Reaction sedimentation tank sludge discharge control system and method under diffusion analysis

Abstract

The invention provides a reaction sedimentation tank sludge discharge control system and method under diffusion analysis, and relates to the technical field of water treatment.The method comprises the steps that multiple pieces of water source data of a target reaction sedimentation tank are collected; performing sludge precipitation simulation analysis to obtain a plurality of sludge precipitation simulation results; carrying out precipitation prediction to obtain a plurality of sludge precipitation prediction results; whether a first sludge precipitation prediction result in the multiple sludge precipitation prediction results meets a preset condition or not is judged, if not, an optimal sludge discharge control scheme is obtained through optimization, and sludge discharge control is carried out. The technical problem that in the prior art, due to the fact that traditional sludge discharge control depends on manual operation and lacks real-time data analysis and simulation prediction, the sludge discharge control efficiency is poor can be solved, automatic sludge discharge control is achieved through sludge precipitation simulation and prediction in combination with automatic data collection and processing, and the sludge discharge control efficiency is improved. And the efficiency and the accuracy of sludge discharge control are improved.

Description

Technical Field

[0001] The present application relates to the field of water treatment technology, and in particular to a reaction sedimentation tank sludge discharge control system and method under diffusion analysis. Background Art

[0002] In industrial production or manufacturing, water resources are an indispensable element. In order to efficiently utilize and protect water resources, these links tend to reduce the direct use of groundwater and tap water. It is usually chosen to directly extract water from rivers, and by adding coagulants and other chemical reagents, it undergoes sedimentation, filtration and strict sterilization to ensure that the water quality meets the strict requirements of circulating water systems, production water, chemical water equipment or boiler operation. During the sedimentation stage, impurities in the water body will gradually gather and settle to the bottom of the pool to form sludge. Traditional sludge discharge control relies on regular manual cleaning, which is time-consuming and laborious. Manual sludge cleaning makes it difficult to accurately control the amount and time of sludge discharge, which can easily cause water quality fluctuations. Due to the lack of precision in sludge discharge control, resources are wasted and the efficiency of emission control is low.

[0003] In summary, the existing technology has the technical problem that the efficiency of sludge emission control is poor because the traditional sludge emission control relies on manual operation and lacks real-time data analysis and simulation prediction. Summary of the invention

[0004] The purpose of this application is to provide a reaction sedimentation tank sludge discharge control system and method under diffusion analysis, so as to solve the technical problem in the prior art that the traditional sludge discharge control relies on manual operation and lacks real-time data analysis and simulation prediction, resulting in poor sludge discharge control efficiency.

[0005] In view of the above problems, the present application provides a reaction sedimentation tank sludge discharge control system and method under diffusion analysis.

[0006] In the first aspect, the present application provides a sludge discharge control system for a reaction sedimentation tank under diffusion analysis, wherein the sludge discharge control system for a reaction sedimentation tank under diffusion analysis includes: a water source data acquisition module, used to collect multiple water source data of a target reaction sedimentation tank; a simulation analysis module, used to perform sludge precipitation simulation analysis based on the diffusion analysis principle, combined with the multiple water source data and multiple historical emission control parameters, to obtain multiple sludge precipitation simulation results; a prediction model construction module, used to perform precipitation prediction according to the multiple sludge precipitation simulation results, to obtain multiple sludge precipitation prediction results; an emission control module, used to determine whether the first sludge precipitation prediction result among the multiple sludge precipitation prediction results meets the preset conditions, and if not, to optimize and obtain the optimal sludge emission control plan, and perform sludge emission control on the target reaction sedimentation tank.

[0007] In the second aspect, the present application also provides a sludge emission control method for a reaction sedimentation tank under diffusion analysis, wherein the sludge emission control method for a reaction sedimentation tank under diffusion analysis includes: collecting multiple water source data of a target reaction sedimentation tank; based on the principle of diffusion analysis, combining the multiple water source data and multiple historical emission control parameters, performing sludge sedimentation simulation analysis to obtain multiple sludge sedimentation simulation results; performing sedimentation prediction according to the multiple sludge sedimentation simulation results to obtain multiple sludge sedimentation prediction results; judging whether the first sludge sedimentation prediction result among the multiple sludge sedimentation prediction results meets the preset conditions, and if not, optimizing to obtain the optimal sludge emission control plan, and performing sludge emission control on the target reaction sedimentation tank.

