Method and system for calculating pollution load capacity of large overflow discharge port

Abstract

The invention provides a large overflow discharge port pollution load capacity calculation method and system, and the method comprises the steps: deploying a robust multi-mode sensing array with a self-cleaning function and / or a redundancy calibration function in an overflow discharge port, and optimizing the layout position to obtain real-time synchronous flow and pollutant concentration data with high representativeness; a graded variable-frequency dynamic acquisition strategy is adopted, different sampling frequencies are adapted according to hydraulic and water quality characteristics of different overflow stages, and data precision and energy consumption control are both considered; dividing a normal period and an overflow period based on the flow data, respectively calculating pollution load of each stage by adopting a time weighted average method and a real-time integral method, and accumulating to obtain the annual total amount; regular standard solution calibration and laboratory data verification are matched, and the result accuracy is further guaranteed. According to the method, dependence on theoretical model parameters is eliminated, the precision and reliability of pollution load calculation are remarkably improved, the adaptability of system modular design is high, the operation and maintenance cost is low, and data support is provided for drainage basin water environment management, sewage right verification and the like.

Description

Technical Field

[0001] This invention relates to the field of environmental monitoring and management technology, specifically to a method and system for calculating the pollution load of large overflow outlets. Background Technology

[0002] Currently, the calculation of pollution load at large overflow outlets mainly relies on numerical model simulation and traditional fixed-frequency monitoring. The model method requires calibration based on a large number of theoretical parameters such as pipeline deposition state and runoff coefficient. However, pipeline deposition is difficult to quantify and parameter setting is highly subjective, resulting in low simulation accuracy and limited applicability. Traditional monitoring methods often use fixed sampling frequencies, which easily miss the high concentration peak at the beginning of the overflow. At the same time, existing monitoring sensors generally suffer from problems such as easy adhesion of pollutants, large signal interference, and insufficient data representativeness. Furthermore, they lack dynamic adaptive acquisition strategies for different stages of the overflow, making it difficult to meet the requirements of precise watershed water environment management for the scientific accuracy and reliability of pollution load data. Therefore, there is an urgent need for a pollution load calculation method and system based on measured data that combines high accuracy and strong adaptability. Summary of the Invention

[0003] The purpose of this invention is to solve the technical problems mentioned above and to propose a method for calculating the pollution load of large overflow outlets, including the following steps: S1. Deploy a robust multimodal sensor array within the overflow outlet to acquire flow data and pollutant concentration data of the overflow outlet in real time. The sensor array has self-cleaning or redundant calibration functions, and the sensor placement is optimized to ensure data representativeness. S2. Based on real-time monitored flow data or flow change rate, dynamically adjust the data acquisition frequency, including normal baseline frequency and overflow high-frequency mode. S3. Based on the flow data, the monitoring period is divided into normal period and overflow period. During the normal period, the pollution load is calculated using the time-weighted average method. During the overflow period, the pollution load is calculated using the real-time integration method based on the high-frequency flow and pollutant concentration measurements. S4. Add up the pollution loads calculated during the normal period and the overflow period to obtain the total annual pollution load of the overflow outlet.

[0004] In the preferred embodiment, the flow sensor in the robust multimodal sensor array is an ultrasonic flow meter, and the ultrasonic flow meter has an ultrasonic vibration anti-adhesion function.

[0005] In the preferred embodiment, the pollutant concentration sensor in the robust multimodal sensor array is an optical or electrochemical water quality sensor, and the pollutant concentration sensor has a dual-probe cross-validation function or a mechanical scraping self-cleaning function.

[0006] In the preferred embodiment, the sensor placement location is optimized based on the hydraulic characteristics of the overflow outlet, including the outlet width, depth, and flow pattern, and the placement location is determined in conjunction with the outlet cross-sectional dimensions.

