Integrated efficient reaction clarification system based on multi-sensor data fusion

Abstract

The invention provides an integrated efficient reaction clarification system based on multi-sensor data fusion, and relates to the technical field of clarification systems. The self-adaptive sensing module is used for preprocessing the real-time operation parameters; the deep fusion processing module is used for generating trend pre-judgment data through the prediction model; the self-optimization control module is used for calculating and generating an initial equipment regulation and control instruction and optimizing the initial equipment regulation and control instruction; and the intelligent cooperative processing module is used for secondary optimization of the water quality regulation and control parameters. By means of the regression prediction model, risks are pre-judged in advance, and problem pre-prevention and control are achieved; through parameter adaptation, secondary optimization and accurate instruction transmission according to functional areas, all devices are pushed to operate cooperatively, the operation stability of the devices and the rationality of medicament consumption are effectively improved, manual intervention is greatly reduced, and the intelligence, high efficiency and reliability of industrial wastewater treatment are comprehensively enhanced.

Description

Technical Field

[0001] This invention relates to the field of clarification system technology, and in particular to an integrated, high-efficiency reaction clarification system based on multi-sensor data fusion. Background Technology

[0002] With the expansion of industrial production scale and the continuous tightening of environmental regulations on wastewater discharge requirements, industrial wastewater containing fluoride and multiple pollutants generated by industries such as chemical, electronics, and metallurgy needs to be treated by professional systems to achieve compliant discharge. As the core unit in the industrial wastewater treatment process, the clarification system undertakes key functions such as reaction, flocculation, and solid-liquid separation.

[0003] In typical clarification systems, the treatment processes are often fragmented, with pretreatment lacking fine-grained hierarchical connections with subsequent main reactions, flocculation, and sedimentation, making it difficult to achieve seamless and efficient treatment throughout the entire process. Furthermore, the lack of effective predictive mechanisms means that testing can only be conducted post-incidentally, failing to anticipate risks and intervene in a timely manner, easily leading to fluctuations in effluent quality or even failure to meet standards. Simultaneously, the reliance on extensive manual intervention is not only inefficient but also prone to fluctuations in treatment effectiveness due to human error, making it difficult to balance stable effluent quality with economic efficiency in the treatment process.

[0004] To address the shortcomings of the existing technologies, this technical solution proposes an integrated and efficient reaction clarification system based on multi-sensor data fusion. Summary of the Invention

[0005] This invention provides an integrated and efficient reaction clarification system based on multi-sensor data fusion to address the shortcomings of existing technologies.

[0006] On the one hand, the present invention provides an integrated and efficient reaction clarification system based on multi-sensor data fusion, comprising: The main clarification equipment is used for the graded treatment of industrial wastewater, including main reaction, flocculation reaction, sludge sedimentation, and clear water separation. It generates real-time operating parameters and receives external water quality control commands. The adaptive sensing module is used to preprocess real-time operating parameters and convert them into standardized sensing data in a unified format. The deep fusion processing module is used to perform fusion analysis on standardized sensor data, establish multiple correlations, extract key features, and generate predictive data on the risk of fluoride ion exceeding the standard and the trend of sludge concentration fluctuation through a predictive model. The self-optimizing control module is used to calculate and generate initial equipment control commands based on trend prediction data and through a multi-objective collaborative control algorithm, optimize the initial equipment control commands, and output equipment control commands. The intelligent collaborative processing module is used to parse the control parameters in the equipment control instructions, convert the control parameters into suitable water quality control parameters according to the functional area characteristics of the main clarification equipment, perform secondary optimization of the water quality control parameters, and output the optimized water quality control instructions to the main clarification equipment.

[0007] The integrated high-efficiency reaction clarification system based on multi-sensor data fusion provided by the present invention includes a pretreatment and grading unit, a real-time parameter acquisition unit, an instruction execution unit, and a status feedback unit. The pretreatment and grading unit is used to perform preliminary filtration and graded sedimentation treatment on the raw water, and to perform secondary grading treatment through the main reaction zone, flocculation reaction zone, sludge settling zone, and clear water zone. The real-time parameter acquisition unit is used to monitor the real-time operating parameters of the equipment. The instruction execution unit is used to receive and execute externally input water quality control instructions and output equipment status information. The status feedback unit is used to transmit the equipment status information to the adaptive sensing module.

[0008] According to the integrated high-efficiency reaction clarification system based on multi-sensor data fusion provided by the present invention, the pretreatment and grading unit performs grading treatment on raw water, including the following steps: Production wastewater enters the equalization tank through the collection pipeline network. The water quality and quantity are homogenized by hydraulic stirring in the tank. The homogenized raw water is then transported to the first reactor of the pretreatment section by the wastewater lift pump. In the first reactor, lime slurry is added to the homogenized raw water according to the preset logic through the PT-type automatic dosing device of the integrated dosing system. The stirring device is turned on to fully mix the lime slurry with the raw water and to precisely adjust the pH value of the reaction system to 8.5-9 to obtain the initial mixed solution. The initial mixture is transported to the second reaction tank, where a coagulant is added through a dosing system. The stirring speed is maintained to allow the coagulant to fully react with the water, forming initial micro-flocculations and obtaining flocculated water. The flocculated water is sent into the primary settling tank, the strong stirring device is turned off, and the water is switched to a stable and static state. Solid-liquid separation is achieved by gravity settling. The precipitated sludge is temporarily stored at the bottom of the settling tank, and the supernatant flows by gravity to the first-stage reaction zone of the biological defluoridation agent.

[0009] According to the integrated high-efficiency reaction clarification system based on multi-sensor data fusion provided by the present invention, the adaptive sensing module includes a data cleaning unit and a data standardization unit; the data cleaning unit is used to remove outliers and noise from real-time operating parameters and output primary processing parameters; the data standardization unit is used to convert the primary processing parameters into standardized sensor data in a unified format.

[0010] The integrated high-efficiency reaction clarification system based on multi-sensor data fusion provided by the present invention includes the following steps in which the data cleaning unit outputs primary processing parameters: Identify outliers and noise in real-time operating parameters, including instantaneous fluctuation data from the fluoride ion online monitor, sudden jumps in pH sensor data, and abnormal flow data from the dosing pump. For the instantaneous fluctuation data of the fluoride ion online monitoring instrument, the moving average smoothing filter method is used for processing; for the sudden jump data of the pH sensor, the threshold elimination + historical mean completion method is used for processing; for the abnormal flow data of the dosing pump, the average dosage of similar equipment is used for temporary completion, and the fault is marked for investigation. The processed real-time operating parameters are organized in a fixed format and output to the data standardization unit.