[0008] One or more technical solutions provided in this application have at least the following technical effects or advantages: The water source data acquisition module is used to collect multiple water source data of the target reaction sedimentation tank; the simulation analysis module is used to perform sludge precipitation simulation analysis based on the diffusion analysis principle, combined with the multiple water source data and multiple historical emission control parameters, to obtain multiple sludge precipitation simulation results; the prediction model construction module is used to perform precipitation prediction based on the multiple sludge precipitation simulation results, and obtain multiple sludge precipitation prediction results; the emission control module is used to determine whether the first sludge precipitation prediction result among the multiple sludge precipitation prediction results meets the preset conditions. If not, the optimal sludge emission control plan is obtained by optimization, and sludge emission control is performed on the target reaction sedimentation tank. In other words, through sludge precipitation simulation and prediction, combined with automated data collection and processing, automated sludge emission control is achieved, and the efficiency and accuracy of sludge emission control are improved.

[0009] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented according to the contents of the specification, and in order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are specifically cited below. It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easy to understand through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0011] Figure 1This is a schematic diagram of the structure of a reaction sedimentation tank sludge discharge control system under diffusion analysis in this application; Figure 2 This is a schematic flow chart of a method for controlling sludge discharge from a reaction sedimentation tank under diffusion analysis in this application.

[0012] Explanation of the accompanying drawings: water source data collection module 11, simulation analysis module 12, prediction model construction module 13, emission control module 14. DETAILED DESCRIPTION

[0013] The present application provides a reaction sedimentation tank sludge discharge control system and method under diffusion analysis, which solves the technical problem in the prior art that the traditional sludge discharge control relies on manual operation and lacks real-time data analysis and simulation prediction, resulting in poor sludge discharge control efficiency. Through sludge sedimentation simulation and prediction, combined with automated data collection and processing, automated sludge discharge control is achieved, improving the efficiency and accuracy of sludge discharge control.

[0014] Below, the technical solutions in the present application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments of the present application. It should be understood that the present application is not limited to the example embodiments described herein. Based on the embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application. It should also be noted that, for the convenience of description, only the parts related to the present application are shown in the accompanying drawings, rather than all of them.

[0015] For example, please refer to the attached Figure 1 The present application provides a reaction sedimentation tank sludge discharge control system under diffusion analysis, wherein the reaction sedimentation tank sludge discharge control system under diffusion analysis is used to implement the steps of a reaction sedimentation tank sludge discharge control method under diffusion analysis, and the reaction sedimentation tank sludge discharge control system under diffusion analysis includes: The water source data collection module 11 is used to collect multiple water source data of the target reaction sedimentation tank.

[0016] Specifically, according to the monitoring target, select the corresponding sensors, such as pH sensors, turbidity sensors, COD sensors, flow meters, etc. According to the structure of the target reaction sedimentation tank, select a reasonable location to deploy sensors. For example, sensors are deployed at the water inlet of the reaction sedimentation tank to monitor the water quality and flow of the sedimentation tank, sensors are deployed at the outlet to monitor the treated water quality and flow, and sensors are deployed at different depths and positions of the sedimentation tank to monitor the distribution and changes of water quality parameters in the tank. Determine the appropriate sampling frequency based on the operating conditions and water quality changes of the sedimentation tank, and use standardized sampling methods to ensure the representativeness and accuracy of the samples. Collect water source data of the sedimentation tank, including but not limited to water quality parameters (such as pH value, turbidity, chemical oxygen demand, etc.), sludge parameters (such as sludge concentration, sludge volume, etc.) and hydrological parameters (such as flow, temperature, etc.). Since the characteristics of each sedimentation tank may be different, collecting data specific to the target reaction sedimentation tank helps to customize the control strategy and improve the control effect.

[0017] The simulation analysis module 12 is used to perform sludge sedimentation simulation analysis based on the diffusion analysis principle and in combination with the multiple water source data and multiple historical emission control parameters to obtain multiple sludge sedimentation simulation results.

