Full-automatic dosing control system and method for lime coagulation and clarification treatment

Abstract

The application discloses a full-automatic dosing control system and method for lime coagulation and clarification treatment, and belongs to the technical field of water treatment. The application aims to solve the technical problem that the water quality fluctuates greatly due to the lag of dosing control in the existing lime coagulation process. The core scheme of the application comprises the following steps: setting a water inlet multi-parameter detection unit to collect the water inlet flow, alkalinity and temperature in real time, and setting a reaction zone pH detection unit to collect the pH value in the primary reaction zone in real time; a dosing amount feed-forward-feedback compound control module in the central processing unit calculates the reference dosing amount through a feed-forward model according to the water inlet flow, alkalinity and temperature, calculates the correction dosing amount through a feedback algorithm according to the deviation of the real-time pH value in the primary reaction zone from the target pH value, and then superimposes the reference dosing amount and the correction dosing amount to generate a final dosing amount instruction, which is output to a dosing execution mechanism to execute dosing. The application realizes the advanced prediction and real-time correction of the dosing amount, and effectively stabilizes the water quality.

Description

Technical Field

[0001] This application belongs to the field of water treatment technology, and specifically relates to a fully automatic dosing control system and method for lime coagulation and clarification treatment. Background Technology

[0002] Currently, in the field of water treatment automation control, especially in lime coagulation and clarification processes for urban wastewater reuse or circulating cooling water treatment, a dosing control strategy based on influent flow rate ratio control and effluent pH feedback is commonly adopted. Specifically, the system monitors the influent flow rate in real time using a flow meter installed on the influent pipeline and coarsely adjusts the lime dosage according to a preset ratio. Simultaneously, a pH meter installed at the clarifier outlet monitors the effluent pH value. When the effluent pH deviates from the target range, a PID controller provides feedback correction to the dosing dosage. Furthermore, for sludge removal control in the clarifier, the industry commonly uses timed sludge removal or sludge removal based on a single sludge level. This involves setting a fixed sludge removal time interval based on experience, or activating the sludge removal valve when the sludge interface rises to a preset height.

[0003] However, the existing control methods described above have many inherent drawbacks in practical applications. First, due to the significant time lag (typically 15 to 30 minutes) in the dissolution, ionization, and chemical reaction processes of lime, the traditional flow ratio + effluent pH feedback control strategy is difficult to effectively regulate this large lag process, leading to frequent and significant fluctuations in effluent pH. This easily causes overshoot (excessive dosing leading to scaling in pipes and equipment) or undershoot (insufficient dosing leading to excessive hardness and alkalinity in the effluent). Second, existing sludge discharge control methods cannot accurately perceive the actual settling performance of sludge. When sludge expands or ages, its settling performance deteriorates. Relying solely on sludge level height or fixed-time sludge discharge easily leads to sludge overflow with the effluent (i.e., sludge backflow), causing deterioration of effluent quality. Conversely, when sludge is well compacted, timed or excessive sludge discharge can lead to a large loss of clear water, affecting the clarification effect. In addition, existing systems generally lack proactive monitoring and protection of the equipment's own operating status. When the raw water quality changes abruptly, calcium carbonate scale buildup and blockage can easily occur in the dosing pipeline, nozzles, and reaction zone, requiring frequent manual shutdowns for cleaning, which significantly increases operation and maintenance costs and workload. Summary of the Invention

[0004] This application discloses a fully automatic dosing control system and method for lime coagulation clarification treatment, which aims to solve the technical problems in the existing lime coagulation clarification process, such as large fluctuations in effluent water quality and easy over-adjustment or under-adjustment due to the lag in dosing control.

[0005] To achieve the above objectives, this application provides the following technical solution: In a first aspect, this application provides a fully automatic dosing control system for lime coagulation and clarification treatment, used for adding lime reagent to a reaction tank, comprising: an influent multi-parameter detection unit for real-time detection of influent flow rate, alkalinity, and temperature; a reaction zone pH detection unit for real-time detection of pH value in the primary reaction zone of the reaction tank; a central processing unit communicatively connected to the influent multi-parameter detection unit and the reaction zone pH detection unit, wherein the central processing unit contains a dosing dosage feedforward-feedback composite control module; and a dosing actuator communicatively connected to the central processing unit for adding lime reagent to the reaction tank according to its instructions; wherein the dosing dosage feedforward-feedback composite control module is configured to: calculate a baseline dosing dosage based on the influent flow rate, alkalinity, and temperature using a feedforward model; calculate a corrected dosing dosage based on the deviation between the real-time pH value in the primary reaction zone and a preset target pH value using a feedback algorithm; and superimpose the baseline dosing dosage and the corrected dosing dosage to generate a final dosing dosage instruction and output it to the dosing actuator.

