation tank 20 should be greater than or equal to 1 and less than 1.2 times the design flow rate. When the predicted separation efficiency is greater than 80%, it indicates that the operation of the high-efficiency sedimentation tank 20 can basically meet the current influent water quality requirements. Taking into account operating costs and effluent stability, the actual influent flow rate of wastewater entering the high-efficiency sedimentation tank 20 should be adjusted to be greater than or equal to 0.8 and less than 1 times the design flow rate to ensure the stable operation of the high-efficiency sedimentation tank 20.

[0079] The design flow rate refers to the maximum water flow rate that the high-efficiency sedimentation tank 20 can continuously process while meeting the effluent quality requirements. It is a crucial basis for determining the tank's size, structure, and operating parameters, and is typically determined during the design process of the high-efficiency sedimentation tank 20 based on treatment process requirements and relevant design specifications. To address unforeseen flow fluctuations (such as rainy season peaks or industrial shock loads) or equipment performance degradation, the final determined design flow rate is usually slightly lower than the actual maximum flow rate that the high-efficiency sedimentation tank 20 can process. Therefore, in the actual operation of the high-efficiency sedimentation tank 20, operating at a flow rate higher than the design flow rate in the short term will not result in problems such as overload or insufficient sedimentation time leading to substandard effluent quality. The effluent from the mixing reaction unit 10 enters the high-efficiency sedimentation tank 20 tangentially to form a vortex within the high-efficiency sedimentation tank 20, acting as a hydrocyclone. When the actual influent flow rate increases, a vortex field with faster rotation speed and centrifugal force can be formed within the high-efficiency sedimentation tank 20. The higher the vortex speed and the greater the centrifugal force, the faster the suspended solids settle, the shorter the settling time, and the higher the separation efficiency and wastewater treatment efficiency.

[0080] Meanwhile, wastewater typically undergoes coagulation and flocculation treatments in the mixing reaction unit 10, which promotes the aggregation of suspended solids. The wastewater entering the high-efficiency sedimentation tank 20 contains suspended solids with a density significantly different from that of water, making them relatively easy to separate. Solid-liquid separation is even more easily achieved in the swirling flow field. Therefore, when the actual influent flow rate is increased to 1.2 or even 1.5 times the design flow rate, although the stability of the swirling flow field in the high-efficiency sedimentation tank 20 may change to some extent, the large density difference between solids and liquids means that the changes in the swirling flow field are insufficient to cause suspended solids to overflow from the effluent of the high-efficiency sedimentation tank 20, effectively ensuring the quality of the treated water within the high-efficiency sedimentation tank 20's treatment capacity. Of course, when the high-efficiency sedimentation tank 20 operates at a flow rate exceeding its design flow rate for an extended period, it may cause problems such as sludge floating, accelerated equipment wear, long-term equipment overload, and operational instability, leading to deterioration of effluent quality and reduced treatment efficiency. Therefore, when the predicted separation efficiency is greater than 80%, meaning the predicted separation efficiency can basically meet the current influent water quality requirements, the high-efficiency sedimentation tank 20 should be controlled to operate at a flow rate close to or slightly lower than the design flow rate (i.e., greater than or equal to 0.8 times and less than 1 times the design flow rate) to ensure the long-term stable operation of the deep treatment system. In conjunction with the swirling flow pattern within the high-efficiency sedimentation tank 20, the actual influent flow rate of the high-efficiency sedimentation tank 20 is adjusted in real time based on the predicted separation efficiency. This increases the swirling speed and centrifugal force within the high-efficiency sedimentation tank 20 to rapidly improve its separation efficiency, ensuring that the high-efficiency sedimentation tank 20 always maintains high separation efficiency and achieves highly efficient deep treatment. Specifically, when the predicted separation efficiency is less than 50%, the actual influent flow rate of the high-efficiency sedimentation tank 20 can be 1.2, 1.25, 1.3, 1.35, 1.4, 1.45, or 1.5 times the design flow rate, or other values ​​within this range, without any specific restriction. When the predicted separation efficiency is greater than or equal to 50% and less than or equal to 80%, the actual influent flow rate of the high-efficiency sedimentation tank 20 can be 1, 1.05, 1.1, 1.15, 1.16, 1.18, or 1.19 times the design flow rate, or other values ​​within this range, without any specific restriction. When the predicted separation efficiency is greater than 80%, the actual influent flow rate of the high-efficiency sedimentation tank 20 can be 0.8, 0.82, 0.85, 0.86, 0.9, 0.92, 0.95, 0.96, or 0.98 times the design flow rate, or other values ​​within this range, without any specific restriction.

[0081] In some embodiments, the predicted separation efficiency is calculated using the following formula:

[0082]

[0083] Among them, E sep For the predicted separation efficiency, the The actual total suspended solids concentration data of the influent. The predicted total suspended solids concentration data for the effluent.

[0084] By using actual influent total suspended solids concentration data and predicted effluent total suspended solids concentration data, the separation efficiency of the high-efficiency sedimentation tank 20 can be predicted, and the influent flow rate of the high-efficiency sedimentation tank 20 can be adjusted in a timely manner, thereby improving the settling performance of suspended solids in the high-efficiency sedimentation tank 20 and enhancing the actual separation efficiency.

[0085] In some embodiments, the step of predicting the total suspended solids concentration of the effluent from the advanced treatment system using a pre-built first prediction model based on the actual influent total suspended solids concentration data, to obtain predicted effluent total suspended solids concentration data, includes:

[0086] Based on the actual total suspended solids concentration data of the influent, the total suspended solids concentration of the effluent from the deep treatment system is predicted using a prediction sub-model trained based on historical data, thus obtaining the first prediction data.

[0087] Based on the actual influent total suspended solids concentration data, the total suspended solids concentration of the effluent from the advanced treatment system is predicted using an expert model to obtain second prediction data.

[0088] In response to the fact that the deviation between the first predicted data and the second predicted data is within a preset deviation threshold range, the average value of the first predicted data and the second predicted data is determined as the predicted total suspended solids concentration data of the effluent.

[0089] The first predictive model comprises a predictive sub-model and an expert model. An expert model is a comprehensive system combining wastewater treatment process mechanisms, expert experience, and mathematical modeling techniques, capable of simulating, predicting, or optimizing wastewater treatment processes. Several companies already offer relevant expert models for industry use, such as the ASM model developed by the International Water Association (IWA) and Sumo designed and developed by the French company DYNAMITA. However, while expert models can integrate expert knowledge and experience in the wastewater treatment field and provide services such as water quality prediction, their accuracy is limited. Furthermore, expert experience is significantly influenced by regional and process differences, making it difficult to filter and constrain the historical data used for training, resulting in generally low relevance of expert models. Predictive sub-models, on the other hand, can be trained using historical data from advanced treatment systems in the same region or at the same wastewater treatment plant. The resulting predictive sub-model is more consistent with the characteristics of wastewater in the current region or at the current wastewater treatment plant. However, although predictive sub-models are trained based on historical data, the available historical data is more limited than that of expert models, and there are certain differences in model parameters and functionality compared to expert models. Therefore, this application combines expert models and prediction sub-models to avoid problems such as poor targeting and large data bias caused by running a single model.

