An on-line monitoring method and device for polluted water bodies used in sewage treatment

Abstract

The present invention discloses an on-line monitoring method and device for polluted water bodies in sewage treatment, specifically relating to the technical field of sewage treatment monitoring. In the present invention, monitoring devices are deployed in the sewage pretreatment stage, physicochemical treatment stage, biological treatment stage, advanced treatment stage and discharge stage to monitor the characteristic parameters of polluted water bodies. Intelligent control instructions are generated by analyzing the monitoring data at each stage, and the treatment process parameters are dynamically adjusted to achieve process optimization. The present invention calculates the data monitoring stability coefficient and the comprehensive pollution overrun coefficient, and calculates the sewage treatment monitoring quality index by combining the intelligent control reliability coefficient and the data monitoring reliability coefficient, providing a method for quantitatively evaluating the monitoring effect. By collecting the process data in the sewage treatment log and dynamically updating the monitoring effect compliance rate in combination with the monitoring results, a "monitoring - control - evaluation - optimization" closed loop is formed.

Description

Technical Field

[0001] The present invention relates to the technical field of sewage treatment monitoring. More specifically, the present invention relates to an on-line monitoring method and device for polluted water bodies used in sewage treatment. Background Art

[0002] As the core link of water pollution control, sewage treatment, the elimination of its pollutants is directly related to the reduction degree of water pollution. The monitoring method of pollutants in polluted water bodies during the sewage treatment process is an important tool to ensure the efficient operation of the sewage treatment process.

[0003] Existing sewage treatment monitoring methods deploy monitoring equipment at the sewage discharge outlet to monitor indicators such as the pH value, COD concentration, BOD5 concentration, DO concentration, TP concentration, and TN concentration of the discharged sewage. If the monitoring results do not meet the expectations, an alarm is issued, and the process flow is optimized based on the alarm information to ensure that the characteristic pollutant parameters meet the standards during the next sewage discharge, which can ensure the elimination rate of water pollutants to a certain extent.

[0004] However, there are still some problems with the existing methods: only deploying monitoring equipment at the discharge outlet makes it difficult to comprehensively reflect the changes in the pollution load of each link in the process stage, and it is easy to miss abnormal fluctuations in the intermediate process; relying on fixed threshold alarms, the response is lagging and it is difficult to achieve self-adaptive water quality fluctuations, and the sewage treatment monitoring method still needs to be further optimized; the monitored characteristic pollutant parameter indicators are relatively single and difficult to meet the requirements of multi-pollutant collaborative control. Summary of the Invention

[0005] In order to overcome the above-mentioned defects of the prior art, the present invention deploys monitoring equipment in the sewage pretreatment stage, physicochemical treatment stage, biological treatment stage, advanced treatment stage, and discharge stage to monitor the characteristic parameters of polluted water bodies, realizing real-time monitoring of the entire sewage treatment process; generating intelligent control instructions by analyzing the monitoring data of each stage, dynamically adjusting the treatment process parameters, and realizing process optimization; the monitored characteristic pollutant parameter indicators are more diverse and can better meet the requirements of multi-pollutant collaborative control.

[0006] To achieve the above object, the present invention provides the following technical solution: An on-line monitoring method for polluted water bodies used in sewage treatment, comprising the following steps:

[0007] S1. Deploy monitoring equipment: Deploy monitoring equipment in the sewage pretreatment stage, physicochemical treatment stage, biological treatment stage, advanced treatment stage, and discharge stage to monitor the characteristic parameters of polluted water bodies;

[0008] S2. Set monitoring standards: Set the corresponding characteristic parameter monitoring standards for each process stage of sewage treatment;

[0009] S3. Collect monitoring data for each stage of the sewage treatment process: Obtain the monitoring data of polluted water bodies at each stage of sewage treatment through the deployed monitoring equipment, and transmit the monitoring data to the database based on ZigBee and the data transmission protocol;

[0010] S4. Analyze the monitoring data: Analyze the monitoring data collected in the pretreatment stage, physicochemical treatment stage, biological treatment stage, and advanced treatment stage, generate intelligent regulation instructions for each process stage, analyze the monitoring data collected in the discharge stage, and calculate the data monitoring stability coefficient and the comprehensive pollution overrun coefficient;

[0011] S5. Intelligently regulate each stage of the sewage treatment process: Generate an intelligent regulation plan for each process stage based on the intelligent regulation instructions for each process stage, and regulate each stage of the sewage treatment process according to the generated intelligent regulation plan for each process stage;

[0012] S6. Collect data on the sewage treatment process: Collect the intelligent regulation data of the sewage treatment process and the application data of the monitoring equipment from the sewage treatment log;

[0013] S7. Analyze the data on the sewage treatment process: Analyze the intelligent regulation data of the sewage treatment process and the application data of the monitoring equipment collected, and calculate the intelligent regulation reliability coefficient and the data monitoring reliability coefficient;

[0014] S8. Evaluate the monitoring effect: Calculate the sewage treatment monitoring quality index, evaluate whether the monitoring effect meets the expectations, and update the monitoring effect compliance rate.