[0006] Preferably, it further includes: an adaptive sludge discharge control submodule, which is communicatively connected to the central processing unit and configured to acquire the sludge level in the clarifier and trigger a sludge discharge action based on a two-factor logic combination of the sludge level and the sludge settling rate.

[0007] Preferably, the dual-factor logic combination includes: a first trigger condition, which triggers sludge discharge when the sludge level reaches or exceeds a preset high sludge level threshold; and a second trigger condition, which triggers sludge discharge even if the sludge level has not reached the high sludge level threshold, when the sludge settling rate is lower than a preset minimum settling rate threshold; wherein the sludge settling rate is obtained by the central processing unit through differential calculation of continuously collected sludge level data.

[0008] Preferably, it further includes: an anti-scaling and self-cleaning submodule, which is communicatively connected to the central processing unit and configured to: dynamically calculate the Langerier saturation index based on the real-time pH, temperature, calcium hardness and total alkalinity of the influent; and automatically execute at least one of the following protective measures when the Langerier saturation index reaches or exceeds a preset warning threshold: limit the maximum dosage of the dosing actuator and start a preset self-cleaning program.

[0009] Preferably, it further includes: a flocculation stirring intensity linkage submodule, which is communicatively connected to the central processing unit and configured to automatically adjust the stirring intensity of the flocculation mixer in the reaction tank according to the real-time turbidity and temperature of the influent.

[0010] Secondly, this application provides a fully automated dosing control method for lime coagulation and clarification treatment, based on the fully automated dosing control system for lime coagulation and clarification treatment described in any of the above claims, comprising the following steps: The influent multi-parameter detection unit collects the influent flow rate, alkalinity, and temperature parameters in real time, and the pH value in the primary reaction zone is collected in real time by the reaction zone pH detection unit. The dosing feedforward-feedback composite control module in the central treatment unit calculates the theoretical baseline dosing amount based on the influent flow rate, alkalinity, and temperature, and calculates the corrected dosing amount based on the deviation between the real-time pH value in the primary reaction zone and the target pH value. The baseline dosing amount and the corrected dosing amount are then superimposed to generate the final dosing amount command. The dosing execution mechanism executes the dosing operation according to the final dosing amount command.

[0011] Preferably, the method further includes the step of: performing adaptive sludge discharge control, including: continuously monitoring the sludge level in the clarifier; calculating the sludge settling rate; and initiating sludge discharge when either the sludge level reaches the upper limit threshold or the sludge settling rate is lower than the minimum threshold.

[0012] Preferably, after the step of initiating sludge discharge, the method further includes: delaying for a preset time or waiting for the sludge level to drop to a lower threshold before shutting off sludge discharge.

[0013] Preferably, the method further includes the step of: performing anti-scaling and self-cleaning control, including: periodically calculating the Langerier saturation index; when the Langerier saturation index exceeds a preset warning value, automatically limiting the upper limit of lime dosage and initiating a high-pressure water flushing or acid washing procedure.

[0014] Preferably, the method further includes the step of: performing linkage control of flocculation stirring intensity, including: real-time detection of the turbidity and temperature of the influent; increasing the stirring intensity of the flocculation mixer under low temperature and low turbidity conditions, and decreasing the stirring intensity of the flocculation mixer under high temperature and high turbidity conditions.

[0015] Compared with the prior art, this application has at least the following beneficial effects: This application fundamentally solves the control problem caused by the lag in chemical reaction in lime coagulation processes by constructing a composite dosing control model of multivariate feedforward and reaction zone feedback. Specifically, the feedforward module, by collecting influent flow rate, alkalinity, and temperature in real time, can predict and adjust the dosing dosage in advance before water quality fluctuations affect the reaction tank, significantly shortening the system response time. The feedback module, by monitoring the real-time pH value in the primary reaction zone, can quickly and accurately correct the inherent error of the feedforward model, avoiding the overshoot or undershoot problems caused by excessive lag time in traditional effluent pH feedback methods. The combined output of the two modules ensures that effluent pH fluctuations can be controlled within ±0.3, and that indicators such as total hardness and total phosphorus consistently meet standards. Furthermore, this application, through the synergistic effect of feedforward and feedback, avoids excessive lime dosing, saving 10%-20% of the reagents compared to traditional control methods, thus reducing operating costs. This application achieves automation and intelligence in the dosing process, eliminating the lag and experience dependence of manual adjustment, and providing a closed-loop control solution for lime coagulation and clarification processes. Attached Figure Description

[0016] The accompanying drawings described herein are for illustrative purposes only and do not limit the scope of this application in any way. Furthermore, the shapes and scales of the components in the drawings are merely schematic to aid in understanding this application and do not specifically limit the shapes and scales of the components. In the drawings: Figure 1 : A schematic diagram of the fully automated operation and control system for lime coagulation and clarification treatment in this application example; Figure 2 : Algorithm flowchart of the intelligent dosing control method in this application example; Figure 3 : Logic criterion diagram of the adaptive sludge discharge control method in this application example; Figure 4 : Flowchart illustrating the principle of the anti-scaling and self-cleaning control method in this application example. Detailed Implementation

[0017] To enable those skilled in the art to better understand the technical solutions in this application, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this application.