[0011] The integrated high-efficiency reaction clarification system based on multi-sensor data fusion provided by the present invention includes a deep fusion processing module comprising a multi-source data association unit, a feature extraction unit, a fusion execution unit, and a trend prediction unit. The multi-source data association unit is used to establish the association relationship between different types of standardized sensor data. The feature extraction unit is used to extract key feature information from the standardized sensor data. The fusion execution unit is used to perform fusion analysis on the feature information based on the association relationship and output the processing results including water quality compliance status, rationality of reagent consumption, and equipment operation stability. The trend prediction unit is used to generate trend prediction data based on the processing results and historical data through a regression prediction model.

[0012] According to the integrated high-efficiency reaction clarification system based on multi-sensor data fusion provided by the present invention, the step of the trend prediction unit generating trend prediction data through a regression prediction model includes: Retrieve historical data from the database that matches the current wastewater type and fusion results; A linear regression prediction model and a time series analysis model are used to predict future trends and output the prediction results. If the prediction result is F - The concentration will increase from the first concentration to the second concentration, generating F. - Data for predicting risks of exceeding standards; if it is predicted that the sludge solids content will drop from the first solids content to the second solids content, data for predicting risks of insufficient sludge thickening will be generated; if it is predicted that the dosage of JLT-005 will be less than the preset dosage threshold, data for predicting early warning of insufficient reagent dosage will be generated.

[0013] The integrated high-efficiency reaction clarification system based on multi-sensor data fusion provided by the present invention includes a self-optimizing control module comprising a target parameter setting unit, an algorithm selection unit, an instruction calculation unit, and an instruction optimization unit. The target parameter setting unit is used to set multiple target parameters including quality treatment effect, energy consumption, and efficiency. The algorithm selection unit is used to select an appropriate multi-objective collaborative control algorithm based on the processing results and trend prediction data. The instruction calculation unit is used to calculate and generate initial equipment control instructions through the multi-objective collaborative control algorithm. The instruction optimization unit is used to optimize the initial equipment control instructions and output the equipment control instructions.

[0014] The integrated high-efficiency reaction clarification system based on multi-sensor data fusion provided by the present invention includes an intelligent collaborative processing module comprising a parameter parsing unit, a parameter adaptation unit, a parameter optimization unit, and an instruction output unit. The parameter parsing unit is used to parse the control parameters in the equipment control instructions; the parameter adaptation unit is used to convert the control parameters into suitable water quality control parameters according to the characteristics of the clarification main equipment; the parameter optimization unit is used to perform secondary optimization on the water quality control parameters to obtain optimized water quality control instructions; and the instruction output unit is used to transmit the optimized water quality control instructions to the instruction execution unit of the clarification main equipment.

[0015] According to the integrated high-efficiency reaction clarification system based on multi-sensor data fusion provided by the present invention, the transmission strategy of the instruction output unit for transmitting optimized water quality control instructions to the instruction execution unit of the clarification main equipment includes: transmitting instructions from the pretreatment section to the dosing pumps and stirring motors of the first and second reactors of the pretreatment grading unit; transmitting instructions from the main reaction zone to the JLT-005 dosing pumps and stirring motors of the first and second stage primary reaction zones; transmitting instructions from the flocculation zone to the PAM dosing pump and T3 tank stirring motor of the tertiary reaction tank; transmitting instructions from the sedimentation zone to the sludge return pump, sludge discharge pump, and sludge scraper; and transmitting instructions from the clear water zone to the solenoid valve linked to the online fluoride ion monitoring instrument in the clear water zone.

[0016] This invention provides an integrated, high-efficiency reaction clarification system based on multi-sensor data fusion. Through pretreatment and secondary grading of the main clarification equipment, along with real-time parameter acquisition and feedback, it achieves refined treatment of industrial wastewater throughout the entire process. The system relies on an adaptive sensing module for abnormal data cleaning and standardization, ensuring the reliability of sensor data. Utilizing a deep fusion processing module's multi-source data association, feature extraction, and regression prediction model, it can predict risks such as excessive fluoride ions and insufficient sludge concentration in advance, enabling proactive problem prevention. Through a self-optimizing control module's multi-objective collaborative control algorithm, it balances energy consumption and efficiency while ensuring water quality compliance, generating optimized equipment control commands. Furthermore, the intelligent collaborative processing module's parameter adaptation, secondary optimization, and precise command transmission across functional zones promote the coordinated operation of various devices, effectively improving equipment stability and the rationality of reagent consumption, significantly reducing manual intervention, and comprehensively enhancing the intelligence, efficiency, and reliability of industrial wastewater treatment. This ensures an economical treatment process and consistently compliant effluent quality. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of the integrated high-efficiency reaction clarification system based on multi-sensor data fusion provided in Embodiment 1 of the present invention; Figure 2 This is a flowchart of the pretreatment grading unit for grading raw water according to Embodiment 1 of the present invention; Figure 3 This is a process flow diagram of the integrated high-efficiency reaction clarification system based on multi-sensor data fusion provided in Embodiment 1 of the present invention; Figure 4 This is a schematic diagram of the magnetic coagulation process provided in Embodiment 2 of the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0020] Example 1: The following is combined with Figures 1-4This invention describes an integrated, high-efficiency reaction clarification system based on multi-sensor data fusion.

[0021] like Figures 1-3 As shown in the figure, the integrated high-efficiency reaction clarification system based on multi-sensor data fusion provided in this embodiment of the invention includes: a clarification main device, an adaptive sensing module, a deep fusion processing module, a self-optimizing control module, and an intelligent collaborative processing module.

[0022] The main clarification equipment is used for the treatment of fluorine-containing (F) - Industrial wastewater containing suspended solids (SS), heavy metals (Tl, Pb, Zn, Cd, As, Cu, etc.), COD, phosphorus (P), and hardness undergoes a graded treatment process involving main reaction, flocculation reaction, sludge settling, and clear water separation to produce a solution containing water quality indicators (F). - The system monitors real-time operating parameters, including concentration, suspended solids (SS) content, heavy metal concentration, etc., equipment operating parameters (pH value, stirring speed, upward flow velocity, sludge solids content), and reagent dosing parameters, and receives external water quality control commands.

[0023] The main clarification equipment includes a pretreatment grading unit, a real-time parameter acquisition unit, a command execution unit, and a status feedback unit. The pretreatment grading unit adjusts the pH of the raw water to 8.5-9 by adding lime slurry, performing preliminary filtration and grading sedimentation, which then connects to the main reaction zone (dosing of biological agent JLT-005), the flocculation reaction zone (dosing of PAM), the sludge settling zone (equipped with a patented high-efficiency thickening and scraping machine), and the clear water zone for further grading treatment. The real-time parameter acquisition unit monitors the equipment's real-time operating parameters, including F ion concentrations collected by the online fluoride ion monitor. - The system includes the following parameters: concentration, suspended solids content collected by the SS sensor, Tl / Pb / Zn concentration collected by the heavy metal detector, pH value of the reaction system collected by the pH sensor, stirring speed collected by the speed sensor, and sludge solids content collected by the concentration meter. The instruction execution unit receives and executes externally input water quality control instructions, including the start / stop and parameter adjustment of the dosing pump (controlling lime slurry, JLT-005, and PAM dosing), sludge pump (controlling sludge transport and discharge), solenoid valve (controlling the return of supernatant exceeding standards), and sludge scraper (controlling sludge thickening and transport), and outputs equipment operating status information. The status feedback unit transmits equipment status information (such as the operating frequency of the dosing pump, the working status of the sludge scraper, the compliance status of effluent water quality, and sludge solids content) to the adaptive sensing module.