[0018] Specifically, according to the principle of diffusion analysis, a simulation mathematical model is constructed to simulate the sedimentation behavior of sludge in the reaction sedimentation tank. The model's objectives and the main variables affecting sludge sedimentation are determined, appropriate mathematical equations are selected, boundary conditions and initial conditions are established, and the behavior and initial state of the model at the edge of the simulation area are defined. The model is calibrated through historical emission control parameters, and the model parameters are adjusted by comparing the simulation results with the actual measurement data until the simulation results match the actual data. The collected water source data and historical emission control parameters are input into the simulation mathematical model, and multiple sludge sedimentation simulation results are obtained through model operation, reflecting the sludge sedimentation under different emission control schemes. The simulation results under each scheme are recorded, including sludge concentration, sedimentation rate, and emission. By constructing an accurate simulation mathematical model for predicting and optimizing the sludge emission control of the target reaction sedimentation tank, the sludge emission control strategy can be optimized based on the simulation results, improving the treatment efficiency and reducing resource waste.

[0019] The prediction model building module 13 is used to perform precipitation prediction according to the multiple sludge precipitation simulation results to obtain multiple sludge precipitation prediction results.

[0020] Specifically, through multiple sludge emission control parameters, a suitable prediction model is selected to train the sludge precipitation prediction model. Multiple sludge precipitation results obtained by simulation mathematical models are respectively input into the sludge precipitation prediction model to obtain the corresponding sludge precipitation prediction results. Analyze the prediction results to understand the trend and pattern of sludge precipitation under different simulation conditions. For example, suppose that the sludge precipitation simulation results under different emission control parameters are obtained through simulation mathematical models. Analyze the sludge precipitation simulation results to predict the sludge precipitation under different control schemes. Predict how the speed and thickness of sludge precipitation will change when the emission frequency is increased. Through prediction, multiple sludge precipitation prediction results are obtained, such as the speed and thickness of sludge precipitation under different emission frequencies. Based on the prediction results, the advantages and disadvantages of different emission control schemes are evaluated to provide support for decision-making.

[0021] The emission control module 14 is used to determine whether the first sludge precipitation prediction result among the multiple sludge precipitation prediction results meets the preset conditions. If not, it seeks to obtain the optimal sludge emission control plan and performs sludge emission control on the target reaction sedimentation tank.

[0022] Specifically, it is determined whether each of the multiple sludge precipitation prediction results meets the preset conditions. If so, the sludge discharge control scheme corresponding to the sludge precipitation prediction result is used as the optimal sludge discharge control scheme to control the sludge discharge of the target reaction sedimentation tank. The preset conditions refer to a series of standards or goals used to determine whether the results are acceptable when evaluating the sludge precipitation prediction results, including indicators such as the efficiency, cost, and environmental impact of sludge discharge. If not, the sludge discharge control scheme of the sludge precipitation prediction result is evaluated. According to the evaluation results, the sludge discharge control scheme is optimized to obtain the optimal control scheme. The optimal control schemes obtained by the optimization corresponding to each sludge precipitation prediction result that does not meet the preset conditions are combined to form multiple optimal control schemes. The comprehensive performance scores of multiple optimal control schemes are calculated, and the scheme with the highest score is selected as the optimal sludge discharge control scheme. The optimal sludge discharge control scheme is implemented in the target reaction sedimentation tank, and the performance of the sedimentation tank is continuously monitored during implementation, and adjusted as needed. Through the optimal scheme that meets the preset conditions, sludge discharge is controlled and treatment efficiency is improved.

[0023] Furthermore, the water source data acquisition module 11 in the reaction sedimentation tank sludge discharge control system under the diffusion analysis is also used for: According to the monitoring target, the sensor type and the placement location are determined, and a sensor placement plan is formulated; based on the sensor placement plan, sensors are placed in the target reaction sedimentation tank to collect data and obtain the multiple water source data.

[0024] Specifically, determine the monitoring target, and according to the monitoring target, determine the water quality parameters and flow data that need to be monitored. Select the appropriate sensor type, such as pH sensor, turbidity sensor, flow sensor, temperature sensor, oxygen sensor, etc. According to the structure of the reaction tank, determine the location of the sensor to ensure that the selected sensor can accurately capture the required data, and the location can fully reflect the water quality and flow state of the sedimentation tank. Sensors are installed at the water inlet to monitor the quality and flow of raw water, and sensors are installed at the outlet to monitor the quality and flow of treated water. Sensors are installed at different depths and positions inside the sedimentation tank to monitor the distribution and changes of water quality parameters in the tank. Sensors are also required at key operating points, such as flocculant addition points and near stirring equipment.