[0015] To achieve the above object, the present invention provides the following technical solution: An on-line monitoring device for polluted water bodies used in sewage treatment, implementing the above-mentioned on-line monitoring method for polluted water bodies used in sewage treatment, includes:

[0016] Monitoring equipment deployment module: Deploy monitoring equipment in the sewage pretreatment stage, physicochemical treatment stage, biological treatment stage, advanced treatment stage, and discharge stage to monitor the characteristic parameters of polluted water bodies;

[0017] Monitoring standard setting module: Set the corresponding characteristic parameter monitoring standards for polluted water bodies in the sewage pretreatment stage, physicochemical treatment stage, biological treatment stage, advanced treatment stage, and discharge stage;

[0018] Sewage treatment process stage monitoring data collection module: Obtain the monitoring data of polluted water bodies at each stage of sewage treatment through the deployed monitoring equipment, and transmit the monitoring data to the database based on ZigBee and the data transmission protocol;

[0019] Intelligent Regulation Instruction Generation Module for Process Stages: Analyze the monitored data collected in the pretreatment stage, physicochemical treatment stage, biological treatment stage, and advanced treatment stage, and generate intelligent regulation instructions for process stages;

[0020] Emission Stage Monitored Data Analysis Module: Analyze the monitored data collected in the emission stage, and calculate the data monitoring stability coefficient and the comprehensive pollution overlimit coefficient;

[0021] Intelligent Regulation Module for Sewage Treatment Process Stages: Generate an intelligent regulation plan for the sewage treatment process stage based on the intelligent regulation instructions for process stages, and regulate the sewage treatment process stage according to the generated intelligent regulation plan;

[0022] Sewage Treatment Process Data Collection Module: Collect the intelligent regulation data of the sewage treatment process and the application data of monitoring equipment from the sewage treatment log;

[0023] Sewage Treatment Process Data Analysis Module: Analyze the intelligent regulation data of the sewage treatment process and the application data of monitoring equipment collected, and calculate the intelligent regulation reliability coefficient and the data monitoring reliability coefficient;

[0024] Sewage Treatment Monitoring Effect Evaluation Module: Calculate the sewage treatment monitoring quality index based on the data monitoring stability coefficient, the comprehensive pollution overlimit coefficient, the intelligent regulation reliability coefficient, and the data monitoring reliability coefficient, evaluate whether the monitoring effect meets the expectations and update the monitoring effect compliance rate, and output the evaluation results, the total number of evaluations, and the updated monitoring effect compliance rate to the sewage treatment management center.

[0025] Technical Effects and Advantages of the Present Invention:

[0026] 1. In the present invention, monitoring equipment is deployed in the sewage pretreatment stage, physicochemical treatment stage, biological treatment stage, advanced treatment stage, and emission stage to monitor the characteristic parameters of polluted water bodies, realizing real-time monitoring of the entire sewage treatment process; by analyzing the monitored data of each stage, intelligent regulation instructions are generated to dynamically adjust the treatment process parameters and achieve process optimization; the monitored characteristic pollutant parameter indicators are more diverse and can better meet the requirements of multi-pollutant collaborative control.

[0027] 2. The present invention calculates the data monitoring stability coefficient and the comprehensive pollution overlimit coefficient, combines the intelligent regulation reliability coefficient and the data monitoring reliability coefficient, constructs a monitoring quality index from four aspects: the long-term reliability of monitoring equipment, the risk of pollutant exceeding the standard, the effectiveness of regulation measures, and the operating status of monitoring equipment, and quantitatively evaluates the monitoring effect.

[0028] 3. Adopt the ZigBee protocol and data transmission protocol to achieve low-power, multi-node wireless networking, adapt to the complex environment of the sewage treatment plant, collect process data in the sewage treatment log, and dynamically update the monitoring effectiveness compliance rate in combination with the monitoring results to form a "monitoring - regulation - evaluation - optimization" closed loop. All monitoring data, regulation instructions, and evaluation results are stored in the database and uploaded to the management center, supporting historical data retrieval and auditing, meeting the transparency requirements of environmental protection supervision. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 It is a flowchart of the method steps of the present invention.

[0030] Figure 2 It is a connection diagram of the device modules of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0031] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0032] As Figure 1 shown, this embodiment provides an on-line monitoring method for polluted water bodies used in sewage treatment, including the following steps:

[0033] S1. Deploy monitoring devices: Deploy monitoring devices in the sewage pretreatment stage, physicochemical treatment stage, biological treatment stage, advanced treatment stage, and discharge stage to monitor the characteristic parameters of polluted water bodies.

[0034] Furthermore, the characteristic parameters of polluted water bodies in the sewage pretreatment stage include SS concentration and pH value; the characteristic parameters of polluted water bodies in the sewage physicochemical treatment stage include SS concentration, COD concentration, BOD5 concentration, and sludge interface height; the characteristic parameters of polluted water bodies in the sewage biological treatment stage include DO concentration, ammonia nitrogen concentration, nitrate nitrogen concentration, MLSS, and temperature; the characteristic parameters of polluted water bodies in the sewage advanced treatment stage include TP concentration, residual chlorine concentration, ozone concentration, and fecal coliform concentration; the characteristic parameters of polluted water bodies in the sewage discharge stage include effluent SS concentration, effluent pH value, effluent COD concentration, effluent BOD5 concentration, effluent DO concentration, effluent MLSS, effluent TP concentration, effluent TN concentration, effluent residual chlorine concentration, effluent ozone concentration, and effluent fecal coliform concentration.

