Wastewater treatment control optimization method and system based on monitoring data

Abstract

The present application provides a wastewater treatment control optimization method and system based on monitoring data, which relates to the field of wastewater treatment technology, including: obtaining wastewater treatment process nodes, monitoring wastewater treatment process nodes to generate real-time monitoring process data; determining wastewater treatment process benchmarks, making compliance judgments on real-time monitoring process data based on wastewater treatment process benchmarks, and obtaining first judgment results; extracting abnormal nodes according to the first judgment results, and compensating the next node of the abnormal node to obtain a second judgment result; and optimizing the control of wastewater treatment process nodes according to the second judgment results. This application can solve the technical problem in the prior art that the effects of optimization measures are difficult to evaluate in real time due to the imperfect dynamic monitoring feedback mechanism, and realize the technical goal of a wastewater treatment optimization system with dynamic monitoring and real-time feedback, so as to achieve the technical effect of improving treatment efficiency and ensuring that the effluent water quality is stable and up to standard.

Description

Technical Field

[0001] The present application relates to the technical field of wastewater treatment, and in particular to a wastewater treatment control optimization method and system based on monitoring data. Background Art

[0002] With the acceleration of industrial and urbanization, wastewater treatment has become an important task in environmental protection. Existing wastewater treatment systems usually adopt a multi-stage treatment process to ensure that wastewater meets discharge standards through treatment at each stage.

[0003] However, the existing technology has some defects in the treatment process. It usually lacks a dynamic monitoring and feedback mechanism, and the effect of optimization measures is difficult to track and evaluate in real time, resulting in low system operation efficiency and unstable treatment effect. This limits the overall performance improvement of the wastewater treatment system and cannot fully cope with the complex and changing wastewater treatment needs. Therefore, there is an urgent need for a wastewater treatment optimization system that can monitor and adjust dynamically in real time to improve treatment efficiency and effect and ensure that the effluent water quality is stable and meets the standards.

[0004] In summary, there are technical problems in the prior art that the dynamic monitoring feedback mechanism is imperfect, which makes it difficult to evaluate the effects of optimization measures in real time, further affecting the overall performance of the wastewater treatment system and the stability of the effluent water quality. Summary of the invention

[0005] The purpose of this application is to provide a wastewater treatment control optimization method and system based on monitoring data, so as to solve the technical problem in the prior art that due to the imperfect dynamic monitoring feedback mechanism, the effects of optimization measures are difficult to evaluate in real time, which further affects the overall performance of the wastewater treatment system and the stability of the effluent water quality.

[0006] In view of the above problems, the present application provides a wastewater treatment control optimization method and system based on monitoring data.

[0007] In the first aspect, the present application provides a wastewater treatment control optimization method based on monitoring data, which is implemented through a wastewater treatment control optimization system based on monitoring data, including: obtaining wastewater treatment process nodes, monitoring the wastewater treatment process nodes to generate real-time monitoring process data; determining a wastewater treatment process benchmark, and making a compliance judgment on the real-time monitoring process data based on the wastewater treatment process benchmark to obtain a first judgment result; extracting abnormal nodes based on the first judgment result, and compensating the next node of the abnormal node to obtain a second judgment result; and optimizing the control of the wastewater treatment process nodes based on the second judgment result.

[0008] In the second aspect, the present application also provides a wastewater treatment control optimization system based on monitoring data, which is used to execute the wastewater treatment control optimization method based on monitoring data as described in the first aspect, including: a real-time monitoring process data generation module, the real-time monitoring process data generation module is used to obtain wastewater treatment process nodes, monitor the wastewater treatment process nodes to generate real-time monitoring process data; a first judgment result acquisition module, the first judgment result acquisition module is used to determine the wastewater treatment process benchmark, and perform a compliance judgment on the real-time monitoring process data based on the wastewater treatment process benchmark to obtain a first judgment result; a second judgment result acquisition module, the second judgment result acquisition module is used to extract abnormal nodes according to the first judgment result, and compensate the next node of the abnormal node to obtain a second judgment result; a control optimization module, the control optimization module is used to perform control optimization of the wastewater treatment process nodes according to the second judgment result.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0010] By acquiring wastewater treatment process nodes, the wastewater treatment process nodes are monitored to generate real-time monitoring process data; the wastewater treatment process benchmark is determined, and the compliance judgment of the real-time monitoring process data based on the wastewater treatment process benchmark is obtained to obtain a first judgment result; according to the first judgment result, abnormal nodes are extracted, and the next node of the abnormal node is compensated to obtain a second judgment result; according to the second judgment result, the control optimization of the wastewater treatment process nodes is performed to achieve the technical goal of the wastewater treatment optimization system with dynamic monitoring and real-time feedback, and achieve the technical effect of improving treatment efficiency and ensuring that the effluent water quality is stable and meets the standards.

[0011] 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

[0012] 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.

[0013] Figure 1 A schematic diagram of the process of the wastewater treatment control optimization method based on monitoring data in this application;

[0014] Figure 2 This is a schematic diagram of the structure of the wastewater treatment control optimization system based on monitoring data in this application.