[0025] Mark the specific location of each sensor on the plan and cross-section of the sedimentation tank to ensure that the sensor is not disturbed by the water flow and is easy to maintain. According to the layout plan, install the sensor at the predetermined location and connect the sensor to the data collector or SCADA system to ensure that the data can be transmitted and recorded in real time. Start data collection and set the appropriate sampling frequency. Monitor the quality of the collected data to ensure the accuracy and completeness of the data. Check the status of the sensor regularly and perform necessary maintenance and calibration. For example, in order to monitor the thickness of the sludge settled at the bottom, an ultrasonic sludge interface meter is selected as the sensor. The interface position between the sludge layer and the clear water layer is detected by emitting ultrasonic waves and measuring their reflected signals, thereby determining the sludge thickness. The ultrasonic sludge interface meter needs to be laid on the side or bottom of the sedimentation tank to ensure that the changes in the sludge layer can be accurately captured. By laying out sensors at key locations, the water quality and flow status of the sedimentation tank can be fully monitored to ensure that the collected data accurately reflects the actual situation of the sedimentation tank.

[0026] Furthermore, the simulation analysis module 12 in the reaction sedimentation tank sludge discharge control system under the diffusion analysis is also used for: Retrieve the historical emission control parameters of the target reaction sedimentation tank; establish boundary conditions and initial conditions based on the principle of diffusion analysis, and construct a simulation mathematical model, wherein the boundary conditions are the water inlet, water outlet and tank wall determined based on the geometric structure of the target reaction sedimentation tank; calibrate the model using the multiple historical emission control parameters; input the multiple water source data and the multiple historical emission control parameters into the simulation mathematical model to obtain the multiple sludge precipitation simulation results, wherein the multiple sludge precipitation simulation results include multiple simulation results corresponding to multiple sludge emission control schemes.

[0027] Specifically, historical emission control parameters, including sludge discharge frequency, discharge volume, water quality parameters, etc., are extracted from the operation records or database of the sedimentation tank. Boundary conditions are determined based on the geometric structure of the target reaction sedimentation tank (such as the water inlet, water outlet, and tank wall), and water quality parameters and sludge distribution at the beginning of the simulation are set. According to the principle of diffusion analysis, appropriate mathematical equations are selected to describe the movement of sludge particles in the water flow. The model is calibrated using historical emission control parameters to ensure that the model can accurately reflect the actual sedimentation process. By comparing the simulation results with the actual measured data, the model parameters are adjusted until the simulation results match the actual data. The collected multiple water source data and multiple historical emission control parameters are input into the simulation mathematical model, and the simulation model is run to simulate the sludge sedimentation process under different emission control schemes. The simulation results under each scheme are recorded, including sludge concentration, sedimentation rate, and discharge volume. Multiple sludge sedimentation simulation results reflect the sludge sedimentation under different emission control schemes. Analyze multiple sludge sedimentation simulation results, understand the impact of different emission control schemes on the sedimentation process, and identify the best and worst emission control schemes. By establishing an accurate simulation model to simulate the sludge sedimentation under different emission control schemes, it is used to predict and optimize the sludge emission control of the target reaction sedimentation tank, which helps to improve the water treatment efficiency.

[0028] Furthermore, the prediction model building module 13 in the reaction sedimentation tank sludge discharge control system under the diffusion analysis is also used for: The data processing center performs data preprocessing on multiple sludge discharge control parameters to obtain a first control data set; the first control data set is trained and tested according to a neural network to generate the sludge sedimentation prediction model; the multiple sludge sedimentation simulation results are input into the sludge sedimentation prediction model to obtain the multiple sludge sedimentation prediction results.