[0035] Specifically, in this embodiment, there are differences in the values of the same characteristic pollutant parameters in different process stages. In the characteristic pollutant parameters, SS refers to suspended solids, COD refers to chemical oxygen demand, BOD5 refers to biochemical oxygen demand, DO refers to dissolved oxygen, MLSS refers to mixed liquor suspended solids, TP refers to total phosphorus, and TN refers to total nitrogen.

[0036] Specifically, in this embodiment, the equipment for monitoring the SS concentration and pH value of the polluted water body in the pretreatment stage are a turbidimeter and a pH sensor in sequence; the equipment for monitoring the SS concentration, COD concentration, BOD5 concentration, and sludge interface height of the polluted water body in the physicochemical treatment stage are a turbidimeter, an online UV spectrum analyzer, a BOD5 analyzer, and an ultrasonic sludge interface meter in sequence; the equipment for monitoring the DO concentration, ammonia nitrogen concentration, nitrate nitrogen concentration, MLSS, and temperature of the polluted water body in the biological treatment stage are a fluorescence method DO sensor, an ion selective electrode, an online UV spectrum analyzer, an infrared absorption sludge concentration meter, and a temperature sensor in sequence; the equipment for monitoring the TP concentration, residual chlorine concentration, ozone concentration, and fecal coliform concentration of the polluted water body in the advanced treatment stage are an ammonium molybdate spectrophotometry analyzer, a membrane electrode residual chlorine analyzer, an ultraviolet absorption ozone detector, and a UV sensor array in sequence; the equipment for monitoring the effluent SS concentration, pH value, effluent COD concentration, effluent BOD5 concentration, effluent DO concentration, effluent MLSS, effluent TP concentration, effluent TN concentration, effluent residual chlorine concentration, effluent ozone concentration, and effluent fecal coliform concentration of the polluted water body in the discharge stage are a turbidimeter, a pH sensor, an online UV spectrum analyzer, a BOD5 analyzer, a fluorescence method DO sensor, an infrared absorption sludge concentration meter, an ammonium molybdate spectrophotometry analyzer, a TN analyzer, a membrane electrode residual chlorine analyzer, an ultraviolet absorption ozone detector, and a UV sensor array in sequence.

[0037] Specifically, in this embodiment, the turbidimeter of the monitoring equipment used in the pretreatment stage is deployed behind the grille, and the pH sensor is deployed at the outlet pipeline of the regulating tank; the turbidimeter and the on-line UV spectrum analyzer of the monitoring equipment used in the physicochemical treatment stage are deployed at the outlet of the coagulation tank, the BOD5 meter is deployed at the outlet trough of the sedimentation tank, and the ultrasonic sludge interface meter is deployed at the middle pool wall of the sedimentation tank; the fluorescence method DO sensor, ion selective electrode and infrared absorption sludge concentration meter of the monitoring equipment used in the biological treatment stage are deployed in the aerobic tank, the on-line UV spectrum analyzer is deployed at the bottom of the anoxic tank, and the temperature sensor is deployed in the anaerobic tank; the ammonium molybdate spectrophotometry analyzer in the advanced treatment stage is deployed at the outlet of the filter tank, the membrane electrode residual chlorine analyzer and the UV sensor array are deployed at the outlet of the disinfection tank, and the ultraviolet absorption ozone detector is deployed in the gas phase space of the ozone contact tank; the turbidimeter, pH sensor, on-line UV spectrum analyzer, BOD5 meter, fluorescence method DO sensor, infrared absorption sludge concentration meter, ammonium molybdate spectrophotometry analyzer, TN analyzer, membrane electrode residual chlorine analyzer, ultraviolet absorption ozone detector and UV sensor array of the monitoring equipment used in the discharge stage are deployed 1 m upstream of the discharge outlet.

[0038] S2. Set monitoring standards: Set the monitoring standards for the corresponding characteristic parameters in each process stage of sewage treatment.

[0039] Furthermore, the monitoring standards for the polluted water body in the set pretreatment stage include the upper limit value of the effluent SS concentration standard and the pH value standard range; the monitoring standards for the polluted water body in the set physicochemical treatment stage include the upper limit value of the effluent SS concentration standard, the upper limit value of the effluent COD concentration standard, the upper limit value of the effluent BOD5 concentration standard and the upper limit value of the sludge interface height; the monitoring standards for the polluted water body in the set biological treatment stage include the effluent DO concentration standard range, the upper limit value of the effluent ammonia nitrogen concentration standard, the upper limit value of the effluent nitrate nitrogen concentration standard, the effluent MLSS standard range and the temperature standard range; the monitoring standards for the polluted water body in the set advanced treatment stage include the upper limit value of the effluent TP concentration standard, the upper limit value of the effluent residual chlorine concentration standard, the upper limit value of the effluent ozone concentration standard and the upper limit value of the effluent fecal coliform concentration standard.

