Dynamic regulation and control system for sewage treatment

Abstract

The invention relates to the technical field of sewage treatment, in particular to a dynamic regulation and control system for sewage treatment. The invention provides a sewage treatment dynamic regulation and control system which comprises an inlet water sampler, an outlet water sampler, a sampling switcher, a water quality analyzer and a controller, the inlet water sampler is used for collecting an inlet water sample, the outlet water sampler is used for collecting an outlet water sample, and the sampling switcher is used for sampling the outlet water sample according to a preset time interval. Controlling the water quality analyzer to alternately collect and detect inlet and outlet water samples; the controller receives the alternately obtained detection data, calculates the processing efficiency and outputs a process regulation and control instruction according to the processing efficiency; a plurality of sampling points are monitored through the sampling switcher, the water quality of inlet and outlet water is comprehensively monitored, regulation and control are more accurate, meanwhile, the frequency of automatic sampling is higher than that of manual sampling, and the timeliness of regulation and control is improved.

Description

Technical Field

[0001] The present application relates to the technical field of sewage treatment, and in particular to a sewage treatment dynamic control system. Background Art

[0002] As the demand for rural domestic sewage treatment increases, integrated sewage treatment equipment has been widely used due to its advantages of small footprint and flexible installation. In order to ensure the treatment effect, it is necessary to monitor the inlet and outlet water quality in real time and adjust the process parameters accordingly, which puts forward the requirements of miniaturization, low cost and high efficiency for the equipment's detection system.

[0003] When monitoring water quality, existing integrated sewage treatment equipment sets up fixed online monitoring equipment at the water inlet or outlet, and performs manual sampling and inspection at regular intervals. The manual sampling frequency is low and cannot reflect water quality changes in a timely manner. At the same time, there is a lack of correlation analysis between the inlet and outlet water quality, and precise regulation cannot be achieved. This situation needs to be further improved. Summary of the invention

[0004] In order to solve the problem that the existing integrated sewage treatment equipment has low sampling frequency and cannot achieve precise control, the present application provides a sewage treatment dynamic control system, which adopts the following technical solutions: A sewage treatment dynamic control system, characterized by comprising: An inlet water sampler is provided at the water inlet of the treatment equipment and is used to collect inlet water samples; An outlet water sampler is provided at the outlet of the treatment equipment and is used to collect outlet water samples; The sampling switch is connected to the water inlet sampler and the water outlet sampler to control the time-sharing sampling switching between the water inlet and the water outlet of the water quality analyzer; A water quality analyzer, connected to the sampling switch, is used to detect pollutant indicators in the inlet and outlet water samples in a time-sharing manner; The controller is used to receive the detection data from the water quality analyzer, calculate the processing efficiency and output process control instructions.

[0005] By adopting the above technical scheme, the prior art only sets water quality monitoring equipment at the water inlet or outlet, lacks correlation analysis of the inlet and outlet water quality, and cannot achieve precise control; the sampling switch of the present application controls the water quality analyzer to alternately collect and detect inlet and outlet water samples according to a preset time interval; the controller receives these alternately obtained detection data, calculates the processing efficiency and outputs process control instructions accordingly; by monitoring multiple sampling points through the sampling switch, comprehensive monitoring of the inlet and outlet water quality is achieved, and the control is more precise. At the same time, the frequency of automatic sampling is higher than that of manual sampling, which improves the timeliness of the control.

[0006] Optionally, the sampling switch includes: A sampling timing module is used to generate a sampling trigger signal according to a preset switching cycle to obtain a switching execution instruction; A flow detection module, used to detect the real-time flow in the pipeline according to the switching execution instruction, and obtain flow status data; A pressure stabilization control module, used to adjust the pipeline pressure according to the flow state data to obtain the inlet and outlet water pressures; The switching execution module is used to control the switching execution of the inlet water sampling and the outlet water sampling according to the inlet and outlet water pressures.

[0007] By adopting the above technical scheme, the existing sewage treatment equipment often adopts a simple timed switching method when performing sampling switching, without considering the pressure fluctuation problem in the pipeline, resulting in the sampling accuracy being affected; the present application first generates a trigger signal according to a preset period by the sampling timing module, triggers the flow detection module to monitor the pipeline flow in real time, and the pressure stabilization control module then dynamically adjusts the pipeline pressure according to the detected flow status data, and finally, the switching execution module completes the sampling switching under the condition of ensuring the stability of the inlet and outlet water pressures; through a progressive switching scheme based on pressure balance, the cross-contamination problem in traditional sampling switching is solved, and the reliability of water quality data is improved.