[0090] Using actual influent total suspended solids concentration data, first and second predicted data are independently obtained using a prediction sub-model and an expert model, respectively. The deviation between the first and second predicted data is then calculated. If the deviation is too large, it indicates a significant anomaly in the prediction sub-model or the input actual influent total suspended solids concentration data. Adjusting the operating parameters of the advanced treatment system based on this data could lead to serious problems. In this case, instead of calculating the predicted separation efficiency and adjusting the influent flow rate of the high-efficiency sedimentation tank 20 based on this data, a thorough investigation is conducted into the data acquisition and calculation process of the advanced treatment system. When the deviation between the first and second predicted data is outside the preset deviation threshold range, both the first and second predicted data can be output separately with an early warning message. Alternatively, only an early warning message can be output to indicate that the data is unusable; there are no specific restrictions.

[0091] When the deviation between the first and second predicted data obtained from the prediction sub-model and the expert model is within the preset deviation threshold range, it indicates that the data predicted by the two models are relatively close, the data are relatively accurate, and the usability is high. In this case, the average of the first and second predicted data is output as the predicted total suspended solids concentration in the effluent. Specifically, the deviation between the first and second predicted data = |first predicted data - second predicted data| / second predicted data, that is, the deviation between the two is determined by the ratio of the absolute difference between the first and second predicted data to the second predicted data. The preset deviation threshold range can be 0–50%, or 0–45%, 0–40%, 0–35%, 0–30%, etc., without specific limitations.

[0092] The historical data for the prediction sub-model is the historical processing data of the advanced treatment system, or the historical data of the same treatment system in the wastewater treatment plant or region. When using historical data for training, the historical data needs to undergo preprocessing operations including at least one of the following:

[0093] (1) Time series alignment: Historical data is a dataset with time series. After obtaining the historical data, ensure that the time index of all data is the same.

[0094] (2) Missing value handling: Use linear interpolation or nearest neighbor interpolation to fill missing values.

[0095] (3) Outlier detection: Detect outliers in historical data. If a data value is not within the normal range (i.e., [μ-3σ, μ+3σ]), it is considered an outlier.

[0096] (4) Use statistical methods to determine whether the time series of historical data is stationary. If the time series is not stationary, perform difference processing or trend term extraction until the time series is stationary.

[0097] The predictive sub-model can be constructed based on the linear regression method, which has low computational complexity, fast computation speed, low resource consumption during terminal deployment, and wide application scenarios. The following uses specific formulas to illustrate the process of constructing a predictive sub-model using linear regression.

[0098] The AIC expression for building the model is:

[0099] AIC=nln(σe 2 )+2k

[0100] Where, σe 2 ρ represents the residual variance of the fitted model; n is the sample size; k is the number of parameters in the model. If the model includes an intercept or constant term, then k = p + q + 1; otherwise, k = p + q. p represents the order of the autoregressive (AR) component in the model, i.e., the number of past observations used in the model, and q represents the order of the moving average (MA) component in the model, i.e., the number of past error terms used in the model. The smaller the AIC value, the better the model fits the actual data and meets the requirements for prediction.

[0101] The parameter estimates are used to determine the parameter estimates of the predictive sub-model.

[0102] set up For parameters The estimated value can be obtained by using the sum of squared residuals from the model fit:

[0103]

[0104] in, θ represents the parameters of the autoregressive (AR) part, indicating the weights of past observations used in the model, m∈{1,2,3,…,p}; l For the moving average (MA) component, represents the weights of the past error term used in the model, l∈{1,2,3,…,q}; C t Q represents the TSS concentration value over a time series. t Here, t represents the flow rate value in the time series, and t is the index of the time point; i = 1 - p.

[0105] Minimum solution of the function This is the conditional least squares estimate of the model parameters.

[0106] residual

[0107] Using the coefficient of determination R 2 R is used to evaluate the goodness of fit of a regression model. 2 The closer the value is to 1, the closer the model's predicted value is to the actual value.

[0108]

[0109] The test samples for the hypothetical model are assumed to be: j = T+1, T+2, ..., T+h, where T is the sample length for model building and h is the length of the model evaluation sequence. and C tr The predicted and actual TSS concentrations at time t are labeled, respectively.

[0110] Based on the real-time influent TSS concentration and effluent TSS concentration at different time periods, the p and q values ​​in the model are determined, and the corresponding predicted TSS concentration values ​​are finally obtained. The first predicted data, the model expression is:

[0111]

[0112] The TSS concentration of the effluent is related not only to the TSS concentration of the influent but also to factors such as influent flow rate, pH, temperature, and coagulant dosage. Therefore, to improve the accuracy of the first prediction model, it can be trained using historical data including influent flow rate, pH, temperature, and coagulant dosage. When using the first prediction model for prediction, the actual total suspended solids concentration of the influent to the advanced treatment system, influent flow rate, influent pH, influent temperature, and the current coagulant dosage are obtained. Then, the total suspended solids concentration of the effluent from the advanced treatment system is predicted, i.e., the predicted total suspended solids concentration data. In some embodiments, the step of predicting the total suspended solids concentration of the effluent from the advanced treatment system using the pre-built first prediction model based on the actual influent total suspended solids concentration data to obtain the predicted total suspended solids concentration data includes:

[0113] Obtain the actual influent flow rate, pH, and temperature of the deep treatment system, as well as the current coagulant dosage.

[0114] Based on the actual total suspended solids concentration data of the influent, the actual influent flow rate, pH, and temperature of the deep treatment system, and the current coagulant dosage, the total suspended solids concentration of the effluent from the deep treatment system is predicted using a pre-built first prediction model, thus obtaining the predicted total suspended solids concentration data of the effluent.