[0018] It should be noted that when an element is referred to as being disposed on another element, it can be directly on the other element or there may be an intervening element. When an element is indicated as being connected to another element, it can be directly connected to the other element or there may be an intervening element. The terms vertical, horizontal, left, right, and similar expressions used herein are for illustrative purposes only and do not represent the only embodiments.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein in the specification of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The terminology used herein includes any and all combinations of one or more of the associated listed items.

[0020] This application aims to provide a closed-loop automatic system for the entire lime coagulation and clarification process that can adapt to fluctuations in raw water quality, precisely control the dosing of chemicals and the sludge discharge process, and has self-cleaning and scale prevention functions, in order to solve the problems of control lag, crude sludge discharge and easy scaling and clogging in existing technologies.

[0021] Example 1 This application provides a fully automated dosing control system for lime coagulation and clarification treatment. This system aims to solve the technical problem of large fluctuations in effluent quality caused by lag in dosing control in existing technologies.

[0022] See Figure 1 The system control principle and process layout diagram shown in this application mainly includes: an influent multi-parameter detection unit, a reaction zone pH detection unit, a central treatment unit, and a dosing actuator.

[0023] 1. System composition and functional division (1) Inlet water multi-parameter detection unit This unit is one of the sensing front-ends of the system, used to collect the raw water quality and quantity parameters entering the treatment system in real time and continuously. Specifically, the influent multi-parameter detection unit includes, but is not limited to: an influent flow meter, an influent alkalinity meter, and an influent temperature sensor installed on the influent pipeline.

[0024] Among these, flow rate, alkalinity, and temperature are the three most critical feedforward parameters determining the theoretical lime dosage. Flow rate determines the processing scale, alkalinity directly corresponds to the hardness of the carbonates to be removed, while temperature significantly affects the chemical reaction rate and the solubility of lime.

[0025] By simultaneously collecting these three key parameters, this system provides a comprehensive and accurate data foundation for subsequent feedforward calculations, making the prediction of dosage more precise and avoiding the drawbacks of relying solely on a single flow parameter for extensive control.

[0026] (2) pH detection unit in the reaction zone This unit is also the system's sensing front end, but its monitoring location differs from that of the inlet water unit. It is specifically designed to monitor the pH value in the primary reaction zone of the reaction tank in real time.

[0027] Unlike existing technologies that typically monitor the pH of the effluent, this application selects to monitor the real-time pH value of the reaction zone. Since the chemical reaction between lime and alkalinity in the water mainly occurs in this area, the pH value at this point can most quickly and directly reflect whether the current dosage is appropriate. Its response time is much faster than monitoring the pH value at the distant effluent outlet, effectively overcoming the lag of traditional feedback control.

[0028] Using the pH of the reaction zone as a feedback signal significantly reduces the system's response time from 15-30 minutes in traditional processes to minutes or even seconds, creating conditions for implementing rapid and accurate closed-loop corrections. This is one of the key technical means to solve the problem of large lag.

[0029] (3) Central Processing Unit The central processing unit is communicatively connected to the influent multi-parameter detection unit and the reaction zone pH detection unit. The central processing unit contains a core functional module: a dosing feedforward-feedback composite control module. This module is the core technology for achieving precise dosing control in this application.

[0030] (4) Dosing agency The dosing actuator is communicatively connected to the central processing unit and is used to precisely add lime reagent to the reaction tank according to instructions issued by the central processing unit. In this embodiment, the dosing actuator is preferably one or more variable frequency metering pumps connected to the lime slurry delivery pipeline.

[0031] 2. Core Control Logic and Working Process The dosing dosage feedforward-feedback composite control module is configured to execute the following core logic to achieve dynamic, closed-loop control of the dosing dosage: Step 1: Calculate the baseline dosage The module reads in real-time data on influent flow rate, alkalinity, and temperature from the influent multi-parameter detection unit. Then, it calls an internally pre-built mathematical model based on chemical reaction equivalence and water temperature correction to dynamically calculate a theoretical baseline dosage. The core idea of ​​this model is to calculate the theoretically required basic dosage for complete reaction based on the current water quality and quantity conditions.

[0032] The core advantage of this step lies in its proactive prediction. When the alkalinity of the influent suddenly increases, the system will immediately increase the dosage command proportionally based on the model calculation results, without waiting for the pH in the reaction tank to change before the reaction begins. This fundamentally solves the problem of significant lag in lime reaction.