[0024] Specifically, the pretreatment and grading unit performs grading treatment on raw water, including the following steps: The production wastewater enters the equalization tank through the collection pipeline network. The water quality and quantity are homogenized by hydraulic stirring in the tank (eliminating the impact of fluctuations in the influent load). Then, the homogenized raw water is transported to the first reactor of the pretreatment section by the wastewater lift pump.

[0025] In the first reactor, lime slurry is added according to the "water quality monitoring - dosage matching" logic through the PT-type automatic dosing device of the integrated dosing system (lime slurry is output from the solution tank of the three-chamber dosing tank). The stirring device is turned on (refer to the T1 / T2 tank speed of 250r / min) to make the lime slurry fully mixed with the raw water and to precisely adjust the pH value of the reaction system to 8.5-9.

[0026] The pH-adjusted water is transported to the second reaction tank, where a coagulant (such as PAC) is added through a dosing system. The stirring device is kept at a speed of 250 r / min to allow the coagulant to fully react with the water, breaking down the stability of colloidal particles and forming initial micro-flocs.

[0027] The water that has completed the flocculation reaction is sent to the primary settling tank. The strong stirring device is turned off and the water is switched to a stable and static state (to avoid disturbing the flocs). Solid-liquid separation is achieved by gravity settling. The settled sludge is temporarily stored at the bottom of the settling tank (to be sent to the sludge thickening tank later). The supernatant flows by gravity to the first-stage reaction zone of the biological defluoridation agent.

[0028] The real-time parameter acquisition unit monitors the real-time operating parameters of the equipment in the following ways: Fluoride ion concentration: An online fluoride ion monitoring device is installed in the clear water tank to collect real-time fluoride ion concentration data in the effluent. - Concentration, data sampling intervals should be no less than 5 minutes (to ensure timely detection of exceedances).

[0029] SS content: SS sensors are installed at the outlet of the supernatant of the primary sedimentation tank and the outlet of the secondary defluorination sedimentation tank to collect the suspended solids content in real time.

[0030] Heavy metal concentration: Heavy metal detectors (for Tl, Pb, Zn, Cd, As, Cu, etc.) were installed after the first stage of biological defluorination reaction and after the second stage of defluorination reaction to collect heavy metal concentrations.

[0031] Water quality after chemical reaction: A pH sensor was installed in the main reaction zone (after adding JLT-005) to collect the pH value of the reaction system in real time (monitoring the stability in the 8.5-9 range).

[0032] Equipment operating parameter acquisition methods include: Stirring speed: Speed ​​sensors are installed on the stirring motors in the T1 / T2 mixing tank (250 r / min), T3 mixing tank (70-80 r / min), and the main reaction zone to collect the stirring speed in real time. The mixing tanks are generally divided into three tanks, referred to as T1, T2, and T3 mixing tanks. The T1 mixing tank is used to add defluoridating agents, PAC, and other coagulants, and rapid stirring is used to quickly mix them with the influent. The stirrer speed is generally 250 r / min. The T3 mixing tank is used for adding and mixing flocculants, better promoting the sedimentation of magnetic powder and insoluble substances in the water. Slow stirring should be used in this tank, generally set at 70-80 r / min. Rapid stirring will break up the flocs, leading to flocculation failure.

[0033] Upward velocity: Install a flow meter in the sludge settling zone to collect the upward velocity of the water body (matching the characteristics of the "ultra-high upward velocity" equipment).

[0034] Sludge scraper status: An operating status sensor is installed on the patented high-efficiency thickening sludge scraper to collect the scraping frequency and scraper movement speed (to ensure continuous sludge delivery).

[0035] The collection of chemical dosing parameters includes: collecting the dosing flow rates of lime slurry, biological agent JLT-005, and PAM using the flow meter of the PT-type automatic dosing device, and converting these flow rates into dosages (e.g., controlling JLT-005 at 25-30 mg / L and PAM at 0.5-1 mg / L). A pressure sensor is installed at the outlet of the dosing pump to collect the chemical delivery pressure, ensuring dosing stability.

[0036] Sludge parameter acquisition: Install sludge concentration meters in the sludge settling zone and sludge thickening tank to collect sludge solids content in real time and ensure it is within the range of 3%-7%.

[0037] The adaptive sensing module is used to preprocess real-time operating parameters for outliers (such as fluctuations in fluoride ion monitoring, pH changes, and abnormal dosage of chemicals) and noise removal, and to convert water quality indicators, equipment operating parameters, and chemical dosage parameters into standardized sensor data in a unified format.

[0038] The adaptive sensing module includes a data cleaning unit and a data standardization unit. The data cleaning unit removes outliers and noise from real-time operating parameters, including instantaneous fluctuations in fluoride ion monitoring data, sudden pH jumps, and abnormal flow rates from the chemical dosing pump. It outputs primary processing parameters through smoothing filtering and threshold removal. The data standardization unit converts these primary processing parameters into standardized sensor data in a unified format, with unified dimensions including water quality indicators (F...). -Concentration units: mg / L, SS content units: mg / L, heavy metal concentration units: mg / L), equipment operating parameters (pH value: no unit, stirring speed units: r / min, upward flow velocity units: m / h, sludge solids content units: %), reagent parameters (JLT-005 dosage units: mg / L, PAM dosage units: mg / L, lime slurry dosage units: mg / L).

[0039] The data cleaning unit identifies abnormal data in the following ways: It identifies instantaneous fluctuations in fluoride ion online monitoring data, such as concentration changes >5 mg / L within 1 minute, exceeding the normal reaction fluctuation range. It identifies sudden jumps in pH sensor data, such as pH changes >1 within 30 seconds, which does not conform to the gradual adjustment characteristics of lime slurry. It identifies abnormal dosing pump flow data, such as the dosage suddenly exceeding the normal range of 25-30 mg / L (JLT-005) or 0.5-1 mg / L (PAM). It identifies sudden changes in stirring speed, such as the T3 tank speed suddenly exceeding 80 r / min or <70 r / min.

[0040] The steps for handling abnormal data include: for instantaneous fluctuations in water quality indicators such as fluoride ions and suspended solids (SS), a "moving average smoothing filter" method is used (the average of three adjacent data points within a 5-minute period is used to replace outliers). For jumps in pH and rotation speed, a "threshold removal + historical average completion" method is used (jumps in values ​​exceeding the normal range are removed, and the average data from the previous 10 minutes is used to complete the data). If the dosing pump flow rate is 0 (indicating a fault), the average dosage of similar equipment is used to temporarily complete the data, and the system is marked as "fault pending investigation." The treated water quality indicators, equipment operating parameters, and chemical dosing parameters are organized in a "timestamp + parameter type" format and output to the data standardization unit.