[0115] In conventional advanced treatment processes, the influent flow rate affects the residence time of wastewater in the sedimentation process, thus affecting particle settling time and consequently the effluent TSS concentration. Coagulants alter the interactions between suspended solids or colloidal particles, causing them to aggregate into larger clusters and settle to the bottom of the water body, thereby achieving water purification and solid-liquid separation. Water pH and temperature affect the activity of coagulants; excessively low temperatures can hinder coagulant hydrolysis and floc formation, thus impacting coagulation efficiency. Furthermore, temperature affects water viscosity, further influencing settling performance. Therefore, the actual influent flow rate, pH, and temperature of the advanced treatment system, as well as the current coagulant dosage, all have a significant impact on the TSS concentration. Therefore, to further improve the prediction effect of effluent TSS concentration, multidimensional data can be obtained to comprehensively predict the effluent TSS concentration. This involves acquiring actual influent total suspended solids (TSS) concentration data, actual influent flow rate, influent pH, influent temperature, and current system coagulant dosage data from the advanced treatment system to predict the effluent TSS concentration. By comprehensively considering the influence of various environmental factors on the effluent TSS concentration, the prediction results become more accurate. When using multidimensional data to comprehensively predict the effluent TSS concentration, the corresponding first prediction model is also trained using historical data containing multidimensional data. Specifically, the model is trained using historical data including actual influent TSS concentration data, actual influent flow rate, influent pH, influent temperature, and current system coagulant dosage data from the advanced treatment system. During the training of the first prediction model, through calculation and learning from a large amount of historical data, the influence of various environmental factors on the effluent TSS concentration can be discovered and learned, such as the actual influent total suspended solids concentration, actual influent flow rate, influent pH, influent temperature, and current system coagulant dosage. Therefore, after obtaining the corresponding data, the effluent total suspended solids concentration can be accurately predicted. Specifically, when using multidimensional data to comprehensively predict the effluent TSS concentration, the first prediction model can be constructed based on multiple linear regression, random forest, or LSTM neural networks. Other algorithms and models capable of analyzing and predicting multiple influencing factors can also be applied to this application; no specific limitations are imposed.

[0116] In some embodiments, the method further includes:

[0117] Obtain the total suspended solids concentration of the actual effluent from the deep treatment system to obtain the actual effluent total suspended solids concentration data.

[0118] In response to the actual effluent total suspended solids concentration data exceeding a preset first warning value, the real-time influent flow rate of the high-efficiency sedimentation tank 20 is dynamically adjusted within a flow range determined based on the predicted separation efficiency, until the actual effluent total suspended solids concentration data does not exceed the preset first warning value or reaches the adjustment limit of the corresponding flow range.

[0119] The predicted separation efficiency is calculated based on the predicted total suspended solids concentration in the effluent from the first prediction model. However, in actual operation, due to the combined effects of various factors such as the accuracy of the first prediction model, real-time data acquisition errors, and sensor errors, the predicted total suspended solids concentration in the effluent may deviate from the actual data, resulting in a certain discrepancy between the predicted and actual separation efficiency. Therefore, while adjusting the influent flow rate of the high-efficiency sedimentation tank 20 using the predicted separation efficiency, the actual total suspended solids concentration in the effluent is monitored in real time. The actual influent flow rate of the high-efficiency sedimentation tank 20 is then corrected using the actual total suspended solids concentration data to further ensure efficient sedimentation in the high-efficiency sedimentation tank 20, thereby ensuring stable effluent quality. When the actual effluent total suspended solids concentration exceeds the preset first warning value, the real-time influent flow rate of the high-efficiency sedimentation tank 20 is dynamically adjusted within a flow range determined based on the predicted separation efficiency. Specifically, when the actual influent flow rate determined based on the predicted separation efficiency is greater than or equal to 1.2 times and less than or equal to 1.5 times the design flow rate, it is dynamically adjusted within this range; when the actual influent flow rate determined based on the predicted separation efficiency is greater than or equal to 1 time and less than 1.2 times the design flow rate, it is dynamically adjusted within this range; when the actual influent flow rate determined based on the predicted separation efficiency is greater than or equal to 0.8 times and less than 1 time... When the flow rate is greater than or equal to 0.8 times and less than 1 times the design flow rate, dynamic adjustments are made within this range until the actual total suspended solids concentration in the effluent does not exceed the preset first warning value, or reaches the adjustment limit of the corresponding flow range. For example, when adjusting between 1.2 times and less than or equal to 1.5 times the design flow rate, if the dynamic adjustment fails to ensure that the actual total suspended solids concentration in the effluent does not exceed the preset first warning value even at the upper and lower limits of 1.2 times and 1.5 times the design flow rate, it indicates that the water quality or quantity is fluctuating greatly and has far exceeded the processing capacity of the deep treatment system. In this case, considering the system's operational stability and operating costs, no further dynamic adjustments are made, and the water quality issue is addressed through subsequent measures.

[0120] Specifically, the preset first warning value can be determined based on the upper limit standard value of the total suspended solids concentration in the effluent. It can be set to 80%, 82%, 85%, 86%, 88%, 90%, 92%, 95%, 98%, 99% of the upper limit standard value of the total suspended solids concentration in the effluent, or other values ​​according to the actual situation. There are no specific restrictions. The upper limit standard value of the total suspended solids concentration in the effluent varies depending on different fields, regions, water quality, and wastewater treatment plants. It can be set according to the actual situation and there are no specific restrictions.

[0121] In some embodiments, the method further includes:

[0122] Obtain the actual influent flow rate and actual total phosphorus concentration of the biochemical treatment system at the front end of the deep treatment system to obtain actual influent water volume data and actual influent total phosphorus concentration data.

[0123] Based on the actual biochemical influent volume data and the actual biochemical influent total phosphorus concentration data, the influent flow rate and total phosphorus concentration of the deep treatment system are predicted using a pre-built second prediction model, thereby obtaining predicted influent flow rate data and predicted influent total phosphorus concentration data.

[0124] The amount of coagulant used in the mixing reaction unit 10 is calculated using the predicted influent flow rate data and the predicted total phosphorus concentration data, and the appropriate amount of coagulant is added to the mixing reaction unit 10.

[0125] Phosphorus is a major source of water pollution. Excessive phosphorus levels in water bodies can easily lead to eutrophication, drinking water source pollution, and can also cause problems such as clogged pipes and accelerated metal corrosion. Therefore, phosphorus removal is a crucial objective of wastewater treatment. Biological treatment processes primarily rely on polyphosphate-accumulating bacteria (PACs) for biological phosphorus removal. However, insufficient readily biodegradable carbon sources in the wastewater can affect phosphorus removal efficiency. Furthermore, biological phosphorus removal requires a relatively short sludge age (to prevent PACs from being eliminated by older PACs), while denitrification processes (such as nitrification) require a longer sludge age. Achieving a balance between these two factors can easily lead to a decrease in phosphorus uptake capacity. In addition, environmental sensitivity and fluctuations in influent water quality can also affect the phosphorus removal efficiency of biological treatment processes. Therefore, the effluent from existing biological treatment processes often contains high phosphorus levels, necessitating further phosphorus removal in advanced treatment processes.