[0007] In the preferred scheme, the specific method for dynamically adjusting the data acquisition frequency is as follows: when the real-time traffic reaches the preset overflow threshold, or the traffic increase rate exceeds the preset change rate threshold, the data acquisition frequency is switched from the normal baseline frequency to the overflow high-frequency mode. The normal baseline frequency is once per hour, and the overflow high-frequency mode is once per minute or more.

[0008] In the preferred scheme, the real-time integration method during the overflow period is as follows: the instantaneous flow rate and instantaneous pollutant concentration corresponding to each high-frequency sampling point are multiplied, the product is multiplied by the corresponding sampling interval duration, and finally the calculation results of all sampling points are accumulated and integrated over the entire overflow duration.

[0009] In the preferred embodiment, calibration and verification steps are also included: periodically calibrating the sensors in the robust multimodal sensor array on-site using standard solutions; periodically manually sampling and sending samples to the laboratory for analysis, comparing the laboratory analysis results with the online monitoring data, and verifying and correcting the online monitoring data.

[0010] In the preferred embodiment, the pollutant concentration data includes at least one of chemical oxygen demand, ammonia nitrogen, and total phosphorus; The time-weighted average method during normal periods is as follows: within each sampling interval, the product of flow rate and pollutant concentration is multiplied by the duration of that interval, and then the calculation results for all sampling intervals are summed.

[0011] In the preferred scheme, the dynamic adjustment of the data acquisition frequency adopts a tiered frequency conversion strategy, specifically including: When the real-time flow reaches the preset overflow threshold or the flow rate exceeds the preset change rate threshold, and the pollutant concentration change rate is ≥20% within 5 minutes, it is determined to be the initial stage of overflow. The data acquisition frequency is switched to ultra-high frequency mode, and the sampling interval of ultra-high frequency mode is 10 seconds to 30 seconds. When the flow rate is stable above the preset overflow threshold and the fluctuation range is ≤10%, and the pollutant concentration change rate is <10% within 5 minutes, it is determined to be the overflow peak period, and the data collection frequency is switched to high frequency mode. The sampling interval of high frequency mode is 1 minute to 2 minutes. When the flow rate starts to decrease from the peak and the rate of decrease is ≥5% / minute, or when the pollutant concentration continues to decrease and the rate of decrease is ≥15% / 30 minutes, it is determined to be the overflow drainage period. The data acquisition frequency is switched to medium-high frequency mode, and the sampling interval of medium-high frequency mode is 3 minutes to 5 minutes. When the flow rate drops below the preset overflow threshold and remains below it for more than 30 minutes, the data collection frequency returns to the normal baseline frequency.

[0012] This application also provides a system for calculating the pollution load of large overflow outlets, including: A multimodal sensor array is deployed directly inside a large overflow outlet; it includes online flow sensors and online pollutant concentration sensors. Choose an ultrasonic flow meter with ultrasonic vibration anti-adhesion function. Choose optical or electrochemical water quality sensors; some are equipped with dual probes. It features self-cleaning and redundant calibration functions; Based on the hydraulic characteristics and cross-sectional dimensions of the outlet, select areas where the water flow is well mixed and the data is highly representative, or deploy several sensors to perform weighted averaging of data for complex flow patterns; Real-time and synchronous collection of flow data and pollutant concentration data provides basic measured data for subsequent calculations; The data acquisition and control module is directly electrically connected to the robust multimodal sensor array; it receives the raw flow and concentration data collected by the sensor array and performs preliminary storage; it has a built-in adaptive algorithm that dynamically adjusts the data acquisition frequency of the sensor array based on real-time monitored flow data or flow change rate; and it performs preliminary filtering of obviously abnormal data to ensure the validity of transmitted data. The data transmission module is located between the data acquisition and control module and the data processing module; it uses wireless network transmission and partially supports primary and backup dual-link switching; it transmits the effective data processed by the data acquisition and control module to the cloud data processing center or local server in real time. The data processing module, located on a cloud server or local computer, comprises several sub-units, including: Period identification unit: Based on the received flow data, automatically identify the normal period and overflow period within the monitoring cycle; Load calculation unit: Adapts to different algorithms based on period type, including: Normal period: Time-weighted average method is used; Overflow period: Real-time integration method based on dynamic coupling relationship of real-time measurement value is adopted; Load accumulation unit: The pollution load of all normal periods and each overflow period is superimposed to obtain the total annual pollution load; Reduce reliance on theoretical model parameters and drive calculations entirely based on measured data.