[0033] Output: The output value is the baseline dosage, denoted as D. b .

[0034] Step 2: Calculate the corrected dosage Simultaneously, the module reads the real-time pH value within the primary reaction zone from the pH detection unit in the reaction zone. It compares this real-time pH value with a preset target pH value and calculates the deviation. Then, using a proportional-integral-derivative control algorithm, a corrected dosage is generated based on the magnitude and trend of this deviation.

[0035] The feedforward model is based on theoretical calculations and may contain inherent errors. pH feedback in the reaction zone serves to correct these errors in real time. If the pH in the reaction zone is lower than the target value, it indicates insufficient dosage, and the PID algorithm will calculate a positive correction; conversely, it will calculate a negative correction. This step ensures control accuracy.

[0036] Output: The output value is the corrected dosage, denoted as ΔD.

[0037] Step 3: Generate and output the final command The module will use the baseline dosage D calculated above. b The dosage is added to the corrected dosage ΔD to generate the final dosage instruction, i.e., D. final =D b +ΔD. This final command is then output to the dosing actuator, controlling it to operate at the corresponding frequency or stroke, thereby achieving precise dosing.

[0038] 3. Summary of Overall Beneficial Effects Through the aforementioned combined control strategy of feedforward prediction and feedback correction, this system achieves rapid, precise, and stable control of the dosage. Compared to existing technologies, the pH fluctuation of the effluent can be effectively controlled within an extremely narrow range of ±0.3, and key indicators such as total hardness and total phosphorus consistently meet standards. Simultaneously, by avoiding excessive dosing due to lag, lime reagent consumption can be reduced by 10%-20%, achieving the dual goals of cost reduction, efficiency improvement, and stable effluent.

[0039] In a more complete embodiment of this application, in addition to including all the technical features of the first part described above, multiple sub-modules such as adaptive sludge discharge, anti-scaling self-cleaning, and flocculation-stirring linkage are integrated, thereby constructing a fully automated operation and control system for lime coagulation and clarification covering the entire process of chemical dosing, sludge discharge, scale prevention, and stirring. The specific implementation process of this embodiment will be described in detail below with reference to the accompanying drawings.

[0040] like Figure 1 As shown, the system in this embodiment specifically includes a perception layer, a control layer, and an execution layer.

[0041] Sensing layer: including an influent flow meter, an influent alkalinity meter, and an influent temperature sensor installed sequentially on the influent pipe; a pH sensor for the reaction zone installed in the reaction tank; a high-precision ultrasonic sludge level meter installed at the bottom or side wall of the clarifier for continuous monitoring of the sludge interface height; and a turbidity meter installed at the effluent end for monitoring the final effluent quality.

[0042] The execution layer includes a variable frequency metering pump installed on the lime slurry dosing pipe; a frequency converter installed in the reaction tank to drive the agitator; an electric sludge discharge valve installed on the sludge discharge pipe; and a high-pressure flushing water valve for flushing the dosing pipeline and nozzles.

[0043] Control layer: A PLC / DCS control cabinet is used as the central processing unit. It is electrically connected to the devices in the sensing layer and execution layer through shielded cables. It is used to collect data, execute algorithms and issue instructions.

[0044] like Figure 2 As shown, after the system is powered on, the central processing unit executes the following intelligent dosing control process cyclically according to a preset cycle: Step S1: Data Acquisition. The central processing unit collects real-time data on influent flow rate Q, influent alkalinity A, influent temperature T, and the real-time pH value (pH_reaction zone) of the primary reaction zone through the sensing layer.

[0045] Step S2: Calculate the baseline dosage. The central processing unit calls the built-in feedforward mathematical model. As one implementation, this model can be calculated in the following form: D b =k×Q×A×f(T). Where, D b Let Q be the baseline dosage, A be the influent flow rate, and f(T) be a correction factor function with respect to the influent temperature T. For example, when the water temperature is low, the lime dissolution rate is slower, and the correction factor can be appropriately reduced; when the water temperature is normal, the correction factor is 1. k is a proportionality coefficient calibrated through experiments or experience.

[0046] Step S3: Calculate the corrected dosage. The central processing unit reads the pH sensor data from the primary reaction zone and compares it with the target pH value preset by the process. If the pH of the reaction zone is lower than the set value, a positive correction amount ΔD is calculated using a PID algorithm to increase the dosage; if it is higher than the set value, a negative correction amount ΔD is calculated to reduce the dosage.

[0047] Step S4: Output the final instruction. The central processing unit will output the baseline dosage D. b Add the corrected dosage ΔD to obtain the final dosage instruction D. final =D b +ΔD. This command is output to the variable frequency metering pump to control its speed or stroke in real time, thereby precisely controlling the amount of lime slurry added.