[0126] In advanced treatment processes, coagulants, such as aluminum salts (e.g., aluminum sulfate), iron salts (e.g., ferric chloride), or lime, can react with phosphorus to form insoluble precipitates (e.g., aluminum phosphate, ferric phosphate). These precipitates then separate the solid and liquid phases, achieving phosphorus removal. Current technologies typically use current water quality and flow rates to calculate coagulant dosage. However, there is a time lag between collecting water quality and quantity data, calculating the dosage, and actually adding the coagulant. This results in a delay in coagulant addition; the actual water quality and quantity at the time of addition have changed from those used in the calculation. The coagulant dosage deviates from the actual requirements of the current water quality and flow rate. This deviation is particularly pronounced when the influent water quality and flow rate fluctuate significantly, leading to fluctuations in the total phosphorus concentration in the effluent and impacting wastewater treatment effectiveness and efficiency.

[0127] The actual influent flow rate and total phosphorus concentration of the biological treatment system are related to its effluent flow rate and total phosphorus concentration. When the influent flow rate and water quality fluctuate, the effluent will also fluctuate. The effluent from the biological treatment system is the influent to the advanced treatment system. Therefore, by using the actual influent flow rate and total phosphorus concentration of the biological treatment system, the influent flow rate and total phosphorus concentration of the advanced treatment system can be predicted, allowing for advance assessment of the influent conditions. Then, based on the predicted influent flow rate and total phosphorus concentration data, the coagulant dosage in the mixing reaction unit 10 can be calculated, thus enabling advance prediction of coagulant dosage. This allows sufficient time for coagulant preparation and delivery, and also better addresses fluctuations in water quality and quantity, thereby stabilizing the effluent and improving wastewater treatment efficiency.

[0128] The second prediction model can be constructed based on linear regression, random forest, or LSTM neural network, etc. Other algorithms and models capable of prediction can also be applied to this application, without any specific limitations. The second prediction model is trained based on historical data including the influent flow rate, influent total phosphorus concentration, effluent total phosphorus concentration, and effluent flow rate of the biochemical treatment system. Through training with a large amount of historical data, the second prediction model can learn the relationship between the effluent total phosphorus concentration, effluent flow rate, and effluent total phosphorus concentration and effluent volume in the biochemical treatment system, thereby realizing the prediction of effluent total phosphorus concentration and flow rate in practical applications, that is, the prediction of the influent flow rate and influent total phosphorus concentration of the advanced treatment system. In the construction of the second prediction model, the influent flow rate and total phosphorus concentration of the advanced treatment system can be predicted independently. That is, the influent flow rate of the advanced treatment system can be predicted independently using the influent flow rate of the biological treatment system, and the total phosphorus concentration of the influent of the advanced treatment system can be predicted independently using the influent total phosphorus concentration of the biological treatment system. Considering that the effluent total phosphorus concentration of the biological treatment system is also affected by the flow rate, a composite model can also be constructed. That is, when predicting the influent total phosphorus concentration and influent flow rate of the advanced treatment system, the mutual influence relationship between the influent total phosphorus concentration and influent flow rate of the biological treatment system is comprehensively considered, without any specific restrictions.

[0129] In some embodiments, calculating the amount of coagulant used in the mixing reaction unit 10 using the predicted influent flow rate data and the predicted influent total phosphorus concentration data includes:

[0130] Obtain the upper limit standard value of total phosphorus concentration in the effluent of the advanced treatment system;

[0131] The coagulant dosage ratio is calculated using the predicted influent total phosphorus concentration data and the upper limit standard value of the effluent total phosphorus concentration of the advanced treatment system.

[0132] The amount of coagulant used in the mixing reaction unit 10 is calculated using the dosage ratio and the predicted influent flow rate data.

[0133] The specific formula for calculating the dosage of coagulant is as follows:

[0134]

[0135] Among them, Dosage coag k is the dosage of coagulant. coag This refers to the dosage ratio of the coagulant. This refers to the predicted influent flow rate data for the deep processing system. The predicted total phosphorus concentration data for the influent of the advanced treatment system. is the upper limit standard value of total phosphorus concentration in effluent; k is the solid content in the coagulant.

[0136] The mixing unit includes a coagulation tank 11 and a flocculation tank 12 connected in sequence. Coagulant is added to the coagulation tank 11, and incoming water enters the coagulation tank 11 to react fully with the coagulant. Phosphorus in the wastewater reacts with the coagulant to form solid precipitates, which then enter the flocculation tank 12. The effluent from the flocculation tank 12 then enters the high-efficiency sedimentation tank 20 tangentially, forming a vortex within the high-efficiency sedimentation tank 20 to achieve solid-liquid separation, thereby removing phosphorus. While removing phosphorus, the coagulant also promotes the aggregation of colloidal particles to form flocs, further reducing TSS concentration and improving wastewater turbidity and color. A stirrer can also be installed in the coagulation tank 11, with the stirrer speed controlled at 80-120 r / min to ensure rapid mixing of the coagulant and raw water.

[0137] In some embodiments, the method further includes:

[0138] Obtain the total phosphorus concentration of the actual effluent from the deep treatment system to obtain the actual effluent total phosphorus concentration data.

[0139] In response to the actual effluent total phosphorus concentration data exceeding the preset second warning value, a correction coefficient is used to correct the coagulant dosage calculated based on the predicted influent flow rate data and the predicted influent total phosphorus concentration data, and the corrected dosage of coagulant is added to the mixing reaction unit 10.

[0140] The correction coefficient is determined based on the actual total phosphorus concentration data of the effluent and the preset second warning value.

[0141] The coagulant dosage is calculated based on the influent flow rate and total phosphorus concentration of the advanced treatment system predicted by the second prediction model. However, in actual operation, various factors such as the accuracy of the second prediction model, real-time data acquisition errors, and sensor errors can cause deviations between the predicted influent flow rate and total phosphorus concentration data and the actual data, resulting in a certain discrepancy between the coagulant dosage and the actual requirement. Therefore, while calculating the coagulant dosage using the predicted influent flow rate and total phosphorus concentration data, the actual total phosphorus concentration of the effluent from the advanced treatment system is monitored in real time. The actual effluent total phosphorus concentration is then used to correct the coagulant dosage, thereby further ensuring the efficient phosphorus removal of the advanced treatment system and thus ensuring stable effluent quality.

[0142] The correction factor is determined based on the actual effluent total phosphorus concentration data and the preset second warning value. Specifically, the correction factor is the ratio of the actual effluent total phosphorus concentration data to the preset second warning value. When the actual effluent total phosphorus concentration data exceeds the preset second warning value, the correction factor is multiplied by the coagulant dosage calculated based on the predicted influent flow rate data and the predicted influent total phosphorus concentration data to obtain the corrected coagulant dosage. Then, the corrected dosage of coagulant is added to the mixing reaction unit 10 (such as the coagulation tank 11) through an external dosing device to correct the coagulant dosage of the deep treatment system.