[0008] Optionally, the water quality analyzer comprises: COD water quality analyzer, used to detect chemical oxygen demand indicators; Ammonia nitrogen water quality analyzer, used to detect ammonia nitrogen content indicators; Total phosphorus water quality analyzer, used to detect total phosphorus concentration indicators; The COD water quality analyzer, the ammonia nitrogen water quality analyzer and the total phosphorus water quality analyzer are all connected to the sampling switch.

[0009] By adopting the above-mentioned technical solution, this application realizes time-sharing detection of multiple pollutant indicators by connecting the COD water quality analyzer, ammonia nitrogen water quality analyzer and total phosphorus water quality analyzer to the sampling switch. The three water quality analyzers synchronously receive the inlet and outlet water samples allocated by the sampling switch, and respectively detect the chemical oxygen demand, ammonia nitrogen content and total phosphorus concentration therein, thereby obtaining comprehensive water quality data.

[0010] Optionally, the water quality analyzer further includes: The sampling pretreatment module is used to receive the water sample and filter it to obtain the pretreated water sample; A temperature compensation module, used to detect the temperature of the pretreated water sample and generate a compensation coefficient according to the detected temperature; A multi-parameter detection module, used to perform multi-parameter detection on the pre-treated water sample to obtain original detection data; The data calibration module is used to perform data calibration according to the original detection data and the compensation coefficient to obtain calibrated pollutant index data.

[0011] By adopting the above technical scheme, the existing water quality analyzer is easily disturbed by the turbidity of the sample and the temperature fluctuation during direct detection, resulting in large errors in the detection results; the present application first filters the water sample by the sample pretreatment module to remove impurities that may affect the detection; at the same time, the temperature compensation module monitors the water sample temperature in real time and generates a compensation coefficient; after the multi-parameter detection module obtains the preliminary detection data, the data calibration module combines the temperature compensation coefficient to make corrections, and finally obtains accurate pollutant index data; it solves the problems of insufficient sample pretreatment and temperature influence in traditional detection, and also improves the reliability of the detection results through a systematic data calibration mechanism.

[0012] Optionally, the temperature compensation module includes: A temperature acquisition unit, used to acquire the temperature of the pre-treated water sample in real time to obtain temperature acquisition data; A temperature partitioning unit, used to divide the temperature interval according to the temperature collection data to obtain a partition temperature range; A coefficient query unit, used to query the corresponding basic compensation coefficient according to the partition temperature range to obtain a basic compensation value; The dynamic correction unit is used to perform interpolation calculation on the basic compensation value according to the specific position of the temperature acquisition data within the partition temperature range to obtain a real-time compensation coefficient.

[0013] By adopting the above technical scheme, the existing temperature compensation methods often use fixed compensation coefficients or simple segmented compensation, which cannot accurately reflect the actual impact of continuous temperature changes on the detection results; the present application first uses a temperature acquisition unit to obtain the water sample temperature in real time, and the temperature partition unit divides the collected temperature into corresponding intervals. The coefficient query unit obtains the basic compensation coefficient of the interval, and finally the dynamic correction unit performs interpolation calculations based on the specific position of the actual temperature in the interval to obtain a more accurate real-time compensation coefficient; the problem of compensation coefficient jumps in traditional temperature compensation is reduced, and the accuracy of detection data is improved.

[0014] Optionally, the controller includes: A data receiving module, used to receive the calibrated pollutant index data and obtain an inlet and outlet water index data pair; A fluctuation analysis module, used to perform fluctuation analysis on the water inlet and outlet index data pairs to obtain index fluctuation characteristics; An efficiency calculation module, used to calculate the processing efficiency of the inlet and outlet water index data according to the index fluctuation characteristics to obtain a dynamic processing efficiency; The instruction generation module is used to generate a process control instruction according to the dynamic processing efficiency and a preset target processing efficiency.

[0015] By adopting the above technical scheme, the existing control systems often directly calculate the processing efficiency and adjust the process parameters based on single detection data only, without considering the dynamic characteristics of water quality fluctuations, resulting in delayed or excessive control instructions; the present application first obtains the calibrated inlet and outlet water index data pairs by the data receiving module, the fluctuation analysis module extracts dynamic characteristics of these data, the efficiency calculation module calculates the actual processing efficiency based on the fluctuation characteristics, and finally the instruction generation module intelligently outputs the control instructions based on the efficiency deviation; the impact of excessive response to instantaneous data is reduced, and the accuracy of the control instructions is improved.