[0015] Description of reference numerals:

[0016] A real-time monitoring process data generating module 11 , a first judgment result obtaining module 12 , a second judgment result obtaining module 13 , and a control optimization module 14 . DETAILED DESCRIPTION

[0017] This application provides a wastewater treatment control optimization method and system based on monitoring data, which solves the technical problem in the prior art that the effect of optimization measures is difficult to evaluate in real time due to the imperfect dynamic monitoring feedback mechanism, further affecting the overall performance of the wastewater treatment system and the stability of the effluent water quality. The technical goal of the wastewater treatment optimization system with dynamic monitoring and real-time feedback is achieved, and the technical effect of improving treatment efficiency and ensuring that the effluent water quality is stable and meets the standards is achieved.

[0018] 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.

[0019] For example, please refer to the attached Figure 1 The present application provides a wastewater treatment control optimization method based on monitoring data, which is applied to a wastewater treatment control optimization system based on monitoring data, specifically including:

[0020] Step 1: Obtain wastewater treatment process nodes, monitor the wastewater treatment process nodes and generate real-time monitoring process data.

[0021] Specifically, in the process of wastewater treatment, the wastewater treatment process nodes are obtained. For example, the wastewater treatment process nodes include processing nodes such as screens, grit chambers, primary sedimentation tanks, aerobic tanks, anaerobic tanks, secondary sedimentation tanks, filtration equipment, and disinfection equipment. Monitoring the wastewater treatment process nodes refers to installing various sensors and monitoring equipment at the wastewater treatment process nodes to detect various indicators of wastewater in real time, such as flow, pH value, dissolved oxygen, COD, BOD, ammonia nitrogen, total phosphorus, total nitrogen, suspended solids, temperature, etc. Monitoring equipment includes online sensors, automatic samplers, data acquisition systems, etc. Through monitoring equipment, real-time data of wastewater in different treatment links can be obtained, accurately reflecting the dynamic changes of wastewater treatment, and generating real-time monitoring process data, which is to process and store the data collected by the monitoring equipment in real time to form a series of real-time monitoring process data.

[0022] Step 2: Determine a wastewater treatment process benchmark, and make a compliance judgment on the real-time monitoring process data based on the wastewater treatment process benchmark to obtain a first judgment result.

[0023] Specifically, determining the wastewater treatment process benchmark is an important part of the design and operation of the wastewater treatment system, including pretreatment benchmark, primary treatment benchmark, secondary treatment benchmark, tertiary treatment benchmark and subsequent treatment benchmark, and each benchmark value corresponds to a key indicator in the treatment process. For example, the pretreatment benchmark may include the removal rate of suspended solids, the primary treatment benchmark may include the reduction rate of BOD and COD, the secondary treatment benchmark may include the removal rate of ammonia nitrogen and total phosphorus, the tertiary treatment benchmark may include the removal rate of trace organic matter and heavy metals, and the subsequent treatment benchmark may include the disinfection effect of the final effluent water quality. The effectiveness and compliance of the wastewater treatment process can be ensured by determining the benchmark value. The real-time monitoring process data is judged based on the wastewater treatment process benchmark. Monitoring equipment is installed at each treatment node to collect wastewater water quality parameters in real time, such as flow, pH value, dissolved oxygen, COD, BOD, ammonia nitrogen, total phosphorus, suspended solids, etc., and the real-time monitoring data is compared with the corresponding treatment benchmark to determine whether the current treatment process meets the preset standards. For example, if the COD value of a certain treatment node is higher than the preset benchmark, an alarm can be issued immediately to prompt the operator to make adjustments. Through real-time comparison and judgment methods, abnormal situations in the processing process can be discovered and corrected in a timely manner, improving processing efficiency and effectiveness. By making compliance judgments on the real-time monitoring data of each processing node, the processing results of each node can be obtained, forming the first judgment result of the entire processing system.

[0024] Step three: extracting abnormal nodes according to the first judgment result, and compensating the next node of the abnormal node to obtain a second judgment result.

[0025] Specifically, abnormal nodes are extracted according to the first judgment result. In the wastewater treatment process, by analyzing the monitoring data of each processing node, nodes with abnormal conditions are identified, and the first judgment result is obtained, which includes data on whether each processing node meets the preset benchmark. Nodes with substandard treatment effects can be determined and marked as abnormal nodes. Specific methods for extracting abnormal nodes include checking whether the monitoring data exceeds the benchmark value range, analyzing the downward trend of treatment efficiency, or detecting abnormal operating parameters, etc., and correcting the abnormal situation by adjusting the operating parameters or processing methods of the next processing node. Evaluate the compensation effect, determine whether the compensation is successful, and obtain the second judgment result.

[0026] Step 4: Optimize the control of the wastewater treatment process nodes according to the second judgment result.

[0027] Specifically, the second judgment result, i.e., the evaluation result of the compensation effect, is used to adjust and optimize the operating parameters and operation methods of each processing node to ensure that the operating status and treatment effect of each processing node are optimal. For example, if the second judgment result shows that the treatment effect of the primary processing node is not good, it may be necessary to adjust the filter aperture of the primary processing node or the residence time of the sedimentation tank to improve the removal rate of large suspended solids. By optimizing and adjusting each processing node, the efficiency and effect of the entire wastewater treatment system can be effectively improved.