[0029] Specifically, multiple sludge discharge control parameters are input into the data processing center for data preprocessing to remove outliers, missing values ​​and inconsistent data to ensure data quality. The data is normalized or standardized to convert the data into a format suitable for neural network processing. Features that have a significant impact on sludge sedimentation are selected from multiple sludge discharge control parameters to obtain the first control data set. The processed data are divided into a training set, a validation set and a test set. The neural network model is a computational model that imitates the way neurons in the human brain are connected. A large number of simple units (called neurons) are interconnected to form a complex network structure for performing various complex computing tasks. Select a suitable neural network structure, including the number of layers, the number of neurons, the activation function, etc. Use the first control data set to train the neural network and adjust the network weights and biases until the network loss on the training set drops to an acceptable level.

[0030] Use the validation set to adjust the network parameters to prevent overfitting. Use the test set to evaluate the generalization ability of the neural network to ensure that the model has good prediction performance. After the neural network training is completed, save the trained model parameters and deploy the model to the prediction system to predict sludge precipitation. Input multiple sludge precipitation simulation results as input data into the sludge precipitation prediction model, run the prediction model, process the input data, and obtain the prediction results of sludge precipitation. Analyze the prediction results to understand the impact of different control parameters on sludge precipitation. The prediction model trained by the neural network can more accurately predict the sludge precipitation situation, thereby improving the accuracy of emission control.

[0031] Furthermore, the emission control module 14 in the reaction sedimentation tank sludge emission control system under the diffusion analysis is also used for: Analyze the first sludge sedimentation prediction result to obtain a first sludge discharge control plan; evaluate the first sludge discharge control plan to obtain a first control evaluation result; based on the first control evaluation result, optimize the first sludge discharge control plan to obtain a first optimal control plan, and form multiple optimal control plans; calculate the comprehensive performance scores of the multiple optimal control plans, sort them in descending order, and extract the first plan as the optimal sludge discharge control plan.

[0032] Specifically, a sludge precipitation prediction result is randomly selected from multiple sludge precipitation prediction results and analyzed in detail. Based on the prediction results, a first sludge discharge control plan is initially formulated, including specific discharge frequency, discharge volume, flocculant addition amount, etc. The performance indicators of the evaluation plan, such as sludge treatment efficiency, cost, environmental impact, etc., are determined. The first sludge discharge control plan is evaluated using a preset evaluation method to obtain a first control evaluation result. Based on the first control evaluation result, the first sludge discharge control plan is optimized using an optimization algorithm, such as a genetic algorithm, a particle swarm optimization, a simulated annealing, etc. Through multiple iterations, the control parameters are adjusted to obtain the optimal control plan, which has the best performance under the current evaluation criteria. The sludge precipitation prediction results are optimized to obtain the optimal control plan, and a plan set is formed to ensure that the plans in the plan set have sufficient diversity in control parameters to avoid falling into a local optimum. A standard for comprehensive performance scoring is formulated, including technical, economic, environmental and social factors. A comprehensive performance score is given to each optimal control plan, and multiple optimal control plans are sorted in descending order according to the comprehensive performance score. The scheme with the highest comprehensive performance score is extracted from the sorted schemes, i.e. the first scheme, as the optimal sludge discharge control scheme. Through evaluation and optimization, the sludge discharge control scheme is selected to improve the accuracy and effectiveness of decision-making. The optimal control scheme can improve the sludge treatment efficiency.

[0033] Furthermore, the emission control module 14 in the reaction sedimentation tank sludge emission control system under the diffusion analysis is also used for: Acquire a sludge discharge assessment record set; train a sludge discharge assessment model based on the sludge discharge assessment record set; input the first sludge discharge control plan into the sludge discharge assessment model to obtain the first control assessment result.

[0034] Specifically, the evaluation records of sludge discharge are collected from the operation records, monitoring data and environmental reports of the sedimentation tank, including the effect evaluation, cost, environmental impact, etc. of different emission control schemes. The collected data are sorted to ensure the consistency and integrity of the data to form a sludge discharge evaluation record set. Features related to sludge discharge evaluation, such as sludge discharge volume, discharge frequency, treatment efficiency, environmental impact indicators, etc., are selected from the evaluation record set. The evaluation record set is preprocessed, including data cleaning, normalization or standardization. A suitable machine learning model is selected for training, such as random forest, support vector machine, etc. The sludge discharge evaluation model is trained using the preprocessed data set, and the model performance is optimized by adjusting the model parameters. The accuracy and generalization ability of the model are evaluated by cross-validation or other validation methods. The relevant parameters of the first sludge discharge control scheme are input into the trained sludge discharge evaluation model, and the evaluation results are calculated by the internal algorithm. The first control evaluation result calculated by the model is output, which reflects the performance of the first sludge discharge control scheme in various evaluation indicators. Similar operations are performed for other schemes, and finally the evaluation results of each scheme are obtained, reflecting the possible effects and performance of the corresponding scheme. By training the evaluation model, the automatic evaluation of the sludge discharge control scheme is realized. The new control scheme is evaluated through the model, which provides a basis for selecting the optimal sludge discharge control scheme.