[0143] Specifically, the preset second warning value can be determined based on the upper limit standard value of total phosphorus concentration in effluent. It can be set to 80%, 82%, 85%, 86%, 88%, 90%, 92%, 95%, 98%, 99% of the upper limit standard value of total phosphorus concentration in effluent, or other values ​​according to actual conditions. There are no specific restrictions. The upper limit standard value of total phosphorus concentration in effluent varies depending on different fields, regions, water quality, and wastewater treatment plants. It can be set according to actual conditions, and there are no specific restrictions.

[0144] In some embodiments, a heavy medium is added to the deep processing system to improve the separation effect;

[0145] The advanced treatment system also includes a heavy media recovery device 30 connected to the bottom of the high-efficiency sedimentation tank 20, which is used to screen the mixed sludge in the high-efficiency sedimentation tank 20 to recover the heavy media, and to re-input the recovered heavy media into the mixing reaction unit 10.

[0146] The method further includes:

[0147] Obtain the total suspended solids concentration of the actual effluent from the deep treatment system to obtain the actual effluent total suspended solids concentration data.

[0148] In response to the actual effluent total suspended solids concentration data exceeding a preset first warning value, the heavy media recovery device 30 is activated, the recovery efficiency of the heavy media is monitored, and the operating parameters of the heavy media recovery device 30 are adjusted based on the recovery efficiency to ensure efficient recovery of the heavy media.

[0149] Heavy media refers to high-density solid particles that separate pollutants through density differences. Commonly used heavy media include microsand and magnetic powder. In advanced treatment processes, adding heavy media promotes pollutant sedimentation and improves solid-liquid separation efficiency. In the high-efficiency sedimentation tank 20, heavy media settles at the bottom with the flocs in the water. By adding a heavy media recovery device 30 to the side flow, the heavy media can be recovered and recycled. When the total suspended solids concentration in the actual effluent of the advanced treatment system exceeds the preset first warning value, it indicates that the separation efficiency in the high-efficiency sedimentation tank 20 has decreased. Continued operation may lead to excessive total suspended solids concentration in the effluent. At this time, the heavy media recovery device 30 is activated. The mixed sludge containing heavy media at the bottom of the high-efficiency sedimentation tank 20 is passed into the heavy media recovery device 30 for screening, separating the heavy media from the sludge and recovering the heavy media. The heavy media is then reintroduced into the mixing reaction unit 10 to promote pollutant sedimentation and solid-liquid separation, thereby improving the separation efficiency in the high-efficiency sedimentation tank 20 and improving effluent quality and wastewater treatment efficiency. Once the heavy media recovery device 30 is started, its recovery efficiency is monitored, and its operating parameters are adjusted based on this efficiency to ensure efficient recovery. By adjusting the operating parameters of the heavy media recovery device 30, its recovery efficiency can be improved. When the actual effluent total suspended solids concentration does not exceed the preset target value, the heavy media recovery device 30 can be shut down. The preset target value can be determined based on the upper limit standard value of the effluent total suspended solids concentration, and can be set to 50%, 52%, 55%, 58%, 60%, 62%, 65%, 68%, 70%, etc., or other values ​​depending on the actual situation; no specific restrictions apply.

[0150] In some embodiments, the heavy media recovery device 30 includes a feed inlet disposed on the side wall, an underflow outlet disposed at the bottom, and an overflow outlet disposed at the top; the feed inlet is connected to the bottom of the high-efficiency sedimentation tank 20, the underflow outlet is connected to the mixing reaction unit 10, and the overflow outlet is used to discharge the overflow product to the outside of the system.

[0151] The method of adjusting the operating parameters of the heavy medium recovery device 30 based on the recovery efficiency includes:

[0152] In response to the recovery efficiency being less than 50%, the diameter of the underflow outlet is adjusted to be greater than or equal to 0.3 times and less than or equal to 0.5 times the design diameter value;

[0153] In response to a recovery efficiency greater than or equal to 50% and less than or equal to 80%, the diameter of the underflow outlet is adjusted to be greater than 0.5 times and less than 0.8 times the design diameter value;

[0154] In response to the recovery efficiency being greater than 80%, the diameter of the underflow outlet is adjusted to be greater than or equal to 0.8 times and less than or equal to 1 times the design diameter value.

[0155] The heavy media recovery device 30 can be a hydrocyclone. A hydrocyclone is a high-efficiency separation device that utilizes centrifugal force for solid-liquid separation, particle classification, impurity removal, and sludge screening. The hydrocyclone uses centrifugal separation to separate the mixed sludge in the feed into different parts in a high-speed rotating flow field. The heavier media, with higher density, moves towards the periphery of the hydrocyclone under centrifugal force and is discharged through the lower outlet; the lighter sludge flocs move towards the center of the hydrocyclone under the action of internal swirling flow and are discharged through the top outlet, thus achieving the separation and recovery of the heavy media. In this application, the heavy media recovery device 30 includes an inlet on the side wall, a bottom outlet at the bottom, and an overflow outlet at the top. The mixed sludge at the bottom of the high-efficiency sedimentation tank 20 enters the interior of the heavy media recovery device 30 through the inlet. Under the action of centrifugal force, the heavy media settles to the bottom and flows out from the bottom outlet into the mixing reaction unit 10, while the lighter sludge flocs float to the top and are finally discharged through the overflow outlet.

[0156] In the heavy medium recovery device 30, the recovery efficiency of the heavy medium recovery device 30 is monitored, and the diameter of the underflow orifice is adjusted in real time based on the recovery efficiency. When the diameter of the underflow orifice is smaller, the underflow discharge is smaller, and the concentration of heavy medium in the underflow is higher. At the same time, when the flow rate of the underflow orifice is reduced, the residence time of the heavy medium in the hydrocyclone can be extended, which can enhance the centrifugal separation effect and thus improve the recovery efficiency of the heavy medium. Specifically, when the recovery efficiency is less than 50%, it indicates that the separation efficiency of the heavy medium and sludge is poor. Adjust the diameter of the underflow outlet to be greater than or equal to 0.3 times and less than or equal to 0.5 times the design diameter value, that is, control the diameter of the underflow outlet to the minimum to quickly improve the recovery efficiency. When the recovery efficiency is greater than or equal to 50% and less than or equal to 80%, adjust the diameter of the underflow outlet to be greater than 0.5 times and less than 0.8 times the design diameter value. When the recovery efficiency is greater than 80%, adjust the diameter of the underflow outlet to be greater than or equal to 0.8 times and less than or equal to 1 times the design diameter value, that is, adjust the diameter of the underflow outlet to be as close as possible to the design diameter value to ensure the long-term stable operation of the system.