[0028] The wastewater treatment control optimization method based on monitoring data is applied to the wastewater treatment control optimization system based on monitoring data, which can achieve the technical goals of the wastewater treatment optimization system with dynamic monitoring and real-time feedback, and achieve the technical effect of improving treatment efficiency and ensuring that the effluent water quality is stable and meets the standards.

[0029] Furthermore, the present application also includes:

[0030] The wastewater treatment process nodes include pretreatment nodes, primary treatment nodes, secondary treatment nodes, tertiary treatment nodes and subsequent treatment nodes; the pretreatment nodes, primary treatment nodes, secondary treatment nodes, tertiary treatment nodes and subsequent treatment nodes are monitored in real time to obtain real-time monitoring pretreatment data, real-time monitoring primary treatment data, real-time monitoring secondary treatment data, real-time monitoring tertiary treatment data and real-time monitoring subsequent treatment data respectively; the wastewater treatment process benchmark includes pretreatment benchmark, primary treatment benchmark, secondary treatment benchmark, tertiary treatment benchmark and subsequent treatment benchmark; according to the real-time monitoring pretreatment data, real-time monitoring primary treatment data, real-time monitoring secondary treatment data, real-time monitoring tertiary treatment data and real-time monitoring subsequent treatment data, a compliance judgment based on the pretreatment benchmark, primary treatment benchmark, secondary treatment benchmark, tertiary treatment benchmark and subsequent treatment benchmark is performed to obtain an abnormal result of the wastewater treatment process or a normal result of the wastewater treatment process; the abnormal result of the wastewater treatment process and the normal result of the wastewater treatment process are added to the first judgment result.

[0031] Specifically, the wastewater treatment process nodes include pretreatment nodes, primary treatment nodes, secondary treatment nodes, tertiary treatment nodes and subsequent treatment nodes. The wastewater treatment process nodes represent the main stages in the wastewater treatment process. Pretreatment nodes are used to remove large particles and suspended matter, primary treatment nodes remove suspended solids and some organic matter, secondary treatment nodes remove most organic matter through biological treatment, tertiary treatment nodes further remove residual pollutants and special pollutants, and subsequent treatment nodes include disinfection and sludge treatment. The setting of each node ensures the integrity and effectiveness of the wastewater treatment process.

[0032] Then, the pre-treatment nodes, primary treatment nodes, secondary treatment nodes, tertiary treatment nodes and subsequent treatment nodes are monitored in real time to obtain real-time monitoring pre-treatment data, real-time monitoring primary treatment data, real-time monitoring secondary treatment data, real-time monitoring tertiary treatment data and real-time monitoring subsequent treatment data. Corresponding monitoring equipment is installed at each wastewater treatment process node to collect water quality index data in real time, such as flow rate, pH value, dissolved oxygen, COD, BOD, etc.

[0033] Next, the wastewater treatment process benchmark includes pretreatment benchmark, primary treatment benchmark, secondary treatment benchmark, tertiary treatment benchmark and subsequent treatment benchmark. The wastewater treatment process benchmark is determined according to the design requirements of the industry standard or obtained by technical personnel in the field of technology through custom settings according to actual conditions. Each wastewater treatment process benchmark reflects the treatment effect and water quality indicators that should be achieved at the wastewater treatment process node. For example, the pretreatment benchmark may include suspended solids removal rate, the primary treatment benchmark may include BOD and COD reduction rate, and the secondary treatment benchmark may include further reduction of organic matter and ammonia nitrogen and other indicators. By setting the wastewater treatment process benchmark, the standardization and standardization of the treatment process can be ensured.

[0034] Next, according to the real-time monitoring pretreatment data, real-time monitoring primary treatment data, real-time monitoring secondary treatment data, real-time monitoring tertiary treatment data and real-time monitoring subsequent treatment data, the compliance judgment based on the pretreatment benchmark, primary treatment benchmark, secondary treatment benchmark, tertiary treatment benchmark and subsequent treatment benchmark is performed, and the real-time monitoring data is compared with the benchmark of the corresponding node to judge whether the treatment effect meets the standard, and obtain the abnormal result of the wastewater treatment process or the normal result of the wastewater treatment process. If the data of a certain node does not meet the benchmark, it is judged as an abnormal result of the wastewater treatment process, otherwise it is a normal result of the wastewater treatment process.

[0035] By monitoring the data of each node in real time, compliance judgments are made based on the corresponding processing benchmarks, abnormal or normal results of the processing flow are obtained and added to the overall judgment, forming a complete monitoring and management closed loop to ensure efficient, stable and compliant operation of the wastewater treatment system.

[0036] Furthermore, the present application also includes:

[0037] According to the abnormal result of the wastewater treatment process, an abnormal node is obtained, and abnormal data of the abnormal node is extracted; according to the abnormal node, the next node of the abnormal node is extracted, the abnormal data is compensated through the next node, and it is determined whether the abnormal data is compensated, and the second judgment result is obtained.