[0016] Optionally, the instruction generation module includes: a deviation calculation unit, used to calculate the difference between the dynamic processing efficiency and a preset target processing efficiency to obtain efficiency deviation data; A trend judgment unit, used for obtaining a deviation development trend according to a change trend of the efficiency deviation data; A response threshold unit, used to determine a control response threshold according to the deviation development trend to obtain a graded control threshold; The instruction optimization unit is used to optimize the process control instructions according to the hierarchical control threshold to obtain a stepped control instruction.

[0017] By adopting the above technical scheme, the existing sewage treatment control system often adopts a fixed control threshold and a linear response method when generating control instructions, and fails to perform dynamic optimization according to the changing trend of the efficiency deviation, which is prone to problems of untimely or excessive control. The present application first obtains the efficiency deviation data by the deviation calculation unit, and the trend judgment unit analyzes its changing trend. The response threshold unit dynamically sets the graded control threshold based on this, and finally the instruction optimization unit generates a stepped control instruction that meets actual needs. The flexibility of the control response of the control system is improved, and the stability and pertinence of the control instructions are ensured through the dynamic optimization mechanism of multi-level thresholds.

[0018] Optionally, the controller further includes: The range control module is used to automatically adjust the detection range of the water quality analyzer according to the difference in pollutant indicators of the inlet and outlet water samples and perform quality control verification and automatic calibration during the idle detection period; A process control module, used to dynamically adjust the sedimentation time, dosage, aeration time and bacterial strain reaction time according to the step-by-step control instructions; The sample supply control module is used to control the inlet and outlet water samplers to supply test water samples to the water quality analyzer in different time periods according to the preset sampling plan.

[0019] By adopting the above technical scheme, the range control module of this application automatically adjusts the detection range according to the water quality characteristics and performs quality control calibration. The process control module coordinates and controls core process parameters such as sedimentation, dosing, aeration and biochemical reactions. The sample supply control module ensures that water samples are supplied to the analytical instrument in an orderly manner as planned. It not only solves the problems of fixed detection range and fragmented process control in traditional control systems, but also improves the system's adaptability and operation efficiency through the multi-module collaborative operation mechanism.

[0020] Optionally, the controller further includes: The pipeline maintenance module is used to control the sampling switch to backwash the sampling pipeline to obtain a clean sampling channel before the water quality analyzer performs sample detection; A rinse control module is used to generate rinse instructions according to a preset maintenance cycle and control the regular rinsing of the inlet sampler and the outlet sampler; The pipeline monitoring module is used to monitor the cleanliness status of the sampling pipeline and trigger the emergency rinsing procedure when the risk of pipeline blockage is detected.

[0021] By adopting the above-mentioned technical scheme, the pipeline maintenance module of the present application performs backwash pretreatment before each sampling, the rinse control module performs regular maintenance according to the preset cycle, and the pipeline monitoring module monitors the pipeline status in real time and triggers emergency treatment when necessary; through the maintenance scheme that combines prevention and monitoring, the reliability and service life of the sampling system are improved.

[0022] In summary, the present application includes at least one of the following beneficial technical effects: The sampling switch of the present application controls the water quality analyzer to alternately collect and detect inlet and outlet water samples according to a preset time interval; the controller receives these alternately obtained detection data, calculates the processing efficiency and outputs process control instructions accordingly; by monitoring multiple sampling points through the sampling switch, comprehensive monitoring of the inlet and outlet water quality is achieved, and the control is more precise. At the same time, the automatic sampling frequency is higher than that of manual sampling, which improves the timeliness of the control; Existing sewage treatment equipment often uses a simple timed switching method when performing sampling switching, without considering the pressure fluctuation problem in the pipeline, which affects the sampling accuracy; the present application first generates a trigger signal according to a preset period by the sampling timing module, triggers the flow detection module to monitor the pipeline flow in real time, and then the pressure stabilization control module dynamically adjusts the pipeline pressure according to the detected flow state data. Finally, under the condition of ensuring the stability of the inlet and outlet water pressure, the switching execution module completes the sampling switching; through a progressive switching scheme based on pressure balance, the cross-contamination problem in traditional sampling switching is solved, and the reliability of water quality data is improved; Existing water quality analyzers are easily disturbed by sample turbidity and temperature fluctuations during direct detection, resulting in large errors in the test results. The present application first filters the water sample by the sample pretreatment module to remove impurities that may affect the detection. At the same time, the temperature compensation module monitors the water sample temperature in real time and generates a compensation coefficient. After the multi-parameter detection module obtains preliminary test data, the data calibration module uses the temperature compensation coefficient to make corrections and finally obtain accurate pollutant index data. The problems of insufficient sample pretreatment and temperature influence in traditional detection are solved, and the reliability of the test results is improved through a systematic data calibration mechanism. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a structural block diagram of a sewage treatment dynamic control system according to an embodiment of the present application; Figure 2 is a structural block diagram of a sampling switch in an embodiment of the present application; Figure 3 It is one of the structural block diagrams of the water quality analyzer in the embodiment of the present application; Figure 4 This is the second structural block diagram of the water quality analyzer in the embodiment of the present application; Figure 5 is a structural block diagram of a temperature compensation module in an embodiment of the present application; Figure 6 It is one of the structural block diagrams of the controller in the embodiment of the present application; Figure 7 It is a structural block diagram of the instruction generation module in an embodiment of the present application; Figure 8 This is the second structural block diagram of the controller in the embodiment of the present application; Fig. 9 This is the third structural block diagram of the controller in the embodiment of the present application. DETAILED DESCRIPTION