[0040] Specifically, in this embodiment, the monitoring standards for the polluted water body in the set discharge stage include the upper limit value of the effluent SS concentration standard, the upper limit value of the effluent pH value standard, the upper limit value of the effluent COD concentration standard, the upper limit value of the effluent BOD5 concentration standard, the effluent DO concentration standard range, the effluent MLSS standard range, the upper limit value of the effluent TP concentration standard, the upper limit value of the effluent TN concentration standard, the upper limit value of the effluent residual chlorine concentration standard, the upper limit value of the effluent ozone concentration standard and the upper limit value of the effluent fecal coliform concentration standard.

[0041] Specifically in this embodiment, it should be noted that since the removal of suspended solids is also involved in the physicochemical treatment stage of sewage, the SS concentration of the polluted water at the end of the physicochemical treatment stage is lower than that at the end of the pretreatment stage. Therefore, the upper limit value of the SS concentration standard for the effluent of the polluted water in the pretreatment stage is set to be greater than the upper limit value of the SS concentration standard for the effluent of the polluted water in the physicochemical treatment stage.

[0042] S3. Collect monitoring data of the sewage treatment process stage: Obtain the monitoring data of the polluted water in each process stage of sewage treatment through the deployed monitoring equipment, and transmit the monitoring data to the database based on ZigBee and the data transmission protocol.

[0043] S4. Analyze the monitoring data: Analyze the monitoring data collected in the pretreatment stage, physicochemical treatment stage, biological treatment stage, and advanced treatment stage to generate intelligent regulation instructions for the process stage, and analyze the monitoring data collected in the discharge stage to calculate the data monitoring stability coefficient and the comprehensive pollution overrun coefficient.

[0044] Specifically in this embodiment, the steps for generating the intelligent regulation instructions for the process stage are as follows:

[0045] A1. Compare the numerical relationship between the monitored value and the standard value of the SS concentration of the polluted water in the pretreatment stage. If the monitored value is greater than the standard value, generate an instruction to reduce the SS concentration of the polluted water. Compare the monitored value of the pH value of the polluted water in the pretreatment stage with the standard range. If the monitored value is greater than the maximum value of the standard range, generate an instruction to reduce the pH value of the polluted water. If the monitored value is less than the standard range, generate an instruction to increase the pH value of the polluted water. If the SS concentration and pH value of the polluted water both meet the standards, generate a polluted water transmission instruction to transfer the polluted water in the pretreatment stage to the physicochemical treatment stage.

[0046] A2. Compare the numerical relationship between the monitored values of the SS concentration, COD concentration, BOD5 concentration, and sludge interface height of the polluted water in the physicochemical treatment stage and the corresponding standard values. If the monitored value of the SS concentration is greater than the standard value, generate an instruction to reduce the SS concentration. If the monitored value of the COD concentration is greater than the standard value, generate an instruction to reduce the COD concentration. If the monitored value of the BOD5 concentration is greater than the standard value, generate an instruction to reduce the BOD5 concentration. If the monitored value of the sludge interface height is greater than the standard value, generate an instruction to reduce the sludge interface height. If the monitored values of the SS concentration, COD concentration, BOD5 concentration, and sludge interface height of the polluted water are all less than the corresponding standard values, generate a polluted water transmission instruction to transfer the polluted water in the physicochemical treatment stage to the biological treatment stage.

[0047] A3. Compare the numerical relationships between the monitored values of DO concentration, ammonia nitrogen concentration, nitrate nitrogen concentration, MLSS, and temperature in the polluted water during the biological sewage treatment stage and the corresponding standard values or standard ranges. If the monitored value of DO concentration is greater than the maximum value of the standard range, generate an instruction to decrease the DO concentration in the polluted water; if the monitored value of DO concentration is less than the minimum value of the standard range, generate an instruction to increase the DO concentration in the polluted water. If the monitored value of ammonia nitrogen concentration is greater than the standard value, generate an instruction to decrease the ammonia nitrogen concentration; if the monitored value of nitrate nitrogen concentration is greater than the standard value, generate an instruction to decrease the nitrate nitrogen concentration. If the monitored value of MLSS is greater than the maximum value of the standard range, generate an instruction to decrease MLSS; if the monitored value of MLSS is less than the minimum value of the standard range, generate an instruction to increase MLSS. If the monitored value of temperature is greater than the maximum value of the standard range, generate an instruction to decrease the temperature; if the monitored value of temperature is less than the minimum value of the standard range, generate an instruction to increase the temperature. If the DO concentration, ammonia nitrogen concentration, nitrate nitrogen concentration, MLSS, and temperature of the polluted water all meet the standards, generate an instruction to transfer the polluted water in the biological treatment stage to the advanced treatment stage;

[0048] A4. Compare the numerical relationships between the monitored values of TP concentration, residual chlorine concentration, ozone concentration, and fecal coliform concentration in the polluted water during the advanced sewage treatment stage and the corresponding standard values. If the monitored value of TP concentration is greater than the standard value, generate an instruction to decrease the TP concentration; if the monitored value of residual chlorine concentration is greater than the standard value, generate an instruction to decrease the residual chlorine concentration; if the monitored value of ozone concentration is greater than the standard value, generate an instruction to decrease the ozone concentration; if the monitored value of fecal coliform concentration is greater than the standard value, generate an instruction to decrease the fecal coliform concentration. If the monitored values of TP concentration, residual chlorine concentration, ozone concentration, and fecal coliform concentration in the polluted water are all less than the corresponding standard values, generate an instruction to transfer the polluted water in the advanced sewage treatment stage to the discharge stage.