[0038] Specifically, in the wastewater treatment process, abnormal nodes are obtained based on the abnormal results of the wastewater treatment process. Abnormal nodes refer to wastewater treatment process nodes where the real-time monitoring data in the abnormal results of the wastewater treatment process fails to meet the wastewater treatment process benchmark. For example, if the COD value detected at the primary treatment node exceeds the benchmark value, the primary treatment node is marked as an abnormal node. By identifying abnormal nodes, resources and energy can be concentrated on problem investigation and processing to avoid the spread of problems.

[0039] Then, extracting abnormal data of abnormal nodes means obtaining specific abnormal indicator values ​​and related data from marked abnormal nodes. These data include the value, timestamp, impact range, etc. of abnormal indicators. For example, the COD value detected at the primary processing node, the change trend of the value, the specific time when the abnormality occurred, etc. Extracting abnormal data helps to deeply analyze the cause of the problem and provide a basis for subsequent compensation and adjustment.

[0040] Next, the next node of the abnormal node is extracted based on the abnormal node. The next node refers to the processing node that is determined to be immediately after the abnormal node in the processing flow. For example, if an abnormality occurs in the primary processing node, its next node may be a secondary processing node. By determining the next node, targeted processing adjustments can be made to ensure the continuity and effectiveness of the overall process.

[0041] Next, the abnormal data is compensated through the next node. Compensation means that after the abnormal data is discovered, the abnormality is corrected by adjusting the processing parameters or methods of the next node. For example, if the COD value of the primary treatment node is too high, the aeration volume can be increased or the microbial population can be adjusted in the secondary treatment node to enhance the degradation of organic matter and compensate for the deficiency of primary treatment. Compensation measures need to be reasonably selected and implemented according to the specific situation of the abnormal data and the design characteristics of the treatment system.

[0042] Then, judging whether the abnormal data has been compensated means that after implementing the compensation measures, the effectiveness of the compensation measures is evaluated by monitoring and analyzing the treatment effect of the next node, and the second judgment result is obtained. If the monitoring data of the next node shows that the abnormal data has been effectively compensated, for example, the COD value has dropped to the normal range, then the compensation is successful; otherwise, further adjustment measures or finding other root causes of the problem are required. The treatment process can be dynamically adjusted to ensure that the final effluent water quality meets the standard.

[0043] By identifying abnormal nodes, extracting abnormal data, determining the next node and implementing compensation measures, and evaluating the compensation effect, a closed-loop abnormality handling process can be formed, which can not only timely discover and handle abnormal situations in the wastewater treatment process, but also ensure the overall stability and treatment effect of the treatment system through dynamic adjustment. Through the second judgment result, managers can make more scientific and effective decisions to improve the overall efficiency and reliability of the wastewater treatment system.

[0044] Furthermore, the present application also includes:

[0045] If the second judgment result is that the abnormal data is compensated, the wastewater treatment control is performed according to the process node sequence; if the second judgment result is that the abnormal data is not compensated, the wastewater treatment control is performed according to the reverse sequence of the process nodes.

[0046] Specifically, if the second judgment result is that the abnormal data is compensated, the wastewater treatment control is performed according to the process node sequence, indicating that the treatment process has returned to normal, and the treatment can continue according to the predetermined wastewater treatment process. The process node sequence includes pretreatment, primary treatment, secondary treatment, tertiary treatment and subsequent treatment. The process node sequence ensures that each treatment stage is carried out according to the set steps and parameters, thereby ensuring the stability and efficiency of wastewater treatment. For example, after compensation, the pretreatment stage removes large particles and suspended matter, the primary treatment stage removes most organic matter, the secondary treatment stage further degrades organic matter, and the tertiary treatment stage removes difficult-to-degrade organic matter and heavy metals. Finally, disinfection and sludge treatment are carried out through subsequent treatment to ensure that the effluent meets the standards.

[0047] However, if the second judgment result is that the abnormal data has not been compensated, the wastewater treatment control is carried out in reverse order according to the process nodes. This is a reverse treatment strategy aimed at further finding and correcting problems in the treatment process. The process node reverse order is to start from the subsequent treatment node and check and adjust each treatment node in turn. For example, starting from the subsequent treatment node, check the disinfection effect and sludge treatment. If problems are found, check the tertiary treatment node forward, analyze the removal effect of trace organic matter and heavy metals, and then check the biological treatment effect of the secondary treatment node, and so on, until the root cause of the abnormality is found and adjusted, and the treatment effect and parameter settings of each node are comprehensively checked to ensure that each link can operate normally.

[0048] Through forward and reverse processing control strategies, it can be ensured that during the wastewater treatment process, not only can abnormalities be discovered and handled in a timely manner, but also the fundamental problems can be found and solved through reverse investigation and adjustment, ensuring the stability and efficiency of the entire treatment system.

[0049] Furthermore, the present application also includes:

[0050] Perform particle size analysis on suspended matter in wastewater to determine the size range of the suspended matter; perform classification based on the size range to determine the size threshold for interception in the wastewater treatment process benchmark; perform filtering treatment on the primary treatment node, secondary treatment node, and tertiary treatment node based on the size threshold.