[0013] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) This invention significantly improves the reliability and accuracy of pollution load calculation by optimizing the data acquisition foundation and core algorithm. The robust multimodal sensor array integrates self-cleaning function, redundant calibration function and optimized layout design, which effectively solves the pain points of traditional sensors that are susceptible to pollutant adhesion, data distortion and insufficient representativeness. The synchronously collected flow rate and pollutant concentration data provide a highly reliable foundation for load calculation. In addition, the dual guarantee of regular standard solution calibration and laboratory data verification further ensures the accuracy of monitoring data.

[0014] (2) This invention innovatively adopts a graded frequency conversion dynamic acquisition strategy and a segmented adaptive calculation algorithm to achieve refined calculation of pollution load. Targeting the different hydraulic and water quality characteristics of the initial overflow, peak, and receding stages, the acquisition frequency is dynamically adjusted. This captures key data on the high concentration peak at the initial overflow stage while avoiding data redundancy in non-critical stages. Combined with the precise adaptation of the time-weighted average method during the normal period and the real-time integral method during the overflow period, it significantly reduces the load calculation error caused by traditional fixed-frequency monitoring and a single algorithm, making it particularly suitable for large overflow outlets under complex operating conditions.

[0015] (3) The system of the present invention has strong engineering practicality and scenario adaptability. The modular architecture design can flexibly combine sensing modules and transmission methods to adapt to large overflow outlets of different types and hydraulic characteristics. The dynamic frequency adjustment strategy reduces system energy consumption and operation and maintenance costs while ensuring data accuracy. The dual-link transmission design avoids the risk of data loss. The fully automated data acquisition, transmission and processing process reduces manual intervention, significantly improves the efficiency of monitoring and calculation, and facilitates long-term stable operation.

[0016] (4) This invention is based entirely on measured data-driven calculations, eliminating the reliance on theoretical parameters of traditional numerical models and effectively avoiding the errors and limitations caused by parameter calibration. The total annual pollution load is obtained by accumulating the loads during normal periods and each overflow period. The calculation logic is clear and the results are intuitive. It can be directly applied to water environment management needs such as pollution discharge rights verification, pollution source tracing, and treatment plan formulation, providing scientific and reliable data support for the precise management of watershed water environment, and has significant application value. Attached Figure Description

[0017] Figure 1 This is a flowchart of the method for calculating the pollution load of a large overflow outlet in Example 1.

[0018] Figure 2 This is a flowchart illustrating a method for calculating the pollution load of a large overflow outlet in Example 2.

[0019] Figure 3 This is a structural block diagram of a large overflow outlet pollution load calculation system in Example 2. Detailed Implementation

[0020] Example 1 like Figure 1 As shown, this embodiment provides a method for calculating the pollution load of large overflow outlets, including the following steps: S1. Deploy at least one robust multimodal sensor array within the overflow outlet to synchronously acquire the flow data and at least one pollutant concentration data of the overflow outlet in real time. The sensor array has a self-cleaning function and / or redundant calibration function, and the sensor placement is optimized to ensure data representativeness. S2. Based on real-time monitored flow data or flow change rate, dynamically adjust the data acquisition frequency, which includes normal baseline frequency and overflow high-frequency mode. S3. The monitoring period is divided into normal period and overflow period according to the flow data. The pollution load is calculated using the time-weighted average method during the normal period and the pollution load is calculated using the real-time integral method based on the high-frequency flow and pollutant concentration measurements during the overflow period. S4. Add up the pollution loads calculated during the normal period and the overflow period to obtain the total annual pollution load of the overflow outlet.