[0041] The data standardization unit converts primary processing parameters into standardized sensor data in a unified format through the following steps: Primary treatment parameters are divided into three main categories: water quality indicators, equipment operation parameters, and chemical dosing parameters. The water quality indicator category includes F... -Concentration, SS content, heavy metal (Tl / Pb / Zn, etc.) concentration, COD, P concentration, hardness. Equipment operation includes pH value, stirring speed, upward flow velocity, sludge solids content, and scraper frequency. Chemical dosing includes lime slurry dosage, JLT-005 dosage, PAM dosage, and magnetic powder dosage (for magnetic coagulation processes). Unit conversion is standardized as follows: water quality indicators are uniformly converted to "mg / L" (e.g., heavy metal concentration is converted from "μg / L" to "mg / L", 1mg / L = 1000μg / L). Equipment operation: pH value remains unitless, stirring speed is uniformly "r / min", upward flow velocity is uniformly "m / h", and sludge solids content is uniformly "%". Chemical dosing is uniformly converted to "mg / L" (e.g., lime slurry dosage is converted from "L / h" combined with influent flow rate to "mg / L").

[0042] Finally, standardized sensor data is generated in a fixed format of "timestamp (YYYY-MM-DDHH:MM:SS) + parameter name + unified unit + value" and transmitted to the deep fusion processing module.

[0043] The deep fusion processing module is used to perform fusion analysis on standardized sensor data, establish the correlation between pH and fluoride ion removal rate, biological agent dosage and heavy metal removal effect, and sludge concentration and settling velocity, extract key features such as fluoride ion compliance status, sludge solids content (3%-7%), and reagent reaction efficiency, and output the treatment results using a fusion algorithm adapted to different wastewater types (fluoride and phosphorus wastewater, organic wastewater, and high-hardness wastewater). Based on the treatment results and historical effluent compliance rate and reagent consumption curve, the module generates predictive data on the risk of fluoride ion exceeding the standard and the trend of sludge concentration fluctuation through a predictive model.

[0044] The deep fusion processing module includes a multi-source data association unit, a feature extraction unit, a fusion execution unit, and a trend prediction unit. The multi-source data association unit is used to establish correlations between different types of standardized sensor data, specifically: the pH value of the main reaction zone and F... - Correlation of removal rate, statistical analysis of F within the "pH=8.5-9" range. - Removal rate (core parameter of the file), establish "pH value → F - A linear correlation model for "removal rate" (e.g., for every 0.1 decrease in pH, F...). -The removal rate decreased by 2%. The correlation between JLT-005 dosage and the removal efficiency of heavy metals (such as Ti and Pb) was investigated. The removal rate of heavy metals (such as Ti) within the range of "JLT-005 = 25-30 mg / L" was statistically analyzed, and a correlation model of "dosage → removal rate" was established (e.g., for every 1 mg / L increase in dosage, the Ti removal rate increased by 1.5%). The correlation between sludge solids content and the treatment efficiency of the settling zone was investigated. The settling velocity within the range of "sludge solids content 3%-7%" was statistically analyzed, and a correlation model of "solids content → settling velocity" was established (e.g., for every 1% increase in solids content, the settling velocity increased by 0.2 m / h). The correlation between PAM dosage and floc formation state was investigated. The floc particle size within the range of "PAM = 0.5-1 mg / L" was statistically analyzed, and a correlation model of "dosage → floc particle size" was established (e.g., at a dosage of 0.8 mg / L, the floc particle size was the largest, and the settling effect was optimal).

[0045] The feature extraction unit is used to extract key feature information from standardized sensor data, including effluent F. - Whether the concentration meets the standard (complies with emission standards) is compared with real-time F. - Based on the concentration and the document's "Relevant Pollutant Emission Standards," extract the "compliant (≤ standard value) / exceeding (> standard value)" characteristics. Also consider whether the sludge solids content is within the 3%-7% range and the reagent reaction efficiency (e.g., JLT-005's effect on F). - The removal rate is ≥95%, and the stirring speed matches the reaction requirements (250 r / min for T1 / T2 tanks, 70-80 r / min for T3 tank). For the magnetic coagulation process, the characteristic of "magnetic powder flocculation rate (≥95% is qualified)" is extracted.

[0046] Calculate JLT-005 against F - Removal rate (influent F) - Concentration - Effluent F - Concentration) / Influent F - (Concentration × 100%), extract the characteristics of "high efficiency (≥95%) / low efficiency (<95%)".

[0047] Among them, F - The removal rate is calculated as follows:

[0048] In the formula, For F - The removal rate was used to measure the difference between the biological agent JLT-005 and F in the wastewater. - The effect of the complexation reaction is the core indicator for judging the defluorination ability of a drug. For water inlet F - The concentration, i.e. the fluoride content of the wastewater before entering the JLT-005 reaction zone, is the initial baseline value for the defluorination process. For water outlet F -Concentration, which is the fluoride content of the wastewater after reaction with JLT-005, flocculation and sedimentation, is the final effect value of the defluorination process.

[0049] Calculate the floc formation efficiency of PAM (floc particle size ≥ 0.5 mm is considered effective), and extract the "effective / ineffective" feature. The formula for calculating floc formation efficiency is expressed as:

[0050] In the formula, η PAM For floc formation efficiency, η PAM Extract "effective" features when ≥80% are achieved, η PAM When the percentage is less than 80%, the "invalid" feature is extracted. N0 is the number of effective flocs with a particle size ≥ 0.5 mm, that is, the number of flocs that meet the "accelerated sedimentation" requirement. N1 is the total number of flocs, that is, the total amount of all flocs (including effective flocs and invalid flocs with a particle size < 0.5 mm) within the monitoring range.

[0051] Calculate the pH adjustment efficiency of lime slurry (effective if the adjusted pH is between 8.5 and 9), and extract the "effective / ineffective" characteristic. The formula is expressed as:

[0052] Where, η SH η represents the pH adjustment efficiency of lime slurry. SH When ≥90% of the features are extracted as “effective” features, η SH When the percentage is less than 90%, "invalid" features are extracted. pH T represents the number of times the pH remained in the 8.5-9 range after adjustment. pH1 This represents the total number of pH adjustments.

[0053] The methods for extracting equipment operational stability features are as follows: Analyzing the fluctuation of stirring speed (stable within ±5 r / min), extracting the "stable / fluctuating" feature. Analyzing the fluctuation of sludge solids content (stable within ±0.5%), extracting the "stable / fluctuating" feature. Analyzing the sludge scraper's operating status (continuous uninterrupted conveying is normal), extracting the "normal / fault" feature.