[0051] Specifically, particle size analysis is performed on suspended solids in wastewater. Particle size analysis uses equipment such as a particle size analyzer to measure the particle size distribution of suspended solids in wastewater in detail. Through particle size analysis, the specific size range of suspended solids can be understood, thereby providing a scientific basis for subsequent treatment steps. For example, the particle size of suspended solids can be measured by laser particle size analyzer or microscope, and a detailed particle size distribution diagram can be obtained to determine the main size range of suspended solids, so as to provide a basis for classification and filtration in the treatment process.

[0052] Then, the size range is classified and divided to determine the size threshold for interception in the wastewater treatment process benchmark. The classification is to classify the suspended matter into different size intervals based on the results of the particle size analysis, and set the corresponding interception thresholds of different particle sizes for each treatment node. For example, a larger interception threshold can be set in the pretreatment stage, a medium interception threshold can be set in the primary treatment stage, and a smaller interception threshold can be set in the secondary and tertiary treatment stages. The interception threshold is optimized according to the actual particle size distribution and the capacity of the treatment equipment to ensure that each stage can effectively intercept the suspended matter of the corresponding size range and improve the treatment efficiency.

[0053] Next, filtration treatment is performed at primary, secondary and tertiary treatment nodes based on size thresholds. Primary treatment nodes usually include sedimentation tanks or coarse filtration equipment to intercept large suspended particles. According to the set threshold, the residence time of the sedimentation tank or the filter mesh aperture of the coarse filtration equipment can be adjusted to ensure the effective removal of large particles. Secondary treatment nodes usually use biological treatment or medium filtration equipment to further remove medium-sized suspended particles. The removal effect of medium particles can be optimized by adjusting the aeration volume, biofilm thickness or filter mesh aperture of the medium filtration equipment. Tertiary treatment nodes usually use technologies such as ultrafiltration, nanofiltration or reverse osmosis to remove the smallest suspended particles and soluble pollutants. By setting fine filtration parameters, the complete removal of fine suspended matter is ensured.

[0054] By analyzing the particle size of suspended solids in wastewater, the size range of suspended solids is determined, and the size range is classified and divided according to the size range to determine the interception size threshold of each treatment stage. According to the interception threshold, corresponding filtration treatment is performed at the primary treatment node, the secondary treatment node and the tertiary treatment node respectively, which can effectively remove suspended solids of different particle sizes, improve the overall efficiency and effect of wastewater treatment, ensure that each treatment node can operate efficiently, and finally achieve high-quality treatment of wastewater and discharge standards.

[0055] Furthermore, the present application also includes:

[0056] Based on the size range, the maximum size threshold and the minimum size threshold of the maximum size and the minimum size under the preset threshold are extracted; the primary processing node and the tertiary processing node are set according to the maximum size threshold and the minimum size threshold respectively, and the suspended matter is filtered to obtain an intermediate filtering result; if the intermediate filtering result meets the filtering effect threshold, the intermediate filtering result of the secondary processing node is verified, and the filtering of the secondary processing node is completed; if the intermediate filtering result does not meet the filtering effect threshold, the secondary processing node is divided into multiple levels according to the intermediate size threshold, and the intermediate filtering result of the secondary processing node is verified to complete the filtering of the secondary processing node, wherein the number of division levels is correlated with the difference between the maximum size and the minimum size.

[0057] Specifically, the maximum size threshold and the minimum size threshold under the preset threshold are extracted based on the size range. First, the particle size distribution range of suspended matter in the wastewater is determined by particle size analysis, and the maximum and minimum particle sizes are extracted from it. Then, a reasonable preset threshold is set to determine the processing capacity and effect of the filtration equipment. For example, the preset threshold can be determined based on factors such as the filter mesh aperture of the treatment equipment and the system design parameters, and the maximum size threshold and the minimum size threshold can be obtained to guide the operation of the primary treatment and tertiary treatment nodes.

[0058] Then, the primary treatment node and the tertiary treatment node are set according to the maximum size threshold and the minimum size threshold, and the suspended matter is filtered to obtain the intermediate filtration results. The primary treatment node is mainly for suspended matter with larger particle sizes, and large particles are intercepted by setting a larger filter mesh aperture or sedimentation tank. The tertiary treatment node is for suspended matter with the smallest particle size, and fine particles are removed by using fine filtration equipment such as ultrafiltration or nanofiltration. The intermediate filtration result is the remaining suspended matter in the wastewater after treatment at these two nodes, reflecting the filtration effect of the primary and tertiary treatments.

[0059] Next, if the intermediate filtration result meets the filtration effect threshold, the intermediate filtration result of the secondary treatment node is verified and the filtration of the secondary treatment node is completed. The secondary treatment node usually uses biological treatment or medium particle size filtration method to further process the suspended matter in the intermediate filtration result. The verification process includes checking whether the intermediate filtration result has reached the preset filtration effect threshold, such as COD, BOD, suspended matter concentration and other indicators. If the intermediate filtration result meets the requirements, it means that the primary and tertiary treatments are effective, and the operation of the secondary treatment node can be directly carried out.

[0060] However, if the intermediate filtering result does not meet the filtering effect threshold, the secondary processing node is divided into multiple levels of intermediate size thresholds, and the intermediate filtering results of the secondary processing node are verified to complete the filtering of the secondary processing node. At this time, it is necessary to divide the intermediate size threshold of the secondary processing node more finely, and divide the intermediate particle size range into multiple levels, each level corresponding to a different filtering strategy. The number of division levels is correlated with the difference between the maximum size and the minimum size, which means that the larger the particle size range, the more division levels. Through multi-level division, suspended matter with intermediate particle sizes can be processed more accurately and the filtering effect can be improved. The verification process still needs to check the filtering results at each level to ensure that the final processing effect meets expectations.