[0021] Preferably, the flow sensor in the robust multimodal sensor array is an ultrasonic flow meter, and the ultrasonic flow meter has an ultrasonic vibration anti-adhesion function.

[0022] Preferably, the pollutant concentration sensor in the robust multimodal sensor array is an optical or electrochemical water quality sensor, and the pollutant concentration sensor has a dual-probe cross-validation function and / or a mechanical scraping self-cleaning function.

[0023] Preferably, the optimization of the sensor placement location is based on the hydraulic characteristics of the overflow outlet, including the outlet width, depth, and flow pattern, and the placement location is determined in conjunction with the outlet cross-sectional dimensions.

[0024] Preferably, the specific method for dynamically adjusting the data acquisition frequency is as follows: when the real-time traffic reaches a preset overflow threshold, or the traffic increase rate exceeds a preset change rate threshold, the data acquisition frequency is switched from the normal baseline frequency to the overflow high-frequency mode; the normal baseline frequency is once per hour, and the overflow high-frequency mode is once per minute or more.

[0025] Preferably, the real-time integration method during the overflow period is as follows: the instantaneous flow rate and instantaneous pollutant concentration corresponding to each high-frequency sampling point are multiplied, the product is multiplied by the corresponding sampling interval duration, and finally the calculation results of all sampling points are accumulated and integrated over the entire overflow duration.

[0026] Preferably, the method further includes calibration and verification steps: periodically calibrating the sensors in the robust multimodal sensor array on-site using standard solutions; periodically manually sampling and sending samples to the laboratory for analysis, comparing the laboratory analysis results with the online monitoring data, and verifying and correcting the online monitoring data.

[0027] Preferably, the pollutant concentration data includes at least one of chemical oxygen demand, ammonia nitrogen, and total phosphorus; the time-weighted average method for the normal period is specifically as follows: within each sampling interval, the product of flow rate and pollutant concentration is multiplied by the interval duration, and then the calculation results of all sampling intervals are accumulated.

[0028] Preferably, the dynamic adjustment of the data acquisition frequency adopts a graded frequency conversion strategy, specifically including: When the real-time flow reaches the preset overflow threshold or the flow rate exceeds the preset change rate threshold, and the pollutant concentration change rate is ≥20% within 5 minutes, it is determined to be the initial stage of overflow. The data acquisition frequency is switched to ultra-high frequency mode, and the sampling interval of ultra-high frequency mode is 10 seconds to 30 seconds. When the flow rate is stable above the preset overflow threshold and the fluctuation range is ≤10%, and the pollutant concentration change rate is <10% within 5 minutes, it is determined to be the overflow peak period, and the data collection frequency is switched to high frequency mode. The sampling interval of high frequency mode is 1 minute to 2 minutes. When the flow rate starts to decrease from the peak and the rate of decrease is ≥5% / minute, or when the pollutant concentration continues to decrease and the rate of decrease is ≥15% / 30 minutes, it is determined to be the overflow drainage period, and the data acquisition frequency is switched to medium-high frequency mode, with a sampling interval of 3 to 5 minutes in the medium-high frequency mode. When the flow rate drops below the preset overflow threshold and remains below it for more than 30 minutes, the data collection frequency returns to the normal baseline frequency.