[0054] Finally, the extracted "compliance characteristics + efficiency characteristics + stability characteristics" are sorted by "priority" (water quality compliance > reagent efficiency > equipment stability) and output to the fusion execution unit.

[0055] The fusion execution unit is used to perform fusion analysis on feature information based on correlation. Specifically, it uses different treatment methods for different treatment modules of fluoride-phosphorus wastewater, organic wastewater, and high-hardness wastewater, and outputs processing results including water quality compliance status, rationality of reagent consumption, and equipment operation stability.

[0056] The treatment process for fluoride- and phosphorus-containing wastewater is as follows: Fluorine- and phosphorus-containing wastewater is fed into the first reactor of the pretreatment section. Lime slurry is added through a PT-type automatic dosing device, and the mixture is stirred to adjust the pH of the wastewater to 8.5-9, creating a suitable reaction environment for subsequent biological agent defluorination.

[0057] The pretreated wastewater flows by gravity into the primary reaction zone of the biological defluoridation agent. Biological agent JLT-005 is added, and the stirring device is turned on to ensure full contact between the agent and the wastewater. JLT-005 reacts with fluoride... - The combined reaction removes some fluoride ions. It then enters the secondary reaction tank, where the pH value of the system is adjusted according to the actual operating conditions of the wastewater, and then enters the tertiary reaction tank where PAM (cationic type, dosage reference 0.5-1 mg / L) is added to form fluoride-containing flocs.

[0058] Fluorine-containing flocs enter the sedimentation tank, where solid-liquid separation is achieved using the sludge settling function of the integrated high-efficiency reaction clarification equipment. The supernatant then enters the second-stage defluorination process.

[0059] The supernatant after separation enters the first-stage reaction zone of the second-stage biological defluorination agent, where biological agent JLT-005 is added again, and the "co-reaction-pH adjustment-PAM flocculation" steps are repeated to further remove fluoride ions.

[0060] After the second stage of flocculation, the wastewater enters the sedimentation tank for secondary solid-liquid separation. The supernatant is filtered through a precision filter and then enters the clear water tank. The clear water tank is equipped with an online fluoride ion monitor. If the fluoride ion level exceeds the standard, the wastewater is switched back to the equalization tank for retreatment via a solenoid valve and discharged only after meeting the standards.

[0061] The organic wastewater treatment process is as follows: Organic wastewater first enters the pretreatment stage, where it is homogenized by hydraulic stirring and heavy metal hydrolysis is completed, thus initially removing some heavy metal ions from the water.

[0062] The hydrolyzed organic wastewater is sent to a heterogeneous catalytic oxidation reaction unit. Using the "heterogeneous catalytic oxidation technology" mentioned in the document, the chemical structure of organic pollutants in the wastewater is destroyed, the COD concentration is reduced, and the biodegradability of the wastewater is improved.

[0063] Wastewater after multiphase catalytic oxidation enters the flocculation reaction zone, where coagulants (such as PAC) and flocculants (PAM) are added, and the stirring device is turned on to allow organic pollutants, oxidation products and reagents to combine and form larger flocs.

[0064] Wastewater containing flocculent material enters the sludge settling zone of the integrated high-efficiency reaction clarification equipment. Solid-liquid separation is achieved through the equipment's "high-efficiency clarification" function. The supernatant is reused or discharged after meeting the standards, and the settled sludge is temporarily stored in the sludge thickening tank. Subsequently, it is dewatered by a filter press, and the filtrate is returned to the equalization tank.

[0065] The process for treating high-hardness wastewater is as follows: High-hardness wastewater enters the pretreatment unit, where it first undergoes a heavy metal hydrolysis reaction, and then passes through a "decalcification treatment" stage to remove excess calcium and magnesium ions from the wastewater and reduce its hardness.

[0066] After decalcification, the wastewater enters the biological agent reaction zone, where biological agent JLT-005 is added. The stirring device is then turned on to allow the agent to fully react with the residual pollutants (such as heavy metals and some hardness substances) in the wastewater, forming a stable complex.

[0067] After the reaction, the wastewater enters the flocculation reaction zone where PAM is added to form larger flocs. It then enters the clear water zone and sludge settling zone of the integrated high-efficiency reaction clarification equipment to achieve solid-liquid separation and reduce the hardness and pollutant content of the wastewater.

[0068] The sludge produced by separation enters the sludge settling zone. Using the "continuous conveying + concentration" function, the solid content of the sludge is increased to 3%-7%, reducing the amount of sludge discharged. After concentration, the sludge is pumped to the filter press for dewatering, and the filtrate is returned to the equalization tank.

[0069] The treatment process for thallium-containing heavy metal wastewater includes: The thallium-containing wastewater first enters the conditioning unit, where the "stabilizer" mentioned in the document is added. The stirring device is then turned on to fully mix the stabilizer with the wastewater, adjusting the wastewater system environment to create conditions for the removal of thallium ions.

[0070] After being regulated by stabilizers, the wastewater enters the biological agent reaction zone, where biological agent JLT-005 is added. Through the complex reaction between JLT-005 and thallium ions, soluble thallium in the water is converted into an insoluble complex, while other heavy metal ions (such as Pb, Zn, etc.) are removed.

[0071] Wastewater containing thallium complexes enters the flocculation reaction zone, PAM is added, and slow stirring is started to allow the complexes and reagents to combine and form large flocs, preventing small flocs from being lost with the effluent.

[0072] Wastewater containing flocculent material enters an integrated high-efficiency reaction clarification device. Solid-liquid separation is achieved through the device's "high-efficiency sedimentation" function. The supernatant is discharged after meeting the standards, and the settled sludge is sent to a sludge thickening tank. After thickening and dewatering, it is safely disposed of, and the filtrate is returned to the equalization tank.

[0073] Finally, the treatment results include the water quality compliance status, the rationality of reagent consumption, and the stability of equipment operation.

[0074] The trend prediction unit is used to generate trend prediction data based on treatment results and historical data (such as effluent compliance rate under different influent loads in the past 30 days, reagent consumption curves, and sludge thickening efficiency) through a regression prediction model, including F in the next 1-2 hours. -Warnings include risks of exceeding standards, trends of excessively low / high sludge solids content, and insufficient / excessive reagent dosage. Specific steps are as follows: Retrieve historical data from the database that matches the current "wastewater type + fusion result" (e.g., the current wastewater is fluoride-containing wastewater, F...). - If the success rate is 98%, then filter for similar data from the past month.

[0075] A linear regression prediction model (for water quality indicator trends) and a time-series analysis model (for equipment parameter fluctuations) are used to predict future trends. For example, predicting the risk of fluoride ion exceedance: based on the current fluoride ion concentration... - Historical correlation data of "concentration + JLT-005 dosage + pH value" can be used to predict F in the next 1-2 hours. - Concentration change trend. Sludge concentration fluctuation prediction: Based on historical data of "current sludge solids content + return ratio + discharge ratio", predict the sludge solids content change trend in the next hour.