[0049] Furthermore, the calculation steps of the data monitoring stability coefficient are as follows:

[0050] B1. Calculate the fluctuation coefficient α ij between the j-th monitored data value C of the i-th characteristic parameter during sewage discharge and the (j - 1)-th monitored data value C ij-1 of the i-th characteristic parameter during sewage discharge. The specific formula is: ij-1 ; ;

[0051] B2. Compare the calculated fluctuation coefficient with the preset fluctuation threshold. If the calculated value is greater than the set fluctuation threshold, mark the j-th monitored data value of the i-th characteristic parameter and the (j - 1)-th fluctuation coefficient of the i-th characteristic parameter as invalid; otherwise, mark the j-th monitored data value of the i-th characteristic parameter and the (j - 1)-th fluctuation coefficient of the i-th characteristic parameter as valid;

[0052] B3. After extracting the valid fluctuation coefficients, sum them and calculate the average to obtain the average data monitoring fluctuation coefficient α r, the specific formula is: , α ik is the k-th effective fluctuation coefficient of the i-th characteristic parameter, and n ai is the number of effective fluctuation coefficients of the i-th characteristic parameter, and m e is the number of types of emission characteristic parameters of the polluted water body;

[0053] B4. Record the number of valid monitoring data values and the number of invalid monitoring data values, which are represented by m ay and m aw respectively. Then the effective rate coefficient α y of the monitoring data has the following specific calculation formula: ;

[0054] B5. Calculate the data monitoring stability coefficient X d , and the specific formula is: , c α is the data monitoring stability compensation constant value set to avoid the formula calculation result being 0, and c α > 0.

[0055] In this embodiment, it should be specifically noted that for the convenience of calculation, c α is usually taken as 1.

[0056] Furthermore, the calculation steps of the comprehensive pollution overlimit coefficient are as follows:

[0057] C1. Calculate the average value C ri of the valid data of the i-th characteristic parameter monitored during the sewage discharge period, and mark the calculated average value of the i-th characteristic parameter as the final monitoring result of the i-th characteristic parameter;

[0058] In this embodiment, it should be specifically noted that the average value C ri of the valid data of the i-th characteristic parameter monitored during the sewage discharge period can be calculated based on any existing average value calculation formula, so the specific calculation formula is not given here.

[0059] C2. Compare the monitoring result of the i-th characteristic parameter of the polluted water body during the sewage discharge stage with the numerical value of the corresponding characteristic parameter standard value or standard interval. The characteristic parameters less than the standard value and within the standard interval are marked as compliant characteristic parameters, and the remaining characteristic parameters are marked as overlimit characteristic parameters. Record the number m by of the compliant characteristic parameters. Then m by ≤ m e ;

[0060] C3. m by = m eWhen the monitoring results of each characteristic parameter of the polluted water body meet the set standards, the overlimit coefficient value of each characteristic parameter is 0, and the comprehensive pollution overlimit coefficient is the sum of the overlimit coefficients of each characteristic parameter, and its value is 0;

[0061] C4, m by <m e When, the overlimit coefficient X of the i-th overlimit characteristic parameter Ci There are two calculation formulas, which are respectively: , , C ei is the upper limit value of the set standard corresponding to the i-th overlimit characteristic parameter, C uimax is the maximum value of the set standard interval corresponding to the i-th overlimit characteristic parameter, C uimin is the minimum value of the set standard interval corresponding to the i-th overlimit characteristic parameter. When the set standard of the i-th overlimit characteristic parameter is the standard upper limit value, the first formula is automatically used to calculate the overlimit coefficient. When the set standard of the i-th overlimit characteristic parameter is the standard interval, the second formula is automatically used to calculate the overlimit coefficient;

[0062] C5. Calculate the comprehensive pollution overlimit coefficient X w , and the specific formula is: .

[0063] S5. Intelligent regulation of the sewage treatment process stage: Generate an intelligent regulation plan for the process stage based on the intelligent regulation instruction for the process stage and regulate the sewage treatment process stage according to the generated intelligent regulation plan for the process stage;

[0064] S6. Collect sewage treatment process data: Collect intelligent regulation data and monitoring equipment application data during the sewage treatment process from the sewage treatment log;

[0065] Furthermore, the intelligent regulation data includes the generation time t of the i-th intelligent regulation plan ai , the response time t of the i-th intelligent regulation bi , the expected response duration t of the intelligent regulation y , the number m of regulation instructions generated by errors cx and the number m of regulation instructions generated correctly cy ; The monitoring equipment application data includes the fault-free duration t of the i-th monitoring equipment wci , the expected fault-free duration t wsi and the fault clearance duration t qi .