[0048] This process combines proactive prediction with real-time correction, allowing the dosage to quickly track water quality changes and ensure stable effluent pH.

[0049] like Figure 3 As shown, in order to solve the problem of rough sludge discharge, this embodiment integrates an adaptive sludge discharge control submodule, the core of which is to control sludge discharge based on the actual compaction state of the sludge rather than just the sludge height.

[0050] Step S10: Data Acquisition and Processing. The central processing unit reads continuous data from the ultrasonic sludge level gauge in the clarifier at a high frequency.

[0051] Step S11: Calculate the settling rate. The central processing unit performs differential calculations on the continuously collected sludge height data L to obtain the real-time sludge settling rate V. As one implementation method, the settling rate V can be calculated using the following formula: V = dL / dt. Where dL is the change in sludge height per unit time, and dt is the corresponding time interval. When the sludge is well compacted, the interface descent rate V is relatively fast; when the sludge expands or ages, V will decrease significantly or even become negative.

[0052] Step S12: Two-factor logic judgment. The two-factor logic judgment module built into the central processing unit monitors two conditions simultaneously: Condition A: Determine whether the current mud level L has reached or exceeded the system's preset upper limit threshold L. h Condition B: Determine whether the current sludge settling rate V is lower than the system's preset minimum settling rate threshold V. min .

[0053] Step S13: Perform sludge discharge. If either condition A or condition B is met, the central processing unit determines that sludge discharge is necessary. Specifically: if triggered by condition A, it indicates that too much sludge has accumulated at the bottom of the clarifier and needs to be discharged; if triggered by condition B, it indicates that the sludge settling performance has deteriorated, and sludge discharge is forcibly initiated even if the sludge level has not yet reached the upper limit, to avoid sludge overflow with the effluent due to slow sludge settling. After the sludge discharge command is issued, the central processing unit opens the electric sludge discharge valve on the sludge discharge pipe. The duration of sludge discharge can be a preset fixed duration, or it can continue until the sludge level drops to the preset lower limit threshold L_l and then automatically closes.

[0054] This logic effectively avoids sludge overflow accidents in the clarifier caused by sludge bulking, while reducing the loss of clean water caused by timed sludge discharge when sludge is dense, thus optimizing sludge production and moisture content.

[0055] like Figure 4 As shown, to solve the problem of scaling and clogging in equipment, this embodiment integrates an anti-scaling and self-cleaning sub-module.

[0056] Step S20: Calculate the Langerile Index (LSI) online. The system periodically collects parameters such as pH, temperature, calcium hardness, and total alkalinity of the influent or reaction zone. The central processing unit uses the built-in Langerile Saturation Index formula for calculation. As one implementation method, LSI can be calculated using the following formula: LSI = pH - pHs. Where pH is the actual pH value of the water, and pHs is the saturated pH value of the water under the given temperature, alkalinity, and hardness conditions. LSI is used to determine the tendency of water to scale or corrode: LSI > 0 indicates a tendency to scale, and LSI < 0 indicates a tendency to corrode.

[0057] Step S21: Logical Judgment and Early Warning. The system compares the calculated real-time LSI value with a preset early warning threshold. When LSI ≥ the early warning threshold, it indicates a significant increase in the risk of scaling in the system.

[0058] Step S22: Implement protective measures. Once the warning is triggered, the central processing unit immediately and automatically implements a comprehensive set of protective measures to ensure equipment safety. Measure 1: Dynamically limit the dosage. The system automatically locks the maximum allowable dosage of lime dosing actuator within a certain percentage range of the currently calculated value, adopting a conservative control strategy to prevent excessive dosing from exacerbating scaling. Measure 2: Initiate the self-cleaning program. The system automatically triggers a preset self-cleaning circuit, such as turning on the high-pressure flushing water pump connected in parallel with the dosing pipeline to flush the dosing nozzle and the inner wall of the pipeline with high-pressure water, or initiating a micro-acid washing program to briefly clean areas prone to scaling.

[0059] Step S23: Recovery and Cycle. After the self-cleaning procedure is completed, the system resumes normal water quality index control procedures and continues to periodically calculate LSI for the next round of monitoring and protection.

[0060] This module enables online early warning and proactive intervention for equipment scaling risks, effectively preventing pipe and nozzle blockages and significantly reducing the frequency and cost of manual downtime cleaning.

[0061] To further optimize the coagulation effect, this embodiment also integrates a flocculation stirring intensity linkage submodule.

[0062] In the coagulation process, the stirring intensity directly affects the formation and breakup of flocs. The central treatment unit collects data from the influent turbidity meter and thermometer in real time.