[0035] Furthermore, the emission control module 14 in the reaction sedimentation tank sludge emission control system under the diffusion analysis is also used for: If the first sludge sedimentation prediction result meets the preset condition, the first sludge sedimentation prediction result and the first emission control parameter are recorded, and the first sludge sedimentation control scheme is obtained, which is used as the optimal sludge emission control scheme; based on the optimal sludge emission control scheme, sludge emission control is performed on the target reaction sedimentation tank.

[0036] Specifically, according to the preset standards or goals, evaluate whether the first sludge precipitation prediction result achieves the expected effect. These preset conditions include indicators such as efficiency, cost, and environmental impact of sludge discharge. When the first sludge precipitation prediction result meets the preset conditions, record these prediction results and the corresponding emission control parameters. Integrate the recorded first sludge precipitation prediction result and the first emission control parameter to form a first sludge precipitation control plan. Since the first sludge precipitation prediction result has met the preset conditions, this plan can be directly marked as the optimal sludge emission control plan. Deploy the optimal sludge emission control plan to the control system of the target reaction sedimentation tank. According to the control parameters in the plan, guide the operator to adjust the operation settings of the sedimentation tank. During the implementation process, monitor the operating status of the sedimentation tank in real time to ensure the effective implementation of the control plan. According to the actual operation situation, make necessary adjustments and optimizations to the control plan. According to the optimal control plan, accurately control the sludge discharge to ensure that the emission behavior meets the preset standards and conditions. Regularly evaluate the effect of sludge emission control and management to ensure that the treatment efficiency and environmental benefits meet the expected goals. Based on the evaluation results, continuously improve the sludge emission control plan to adapt to possible changes and new requirements. Through the optimal solution that meets the preset conditions, sludge discharge can be effectively controlled and treatment efficiency can be improved.

[0037] In summary, the sludge discharge control system for a reaction sedimentation tank under diffusion analysis provided by this application has the following technical effects: The water source data acquisition module is used to collect multiple water source data of the target reaction sedimentation tank; the simulation analysis module is used to perform sludge precipitation simulation analysis based on the diffusion analysis principle, combined with the multiple water source data and multiple historical emission control parameters, to obtain multiple sludge precipitation simulation results; the prediction model construction module is used to perform precipitation prediction based on the multiple sludge precipitation simulation results, and obtain multiple sludge precipitation prediction results; the emission control module is used to determine whether the first sludge precipitation prediction result among the multiple sludge precipitation prediction results meets the preset conditions. If not, the optimal sludge emission control plan is obtained by optimization, and sludge emission control is performed on the target reaction sedimentation tank. In other words, through sludge precipitation simulation and prediction, combined with automated data collection and processing, automated sludge emission control is achieved, and the efficiency and accuracy of sludge emission control are improved.

[0038] Embodiment 2, based on the same inventive concept as the control system for sludge discharge from a reaction sedimentation tank under diffusion analysis in the above embodiment, the present application also provides a method for controlling sludge discharge from a reaction sedimentation tank under diffusion analysis, please refer to the attached Figure 2 The method for controlling the discharge of sludge from a reaction sedimentation tank under diffusion analysis includes: Collect multiple water source data of the target reaction sedimentation tank; based on the principle of diffusion analysis, combine the multiple water source data and multiple historical emission control parameters to perform sludge sedimentation simulation analysis to obtain multiple sludge sedimentation simulation results; perform sedimentation prediction according to the multiple sludge sedimentation simulation results to obtain multiple sludge sedimentation prediction results; determine whether the first sludge sedimentation prediction result among the multiple sludge sedimentation prediction results meets the preset conditions. If not, find the optimal sludge emission control plan to control the sludge emission of the target reaction sedimentation tank.