[0157] In the design of the heavy media recovery device 30, a design diameter value for the underflow port is determined through theoretical calculations or empirical formulas based on its processing capacity, material characteristics, separation objectives, and operating parameters. Controlling the actual diameter of the underflow port to be smaller than the design diameter value can improve separation accuracy, increase underflow concentration, and extend particle residence time. However, long-term control of the actual diameter to be smaller than the design diameter value can easily lead to problems such as accelerated equipment wear, decreased throughput, and increased risk of blockage. Therefore, in this application, when the recovery efficiency of the heavy media recovery device 30 is significantly low, adjusting the actual diameter of the underflow port to be significantly smaller than the design diameter value can quickly improve the recovery efficiency of heavy media. Conversely, when the recovery efficiency of the heavy media recovery device 30 is high, i.e., it meets the current requirements, the diameter of the underflow port is controlled to be close to or directly equal to the design diameter value. This achieves a dynamic balance between efficient heavy media recovery, throughput, and equipment wear, ensuring efficient heavy media recovery without causing excessive wear on the heavy media recovery device 30.

[0158] This application improves recovery efficiency by adjusting the diameter of the underflow outlet. Compared to adjusting the diameter ratio of the overflow outlet to the underflow outlet, or simultaneously adjusting the diameters of both the overflow and underflow outlets, this method more directly reduces underflow discharge, forces more flocculent sludge into the overflow, rapidly increases the concentration and recovery rate of heavy media in the underflow, focuses more on improving the purity of the underflow products, and is more suitable for scenarios requiring high heavy media recovery rates. Simultaneously, the large density difference between heavy media and sludge makes them easier to separate. Adjusting only the diameter of the underflow outlet does not easily cause heavy media to overflow from the overflow outlet, thus increasing the heavy media concentration at the underflow outlet without causing loss. Furthermore, simultaneous changes in the overflow and underflow may introduce uncontrollable disturbances on the overflow side, while adjusting only the underflow outlet diameter reduces overflow-side interference, more accurately targeting the separation effect. In practical applications, this method is also easier to operate, has less impact on system stability, and significantly improves heavy media recovery efficiency.

[0159] In some embodiments, the formula for calculating the recovery efficiency is as follows:

[0160] R recovery =M recovered / M total

[0161] M recovered =C recovered ×Q O

[0162] M total =C total ×Q E

[0163] Among them, R recovery M represents the recovery efficiency. recoveredM represents the mass of the heavy medium flowing out of the underflow outlet. total C represents the total mass of the heavy media entering the heavy media recovery device 30. recovered C represents the concentration of the heavy medium in the effluent from the underflow outlet. total Q is the concentration of the heavy medium at the feed inlet. O Q is the flow rate of the overflow outlet. E The flow rate at the feed inlet is denoted as .

[0164] The recovery efficiency is calculated by monitoring parameters such as the mass and concentration of heavy medium at the underflow port, the concentration of heavy medium at the feed port, the feed flow rate, the overflow flow rate, and the total mass of heavy medium entering the heavy medium recovery device 30.

[0165] In some embodiments, the bottom of the high-efficiency sedimentation tank 20 is provided with a first sludge discharge port, which is connected to the feed inlet;

[0166] The high-efficiency sedimentation tank 20 has a second sludge discharge port located at a height of 1 / 5 to 1 / 3 from the first sludge discharge port on its side wall. The second sludge discharge port is connected to the outside of the system through a sludge discharge pipeline.

[0167] The method further includes:

[0168] Monitor the real-time sludge level height of the high-efficiency sedimentation tank 20;

[0169] In response to the real-time sludge level height being greater than a preset sludge level height threshold, the second sludge discharge port is opened to discharge a portion of the sludge in the high-efficiency sedimentation tank 20 to the outside of the system through the sludge discharge pipeline.

[0170] Heavy media generally have a higher density than sludge and will settle to the bottom of the high-efficiency sedimentation tank 20. Therefore, the bottom of the high-efficiency sedimentation tank 20 contains mixed sludge with a higher content of heavy media, and the content of heavy media increases further down the tank. Therefore, connecting the lower-positioned first sludge discharge port to the inlet of the heavy media recovery device 30 allows mixed sludge with a higher heavy media content to be fed into the heavy media recovery device 30 for heavy media recovery. In the advanced treatment system, sludge gradually accumulates at the bottom of the high-efficiency sedimentation tank 20, occupying the effective volume of the tank, leading to a shortened hydraulic retention time, decreased settling efficiency, and a tendency for effluent quality to deteriorate. It also easily leads to sludge decay and secondary pollution. Therefore, it is necessary to regularly or irregularly discharge sludge from the high-efficiency sedimentation tank 20. In this application, the second sludge discharge outlet is set at a height of 1 / 5 to 1 / 3 of the height from the first sludge discharge outlet. Since the heavy media has a high density and has largely settled, the sludge above this height is typically ordinary sludge containing no heavy media or with very low heavy media content. Setting the first sludge discharge outlet at this height effectively prevents the discharge of mixed sludge with high heavy media content from the system. This ensures efficient recovery of heavy media while also achieving effective sludge discharge from the high-efficiency sedimentation tank 20, thus ensuring wastewater treatment efficiency. First, a preset sludge level height threshold is set according to the actual situation of the deep treatment system. Then, the real-time sludge level height in the high-efficiency sedimentation tank 20 is monitored. When the real-time sludge level height exceeds the preset threshold, the second sludge discharge outlet is opened, discharging a portion of the sludge from the bottom of the high-efficiency sedimentation tank 20 to the outside of the system through the sludge discharge pipeline, ensuring the efficient and stable operation of the deep treatment system. Specifically, the second sludge discharge outlet can be set at a height of 1 / 5, 1 / 4, 4 / 15, or 1 / 3 of the height from the first sludge discharge outlet, or other height values ​​between 1 / 5 and 1 / 3; no specific limitation is imposed.

[0171] The high-efficiency sedimentation tank 20 can be a hydrocyclone, consisting of a cylindrical section and a conical section arranged vertically. A tangential inlet is located on the cylindrical section. The effluent from the flocculation tank 12 enters the high-efficiency sedimentation tank 20 at a certain pressure through the tangential inlet, generating a high-speed rotating vortex in the cylindrical section and forming a stable swirling field. Solid particles in the wastewater move downwards towards the conical section under centrifugal force, gradually contracting in the conical section, where the centrifugal force increases, accelerating the sedimentation of solid particles and achieving efficient solid-liquid separation. Guide channels, such as guide grooves, guide plates, and guide protrusions, can also be provided on the inner wall of the cylindrical section to further increase the wastewater rotation speed, thereby improving separation efficiency. Meanwhile, compared to ordinary sedimentation tanks, using hydrocyclones as high-efficiency sedimentation tanks20 results in a compact structure and a smaller footprint, typically 10%-30% of that of traditional sedimentation tanks, making them suitable for space-constrained scenarios (such as mines and factory workshops). Multiple hydrocyclones can be connected in parallel to flexibly expand the processing capacity without the need for large-scale civil engineering. They can quickly separate fine particles, shorten settling time, and achieve higher processing capacity.