[0063] Under low temperature and low turbidity conditions: When the influent water temperature and turbidity are both low, the water viscosity is high, and the chance of particle collision is low. At this time, the central treatment unit automatically increases the output frequency of the flocculation mixer inverter to increase the stirring intensity, so as to promote full contact and flocculation between the reagent and colloidal particles.

[0064] Under high temperature and high turbidity conditions: When the influent temperature and turbidity are both high, particle collisions are frequent, resulting in fragile flocs. In this case, the central treatment unit automatically reduces the stirring intensity of the flocculation mixer to prevent the formed flocs from being broken up, thereby ensuring the sedimentation effect.

[0065] By dynamically adjusting the stirring intensity based on water quality and temperature, the coagulation kinetics were optimized, further improving the stability of effluent turbidity.

[0066] This section provides an example of applying the above system under specific working conditions to further illustrate the technical effects of this application.

[0067] A thermal power plant uses municipal greywater as makeup water for its circulating cooling system, employing the fully automated operation and control system described in this application for lime coagulation and clarification treatment. The designed treatment capacity is 500 m³ / h. The raw water quality indicators are as follows: Influent flow rate: 450-550 m³ / h; Influent alkalinity: 180-350 mg / L; Influent temperature: 10-28℃; Influent turbidity: 5-30 NTU; Target pH: 10.0.

[0068] Control process and effects: First, feedforward response. At a certain moment, the influent alkalinity meter detects a sudden jump in raw water alkalinity from 220 mg / L to 320 mg / L. The system responds based on the built-in feedforward model D. b =k×Q×A×f(T) immediately calculates that the baseline dosage needs to be increased by approximately 45%. The frequency of the variable frequency metering pump increases proportionally within seconds, and the lime slurry dosage is rapidly increased.

[0069] Second, feedback correction. Due to a slight error between the calculated value of the feedforward model and the actual optimal dosage, the pH sensor in the primary reaction zone detected a real-time pH of 9.8, lower than the target value of 10.0. The PID controller calculates a positive correction dosage ΔD, which is added to D. b Then, accurately adjust the pH of the reaction zone back to 10.0.

[0070] Third, sludge discharge control. During operation, the ultrasonic sludge level gauge detected a sludge level of 1.2 meters, which did not reach the upper limit threshold of 1.5 meters. However, the calculated sludge settling rate V dropped to 0.05 meters per hour, below the set threshold of 0.1 meters per hour. The system determined that the sludge settling performance had deteriorated and immediately forced the sludge discharge procedure to discharge the aged sludge in advance, avoiding subsequent sludge overturning accidents.

[0071] Fourth, scale prevention control. The system calculates the real-time LSI value, and in one calculation, the LSI was 0.18. Since this value exceeded the warning threshold of 0.15, the system automatically locked the upper limit of the chemical dosing at 95% and started the high-pressure flushing water pump to flush the dosing nozzle for 60 seconds. After flushing, the LSI value dropped back to 0.12.

[0072] Operational results: After 72 hours of continuous operation, the effluent pH remained stable within the range of 10.0±0.2, the total hardness removal rate remained stable above 85%, and the turbidity was below 3 NTU. Compared with historical data from the same period using traditional PID control, the average lime dosage was reduced by approximately 15%. The sludge discharge frequency was optimized from once every 2 hours to once every 4 hours on average, with a higher concentration of discharged sludge and a reduction in moisture content of approximately 10%. Within three months of operation, no pipe blockages or nozzle cleaning incidents due to scaling occurred.

[0073] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

[0074] Example 2 This application constructs a PLC / DCS central control system that includes multi-parameter feedforward, feedback correction, and sludge property evaluation.

[0075] The system includes the following core modules: (1) Intelligent dosing control submodule This module employs a multivariable feedforward + reaction zone feedback composite algorithm to address the large lag problem in lime reaction.

[0076] Feedforward: Real-time acquisition of influent flow rate, influent alkalinity (or pH), and influent temperature. The system incorporates a mathematical model based on lime equivalent and water temperature correction, dynamically calculating the theoretical baseline dosage D based on Q (flow rate), A (alkalinity), and T (temperature). b For example, when a sudden increase in the alkalinity of the influent is detected, the system immediately increases the frequency of the frequency converter of the lime slurry metering pump proportionally to increase the dosage in advance, without having to wait for the pH value of the reaction tank to change.

[0077] Feedback end: Unlike traditional methods of monitoring effluent pH, this application monitors the real-time pH value of the primary reaction zone (rapid mixing zone). Due to the potential inherent errors in the feedforward model, the system employs a PID algorithm to calculate the deviation between the pH of the reaction zone and the target pH (typically 9.5-10.5) and generate a correction amount ΔD.

[0078] Output: Final dosage D = D b +ΔD is output to the variable frequency metering pump to achieve a combination of advanced prediction and real-time correction. This method enables the dosage to quickly track changes in water quality, and the pH fluctuation of the effluent can be controlled within ±0.3.