[0039] Further, the multiple water source data of the target reaction sedimentation tank are collected, including: According to the monitoring target, the sensor type and the placement location are determined, and a sensor placement plan is formulated; based on the sensor placement plan, sensors are placed in the target reaction sedimentation tank to collect data and obtain the multiple water source data.

[0040] Furthermore, the sludge sedimentation simulation analysis is performed to obtain a plurality of sludge sedimentation simulation results, including: Retrieve the historical emission control parameters of the target reaction sedimentation tank; establish boundary conditions and initial conditions based on the principle of diffusion analysis, and construct a simulation mathematical model, wherein the boundary conditions are the water inlet, water outlet and tank wall determined based on the geometric structure of the target reaction sedimentation tank; calibrate the model using the multiple historical emission control parameters; input the multiple water source data and the multiple historical emission control parameters into the simulation mathematical model to obtain the multiple sludge precipitation simulation results, wherein the multiple sludge precipitation simulation results include multiple simulation results corresponding to multiple sludge emission control schemes.

[0041] Further, the performing of precipitation prediction according to the multiple sludge precipitation simulation results to obtain multiple sludge precipitation prediction results includes: The data processing center performs data preprocessing on multiple sludge discharge control parameters to obtain a first control data set; the first control data set is trained and tested according to a neural network to generate the sludge sedimentation prediction model; the multiple sludge sedimentation simulation results are input into the sludge sedimentation prediction model to obtain the multiple sludge sedimentation prediction results.

[0042] Further, the determining whether the first sludge precipitation prediction result among the plurality of sludge precipitation prediction results meets a preset condition, and if not, optimizing to obtain an optimal sludge discharge control scheme includes: Analyze the first sludge sedimentation prediction result to obtain a first sludge discharge control plan; evaluate the first sludge discharge control plan to obtain a first control evaluation result; based on the first control evaluation result, optimize the first sludge discharge control plan to obtain a first optimal control plan, and form multiple optimal control plans; calculate the comprehensive performance scores of the multiple optimal control plans, sort them in descending order, and extract the first plan as the optimal sludge discharge control plan.

[0043] Further, the evaluating the first sludge discharge control scheme to obtain a first control evaluation result includes: Acquire a sludge discharge assessment record set; train a sludge discharge assessment model based on the sludge discharge assessment record set; input the first sludge discharge control plan into the sludge discharge assessment model to obtain the first control assessment result.

[0044] Further, the determining whether the first sludge precipitation prediction result among the plurality of sludge precipitation prediction results meets a preset condition includes: If the first sludge sedimentation prediction result meets the preset condition, the first sludge sedimentation prediction result and the first emission control parameter are recorded, and the first sludge sedimentation control scheme is obtained, which is used as the optimal sludge emission control scheme; based on the optimal sludge emission control scheme, sludge emission control is performed on the target reaction sedimentation tank.

[0045] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. Figure 1 The control system for sludge discharge from a reaction sedimentation tank under a diffusion analysis and the specific examples in Example 1 are also applicable to a method for controlling sludge discharge from a reaction sedimentation tank under a diffusion analysis in this embodiment. Through the detailed description of the control system for sludge discharge from a reaction sedimentation tank under a diffusion analysis, those skilled in the art can clearly know the method for controlling sludge discharge from a reaction sedimentation tank under a diffusion analysis in this embodiment, so for the sake of brevity of the specification, it will not be described in detail here. For the method disclosed in the embodiment, since it corresponds to the system disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the description of the system part.

[0046] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

[0047] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application belong to the scope of the present application and its equivalent technology, the present application is also intended to include these modifications and variations.

Claims

1. A reaction sedimentation tank sludge discharge control system under diffusion analysis, characterized in that: include: A water source data collection module is used to collect multiple water source data of the target reaction sedimentation tank; A simulation analysis module, for performing sludge sedimentation simulation analysis based on the diffusion analysis principle and combining the plurality of water source data and the plurality of historical emission control parameters to obtain a plurality of sludge sedimentation simulation results; A prediction model building module, used to perform precipitation prediction according to the multiple sludge precipitation simulation results to obtain multiple sludge precipitation prediction results; The emission control module is used to determine whether the first sludge precipitation prediction result among the multiple sludge precipitation prediction results meets the preset conditions. If not, the optimal sludge emission control plan is obtained by optimization to control the sludge emission of the target reaction sedimentation tank.