[0024] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification and appended claims of the present application, the singular expressions "one", "a kind of", "said", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations comprising one or more listed items.

[0025] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0026] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0027] In the first aspect, the present application provides a sewage treatment dynamic control system, referring to Figure 1 ,include: The inlet water sampler is arranged at the water inlet of the processing equipment and is used to collect the inlet water samples.

[0028] The outlet water sampler is arranged at the outlet of the processing equipment and is used to collect outlet water samples.

[0029] In this embodiment, the sewage treatment dynamic control system is used for online monitoring and intelligent control of rural domestic sewage treatment facilities. The inlet sampler is installed at the front end of the water collection well or regulating tank of the sewage treatment equipment; the outlet sampler is installed at the discharge port at the end of the treatment equipment.

[0030] The sampling switch is connected to the water inlet sampler and the water outlet sampler to control the time-sharing sampling switching between the water inlet and outlet of the water quality analyzer.

[0031] In this embodiment, the sampling switch adopts a multi-channel electromagnetic valve structure, and realizes the timed switching and collection of inlet and outlet water samples through program control. The water quality analyzer uses a multi-parameter online analyzer, which can simultaneously measure pollutant indicators such as COD, ammonia nitrogen, and total phosphorus.

[0032] The water quality analyzer is connected to the sampling switcher and is used to detect pollutant indicators in the incoming and outgoing water samples in a time-sharing manner.

[0033] In this embodiment, the water quality analyzer uses spectrophotometry to detect water quality, based on the relationship that absorbance is proportional to solution concentration and light transmission path. The analyzer is equipped with a deuterium lamp and a tungsten filament lamp as the light source system, and performs spectral splitting through a diffraction grating to select monochromatic light of a specific wavelength. The colorimetric measurement cell is made of quartz material with an optical path of 10mm, which has good light transmittance and corrosion resistance. The detection system uses a silicon photocell as a photoelectric conversion element to convert optical signals into electrical signals, which are digitally processed after amplification and analog-to-digital conversion.

[0034] Specifically, taking COD detection as an example, the analyzer uses ultraviolet light with a wavelength of 254nm for detection, and the water sample is filtered through a microporous membrane to remove suspended matter before entering the colorimetric cell. The standard curve is established using a potassium dichromate standard solution, and the concentration gradient is set to 0, 100, 200, 400, 800 mg / L for a total of 5 points. The working curve is obtained by least squares fitting. During each detection, the system first measures the reagent blank to obtain the baseline value, and then measures the absorbance of the water sample. According to the pre-established standard curve, the measured absorbance value is converted into the corresponding COD concentration value.

[0035] The controller is used to receive the detection data from the water quality analyzer, calculate the processing efficiency and output process control instructions.

[0036] In this embodiment, the controller adopts a programmable controller with built-in data processing and control algorithms. After the water sample is tested by the water quality analyzer, the data is transmitted to the controller for processing efficiency calculation, and the corresponding process control instructions are output according to the calculation results.

[0037] In one embodiment, referring to Figure 2 , the sampling switcher includes: The sampling timing module is used to generate a sampling trigger signal according to a preset switching cycle to obtain a switching execution instruction.

[0038] In this embodiment, the sampling timing module is composed of a timer chip and a timing control circuit, and has multiple sets of programmable timing control programs built in. The module sets the switching cycle and duration of inlet and outlet water sampling according to the water quality detection requirements. Among them, the timing control adopts a 24-hour system, sets multiple sampling time periods, and the sampling interval in each time period is independently adjusted to achieve differentiated sampling strategies for different time periods.