[0076] If predict F - The concentration will increase from the first concentration (0.8 mg / L) to the second concentration (1.2 mg / L), generating "F". - "Risk of Exceeding Standards (Next 1.5 Hours)" Predictive data. If the sludge solids content is predicted to decrease from the first solids content (3.5%) to the second solids content (2.8%), "Risk of Insufficient Sludge Thickening" predictive data is generated. If the JLT-005 dosage is predicted to be less than the preset dosage threshold (25 mg / L), "Early Warning of Insufficient Reagent Dosing (Next 30 Minutes)" predictive data is generated.

[0077] The predicted data in the format of "risk type + prediction time + impact level" is transmitted to the self-optimization control module along with the fusion results.

[0078] The self-optimizing control module is used to set the effluent quality standards (F) based on trend prediction data. - The system considers multiple objective parameters, including compliance with emission standards for fluoride, suspended solids (SS), and heavy metals; minimizing reagent consumption (optimized dosage of biological agents JLT-005 and PAM); and reducing sludge treatment costs (sludge solids content ≥3%). It selects suitable multi-objective collaborative control algorithms, such as optimized dosing algorithms for fluoride removal reagents in fluoride-containing wastewater and sludge thickening and reflux ratio control algorithms, to calculate and generate initial equipment control commands for dosing pump frequency, stirring speed, and sludge reflux ratio. These initial commands are then optimized based on online fluoride ion monitoring results and sludge solids content data before outputting the final equipment control commands.

[0079] The self-optimizing control module includes a target parameter setting unit, an algorithm selection unit, an instruction calculation unit, and an instruction optimization unit. The target parameter setting unit is used to set multiple target parameters, including water treatment effect, energy consumption, and efficiency. Specifically, the target parameters are: water treatment effect (effluent flow rate). -The emission levels of SS, heavy metals, COD, P, and hardness meet relevant emission standards. Energy consumption is optimized (minimize the energy consumption of stirring motor, dosing pump, and sludge pump). Efficiency targets are set (sludge solids content ≥3% to reduce sludge discharge, and reagent reaction efficiency ≥90% to reduce operating costs).

[0080] The algorithm selection unit is used to select a suitable multi-objective cooperative control algorithm based on the processing results and trend prediction data. Specifically, if the predicted F... - If the value exceeds the limit, select "F". - The concentration-JLT-005 dosage optimization algorithm is used. If the sludge solids content is predicted to be too low, the "sludge return ratio-thickening efficiency" control algorithm is selected; if the reagent consumption is predicted to be too high, the "reagent dosage-removal rate" collaborative algorithm is selected. The instruction calculation unit is used to calculate and generate the initial equipment control instructions through a multi-objective collaborative control algorithm, specifically including: dosing pump frequency, stirring speed, sludge return ratio, and sludge discharge pump frequency. The instruction optimization unit is used to optimize the initial equipment control instructions, specifically: based on the online monitoring results of fluoride ions, if F... - If the concentration exceeds the emission standard, the dosage of JLT-005 will be increased. Based on the sludge solids content test results, if the solids content is greater than 7%, the sludge discharge frequency will be increased; if the solids content is less than 3%, the sludge discharge frequency will be decreased. The "dosing pump frequency + stirring speed + sludge pump frequency" will be integrated according to "equipment type" to generate equipment control instructions, which will be transmitted to the intelligent collaborative processing module.

[0081] The intelligent collaborative processing module analyzes control parameters such as reagent dosage, sludge return ratio, stirring speed, and sludge discharge frequency in equipment control commands. Based on the characteristics of each functional zone (main reaction zone, flocculation reaction zone, and sludge settling zone) of the clarification equipment, it converts these control parameters into suitable water quality control parameters, such as JLT-005 dosage in the main reaction zone, PAM dosage in the flocculation reaction zone, and an 8%-12% return ratio in the sludge settling zone. It then performs secondary optimization of the water quality control parameters, such as activating the return solenoid valve when fluoride ions exceed the standard and reducing the sludge discharge frequency when the sludge solids content is <3%. The optimized water quality control commands are then output to the clarification equipment.

[0082] The intelligent collaborative processing module includes a parameter parsing unit, a parameter adaptation unit, a parameter optimization unit, and an instruction output unit. The parameter parsing unit is used to parse the control parameters in the equipment control instructions. The specific parsing content includes: dosage of biological agent JLT-005, dosage of lime slurry, dosage of PAM, sludge return ratio, stirring speed, sludge pump operating frequency, and solenoid valve on / off status.

[0083] The parameter adaptation unit is used to convert control parameters into suitable water quality control parameters according to the characteristics of the main clarification equipment. Specifically, it adapts the dosage of JLT-005 to the main reaction zone, the dosage of lime slurry to the pretreatment zone, the dosage of PAM to the flocculation reaction zone, the sludge return ratio to the sludge settling zone, and the solenoid valve switch to the clear water zone.

[0084] The parameter optimization unit is used to perform secondary optimization of water quality control parameters. Specifically, when the online fluoride ion monitor detects fluoride ions in the effluent... - When the standard is exceeded, the solenoid valve in the clear water zone is switched to return the supernatant exceeding the standard to the equalization tank. When the sludge concentration meter detects that the sludge solids content is <3%, the frequency of the sludge discharge pump is reduced to improve the concentration effect. When the pH sensor detects that the pH in the main reaction zone deviates from 8.5-9, the lime slurry dosage is adjusted to obtain optimized water quality control instructions.

[0085] The command output unit transmits optimized water quality control commands to the command execution unit of the main clarification equipment, specifically to: dosing pumps, agitator motors, sludge pumps, and solenoid valves. Commands from the pretreatment section are transmitted to the dosing pumps and agitator motors of the first / second reactors in the pretreatment grading unit. Commands from the main reaction zone are transmitted to the JLT-005 dosing pumps and agitator motors of the first / second stage primary reaction zone. Commands from the flocculation zone are transmitted to the PAM dosing pumps and T3 tank agitator motors in the tertiary reaction tank. Commands from the settling zone are transmitted to the sludge return pumps, sludge discharge pumps, and sludge scrapers. Commands from the clear water zone are transmitted to the solenoid valves linked to the online fluoride ion monitor in the clear water zone.

[0086] Example 2: like Figure 4 As shown, based on the integrated high-efficiency reaction clarification system based on multi-sensor data fusion provided in Embodiment 1, this system can also optionally adopt magnetic coagulation loading process to reduce the equipment footprint and improve equipment operating efficiency.

[0087] With the continuous development of wastewater treatment technology and the increasing scarcity of land resources, the more efficient and smaller-footprint magnetic coagulation process is gradually becoming the mainstream choice for pretreatment or advanced treatment. For those working in the environmental protection industry, mastering the core of this technology will allow them to operate and debug with ease.