[0172] This application provides a control method for an advanced wastewater treatment system. Firstly, it predicts the total suspended solids (TSS) concentration of the effluent using the actual influent TSS concentration of the advanced treatment system. Then, it calculates the predicted separation efficiency based on the predicted data and adjusts the actual influent flow rate of the high-efficiency sedimentation tank 20 accordingly. This increases the influent flow rate, thereby increasing the influent rotation speed and centrifugal force, promoting the separation of solid particles from water, rapidly improving the separation efficiency of the high-efficiency sedimentation tank 20, ensuring efficient solid-liquid separation, and improving effluent quality. Secondly, the dosage of coagulant is also a key factor in the wastewater treatment efficiency of the advanced treatment system. Using actual influent biochemical flow rate data and actual influent total phosphorus concentration data, a second prediction model predicts the influent flow rate and total phosphorus concentration of the advanced treatment system, enabling advance prediction of these parameters. This allows for the calculation of the coagulant dosage in advance based on the predicted data. When wastewater enters the advanced treatment system, the corresponding metered coagulant can be directly added, making the calculation and addition of coagulant more timely. This system better meets the current water quality and quantity requirements, thereby promoting better coagulation and settling of pollutants in wastewater, and further improving the separation efficiency of the high-efficiency sedimentation tank 20. Thirdly, it monitors the total phosphorus concentration and total suspended solids concentration of the actual effluent from the deep treatment system in real time, and corrects the coagulant dosage of the mixing reaction unit 10 and the actual influent flow rate of the high-efficiency sedimentation tank 20 based on the real-time monitoring data, reducing unavoidable errors caused by model accuracy and sensor data acquisition. Fourthly, it monitors the total suspended solids concentration of the actual effluent from the deep treatment system, promptly activates the heavy media recovery device 30 to recover heavy media, and calculates the recovery efficiency of the heavy media to adjust the underflow diameter of the heavy media recovery device 30, ensuring that the heavy media recovery device 30 always maintains a high recovery efficiency, allowing the heavy media to quickly flow back to the mixing reaction unit 10, promoting further sedimentation of suspended solids in the wastewater, and further improving the solid-liquid separation efficiency of the high-efficiency sedimentation tank 20. In this application, various factors affecting the separation efficiency of the high-efficiency sedimentation tank 20 are comprehensively considered. Through the design of controlling the actual influent flow rate of the high-efficiency sedimentation tank 20, controlling the underflow diameter of the heavy medium recovery device 30, predicting the amount of coagulant in advance, and using real-time monitoring data to correct the predicted data in a timely manner, the separation efficiency of the high-efficiency sedimentation tank 20 is comprehensively controlled to ensure that the separation efficiency of the high-efficiency sedimentation tank 20 is improved while maintaining the effluent quality meeting the standards and remaining stable.

[0173] Based on the same inventive concept, corresponding to the methods of any of the above embodiments, this application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement a deep processing system control method as described in any of the above embodiments.

[0174] Figure 3 This embodiment illustrates a more specific hardware structure of an electronic device, which may include a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, memory 1020, input / output interface 1030, and communication interface 1040 are interconnected internally via the bus 1050.

[0175] The processor 1010 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0176] The memory 1020 can be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 1020 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program code is stored in the memory 1020 and is called and executed by the processor 1010.

[0177] The input / output interface 1030 is used to connect input / output modules to realize information input and output. Input / output modules can be configured as components within the device (not shown in the figure) or externally connected to the device to provide corresponding functions. Input devices may include keyboards, mice, touchscreens, microphones, various sensors, etc., while output devices may include displays, speakers, vibrators, indicator lights, etc.

[0178] The communication interface 1040 is used to connect a communication module (not shown in the figure) to enable communication between this device and other devices. The communication module can communicate via wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0179] Bus 1050 includes a pathway for transmitting information between various components of the device, such as processor 1010, memory 1020, input / output interface 1030, and communication interface 1040.

[0180] It should be noted that although the above-described device only shows the processor 1010, memory 1020, input / output interface 1030, communication interface 1040, and bus 1050, in specific implementations, the device may also include other components necessary for normal operation. Furthermore, those skilled in the art will understand that the above-described device may only include the components necessary for implementing the embodiments of this specification, and not necessarily all the components shown in the figures.

[0181] The electronic devices described above are used to implement a corresponding deep processing system control method in any of the foregoing embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0182] Based on the same inventive concept, corresponding to the methods of any of the above embodiments, this application also provides a non-transitory computer-readable storage medium that stores computer instructions for causing the computer to execute a deep processing system control method as described in any of the above embodiments.

[0183] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device.

[0184] The computer instructions stored in the storage medium of the above embodiments are used to cause the computer to execute a deep processing system control method as described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0185] Based on the same concept, corresponding to any of the above embodiments, this application also provides a computer program product, including computer program instructions, which, when run on a computer, cause the computer to execute a deep processing system control method as described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0186] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of this application is limited to these examples; under the concept of this application, the technical features of the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations of different aspects of the embodiments of this application as described above, which are not provided in detail for the sake of brevity.

[0187] Furthermore, to simplify the description and discussion, and to avoid obscuring the embodiments of this application, the well-known power / ground connections to integrated circuit (IC) chips and other components may or may not be shown in the provided drawings. While specific details (e.g., circuits) have been set forth to describe exemplary embodiments of this application, it will be apparent to those skilled in the art that the embodiments of this application may be practiced without these specific details or with variations thereof. Therefore, these descriptions should be considered illustrative rather than restrictive.

[0188] Although this application has been described in conjunction with specific embodiments thereof, many substitutions, modifications, and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may be used with the embodiments discussed.

[0189] The embodiments of this application are intended to cover all such substitutions, modifications, and variations that fall within the broad scope of the claims of this application. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the embodiments of this application should be included within the protection scope of this application.

Claims

1. A control method for a deep processing system, characterized in that, The system is applied to an advanced treatment system, which includes a mixing reaction unit and a high-efficiency sedimentation tank connected in sequence. The effluent from the mixing reaction unit enters the high-efficiency sedimentation tank along the tangential direction to form a vortex within the high-efficiency sedimentation tank. The method includes: The total suspended solids concentration of the actual influent to the deep treatment system is obtained, and the actual total suspended solids concentration data of the influent is obtained. Based on the actual influent total suspended solids concentration data, the total suspended solids concentration of the effluent from the deep treatment system is predicted using a pre-built first prediction model, and the predicted effluent total suspended solids concentration data is obtained. The separation efficiency of the high-efficiency sedimentation tank is calculated based on the actual influent total suspended solids concentration data and the predicted effluent total suspended solids concentration data, and the predicted separation efficiency is obtained. The actual influent flow rate of the high-efficiency sedimentation tank is adjusted based on the predicted separation efficiency to ensure efficient separation in the high-efficiency sedimentation tank; The step of predicting the total suspended solids concentration in the effluent of the advanced treatment system using a pre-built first prediction model based on the actual influent total suspended solids concentration data, to obtain predicted effluent total suspended solids concentration data, includes: Based on the actual total suspended solids concentration data of the influent, the total suspended solids concentration of the effluent from the deep treatment system is predicted using a prediction sub-model trained based on historical data, thus obtaining the first prediction data. Based on the actual influent total suspended solids concentration data, the total suspended solids concentration of the effluent from the advanced treatment system is predicted using an expert model to obtain second prediction data. In response to the fact that the deviation between the first predicted data and the second predicted data is within a preset deviation threshold range, the average value of the first predicted data and the second predicted data is determined as the predicted total suspended solids concentration data of the effluent.