[0039] Specifically, in the standard working mode, the system is set to a complete sampling cycle every 2 hours, including 15 minutes of inlet sampling and 15 minutes of outlet sampling, with 30 minutes reserved for pipeline cleaning and system stabilization. During periods of large fluctuations in sewage load (such as 6:00-9:00 in the morning), the sampling interval is shortened to 1 hour to increase the monitoring frequency.

[0040] The flow detection module is used to detect the real-time flow in the pipeline according to the switching execution instruction and obtain the flow status data.

[0041] In this embodiment, the flow detection module uses a combination of a turbine flowmeter and a pressure sensor to monitor the flow and pressure state of the water sample in the sampling pipeline in real time. The turbine flowmeter is installed at the inlet end of the sampling pipeline to measure the instantaneous flow rate; the pressure sensor is installed at the key node of the pipeline to monitor the pressure change during the water sample transportation process.

[0042] The pressure stabilization control module is used to adjust the pipeline pressure according to the flow state data to obtain the inlet and outlet water pressure.

[0043] In this embodiment, the pressure stabilization control module is composed of a proportional control valve and a PID controller. According to the pressure data fed back by the flow detection module, the water sample pressure in the sampling pipeline is adjusted in real time. The module adopts a closed-loop control strategy to keep the pipeline pressure within the set range by adjusting the opening of the proportional valve to ensure the stability of the water sample flow.

[0044] Specifically, the pressure stabilization control adopts an electric proportional control valve. When pressure fluctuations are detected, the controller adjusts the valve opening through an analog output signal to achieve dynamic balance of pressure.

[0045] The switching execution module is used to control the switching execution of inlet water sampling and outlet water sampling according to the inlet and outlet water pressures.

[0046] In this embodiment, the switching execution module is composed of a solenoid valve group and an execution control circuit, and is responsible for the physical switching of the inlet and outlet water sampling.

[0047] Specifically, the switching is performed using two sets of three-way solenoid valves. During the switching process, the system first closes the current sampling channel and opens the target channel after a delay of 1 second to avoid mixing of water samples. After each switching action is completed, the position sensor feedback signal is used to confirm that the switch is in place, and the status information is uploaded to the main controller.

[0048] In one embodiment, referring to Figure 3 , water quality analyzer includes: COD water quality analyzer, used to detect chemical oxygen demand indicators; Ammonia nitrogen water quality analyzer, used to detect ammonia nitrogen content indicators; Total phosphorus water quality analyzer, used to detect total phosphorus concentration indicators; The COD water quality analyzer, ammonia nitrogen water quality analyzer and total phosphorus water quality analyzer are all connected to the sampling switcher.

[0049] Specifically, by connecting the COD water quality analyzer, ammonia nitrogen water quality analyzer and total phosphorus water quality analyzer to the sampling switch, time-sharing detection of multiple pollutant indicators can be achieved. The three water quality analyzers synchronously receive the inlet and outlet water samples allocated by the sampling switch, and respectively detect the chemical oxygen demand, ammonia nitrogen content and total phosphorus concentration, so as to obtain comprehensive water quality data.

[0050] In one embodiment, referring to Figure 4 , the water quality analyzer also includes: The sample pretreatment module is used to receive water samples and perform filtering treatment to obtain pretreated water samples.

[0051] In this embodiment, in addition to simply filtering with a microporous filter membrane, the sample pretreatment module can also adopt a multi-stage filtration system design, including three levels of coarse filtration, fine filtration and ultrafiltration. The coarse filtration uses a stainless steel filter to remove large particles of impurities, the fine filtration uses a PP filter element to remove fine suspended matter, and the ultrafiltration uses a hollow fiber membrane to remove colloidal substances.

[0052] The temperature compensation module is used to detect the temperature of the pre-treated water sample and generate a compensation coefficient according to the detected temperature.

[0053] In this embodiment, the temperature sensor monitors the change of water temperature in real time, the compensation circuit converts the temperature signal into a digital quantity, and obtains the corresponding temperature compensation coefficient by looking up a table.

[0054] The multi-parameter detection module is used to perform multi-parameter detection on the pre-treated water sample to obtain original detection data.

[0055] The data calibration module is used to perform data calibration based on the original detection data and the compensation coefficient to obtain calibrated pollutant index data.

[0056] In this embodiment, the data calibration module receives the original detection signal and the temperature compensation data, and obtains the final pollutant concentration value through processing steps such as standard curve conversion, temperature compensation and data smoothing.

[0057] Furthermore, the system performs single-point calibration using standard solutions every day and full-range multi-point calibration every week. When the measured value exceeds the range or the calibration deviation exceeds 5%, the system automatically marks the data as abnormal and issues an alarm.