[0079] (2) Adaptive sludge discharge control submodule This module primarily relies on the actual compaction state of the sludge rather than its height to discharge sludge, thus solving the problem of blind sludge discharge.

[0080] The logic employs a dual-condition triggering approach: mud level threshold and settling rate change rate.

[0081] Data acquisition: The sludge interface height L is continuously monitored using a high-precision sludge level gauge.

[0082] Logical judgment: The PLC performs differential calculations on the sludge level data to obtain the sludge settling rate V (V=dL / dt).

[0083] Condition A (Mud Full): When L ≥ High Limit Threshold L h At that time, start the sludge removal process.

[0084] Condition B (sludge dispersal): When the settling rate V is less than the minimum threshold Vm (indicating that the sludge settling performance has deteriorated or is aging), sludge discharge is forcibly initiated even if the sludge level has not reached the upper limit.

[0085] This logic effectively avoids sludge overflow accidents in clarifiers caused by sludge expansion, while also reducing the loss of clean water due to ineffective sludge discharge.

[0086] (3) Anti-scaling and self-cleaning submodule This module primarily focuses on preventative equipment protection to address equipment safety issues.

[0087] A dynamic scaling potential (LSI) online early warning system is introduced. The system calculates the Langerilla Saturation Index (LSI) based on real-time water quality parameters. The system applies the Langerilla Saturation Index (LSI) formula based on real-time pH, temperature, calcium hardness, and total alkalinity: (where is the saturation pH value). When LSI is greater than or equal to the warning value (e.g., 0.15), the system automatically takes protective measures: first, it finely adjusts the upper limit of the lime dosage (protecting the equipment takes priority over protecting the index); second, it triggers the bypass high-pressure water flushing / micro-acid washing program of the dosing pipeline or reaction zone to achieve preventive self-cleaning.

[0088] (4) Flocculation and stirring intensity linkage submodule (preferred solution) The frequency converter of the flocculation mixer is automatically adjusted according to the turbidity and temperature of the influent. The stirring intensity (G value) is increased when the temperature and turbidity are low to promote flocculation, and the stirring intensity (G value) is reduced when the temperature and turbidity are high to prevent floc breakage, thereby achieving dynamic optimization of coagulation kinetics.

[0089] This application controls effluent pH fluctuations within ±0.3, and ensures stable compliance with total hardness and total phosphorus standards. Compared to traditional control methods, it saves 10%-20% on lime reagents, reduces sludge moisture content, and lowers sludge disposal costs. It completely eliminates the lag in manual adjustments, realizing a shift from manual experience-based judgment to data-driven decision-making.

[0090] like Figure 1 As shown, a fully automated operation and control system for lime coagulation and clarification treatment includes: Sensing layer: The inlet water flow meter, inlet water alkalinity meter, and inlet water temperature sensor are installed sequentially on the inlet water pipe; the pH sensor of the reaction zone is installed in the reaction tank; the ultrasonic sludge level meter is installed at the bottom of the clarification tank; and the turbidity meter is installed at the outlet water end.

[0091] Execution layer: frequency conversion metering pump on lime slurry dosing pipe, frequency converter of reaction tank agitator, electric sludge discharge valve and high-pressure flushing water valve on sludge discharge pipe.

[0092] Control layer: PLC / DCS control cabinet, electrically connected to the sensing layer and execution layer via shielded cables.

[0093] like Figure 2 As shown, after the system boots up: S1: Real-time collection of influent flow rate, alkalinity, and temperature.

[0094] S2: Call the built-in model (k1 is the temperature correction coefficient) to calculate the baseline dosage.

[0095] S3: Read the pH sensor data in the reaction zone. If the pH is lower than the set value (e.g., 10.0), increase it; if it is higher than the set value, decrease it.

[0096] S4: Outputs the total frequency command to the variable frequency metering pump to control the dosage.

[0097] The implementation of adaptive sludge removal methods, such as Figure 3 As shown, it includes: S10: The PLC reads the mud level gauge data every second.

[0098] S11: Calculate the change in mud level per unit time.

[0099] S12: Judgment Logic: If (high limit) OR (settlement too slow), then proceed to S13; Otherwise, return to S10.

[0100] S13: Open the sludge discharge valve, and close it after a 30-second delay or when the sludge level (low limit) is reached.

[0101] like Figure 4 As shown, the system periodically calculates the LSI index. When LSI > 0.15, the system automatically locks the upper limit of the dosage at 95% of the current value and starts the high-pressure flushing water pump to run for 1 minute to flush the dosing nozzle and the inner wall of the pipeline, and then resumes the normal process.