2. The control method for a deep processing system according to claim 1, characterized in that, Adjusting the actual influent flow rate of the high-efficiency sedimentation tank based on the predicted separation efficiency includes: In response to the predicted separation efficiency being less than 50%, the actual influent flow rate of the high-efficiency sedimentation tank is adjusted to be greater than or equal to 1.2 times and less than or equal to 1.5 times the design flow rate. In response to the predicted separation efficiency being greater than or equal to 50% and less than or equal to 80%, the actual influent flow rate of the high-efficiency sedimentation tank is adjusted to be greater than or equal to 1 and less than 1.2 times the design flow rate. In response to the predicted separation efficiency being greater than 80%, the actual influent flow rate of the high-efficiency sedimentation tank is adjusted to be greater than or equal to 0.8 times and less than 1 times the design flow rate. And / or, the predicted separation efficiency is calculated using the following formula: in, For the predicted separation efficiency, the The actual total suspended solids concentration data of the influent. The predicted total suspended solids concentration data for the effluent.

3. The deep processing system control method according to claim 2, characterized in that, The method further includes: Obtain the total suspended solids concentration of the actual effluent from the deep treatment system to obtain the actual effluent total suspended solids concentration data. In response to the actual effluent total suspended solids concentration exceeding a preset first warning value, the real-time influent flow rate of the high-efficiency sedimentation tank is dynamically adjusted within a flow range determined based on the predicted separation efficiency, until the actual effluent total suspended solids concentration does not exceed the preset first warning value or reaches the adjustment limit of the corresponding flow range.

4. The control method for a deep processing system according to claim 1, characterized in that, The method further includes: Obtain the actual influent flow rate and actual total phosphorus concentration of the biochemical treatment system at the front end of the deep treatment system to obtain actual influent water volume data and actual influent total phosphorus concentration data. Based on the actual biochemical influent volume data and the actual biochemical influent total phosphorus concentration data, the influent flow rate and total phosphorus concentration of the deep treatment system are predicted using a pre-built second prediction model, thereby obtaining predicted influent flow rate data and predicted influent total phosphorus concentration data. The amount of coagulant used in the mixing reaction unit is calculated using the predicted influent flow rate data and the predicted total phosphorus concentration data, and the appropriate amount of coagulant is added to the mixing reaction unit. The step of calculating the amount of coagulant used in the mixing reaction unit using the predicted influent flow rate data and the predicted influent total phosphorus concentration data includes: Obtain the upper limit standard value of total phosphorus concentration in the effluent of the advanced treatment system; The coagulant dosage ratio is calculated using the predicted influent total phosphorus concentration data and the upper limit standard value of the effluent total phosphorus concentration of the advanced treatment system. The amount of coagulant used in the mixing reaction unit is calculated using the dosage ratio and the predicted influent flow rate data.

5. The control method for a deep processing system according to claim 4, characterized in that, The method further includes: Obtain the total phosphorus concentration of the actual effluent from the deep treatment system to obtain the actual effluent total phosphorus concentration data. In response to the actual effluent total phosphorus concentration data exceeding the preset second warning value, a correction coefficient is used to correct the coagulant dosage calculated based on the predicted influent flow rate data and the predicted influent total phosphorus concentration data, and the corrected dosage of coagulant is added to the mixing reaction unit. The correction coefficient is determined based on the actual total phosphorus concentration data of the effluent and the preset second warning value; The correction factor is the ratio of the actual total phosphorus concentration in the effluent to the preset second warning value.

6. A control method for a deep processing system according to any one of claims 1 to 5, characterized in that, Heavy media are added to the deep processing system to improve the separation effect; The advanced treatment system also includes a heavy media recovery device connected to the bottom of the high-efficiency sedimentation tank, which is used to screen the mixed sludge in the high-efficiency sedimentation tank to recover the heavy media, and to re-input the recovered heavy media into the mixing reaction unit. The method further includes: Obtain the total suspended solids concentration of the actual effluent from the deep treatment system to obtain the actual effluent total suspended solids concentration data. In response to the actual effluent total suspended solids concentration data exceeding a preset first warning value, the heavy media recovery device is activated, the recovery efficiency of the heavy media is monitored, and the operating parameters of the heavy media recovery device are adjusted based on the recovery efficiency to ensure efficient recovery of the heavy media.

7. The control method for a deep processing system according to claim 6, characterized in that, The heavy media recovery device includes a feed inlet on the side wall, an underflow outlet at the bottom, and an overflow outlet at the top; the feed inlet is connected to the bottom of the high-efficiency sedimentation tank, the underflow outlet is connected to the mixing reaction unit, and the overflow outlet is used to discharge the overflow product to the outside of the system. The method of adjusting the operating parameters of the heavy medium recovery device based on the recovery efficiency includes: In response to the recovery efficiency being less than 50%, the diameter of the underflow outlet is adjusted to be greater than or equal to 0.3 times and less than or equal to 0.5 times the design diameter value; In response to a recovery efficiency greater than or equal to 50% and less than or equal to 80%, the diameter of the underflow outlet is adjusted to be greater than 0.5 times and less than 0.8 times the design diameter value; In response to the recovery efficiency being greater than 80%, the diameter of the underflow outlet is adjusted to be greater than or equal to 0.8 times and less than or equal to 1 times the design diameter value; The heavy medium recovery device includes a hydrocyclone.

8. The control method for a deep processing system according to claim 7, characterized in that, The bottom of the high-efficiency sedimentation tank is provided with a first sludge discharge port, which is connected to the feed inlet. A second sludge discharge port is provided on the side wall of the high-efficiency sedimentation tank at a height of 1 / 5 to 1 / 3 of the distance from the first sludge discharge port. The second sludge discharge port is connected to the outside of the system through a sludge discharge pipeline. The method further includes: Monitor the real-time sludge level in the high-efficiency sedimentation tank; In response to the real-time sludge level height being greater than a preset sludge level height threshold, the second sludge discharge port is opened to discharge a portion of the sludge in the high-efficiency sedimentation tank to the outside of the system through the sludge discharge pipeline.

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