[0058] In one embodiment, referring to Figure 5 , the temperature compensation module includes: The temperature acquisition unit is used to collect the temperature of the pre-treated water sample in real time to obtain temperature acquisition data.

[0059] The temperature partition unit is used to divide the temperature interval according to the temperature collection data to obtain the partition temperature range.

[0060] In this embodiment, the temperature partition unit divides the entire working temperature range into several temperature intervals according to the temperature characteristics of the water quality parameter measurement. Different compensation strategies are used in each interval to ensure the accuracy of temperature compensation. For example, a nonlinear compensation model is used in the low temperature zone and the high temperature zone, and a linear compensation model is used in the normal temperature zone and the medium temperature zone. The partition boundary points are determined by experimental calibration and stored in the system configuration file.

[0061] The coefficient query unit is used to query the corresponding basic compensation coefficient according to the partition temperature range to obtain the basic compensation value.

[0062] In this embodiment, the coefficient query unit uses a lookup table structure to store the basic compensation coefficients of each temperature interval. The compensation coefficient table is obtained by fitting a large amount of experimental data, and an independent compensation coefficient library is established for different water quality parameters. When the system starts, the compensation coefficient table is loaded into the memory to achieve fast query. Before each measurement of the system, the corresponding basic compensation coefficient is queried according to the current temperature interval.

[0063] The dynamic correction unit is used to perform interpolation calculation on the basic compensation value according to the specific position of the temperature acquisition data within the partition temperature range to obtain the real-time compensation coefficient.

[0064] In this embodiment, the real-time temperature value and temperature interval information of the dynamic correction unit are interpolated to obtain a more accurate compensation coefficient. Furthermore, the interpolation algorithm can adaptively select different interpolation methods according to the severity of the temperature change to ensure the smoothness of the compensation.

[0065] In one embodiment, referring to Figure 6 , the controller includes: The data receiving module is used to receive the calibrated pollutant index data and obtain the inlet and outlet water index data pair.

[0066] In this embodiment, the data receiving module adopts a double buffer data structure design, which is used to store the water quality index data of the inlet water and the outlet water respectively.

[0067] The fluctuation analysis module is used to perform fluctuation analysis on the inlet and outlet water index data to obtain the index fluctuation characteristics.

[0068] In this embodiment, the fluctuation analysis module uses a sliding window algorithm to extract dynamic features of the water inlet and outlet indicators, calculates the statistical features within the sliding window, including the mean, standard deviation and coefficient of variation, and identifies trend changes and periodic fluctuations in the data.

[0069] Specifically, the sliding window size is set to 6 hours, and the window slides forward every 2 hours. For the data in each window, the mean and standard deviation of the influent COD are calculated. When the coefficient of variation exceeds 30%, it is determined that the influent water quality has fluctuated significantly.

[0070] The efficiency calculation module is used to calculate the processing efficiency of the inlet and outlet water index data according to the index fluctuation characteristics to obtain the dynamic processing efficiency.

[0071] In this embodiment, the efficiency calculation module uses an adaptive weighted algorithm to calculate the pollutant removal efficiency. According to the fluctuation analysis results, the weight coefficients of data in different time periods are dynamically adjusted to perform weighted calculations on the treatment efficiency. When the water quality fluctuates greatly, the weight of the stable period data is increased; when the water quality is relatively stable, an equal weight calculation method is used.

[0072] The instruction generation module is used to generate process control instructions based on the dynamic processing efficiency and the preset target processing efficiency.

[0073] In one embodiment, referring to Figure 7 , the instruction generation module includes: The deviation calculation unit is used to calculate the difference between the dynamic processing efficiency and the preset target processing efficiency to obtain efficiency deviation data.

[0074] In this embodiment, the deviation calculation unit adopts a real-time data processing mechanism to continuously monitor the dynamic processing efficiency and calculate the deviation.

[0075] The trend judgment unit is used to obtain the deviation development trend according to the change trend of the efficiency deviation data.

[0076] In this embodiment, the variation trend of the deviation is determined according to the variation trend of the efficiency deviation data, including four basic trend types: continuous deterioration, fluctuating deterioration, stabilization, and gradual improvement.

[0077] The response threshold unit is used to determine the control response threshold according to the deviation development trend to obtain the graded control threshold.

[0078] In this embodiment, the response threshold unit adopts an adaptive threshold setting mechanism to divide the response level into four levels according to the severity of the deviation trend: observation level, warning level, control level and emergency level. Each level corresponds to a different control response threshold, forming a progressive control system.