2. The sludge discharge control system of a reaction sedimentation tank under diffusion analysis according to claim 1 is characterized in that: The water source data acquisition module is also used for: Determine the sensor type and location according to the monitoring objectives, and develop a sensor deployment plan; Based on the sensor deployment scheme, sensors are deployed in the target reaction sedimentation tank to collect data and obtain the multiple water source data.

3. The sludge discharge control system of a reaction sedimentation tank under diffusion analysis according to claim 1 is characterized in that: The simulation analysis module is also used for: Retrieving the historical emission control parameters of the target reaction sedimentation tank; Based on the principle of diffusion analysis, boundary conditions and initial conditions are established to construct a simulation mathematical model, wherein the boundary conditions are the water inlet, water outlet and pool wall determined based on the geometric structure of the target reaction sedimentation pool; calibrating the model using the plurality of historical emission control parameters; The multiple water source data and the multiple historical emission control parameters are input into the simulation mathematical model to obtain the multiple sludge sedimentation simulation results, wherein the multiple sludge sedimentation simulation results include multiple simulation results corresponding to multiple sludge emission control schemes.

4. The sludge discharge control system of a reaction sedimentation tank under diffusion analysis according to claim 3 is characterized in that: The prediction model building module is also used to: Performing data preprocessing on a plurality of sludge discharge control parameters through a data processing center to obtain a first control data set; Training and testing the first control data set according to a neural network to generate the sludge precipitation prediction model; The multiple sludge precipitation simulation results are input into the sludge precipitation prediction model to obtain the multiple sludge precipitation prediction results.

5. The sludge discharge control system of a reaction sedimentation tank under diffusion analysis according to claim 4 is characterized in that: The emission control module is also used to: Analyzing the first sludge precipitation prediction result to obtain a first sludge discharge control plan; Evaluate the first sludge discharge control plan to obtain a first control evaluation result; Based on the first control evaluation result, optimizing the first sludge discharge control scheme to obtain a first optimal control scheme, and forming multiple optimal control schemes; The comprehensive performance scores of the multiple optimal control schemes are calculated, sorted in descending order, and the top scheme is extracted as the optimal sludge discharge control scheme.

6. The sludge discharge control system of a reaction sedimentation tank under diffusion analysis according to claim 5 is characterized in that: The emission control module is also used to: Obtain sludge discharge assessment record set; Based on the sludge discharge assessment record set, training a sludge discharge assessment model; The first sludge discharge control plan is input into the sludge discharge evaluation model to obtain the first control evaluation result.

7. The sludge discharge control system of a reaction sedimentation tank under diffusion analysis according to claim 1 is characterized in that: The emission control module is also used to: If the first sludge precipitation prediction result meets the preset condition, the first sludge precipitation prediction result and the first emission control parameter are recorded, and the first sludge precipitation control scheme is obtained, and the first sludge emission control scheme is used as the optimal sludge emission control scheme; Based on the optimal sludge discharge control scheme, sludge discharge from the target reaction sedimentation tank is controlled.

8. A method for controlling sludge discharge from a reaction sedimentation tank under diffusion analysis, characterized in that: The method is implemented by a reaction sedimentation tank sludge discharge control system under a diffusion analysis according to any one of claims 1 to 7, wherein the reaction sedimentation tank sludge discharge control method under a diffusion analysis comprises: Collect multiple water source data of the target reaction sedimentation tank; Based on the diffusion analysis principle, the sludge sedimentation simulation analysis is performed in combination with the multiple water source data and multiple historical emission control parameters to obtain multiple sludge sedimentation simulation results; Performing sedimentation prediction according to the multiple sludge sedimentation simulation results to obtain multiple sludge sedimentation prediction results; Determine whether a first sludge precipitation prediction result among the multiple sludge precipitation prediction results meets a preset condition. If not, find an optimal sludge discharge control plan to control sludge discharge from the target reaction sedimentation tank.

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