[0102] The apparatuses and methods disclosed in the embodiments provided in this application can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatuses, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0103] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0104] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0105] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the term "include" or any other variations thereof are intended to cover non-exclusive inclusion, such that an article or apparatus that includes a list of elements includes not only those elements but also other elements not expressly listed. Without further limitations, an element defined by the statement "includes a..." does not exclude the presence of other identical elements in the article or apparatus that includes said element.

[0106] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A fully automatic dosing control system for lime coagulation and clarification treatment, characterized in that, include: The inlet water multi-parameter detection unit is used to detect the inlet water flow rate, alkalinity, and temperature in real time. The pH detection unit in the reaction zone is used to detect the pH value in the primary reaction zone of the reaction tank in real time. The central processing unit is communicatively connected to the influent multi-parameter detection unit and the reaction zone pH detection unit. The central processing unit contains a dosing feedforward-feedback composite control module. The dosing actuator is communicatively connected to the central processing unit and is used to add lime reagent to the reaction tank according to its instructions. The dosing dosage feedforward-feedback composite control module is configured as follows: Based on the influent flow rate, alkalinity, and temperature, the baseline dosage is calculated using a feedforward model. The corrected dosage is calculated using a feedback algorithm based on the deviation between the real-time pH value in the primary reaction zone and the preset target pH value. The baseline dosage and the modified dosage are superimposed to generate a final dosage instruction, which is then output to the dosing actuator.

2. The system according to claim 1, characterized in that, Also includes: An adaptive sludge discharge control submodule is communicatively connected to the central processing unit and is configured to acquire the sludge level in the clarifier and trigger a sludge discharge action based on a two-factor logic combination of the sludge level and the sludge settling rate.

3. The system according to claim 2, characterized in that, The two-factor logical combination includes: First triggering condition: When the mud level reaches or exceeds the preset high mud level threshold, mud discharge is triggered; Second triggering condition: When the sludge settling rate is lower than the preset minimum settling rate threshold, sludge discharge is triggered even if the sludge level does not reach the high sludge level threshold. The sludge settling rate is obtained by the central processing unit through differential calculation of continuously collected sludge height data.

4. The system according to claim 1, characterized in that, Also includes: The anti-scaling and self-cleaning submodule, which is communicatively connected to the central processing unit, is configured as follows: The Langerier saturation index is dynamically calculated based on the real-time pH, temperature, calcium hardness, and total alkalinity of the influent. When the Langerilla saturation index reaches or exceeds a preset warning threshold, at least one of the following protective measures will be automatically executed: limiting the maximum dosage of the dosing actuator or initiating a preset self-cleaning program.

5. The system according to claim 1, characterized in that, Also includes: The flocculation stirring intensity linkage submodule is communicatively connected to the central processing unit and is configured to automatically adjust the stirring intensity of the flocculation mixer in the reaction tank according to the real-time turbidity and temperature of the influent.

6. A fully automated dosing control method for lime coagulation and clarification treatment, based on the fully automated dosing control system for lime coagulation and clarification treatment according to any one of claims 1 to 5, characterized in that, include: The influent multi-parameter detection unit collects the influent flow rate, alkalinity, and temperature parameters in real time, and the pH value in the primary reaction zone is collected in real time by the reaction zone pH detection unit. The dosing feedforward-feedback composite control module in the central processing unit calculates the theoretical baseline dosing amount based on the influent flow rate, alkalinity, and temperature, and calculates the corrected dosing amount based on the deviation between the real-time pH value and the target pH value in the primary reaction zone. The baseline dosing amount and the corrected dosing amount are then superimposed to generate the final dosing amount instruction. The dosing actuator performs the dosing operation according to the final dosing amount instruction.

7. The method according to claim 6, characterized in that, It also includes the following steps: Implement adaptive sludge discharge control, including: Continuously monitor the sludge level in the clarifier; Calculate the sludge settling rate; Sludge discharge is initiated when either the sludge level reaches the upper threshold or the sludge settling rate falls below the minimum threshold.

8. The method according to claim 7, characterized in that, After the step of initiating sludge discharge, the method further includes: Sludge discharge will be turned off after a preset delay time or after the sludge level drops to the minimum threshold.

9. The method according to claim 6, characterized in that, It also includes the following steps: Implement anti-scaling and self-cleaning controls, including: Periodically calculate the Langrillly saturation index; When the Langerilla saturation index exceeds the preset warning value, the upper limit of lime dosage is automatically limited, and a high-pressure water flushing or acid washing program is initiated.

10. The method according to claim 6, characterized in that, It also includes the following steps: Implement linkage control of flocculation stirring intensity, including: Real-time monitoring of the turbidity and temperature of the incoming water; Increase the mixing intensity of the flocculation mixer under low temperature and low turbidity conditions, and decrease the mixing intensity of the flocculation mixer under high temperature and high turbidity conditions.

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