[0088] Magnetic coagulation is a technology that combines traditional coagulation techniques with the simultaneous addition of magnetic seeds. These seeds bind with coagulants and pollutants to form a magnetic composite. The magnetic composite then utilizes its high density and rapid settling properties, or employs a magnetic separation device, to accelerate solid-liquid separation, thereby removing pollutants. The magnetic seeds are recovered and recycled through the magnetic separation device, saving costs. The pollutants removed by magnetic coagulation mainly include selenium (SS), heavy metals, carbon dioxide (COD), and phosphorus (TP).

[0089] Compared with traditional natural sedimentation separation, magnetic coagulation technology has advantages such as fast processing speed, high processing efficiency, large processing capacity, wide applicability, small footprint, low energy consumption, convenient operation and management, and high degree of automation.

[0090] Magnetic flocculation with magnetic seeds is not fundamentally different from flocculation without them. The added magnetic seeds, like the fine suspended particles in the soil, act as nuclei in coagulation, and the coagulation mechanism applies to them as well. During magnetic coagulation, the magnetic seeds act as floc nuclei. The addition of flocculants, through flocculation, adsorption, and bridging, combines tiny suspended solids or colloidal particles in the water with the extremely small magnetic seeds. This facilitates the collision and destabilization of the magnetic seeds and colloidal particles or suspended particles, forming flocs. This promotes floc aggregation and increases their ability to capture pollutants. The high relative density of the flocs also significantly increases the settling velocity, accelerating solid-liquid separation.

[0091] The mixing tank is generally divided into three tanks, which we call mixing tanks T1, T2, and T3. Mixing tank T1 is used to add defluorinating agents, PAC, and other coagulants, and uses rapid stirring to quickly mix them with the influent. The stirrer speed is generally 250 rpm. Mixing tank T2 is used for magnetic powder recovery from the magnetic separator, magnetic powder addition, and magnetic powder mixing. Rapid stirring is also used to quickly mix the magnetic powder with the influent from the front-end coagulation process; the stirrer speed is generally 250 rpm. Mixing tank T3 is used for adding and mixing flocculants, better promoting the sedimentation of magnetic powder and insoluble substances in the water. Slow stirring should be used in this tank, generally set at 70-80 rpm; rapid stirring will break up the flocs, leading to flocculation failure.

[0092] The selection of sedimentation tanks is not significantly different from that of general secondary or primary sedimentation tanks. Considering factors such as floor space, inclined tube sedimentation tanks are often chosen. The mixed water settles smoothly into the effluent tank, where magnetic mixing sedimentation is used for reflux, and the supernatant flows out smoothly from the effluent channel. A sludge scraper is also provided to prevent the accumulation of magnetic powder and sludge at the bottom, facilitating better reflux.

[0093] In magnetic coagulation technology, recirculation and sludge removal are crucial. Recirculation primarily involves the reuse of magnetic powder while maintaining a balanced sludge volume within the tank. The recirculation ratio is typically 8%–12% of the influent volume, and can be appropriately increased as the influent volume increases. The sludge removal pump corresponds to the excess sludge pump on the control diagram. Its function is to remove excess sludge at specific times, maintaining a normal solids load within the tank. The sludge removal ratio is usually 2% of the influent volume, but the specific need for sludge removal is determined based on the SS or SV30 of the influent and effluent.

[0094] Coagulant (defluorinating agent): Generally, liquid agents are used. Small-scale test data show that when the dosage of defluorinating agent is 25~30mg / L, the removal rate of fluoride ions can reach 95%. However, in actual operation, the dosage of defluorinating agent needs to be adjusted according to the front-end fluoride ion removal situation. It can be adjusted according to the actual situation.

[0095] Magnetic powder: As the particle size of magnetic powder increases, its specific surface area decreases rapidly, drastically reducing the contact area between the magnetic powder and pollutants. Magnetic powder has a much higher specific gravity than water, and large particles tend to settle quickly. To achieve a high magnetic powder flocculation rate, the particle size should not exceed 10µm. Some of the added magnetic powder settles on its own, while most is flocculated into large flocs by the flocculant and settles. When the amount of magnetic powder added is small, the flocculation rate is high; as the amount of magnetic powder added increases, the flocculation rate gradually decreases. This is because when the amount of magnetic powder added is small, there are many other suspended matter around the magnetic powder, providing ample opportunities for collision, adsorption, and aggregation. Most of the added magnetic powder aggregates with the pollutants into large flocs, resulting in a high flocculation rate. However, as the amount of magnetic powder added increases, in addition to other suspended matter, a considerable amount of magnetic powder remains around it. This increases the chances of magnetic powder colliding and agglomerating with each other, leading to a lower flocculation rate. The more magnetic powder added, the more opportunities there are for collisions and aggregation between the magnetic powder particles, resulting in a lower flocculation rate. Therefore, the appropriate dosage depends on the concentration of pollutants (the dosage can be referenced by observing the formed flocs). Otherwise, it will either be too little, resulting in insufficient magnetic properties of the flocs, or too much, wasting the magnetic seed. During the trial operation, a dosage of 100 mg / L can be used for testing. During subsequent continuous operation, the dosage can be adjusted according to the daily water volume and operating conditions.

[0096] Flocculant (PAM): There are several types of PAM, with cationic PAM being the most common in magnetic coagulation. The dosage of flocculant is determined by observing the flocs. Increasing the amount of flocculant added does not necessarily improve the magnetic powder flocculation rate; in fact, excessive amounts can lead to flocculation failure. Currently, the dosage of PAM in urban wastewater treatment plants is generally 0.5-1 mg / L. During commissioning, experiments can be conducted based on this dosage to determine the most suitable ratio.

[0097] The magnetic powder can be recycled after use, requiring magnetic powder recycling equipment. Currently, the most commonly used magnetic separator is the drum type. The magnetic powder separator uses the magnetic force generated by the permanent magnet system to attract the magnetic seed particles in the feed to the surface of the cylinder and rotate with the cylinder. After being removed from the magnetic field, the magnetic seed is recovered under the action of scraper or flushing water, while the non-magnetic material is discharged from the sludge discharge port, thus completing the recovery of the magnetic seed (magnetic powder magnetic medium). At present, the recycling equipment is relatively mature and the recovery rate can reach 99%.

[0098] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0099] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An integrated, high-efficiency reaction clarification system based on multi-sensor data fusion, characterized in that, include: The main clarification equipment is used for the graded treatment of industrial wastewater, including main reaction, flocculation reaction, sludge sedimentation, and clear water separation. It generates real-time operating parameters and receives external water quality control commands. An adaptive sensing module is used to preprocess the real-time operating parameters and convert them into standardized sensing data in a unified format. The deep fusion processing module is used to perform fusion analysis on the standardized sensor data, establish multiple correlations, extract key features, and generate predictive data on the risk of fluoride ion exceeding the standard and the trend of sludge concentration fluctuation through a prediction model. The self-optimizing control module is used to calculate and generate initial equipment control commands based on the trend prediction data and through a multi-objective collaborative control algorithm, optimize the initial equipment control commands, and output equipment control commands. The intelligent collaborative processing module is used to parse the control parameters in the equipment control command, convert the control parameters into suitable water quality control parameters according to the functional area characteristics of the main clarification equipment, perform secondary optimization of the water quality control parameters, and output the optimized water quality control command to the main clarification equipment.