[0029] This embodiment also proposes a pollution load calculation system for large overflow outlets, including: A multimodal sensor array is deployed directly inside a large overflow outlet; it includes at least one online flow sensor and one or more online pollutant concentration sensors. An ultrasonic flow meter with ultrasonic vibration anti-adhesion function is preferred; Optical or electrochemical water quality sensors are preferred, with some equipped with dual probes; It features self-cleaning and redundant calibration functions; Based on the hydraulic characteristics and cross-sectional dimensions of the outlet, select areas where the water flow is well mixed and the data is highly representative, or deploy multiple sensors to perform weighted averaging of data for complex flow patterns; Real-time, synchronous acquisition of highly reliable flow data and pollutant concentration data provides basic measured data for subsequent calculations; The data acquisition and control module is directly electrically connected to the robust multimodal sensor array; it receives the raw flow and concentration data collected by the sensor array and performs preliminary storage; it has a built-in adaptive algorithm that dynamically adjusts the data acquisition frequency of the sensor array based on real-time monitored flow data or flow change rate; and it performs preliminary filtering of obviously abnormal data to ensure the validity of transmitted data. The data transmission module is located between the data acquisition and control module and the data processing module; it uses wireless network transmission and partially supports primary and backup dual-link switching; it transmits the effective data processed by the data acquisition and control module to the cloud data processing center or local server in real time. The data processing module can be located on a cloud server or a local computer. It comprises several sub-units, implementing the entire process from period identification to load calculation to total load accumulation. Period identification unit: Based on the received flow data, automatically identify the normal period and overflow period within the monitoring cycle; Load calculation unit: Adapts to different algorithms based on period type, including: Normal period: Time-weighted average method is used; Overflow period: Real-time integration method based on dynamic coupling relationship of real-time measurement value is adopted; Load accumulation unit: The pollution load of all normal periods and each overflow period is superimposed to obtain the total annual pollution load; Reduce reliance on theoretical model parameters and drive calculations entirely based on measured data.

[0030] Example 2 This embodiment provides a method and system for calculating the annual pollution load of a large overflow outlet. Its core lies in deploying stable and reliable online monitoring equipment, supplemented by an intelligent data acquisition strategy, and performing segmented and dynamic load calculations based on the obtained measured data. For example... Figures 2-3 As shown, a method for calculating the pollution load of a large overflow outlet mainly includes the following steps: A1: Data Acquisition and Preprocessing.

[0031] In one embodiment of the invention, a robust multimodal sensor array is first deployed within a large overflow outlet. This array includes at least one online flow sensor and one online contaminant concentration sensor.

[0032] Preferably, an ultrasonic flow meter can be used as the flow sensor. This type of flow meter calculates the flow velocity by measuring the time difference of sound wave propagation in the water flow, and then calculates the flow rate by combining the pipe cross-sectional area. To cope with the possible presence of silt, oil, or biological deposits in the sewage, the transducer (probe) of the ultrasonic flow meter can integrate an ultrasonic vibration anti-adhesion function, that is, to remove dirt from the probe surface through high-frequency vibration, ensuring measurement accuracy.

[0033] Pollutant concentration sensors can be selected as needed, such as optical sensors for measuring chemical oxygen demand (COD), ion-selective electrode sensors for measuring ammonia nitrogen (NH3-N), or ultraviolet-visible spectrophotometric sensors for measuring total phosphorus (TP). To further improve reliability, these sensors can have self-cleaning functions, such as integrated scrapers or high-pressure water / air rinsing devices, and can employ redundant calibration designs, such as dual-probe cross-validation. This involves deploying two independent probes at the same measurement point, comparing the data from the two probes to determine the sensor's operating status and measurement accuracy, and triggering calibration or an alarm if a significant deviation occurs.

[0034] Optimizing sensor placement is crucial. For example, in rectangular or circular overflow channels, sensors can be deployed in the lower middle section of a cross-section where water mixing is more thorough and representative. Alternatively, based on hydraulic model analysis, multiple sensors can be deployed and the data weighted averaged in sections where significant concentration gradients may exist to obtain more representative flow and pollutant concentration data.

[0035] A2: Adaptive data monitoring and transmission.

[0036] This step aims to balance data density and energy consumption, and effectively capture overflow events.

[0037] During normal periods without rainfall or low flow, the system uses a lower baseline data acquisition and transmission frequency, such as once per hour. This helps save power and communication bandwidth.

[0038] Once rainfall is detected, or real-time flow data reaches a preset overflow trigger threshold, or the flow change rate reaches a preset rainstorm trigger threshold, the data acquisition and transmission frequency will automatically switch to a high-frequency mode, such as once per minute, or even once every 10 seconds for short periods. This adaptive adjustment mechanism based on flow dynamics ensures that sufficient density of real-time data can be obtained during the initial overflow flushing, peak, and receding periods when pollution load changes most drastically.