[0061] By extracting the maximum and minimum sizes of suspended solids, setting size thresholds for primary and tertiary treatment nodes, filtering them separately, and judging whether multi-level division and treatment of secondary treatment nodes is necessary based on intermediate filtering results, efficient removal of suspended solids in wastewater can be achieved, ensuring that the filtration effect of each treatment node is optimal, and ultimately achieving efficient and stable operation of the wastewater treatment system, ensuring that effluent water quality meets standards.

[0062] Furthermore, the present application also includes:

[0063] The real-time monitoring process data is continuously monitored to obtain continuous monitoring results of real-time monitoring pretreatment data, real-time monitoring primary treatment data, real-time monitoring secondary treatment data, real-time monitoring tertiary treatment data and real-time monitoring subsequent treatment data, and determine whether it meets the pretreatment benchmark, primary treatment benchmark, secondary treatment benchmark, tertiary treatment benchmark and subsequent treatment benchmark; if not, continue to perform reverse wastewater treatment control until the wastewater treatment is completed.

[0064] Specifically, the real-time monitoring process data is continuously monitored to obtain the continuous monitoring results of real-time monitoring pre-treatment data, real-time monitoring primary treatment data, real-time monitoring secondary treatment data, real-time monitoring tertiary treatment data and real-time monitoring subsequent treatment data, and to determine whether the pre-treatment benchmark, primary treatment benchmark, secondary treatment benchmark, tertiary treatment benchmark and subsequent treatment benchmark are met to ensure the stable and efficient operation of the wastewater treatment system. Real-time monitoring includes sensors and monitoring equipment installed at each treatment node, which continuously collect water quality parameters at each node, such as pH value, dissolved oxygen, COD, BOD, ammonia nitrogen, total phosphorus, suspended solids, etc., and obtain continuous monitoring results by dynamically tracking the treatment effect of each node to ensure that any abnormalities in the treatment process can be discovered and handled in a timely manner.

[0065] Then, if it does not meet the requirements, the reverse wastewater treatment control will continue until the wastewater treatment is completed. This means that during the continuous monitoring process, if the real-time monitoring data of a treatment node does not meet the preset benchmark value, the system will immediately start the reverse processing mechanism. Reverse processing control means starting from the subsequent processing nodes, reversely checking and adjusting each processing node until the problem is found and solved. For example, if the monitoring data of the tertiary processing node does not meet the benchmark, first check the situation of the subsequent processing nodes to confirm the disinfection effect and sludge treatment situation, and then check the tertiary processing nodes, secondary processing nodes and primary processing nodes in turn to find the root cause of the problem.

[0066] In the reverse treatment control process, specific operations include: confirming whether the disinfection effect meets the standard, whether the sludge treatment is normal, and whether there are residual pollutants entering the effluent. Check the operation of ultrafiltration and nanofiltration, adjust the filtration parameters, and ensure the removal effect of fine suspended matter and soluble pollutants. Check the operation status of biological treatment units (such as aeration tanks and biofilters), adjust the aeration volume, microbial population and treatment time to ensure the effective degradation of organic matter. Check the operation effect of sedimentation tanks and coarse filtration equipment, increase the sedimentation time or replace the filter if necessary to ensure the removal of large suspended particles.

[0067] Through reverse processing control, step-by-step investigation and optimization of each processing node, any abnormal situation in the wastewater treatment process can be effectively resolved to ensure that the final effluent water quality meets the requirements.

[0068] In summary, the wastewater treatment control optimization method based on monitoring data provided by this application has the following technical effects:

[0069] By acquiring wastewater treatment process nodes, the wastewater treatment process nodes are monitored to generate real-time monitoring process data; the wastewater treatment process benchmark is determined, and the compliance judgment of the real-time monitoring process data based on the wastewater treatment process benchmark is obtained to obtain a first judgment result; according to the first judgment result, abnormal nodes are extracted, and the next node of the abnormal node is compensated to obtain a second judgment result; according to the second judgment result, the control optimization of the wastewater treatment process nodes is performed to achieve the technical goal of the wastewater treatment optimization system with dynamic monitoring and real-time feedback, and achieve the technical effect of improving treatment efficiency and ensuring that the effluent water quality is stable and meets the standards.

[0070] Embodiment 2: Based on the wastewater treatment control optimization method based on monitoring data in the previous embodiment, the present application also provides a wastewater treatment control optimization system based on monitoring data, please refer to the attached Figure 2 ,include:

[0071] A real-time monitoring process data generation module 11, the real-time monitoring process data generation module 11 is used to obtain wastewater treatment process nodes, monitor the wastewater treatment process nodes and generate real-time monitoring process data; a first judgment result acquisition module 12, the first judgment result acquisition module 12 is used to determine the wastewater treatment process benchmark, and perform a compliance judgment on the real-time monitoring process data based on the wastewater treatment process benchmark to obtain a first judgment result; a second judgment result acquisition module 13, the second judgment result acquisition module 13 is used to extract abnormal nodes according to the first judgment result, and compensate the next node of the abnormal node to obtain a second judgment result; a control optimization module 14, the control optimization module 14 is used to perform control optimization of the wastewater treatment process nodes according to the second judgment result.