[0066] S7. Analyze the sewage treatment process data: Analyze the intelligent regulation data and monitoring equipment application data collected during the sewage treatment process, and calculate the intelligent regulation reliability coefficient and the data monitoring reliability coefficient;

[0067] Furthermore, the intelligent regulation reliability coefficient X t has the following specific calculation formula: , where n b is the number of times the intelligent regulation scheme is generated; the data monitoring reliability coefficient X c has the following specific calculation formula: , where n c is the number of monitoring devices.

[0068] S8. Evaluate the monitoring effect: Calculate the sewage treatment monitoring quality index, evaluate whether the monitoring effect meets the expectations, and update the monitoring effect compliance rate.

[0069] Furthermore, the specific steps for evaluating the monitoring effect are as follows:

[0070] D1. Calculate the sewage treatment monitoring quality index YR, and the specific formula is: ;

[0071] D2. Compare the calculated sewage treatment monitoring quality index with the expected value. If the calculated value is greater than or equal to the expected value, the monitoring effect meets the expectations; if the calculated value is less than the expected value, the monitoring effect does not meet the expectations.

[0072] D3. Update the monitoring effect compliance rate. The monitoring effect compliance rate coefficient is expressed as the ratio of the number of monitoring effect evaluation times that meet the expectations to the total number of monitoring effect evaluation times.

[0073] D4. Output the evaluation result, the total number of evaluations, and the updated monitoring effect compliance rate to the sewage treatment management center.

[0074] It should be specifically noted in this embodiment that the preset values, expected values, and set standard values used are all selected based on actual needs, and no specific value limits are given here.

[0075] As Figure 2 shown, this embodiment provides an on-line monitoring device for polluted water bodies used in sewage treatment, including a monitoring equipment deployment module, a monitoring standard setting module, a sewage treatment process stage monitoring data acquisition module, a process stage intelligent regulation instruction generation module, an emission stage monitoring data analysis module, a sewage treatment process stage intelligent regulation module, a sewage treatment process data acquisition module, a sewage treatment process data analysis module, a sewage treatment monitoring effect evaluation module, and a database.

[0076] The monitoring device deployment module, the monitoring standard setting module, the sewage treatment process stage monitoring data acquisition module, the process stage intelligent regulation instruction generation module, the sewage treatment process stage intelligent regulation module, the sewage treatment process data acquisition module, the sewage treatment process data analysis module, and the sewage treatment monitoring effect evaluation module are connected in sequence for communication. The sewage treatment process stage monitoring data acquisition module is communicatively connected to the discharge stage monitoring data analysis module, and the discharge stage monitoring data analysis module is communicatively connected to the sewage treatment monitoring effect evaluation module. Each module in the device is communicatively connected to the database.

[0077] The monitoring device deployment module deploys monitoring devices in the sewage pretreatment stage, physicochemical treatment stage, biological treatment stage, advanced treatment stage, and discharge stage to monitor the characteristic parameters of polluted water bodies.

[0078] The monitoring standard setting module sets the corresponding characteristic parameter monitoring standards for polluted water bodies in the sewage pretreatment stage, physicochemical treatment stage, biological treatment stage, advanced treatment stage, and discharge stage.

[0079] The sewage treatment process stage monitoring data acquisition module obtains the monitoring data of polluted water bodies in each process stage of sewage treatment through the deployed monitoring devices, and transmits the monitoring data to the database based on ZigBee and the data transmission protocol.

[0080] The process stage intelligent regulation instruction generation module analyzes the monitoring data collected in the pretreatment stage, physicochemical treatment stage, biological treatment stage, and advanced treatment stage, and generates process stage intelligent regulation instructions.

[0081] The discharge stage monitoring data analysis module analyzes the monitoring data collected in the discharge stage, and calculates the data monitoring stability coefficient and the comprehensive pollution overlimit coefficient.

[0082] The sewage treatment process stage intelligent regulation module generates a process stage intelligent regulation plan based on the process stage intelligent regulation instructions and regulates the sewage treatment process stage according to the generated process stage intelligent regulation plan.

[0083] The sewage treatment process data acquisition module collects the intelligent regulation data of the sewage treatment process and the monitoring device application data from the sewage treatment log.

[0084] The sewage treatment process data analysis module analyzes the intelligent regulation data of the sewage treatment process and the monitoring device application data collected, and calculates the intelligent regulation reliability coefficient and the data monitoring reliability coefficient.

[0085] The sewage treatment monitoring effect evaluation module calculates the sewage treatment monitoring quality index based on the data monitoring stability coefficient, the comprehensive pollution overrun coefficient, the intelligent regulation reliability coefficient, and the data monitoring reliability coefficient, evaluates whether the monitoring effect meets the expectations and updates the monitoring effect compliance rate, and outputs the evaluation result, the total number of evaluations, and the updated monitoring effect compliance rate to the sewage treatment management center;

[0086] The database is used to store the data information of each module in the device.