[0039] The collected data will be transmitted in real time to a cloud data processing center or a local server for storage via a wireless communication module.

[0040] A3: Dynamic coupling calculation of load.

[0041] The data processing center automatically identifies the "normal period" and "overflow period" throughout the year based on the received traffic data. The identification rules can be based on preset traffic thresholds and durations.

[0042] During normal periods, since the changes in flow rate and concentration are relatively stable, the time-weighted average method can be used to calculate the pollution load. That is, within each sampling interval, the product of flow rate and pollutant concentration is multiplied by the duration of the interval and then accumulated.

[0043] During the overflow period, since flow rate and concentration exhibit nonlinear dynamic changes, this invention employs a real-time integration method based on the dynamic coupling relationship of real-time measurements. Specifically, the system utilizes high-frequency flow rate and pollutant concentration measurements acquired from a robust sensor array to multiply the flow rate and pollutant concentration in real time during each overflow event, and performs high-frequency cumulative integration of these instantaneous loads over the entire overflow duration. Here, "dynamic coupling relationship" refers to the fact that pollutant concentration and flow rate are not independent but typically exhibit some correlation. The system automatically reflects this relationship using measured data, rather than relying on preset, fixed empirical curves. For example, for each high-frequency sampling point i, its instantaneous pollution load... = X

[0044]

[0045] in It is instantaneous flow. This refers to the instantaneous pollutant concentration. The total load of the entire overflow event is also considered. ,in The sampling interval is denoted as .

[0046] Finally, by summing up the pollution loads calculated for all normal and overflow periods, the total annual pollution load of the overflow outlet can be obtained.

[0047] A4: Calibration and Verification.

[0048] To ensure long-term operational accuracy, this embodiment also includes a periodic calibration and verification mechanism.

[0049] The sensor should be calibrated in the field periodically using a standard solution to correct for sensor drift.

[0050] In addition, manual sampling should be conducted regularly, such as quarterly or after critical overflow events, and the water samples should be sent to a professional laboratory for analysis. The laboratory analysis results should be compared with the online monitoring data from the same period to verify the accuracy of the online monitoring, and the internal calibration parameters of the online monitoring system can be fine-tuned based on the comparison results.

[0051] This is a structural block diagram of a large overflow outlet pollution load calculation system as an example.

[0052] The system mainly includes: Robust multimodal sensor array: Deployed at the overflow outlet, including ultrasonic flow meters and various water quality sensors, with self-cleaning and redundant calibration functions, for real-time synchronous acquisition of flow and pollutant concentration data.

[0053] Data acquisition and control module: Connects to the sensor array, responsible for receiving sensor data, performing preliminary data storage, and dynamically controlling the data acquisition frequency of the sensor array based on a built-in adaptive algorithm. For example, it switches between high and low frequencies based on flow rate or flow rate change threshold.

[0054] Data transmission module: Transmits the data processed by the data acquisition and control module to the cloud or local data processing center via wireless network.

[0055] Data processing module: Deployed on a cloud server or local computer, it receives and stores the transmitted data. This module includes: Period identification unit: Automatically identifies normal periods and overflow periods based on flow data.

[0056] Load calculation unit: Based on the period identification results, load calculations are performed for the normal period and the overflow period respectively. The overflow period calculation adopts the real-time integration method based on the dynamic coupling relationship of real-time measurement values.

[0057] Load accumulation unit: The total annual load is obtained by accumulating the load amounts of each period.

[0058] Results output module: Used to display calculation results. Includes: Visualization platform: Displays real-time data and trend charts such as traffic volume, concentration, instantaneous load, and annual cumulative load on a computer web interface or mobile app.

[0059] Alarm and report generation unit: can generate alarms for exceeding limits, daily reports, monthly reports and annual reports according to preset rules.