[0072] Furthermore, the first judgment result obtaining module 12 in the wastewater treatment control optimization system based on monitoring data is also used for:

[0073] The wastewater treatment process nodes include pretreatment nodes, primary treatment nodes, secondary treatment nodes, tertiary treatment nodes and subsequent treatment nodes; the pretreatment nodes, primary treatment nodes, secondary treatment nodes, tertiary treatment nodes and subsequent treatment nodes are monitored in real time to obtain real-time monitoring pretreatment data, real-time monitoring primary treatment data, real-time monitoring secondary treatment data, real-time monitoring tertiary treatment data and real-time monitoring subsequent treatment data respectively; the wastewater treatment process benchmark includes pretreatment benchmark, primary treatment benchmark, secondary treatment benchmark, tertiary treatment benchmark and subsequent treatment benchmark; according to the real-time monitoring pretreatment data, real-time monitoring primary treatment data, real-time monitoring secondary treatment data, real-time monitoring tertiary treatment data and real-time monitoring subsequent treatment data, a compliance judgment based on the pretreatment benchmark, primary treatment benchmark, secondary treatment benchmark, tertiary treatment benchmark and subsequent treatment benchmark is performed to obtain an abnormal result of the wastewater treatment process or a normal result of the wastewater treatment process; the abnormal result of the wastewater treatment process and the normal result of the wastewater treatment process are added to the first judgment result.

[0074] Furthermore, the second judgment result obtaining module 13 in the wastewater treatment control optimization system based on monitoring data is also used for:

[0075] According to the abnormal result of the wastewater treatment process, an abnormal node is obtained, and abnormal data of the abnormal node is extracted; according to the abnormal node, the next node of the abnormal node is extracted, the abnormal data is compensated through the next node, and it is determined whether the abnormal data is compensated, and the second judgment result is obtained.

[0076] Furthermore, the second judgment result obtaining module 13 in the wastewater treatment control optimization system based on monitoring data is also used for:

[0077] If the second judgment result is that the abnormal data is compensated, the wastewater treatment control is performed according to the process node sequence; if the second judgment result is that the abnormal data is not compensated, the wastewater treatment control is performed according to the reverse sequence of the process nodes.

[0078] Furthermore, the second judgment result obtaining module 13 in the wastewater treatment control optimization system based on monitoring data is also used for:

[0079] Perform particle size analysis on suspended matter in wastewater to determine the size range of the suspended matter; perform classification based on the size range to determine the size threshold for interception in the wastewater treatment process benchmark; perform filtering treatment on the primary treatment node, secondary treatment node, and tertiary treatment node based on the size threshold.

[0080] Furthermore, the second judgment result obtaining module 13 in the wastewater treatment control optimization system based on monitoring data is also used for:

[0081] Based on the size range, the maximum size threshold and the minimum size threshold of the maximum size and the minimum size under the preset threshold are extracted; the primary processing node and the tertiary processing node are set according to the maximum size threshold and the minimum size threshold respectively, and the suspended matter is filtered to obtain an intermediate filtering result; if the intermediate filtering result meets the filtering effect threshold, the intermediate filtering result of the secondary processing node is verified, and the filtering of the secondary processing node is completed; if the intermediate filtering result does not meet the filtering effect threshold, the secondary processing node is divided into multiple levels according to the intermediate size threshold, and the intermediate filtering result of the secondary processing node is verified to complete the filtering of the secondary processing node, wherein the number of division levels is correlated with the difference between the maximum size and the minimum size.

[0082] Furthermore, the second judgment result obtaining module 13 in the wastewater treatment control optimization system based on monitoring data is also used for:

[0083] The real-time monitoring process data is continuously monitored to obtain continuous monitoring results of real-time monitoring pretreatment data, real-time monitoring primary treatment data, real-time monitoring secondary treatment data, real-time monitoring tertiary treatment data and real-time monitoring subsequent treatment data, and determine whether it meets the pretreatment benchmark, primary treatment benchmark, secondary treatment benchmark, tertiary treatment benchmark and subsequent treatment benchmark; if not, continue to perform reverse wastewater treatment control until the wastewater treatment is completed.

[0084] Each embodiment in this specification is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The wastewater treatment control optimization method based on monitoring data and the specific examples in the aforementioned embodiment 1 are also applicable to the wastewater treatment control optimization system based on monitoring data in this embodiment. Through the aforementioned detailed description of the wastewater treatment control optimization method based on monitoring data, those skilled in the art can clearly know the wastewater treatment control optimization system based on monitoring data in this embodiment, so for the sake of brevity of the specification, it will not be described in detail here. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be described in the method part.

[0085] 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.