[0087] Finally: The above are only the preferred embodiments of the present invention and are not used to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for online monitoring of polluted water for sewage treatment, characterized in that: The following steps are involved: S1. Deployment of monitoring equipment: Deploy monitoring equipment in the sewage pretreatment stage, physical and chemical treatment stage, biological treatment stage, deep treatment stage and discharge stage to monitor the characteristic parameters of polluted water bodies; S2. Setting monitoring standards: Setting the corresponding characteristic parameter monitoring standards for each process stage of sewage treatment; S3. Collect monitoring data of sewage treatment process stages: obtain monitoring data of polluted water bodies at each process stage of sewage treatment through the deployed monitoring equipment, and transmit the monitoring data to the database based on ZigBee and data transmission protocol; S4. Analyze monitoring data: Analyze the monitoring data collected in the pretreatment stage, physical and chemical treatment stage, biological treatment stage, and deep treatment stage, generate intelligent control instructions for the process stage, analyze the monitoring data collected in the emission stage, and calculate the data monitoring stability coefficient and the comprehensive pollution excess coefficient; The calculation steps of the data monitoring stability coefficient are as follows: B1. Calculate the jth monitoring data value C of the i-th characteristic parameter during sewage discharge ij and the j-1th monitoring data value C of the i-th characteristic parameter during sewage discharge ij-1 The fluctuation coefficient α ij-1 , the specific formula is: ; B2. Compare the calculated fluctuation coefficient with the preset fluctuation threshold. If the calculated value is greater than the preset fluctuation threshold, the jth monitoring data value of the i-th characteristic parameter and the j-1th fluctuation coefficient of the i-th characteristic parameter are marked as invalid. Otherwise, the jth monitoring data value of the i-th characteristic parameter and the j-1th fluctuation coefficient of the i-th characteristic parameter are marked as valid. B3. Extract the effective fluctuation coefficient, sum it up and find the average value to get the average fluctuation coefficient α of data monitoring r , the specific formula is: , α ik is the kth effective fluctuation coefficient of the ith characteristic parameter, n ai is the number of effective fluctuation coefficients of the i-th characteristic parameter, m e is the number of types of characteristic parameters of discharge of polluted water bodies; B4. Record the number of valid monitoring data values ​​and the number of invalid monitoring data values, using m ay and m aw The monitoring data efficiency coefficient α y The specific calculation formula is: ; B5. Calculate the data monitoring stability coefficient X d , the specific formula is: , c α To avoid the formula calculation result being 0, set the data monitoring stability compensation constant value, c α >0; The steps for calculating the comprehensive pollution excess coefficient are as follows: C1. Calculate the average value of effective data of the i-th characteristic parameter monitored during sewage discharge C ri , mark the calculated average value of effective data of the i-th characteristic parameter as the final monitoring result of the i-th characteristic parameter; C2. Compare the monitoring results of the i-th characteristic parameter of the polluted water body during the sewage discharge stage with the numerical value relationship of the corresponding characteristic parameter standard value or standard range. The characteristic parameters that are less than the standard value and in the standard range are marked as compliant characteristic parameters, and the remaining characteristic parameters are marked as out-of-limit characteristic parameters. Record the number of compliant characteristic parameters m by , then m by ≤m e ; C3, m by =m e When the monitoring results of each characteristic parameter of the polluted water body meet the set standards, the over-limit coefficient value of each characteristic parameter is 0, and the comprehensive pollution over-limit coefficient is the cumulative sum of the over-limit coefficients of each characteristic parameter, and its value is 0; C4, m by <m e When the over-limit coefficient X of the i-th over-limit characteristic parameter is Ci There are two calculation formulas: , , C ei is the set standard upper limit value corresponding to the i-th over-limit characteristic parameter, C uimax is the maximum value of the set standard interval corresponding to the i-th over-limit characteristic parameter, C uimin The minimum value of the set standard interval corresponding to the i-th over-limit characteristic parameter. When the set standard of the i-th over-limit characteristic parameter is the standard upper limit value, the first formula is automatically referenced to calculate the over-limit coefficient. When the set standard of the i-th over-limit characteristic parameter is the standard interval, the second formula is automatically referenced to calculate the over-limit coefficient. C5. Calculate the comprehensive pollution excess coefficient X w , the specific formula is: ; S5. Intelligent control of sewage treatment process stage: generating an intelligent control plan for the process stage based on the intelligent control instructions for the process stage and controlling the sewage treatment process stage according to the generated intelligent control plan for the process stage; S6. Collecting sewage treatment process data: Collecting sewage treatment process intelligent control data and monitoring equipment application data from sewage treatment logs; The intelligent control data includes the time t at which the i-th intelligent control scheme was generated ai , the i-th intelligent control response time t bi , Expected response time of intelligent control t y , the number of control instructions generated by errors m cx And the number of control instructions m generated correctly cy The monitoring device application data includes the fault-free time t of the i-th monitoring device wci , Expected time between failures t wsi And the fault clearing time t qi ; S7. Analyze the sewage treatment process data: Analyze the collected sewage treatment process intelligent control data and monitoring equipment application data, and calculate the reliability coefficient of intelligent control and the reliability coefficient of data monitoring; The intelligent control reliability coefficient X t The specific calculation formula is: , where n b is the number of times the intelligent control scheme is generated; the reliability coefficient of the data monitoring is X c The specific calculation formula is: , where n c To monitor the number of devices; S8. Evaluation of monitoring effect: Calculate the sewage treatment monitoring quality index, evaluate whether the monitoring effect meets expectations and update the monitoring effect compliance rate; The specific calculation formula of the sewage treatment monitoring quality index YR is: .