[0079] The instruction optimization unit is used to optimize the process control instructions according to the hierarchical control threshold to obtain the stepped control instructions.

[0080] In this embodiment, the instruction optimization unit adopts a piecewise linear control strategy to establish a corresponding relationship between the process parameter control range and the response level, generates corresponding control instructions according to different response levels, and achieves fine adjustment of the processing efficiency through a step-by-step control method to avoid excessive or insufficient control.

[0081] Specifically, the control instructions include four key parameters: sedimentation time, dosage, aeration time and bacterial reaction time. In the observation level, only data is recorded without control; in the warning level, the control range of a single parameter is limited to ±10%; in the control level, multiple parameters are allowed to be controlled at the same time, and the control range of a single parameter does not exceed ±20%; in the emergency level, the emergency plan is activated, and the control range can reach ±30%.

[0082] In one embodiment, referring to Figure 8 , the controller further comprises: The range control module is used to automatically adjust the detection range of the water quality analyzer according to the difference in pollutant indicators of the incoming and outgoing water samples, and to perform quality control verification and automatic calibration during the idle period of detection.

[0083] In this embodiment, the range control module adopts an intelligent range switching mechanism to automatically select the most suitable detection range by real-time monitoring of the concentration range of inlet and outlet water pollutants.

[0084] The process control module is used to dynamically adjust the sedimentation time, dosage, aeration time and bacterial strain reaction time according to the step-by-step control instructions.

[0085] In this embodiment, the process control module adopts a multi-parameter linkage control strategy to coordinate and adjust various process parameters according to the processing efficiency requirements. The process parameters are divided into two categories: fast response parameters and slow response parameters. Different control cycles and adjustment steps are used to ensure the stability and controllability of the system operation.

[0086] The sample supply control module is used to control the inlet and outlet water samplers to supply test water samples to the water quality analyzer in different time periods according to the preset sampling plan.

[0087] In this embodiment, the sample supply control module adopts a time series control scheme to collect and deliver water samples according to a preset sampling plan, and controls the switching of different sampling points through a multi-way solenoid valve to ensure that the inlet and outlet water samples are delivered to the analyzer in the correct order.

[0088] In one embodiment, referring to Fig. 9 , the controller further comprises: The pipeline maintenance module is used to control the sampling switch to backwash the sampling pipeline before the water quality analyzer performs sample detection to obtain a clean sampling channel.

[0089] In this embodiment, the pipeline maintenance module adopts a multi-stage backwash cleaning mechanism, including two modes: conventional backwashing and enhanced backwashing.

[0090] Specifically, the pressure pulse generator generates water pulses of different frequencies and intensities, and cooperates with special cleaning fluid to achieve deep cleaning of the sampling pipeline. The system automatically selects the appropriate cleaning mode and cleaning time according to the properties of the water sample.

[0091] The rinse control module is used to generate rinse instructions according to a preset maintenance cycle and control the regular rinsing of the water inlet sampler and the water outlet sampler.

[0092] In this embodiment, the rinsing control module adopts an intelligent rinsing scheduling strategy to dynamically adjust the rinsing cycle according to the sampler usage frequency and environmental conditions. The module divides the rinsing process into three stages: pre-rinsing, main rinsing and post-rinsing, and each stage uses different rinsing media and rinsing parameters.

[0093] The pipeline monitoring module is used to monitor the cleanliness status of the sampling pipeline and trigger the emergency rinse procedure when the risk of pipeline blockage is detected.

[0094] In this embodiment, the pipeline monitoring module monitors the pipeline status in real time through pressure sensors, flow meters and turbidity sensors, comprehensively analyzes the changing trends of various parameters, and promptly identifies the risk of pipeline blockage. When the monitoring parameters exceed the warning threshold, the system automatically starts the corresponding emergency treatment procedure.

[0095] The above are all preferred embodiments of the present application, and the protection scope of the present application is not limited thereto. Therefore, any equivalent changes made according to the structure, shape, and principle of the present application should be included in the protection scope of the present application.

Claims

1. A sewage treatment dynamic control system, characterized in that: include: An inlet water sampler is provided at the water inlet of the treatment equipment and is used to collect inlet water samples; An outlet water sampler is provided at the outlet of the treatment equipment and is used to collect outlet water samples; The sampling switch is connected to the water inlet sampler and the water outlet sampler to control the time-sharing sampling switching between the water inlet and the water outlet of the water quality analyzer; A water quality analyzer, connected to the sampling switch, is used to detect pollutant indicators in the inlet and outlet water samples in a time-sharing manner; The controller is used to receive the detection data from the water quality analyzer, calculate the processing efficiency and output process control instructions.