2. The integrated high-efficiency reaction clarification system based on multi-sensor data fusion according to claim 1, characterized in that, The main clarification equipment includes a pretreatment grading unit, a real-time parameter acquisition unit, an instruction execution unit, and a status feedback unit. The pretreatment grading unit is used to perform preliminary filtration and grading sedimentation treatment on the raw water, and to perform secondary grading treatment through the main reaction zone, flocculation reaction zone, sludge settling zone, and clear water zone. The real-time parameter acquisition unit is used to monitor the real-time operating parameters of the equipment, and the instruction execution unit is used to receive and execute externally input water quality control instructions and output equipment status information. The status feedback unit is used to transmit the device status information to the adaptive sensing module.

3. The integrated high-efficiency reaction clarification system based on multi-sensor data fusion according to claim 2, characterized in that, The pretreatment and grading unit performs grading treatment on the raw water, including the following steps: Production wastewater enters the equalization tank through the collection pipeline network. The water quality and quantity are homogenized by hydraulic stirring in the tank. The homogenized raw water is then transported to the first reactor of the pretreatment section by the wastewater lift pump. In the first reactor, lime slurry is added to the homogenized raw water according to the preset logic through the PT-type automatic dosing device of the integrated dosing system. The stirring device is turned on to fully mix the lime slurry with the raw water and to precisely adjust the pH value of the reaction system to 8.5-9 to obtain the initial mixture. The initial mixture is transported to the second reaction tank, where a coagulant is added through a dosing system. The stirring speed is maintained to allow the coagulant to fully react with the water, forming preliminary micro-flocculations and obtaining flocculated water. The flocculated water is sent into the primary settling tank, the strong stirring device is turned off, and the water is switched to a stable and static state. Solid-liquid separation is achieved by gravity settling. The precipitated sludge is temporarily stored at the bottom of the settling tank, and the supernatant flows by gravity to the first-stage reaction zone of the biological defluoridating agent.

4. The integrated high-efficiency reaction clarification system based on multi-sensor data fusion according to claim 1, characterized in that, The adaptive sensing module includes a data cleaning unit and a data standardization unit; the data cleaning unit is used to remove outliers and noise from the real-time operating parameters and output primary processing parameters; the data standardization unit is used to convert the primary processing parameters into standardized sensing data in a unified format.

5. The integrated high-efficiency reaction clarification system based on multi-sensor data fusion according to claim 4, characterized in that, The steps for the data cleaning unit to output primary processing parameters include: Identify outliers and noise in the real-time operating parameters, including instantaneous fluctuation data from the fluoride ion online monitor, sudden jump data from the pH sensor, and abnormal flow data from the dosing pump; The instantaneous fluctuation data of the fluoride ion online monitor is processed using a moving average smoothing filter; the sudden jump data of the pH sensor is processed using a threshold elimination + historical mean completion method; the abnormal flow data of the dosing pump is temporarily completed using the average dosage of similar equipment, and the fault is marked for investigation. The processed real-time operating parameters are organized in a fixed format and output to the data standardization unit.

6. The integrated high-efficiency reaction clarification system based on multi-sensor data fusion according to claim 1, characterized in that, The deep fusion processing module includes a multi-source data association unit, a feature extraction unit, a fusion execution unit, and a trend prediction unit. The multi-source data association unit is used to establish the association relationship between different types of standardized sensor data. The feature extraction unit is used to extract key feature information from the standardized sensor data. The fusion execution unit is used to perform fusion analysis on the feature information based on the association relationship and output processing results including water quality compliance status, rationality of reagent consumption, and equipment operation stability. The trend prediction unit is used to generate trend prediction data based on the processing results and historical data through a regression prediction model.

7. The integrated high-efficiency reaction clarification system based on multi-sensor data fusion according to claim 6, characterized in that, The steps by which the trend prediction unit generates trend prediction data through a regression prediction model include: Retrieve historical data from the database that matches the current wastewater type and fusion results; A linear regression prediction model and a time series analysis model are used to predict future trends and output the prediction results. If in the prediction result, F - The concentration will increase from the first concentration to the second concentration, generating F. - Data for predicting risks of exceeding standards; if it is predicted that the sludge solids content will drop from the first solids content to the second solids content, data for predicting risks of insufficient sludge thickening will be generated; if it is predicted that the dosage of JLT-005 will be less than the preset dosage threshold, data for predicting early warning of insufficient reagent dosage will be generated.

8. The integrated high-efficiency reaction clarification system based on multi-sensor data fusion according to claim 6, characterized in that, The self-optimizing control module includes a target parameter setting unit, an algorithm selection unit, an instruction calculation unit, and an instruction optimization unit. The target parameter setting unit is used to set multiple target parameters, including quality processing effect, energy consumption, and efficiency. The algorithm selection unit is used to select an appropriate multi-objective collaborative control algorithm based on the processing results and the trend prediction data. The instruction calculation unit is used to calculate and generate initial equipment control instructions through the multi-objective collaborative control algorithm. The instruction optimization unit is used to optimize the initial equipment control instructions and output the equipment control instructions.

9. The integrated high-efficiency reaction clarification system based on multi-sensor data fusion according to claim 1, characterized in that, The intelligent collaborative processing module includes a parameter parsing unit, a parameter adaptation unit, a parameter optimization unit, and an instruction output unit; the parameter parsing unit is used to parse the control parameters in the equipment control instruction, and the parameter adaptation unit is used to convert the control parameters into suitable water quality control parameters according to the characteristics of the clarification main equipment. The parameter optimization unit is used to perform secondary optimization on the water quality control parameters to obtain the optimized water quality control command. The instruction output unit is used to transmit the optimized water quality control instruction to the instruction execution unit of the clarification main equipment.

10. The integrated high-efficiency reaction clarification system based on multi-sensor data fusion according to claim 9, characterized in that, The transmission strategy of the instruction output unit for transmitting the optimized water quality control instructions to the instruction execution unit of the clarification main equipment includes: transmitting instructions from the pretreatment section to the dosing pumps and stirring motors of the first and second reactors of the pretreatment grading unit; transmitting instructions from the main reaction zone to the JLT-005 dosing pumps and stirring motors of the first and second stage reaction zones; transmitting instructions from the flocculation zone to the PAM dosing pump and T3 tank stirring motor of the tertiary reaction tank; transmitting instructions from the sedimentation zone to the sludge return pump, sludge discharge pump, and sludge scraper; and transmitting instructions from the clear water zone to the solenoid valve linked to the online fluoride ion monitoring instrument in the clear water zone.

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