2. The method for online monitoring of polluted water for sewage treatment according to claim 1, characterized in that: The characteristic parameters of the polluted water body in the sewage pretreatment stage in step S1 include SS concentration and pH value; the characteristic parameters of the polluted water body in the sewage physicochemical treatment stage include SS concentration, COD concentration, BOD5 concentration and sludge interface height; the characteristic parameters of the polluted water body in the sewage biological treatment stage include DO concentration, ammonia nitrogen concentration, nitrate nitrogen concentration, MLSS and temperature; the characteristic parameters of the polluted water body in the sewage deep treatment stage include TP concentration, residual chlorine concentration, ozone concentration and fecal coliform concentration; the characteristic parameters of the polluted water body in the sewage discharge stage include effluent SS concentration, effluent pH value, effluent COD concentration, effluent BOD5 concentration, effluent DO concentration, effluent MLSS, effluent TP concentration, effluent TN concentration, effluent residual chlorine concentration, effluent ozone concentration and effluent fecal coliform concentration.

3. The method for online monitoring of polluted water for sewage treatment according to claim 1, characterized in that: The monitoring standards for polluted water bodies in the pretreatment stage set in step S2 include the standard upper limit of effluent SS concentration and the standard range of pH value; the monitoring standards for polluted water bodies in the physical and chemical treatment stage set include the standard upper limit of effluent SS concentration, the standard upper limit of effluent COD concentration, the standard upper limit of effluent BOD5 concentration and the upper limit of sludge interface height; the monitoring standards for polluted water bodies in the biological treatment stage set include the standard range of effluent DO concentration, the standard upper limit of effluent ammonia nitrogen concentration, the standard upper limit of effluent nitrate nitrogen concentration, the standard range of effluent MLSS and the standard range of temperature; the monitoring standards for polluted water bodies in the deep treatment stage set include the standard upper limit of effluent TP concentration, the standard upper limit of effluent residual chlorine concentration, the standard upper limit of effluent ozone concentration and the standard upper limit of effluent fecal coliform concentration.

4. The method for online monitoring of polluted water for sewage treatment according to claim 1, characterized in that: The specific steps of step S8 for evaluating the monitoring effect are as follows: D1. Calculate the sewage treatment monitoring quality index; D2. Compare the calculated sewage treatment monitoring quality index with the expected value. If the calculated value is greater than or equal to the expected value, the monitoring effect meets expectations; if the calculated value is less than the expected value, the monitoring effect does not meet expectations; D3. Update the monitoring effect compliance rate. The monitoring effect compliance rate coefficient is expressed as the ratio of the number of monitoring effect evaluations that meet expectations to the total number of monitoring effect evaluations; D4. Output the evaluation results, total evaluation times and updated monitoring effect compliance rate to the sewage treatment management center.

5. An online monitoring device for polluted water for sewage treatment, implementing an online monitoring method for polluted water for sewage treatment as claimed in any one of claims 1 to 4, characterized in that: include: Monitoring equipment deployment module: Deploy monitoring equipment in sewage pretreatment, physical and chemical treatment, biological treatment, deep treatment and discharge stages to monitor characteristic parameters of polluted water bodies; Monitoring standard setting module: setting the corresponding characteristic parameter monitoring standards for polluted water bodies in the sewage pretreatment stage, physical and chemical treatment stage, biological treatment stage, deep treatment stage and discharge stage; Sewage treatment process stage monitoring data acquisition module: obtains polluted water monitoring data at each stage of sewage treatment through deployed monitoring equipment, and transmits the monitoring data to the database based on ZigBee and data transmission protocol; Process stage intelligent control instruction generation module: analyzes the collected monitoring data of the pretreatment stage, physical and chemical treatment stage, biological treatment stage and deep treatment stage, and generates process stage intelligent control instructions; Emission stage monitoring data analysis module: analyzes the collected emission stage monitoring data, calculates the data monitoring stability coefficient and the comprehensive pollution excess coefficient; Intelligent control module for sewage treatment process stage: generates intelligent control scheme for process stage based on intelligent control instructions for process stage and controls sewage treatment process stage according to the generated intelligent control scheme for process stage; Sewage treatment process data collection module: collects sewage treatment process intelligent control data and monitoring equipment application data from sewage treatment logs; Sewage treatment process data analysis module: analyzes the collected sewage treatment process intelligent control data and monitoring equipment application data, and calculates the reliability coefficient of intelligent control and data monitoring; Sewage treatment monitoring effect evaluation module: Calculate the sewage treatment monitoring quality index based on the data monitoring stability coefficient, comprehensive pollution excess coefficient, intelligent control reliability coefficient and data monitoring reliability coefficient, evaluate whether the monitoring effect meets expectations and update the monitoring effect compliance rate, and output the evaluation results, total evaluation times and updated monitoring effect compliance rate to the sewage treatment management center.

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