2. The sewage treatment dynamic control system according to claim 1 is characterized in that: The sampling switch comprises: A sampling timing module is used to generate a sampling trigger signal according to a preset switching cycle to obtain a switching execution instruction; A flow detection module, used to detect the real-time flow in the pipeline according to the switching execution instruction, and obtain flow status data; A pressure stabilization control module, used to adjust the pipeline pressure according to the flow state data to obtain the inlet and outlet water pressures; The switching execution module is used to control the switching execution of the inlet water sampling and the outlet water sampling according to the inlet and outlet water pressures.

3. The sewage treatment dynamic control system according to claim 1 is characterized in that: The water quality analyzer comprises: COD water quality analyzer, used to detect chemical oxygen demand indicators; Ammonia nitrogen water quality analyzer, used to detect ammonia nitrogen content indicators; Total phosphorus water quality analyzer, used to detect total phosphorus concentration indicators; The COD water quality analyzer, the ammonia nitrogen water quality analyzer and the total phosphorus water quality analyzer are all connected to the sampling switch.

4. The sewage treatment dynamic control system according to claim 3 is characterized in that: The water quality analyzer also includes: The sampling pretreatment module is used to receive the water sample and filter it to obtain the pretreated water sample; A temperature compensation module, used to detect the temperature of the pretreated water sample and generate a compensation coefficient according to the detected temperature; A multi-parameter detection module, used to perform multi-parameter detection on the pre-treated water sample to obtain original detection data; The data calibration module is used to perform data calibration according to the original detection data and the compensation coefficient to obtain calibrated pollutant index data.

5. The sewage treatment dynamic control system according to claim 4 is characterized in that: The temperature compensation module comprises: A temperature acquisition unit, used to acquire the temperature of the pre-treated water sample in real time to obtain temperature acquisition data; A temperature partitioning unit, used to divide the temperature interval according to the temperature collection data to obtain a partition temperature range; A coefficient query unit, used to query the corresponding basic compensation coefficient according to the partition temperature range to obtain a basic compensation value; The dynamic correction unit is used to perform interpolation calculation on the basic compensation value according to the specific position of the temperature acquisition data within the partition temperature range to obtain a real-time compensation coefficient.

6. The sewage treatment dynamic control system according to claim 5, characterized in that: The controller comprises: A data receiving module, used to receive the calibrated pollutant index data and obtain an inlet and outlet water index data pair; A fluctuation analysis module, used to perform fluctuation analysis on the water inlet and outlet index data pairs to obtain index fluctuation characteristics; An efficiency calculation module, used to calculate the processing efficiency of the inlet and outlet water index data according to the index fluctuation characteristics to obtain a dynamic processing efficiency; The instruction generation module is used to generate a process control instruction according to the dynamic processing efficiency and a preset target processing efficiency.

7. The sewage treatment dynamic control system according to claim 6, characterized in that: The instruction generation module comprises: a deviation calculation unit, used to calculate the difference between the dynamic processing efficiency and a preset target processing efficiency to obtain efficiency deviation data; A trend judgment unit, used for obtaining a deviation development trend according to a change trend of the efficiency deviation data; A response threshold unit, used to determine a control response threshold according to the deviation development trend to obtain a graded control threshold; The instruction optimization unit is used to optimize the process control instructions according to the hierarchical control threshold to obtain a stepped control instruction.

8. The sewage treatment dynamic control system according to claim 7, characterized in that: The controller further comprises: The range control module is used to automatically adjust the detection range of the water quality analyzer according to the difference in pollutant indicators of the inlet and outlet water samples and perform quality control verification and automatic calibration during the idle detection period; A process control module, used to dynamically adjust the sedimentation time, dosage, aeration time and bacterial strain reaction time according to the step-by-step control instructions; The sample supply control module is used to control the inlet and outlet water samplers to supply test water samples to the water quality analyzer in different time periods according to the preset sampling plan.

9. The sewage treatment dynamic control system according to claim 6, characterized in that: The controller further comprises: The pipeline maintenance module is used to control the sampling switch to backwash the sampling pipeline to obtain a clean sampling channel before the water quality analyzer performs sample detection; A rinse control module is used to generate rinse instructions according to a preset maintenance cycle and control the regular rinsing of the inlet sampler and the outlet sampler; The pipeline monitoring module is used to monitor the cleanliness status of the sampling pipeline and trigger the emergency rinse procedure when the risk of pipeline blockage is detected.

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