[0086] 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 wastewater treatment control optimization method based on monitoring data, characterized in that: include: Acquire wastewater treatment process nodes, monitor the wastewater treatment process nodes and generate real-time monitoring process data; Determine a wastewater treatment process benchmark, and perform compliance judgment on the real-time monitoring process data based on the wastewater treatment process benchmark to obtain a first judgment result; Extracting an abnormal node according to the first judgment result, and compensating the next node of the abnormal node to obtain a second judgment result; Performing control optimization of the wastewater treatment process node according to the second judgment result; The step of determining the wastewater treatment process benchmark and performing compliance judgment on the real-time monitoring process data based on the wastewater treatment process benchmark to obtain a first judgment result includes: The wastewater treatment process nodes include pre-treatment nodes, primary treatment nodes, secondary treatment nodes, tertiary treatment nodes and subsequent treatment nodes; Real-time monitoring of the pre-processing nodes, primary processing nodes, secondary processing nodes, tertiary processing nodes and subsequent processing nodes to obtain real-time monitoring pre-processing data, real-time monitoring primary processing data, real-time monitoring secondary processing data, real-time monitoring tertiary processing data and real-time monitoring subsequent processing data respectively; The wastewater treatment process benchmark includes pre-treatment benchmark, primary treatment benchmark, secondary treatment benchmark, tertiary treatment benchmark and subsequent treatment benchmark; According to the real-time monitoring pretreatment data, real-time monitoring primary treatment data, real-time monitoring secondary treatment data, real-time monitoring tertiary treatment data and real-time monitoring subsequent treatment data, a compliance judgment based on the pretreatment benchmark, primary treatment benchmark, secondary treatment benchmark, tertiary treatment benchmark and subsequent treatment benchmark is performed to obtain an abnormal result of the wastewater treatment process or a normal result of the wastewater treatment process; adding the abnormal result of the wastewater treatment process and the normal result of the wastewater treatment process to the first judgment result; The extracting an abnormal node according to the first judgment result and compensating the next node of the abnormal node to obtain a second judgment result includes: Obtaining abnormal nodes according to abnormal results of the wastewater treatment process, and extracting abnormal data of the abnormal nodes; Extracting the next node of the abnormal node according to the abnormal node, compensating the abnormal data through the next node, judging whether the abnormal data is compensated, and obtaining the second judgment result; If the second judgment result is that the abnormal data is compensated, the wastewater treatment control is performed according to the process node sequence; if the second judgment result is that the abnormal data is not compensated, the wastewater treatment control is performed according to the reverse sequence of the process nodes.

2. The wastewater treatment control optimization method based on monitoring data according to claim 1, characterized in that: The wastewater treatment control is performed in reverse order according to the process nodes, including: Conducting particle size analysis on suspended matter in wastewater to determine the size range of the suspended matter; Classifying according to the size range, determining a size threshold for interception in the wastewater treatment process benchmark; The primary processing nodes, the secondary processing nodes and the tertiary processing nodes are filtered according to the size threshold.

3. The wastewater treatment control optimization method based on monitoring data according to claim 2, characterized in that: The filtering process of the secondary processing node includes: Extracting a maximum size threshold and a minimum size threshold of a maximum size and a minimum size under a preset threshold based on the size range; A primary processing node and a tertiary processing node are set according to the maximum size threshold and the minimum size threshold respectively, and the suspended matter is filtered to obtain an intermediate filtering result; If the intermediate filtering result meets the filtering effect threshold, the intermediate filtering result of the secondary processing node is verified, and the filtering of the secondary processing node is completed; if the intermediate filtering result does not meet the filtering effect threshold, the secondary processing node is divided into multiple levels according to the intermediate size threshold, and the intermediate filtering result of the secondary processing node is verified to complete the filtering of the secondary processing node, wherein the number of division levels is correlated with the difference between the maximum size and the minimum size.

4. The wastewater treatment control optimization method based on monitoring data according to claim 1, characterized in that: The wastewater treatment control is performed in accordance with the sequence of process nodes, including: Continuously monitoring the real-time monitoring process data to obtain continuous monitoring results of real-time monitoring pre-processing data, real-time monitoring primary processing data, real-time monitoring secondary processing data, real-time monitoring tertiary processing data and real-time monitoring subsequent processing data, and judging whether the pre-processing benchmark, primary processing benchmark, secondary processing benchmark, tertiary processing benchmark and subsequent processing benchmark are met; If not met, continue with the reverse wastewater treatment control until the wastewater treatment is completed.

5. Wastewater treatment control optimization system based on monitoring data, characterized in that: The steps for implementing the wastewater treatment control optimization method based on monitoring data as described in any one of claims 1 to 4 include: A real-time monitoring process data generation module, wherein the real-time monitoring process data generation module is used to obtain wastewater treatment process nodes, monitor the wastewater treatment process nodes and generate real-time monitoring process data; A first judgment result obtaining module, the first judgment result obtaining module is used to determine a wastewater treatment process benchmark, perform a compliance judgment on the real-time monitoring process data based on the wastewater treatment process benchmark, and obtain a first judgment result; A second judgment result obtaining module, wherein the second judgment result obtaining module is used to extract an abnormal node according to the first judgment result, and compensate the next node of the abnormal node to obtain a second judgment result; A control optimization module, wherein the control optimization module is used to perform control optimization of the wastewater treatment process node according to the second judgment result.

Images