[0060] Taking the annual COD load calculation of a combined sewer overflow (CSO) outlet as an example: 1. Install an ultrasonic flow meter with integrated self-cleaning function and a dual-probe cross-validated ultraviolet spectral COD online sensor at the CSO outlet, and deploy them in the area where the flow rate and water quality are well mixed at the outlet cross-section.

[0061] 2. The system collects traffic and COD data once per hour by default.

[0062] 3. When rainfall occurs and the flow rate measured by the flow meter continues to rise and exceeds the set overflow threshold, or when the flow rate rises at a rate exceeding 2 m³ / s per minute, the data acquisition frequency automatically switches to once per minute. At this time, the flow and COD sensors synchronously acquire data at a high frequency.

[0063] 4. Data is transmitted to the cloud processing platform in real time. The platform automatically identifies all overflow events and their start and end times based on traffic thresholds and durations.

[0064] 5. During normal periods when there is no overflow, the platform calculates the normal COD load using a time-weighted average method based on the hourly collected flow and COD data.

[0065] 6. For each overflow event, the platform performs high-frequency real-time integral calculations based on the traffic flow and COD data collected every minute, and accumulates the results to obtain the COD load for that overflow event. This calculation directly utilizes high-frequency measured data, reflecting the actual dynamic relationship between traffic flow and COD concentration.

[0066] 7. The total annual COD emissions from the CSO outlet are calculated by summing up the COD loads during all normal and overflow periods within the year.

[0067] 8. The sensor is calibrated with standard solution every quarter, and several water samples are sent to the laboratory for COD analysis and compared with the online monitoring data to ensure that the error of the annual calculation results is controlled within ±15%.

[0068] The present invention, through the above technical solution, can effectively solve the problems of accuracy and reliability in the calculation of annual pollution load of overflow outlets using traditional methods, and provide environmental management departments with more accurate and valuable decision-making basis.

[0069] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for calculating the pollution load of a large overflow outlet, characterized by: Includes the following steps: S1. Deploy a robust multimodal sensor array within the overflow outlet to acquire flow data and pollutant concentration data of the overflow outlet in real time. The sensor array has self-cleaning or redundant calibration functions, and the sensor placement is optimized to ensure data representativeness. S2. Based on real-time monitored flow data or flow change rate, dynamically adjust the data acquisition frequency, including normal baseline frequency and overflow high-frequency mode. S3. Based on the flow data, the monitoring period is divided into normal period and overflow period. During the normal period, the pollution load is calculated using the time-weighted average method. During the overflow period, the pollution load is calculated using the real-time integration method based on the high-frequency flow and pollutant concentration measurements. S4. Add up the pollution loads calculated during the normal period and the overflow period to obtain the total annual pollution load of the overflow outlet.

2. The method for calculating the pollution load of a large overflow outlet according to claim 1, characterized in that, The flow sensor in the robust multimodal sensor array is an ultrasonic flow meter, and the ultrasonic flow meter has an ultrasonic vibration anti-adhesion function.

3. The method for calculating the pollution load of a large overflow outlet according to claim 1, characterized in that, The pollutant concentration sensor in the robust multimodal sensor array is an optical or electrochemical water quality sensor, and the pollutant concentration sensor has a dual-probe cross-validation function or a mechanical scraping self-cleaning function.

4. The method for calculating the pollution load of a large overflow outlet according to claim 1, characterized in that, The optimization of sensor placement is based on the hydraulic characteristics of the overflow outlet, including the outlet width, depth, and flow pattern, and the placement location is determined in conjunction with the outlet cross-sectional dimensions.

5. The method for calculating the pollution load of a large overflow outlet according to claim 1, characterized in that, The specific method for dynamically adjusting the data acquisition frequency is as follows: when the real-time traffic reaches the preset overflow threshold, or the traffic increase rate exceeds the preset change rate threshold, the data acquisition frequency is switched from the normal baseline frequency to the overflow high-frequency mode. The normal baseline frequency is once per hour, and the overflow high-frequency mode is once per minute or more.

6. The method for calculating the pollution load of a large overflow outlet according to claim 1, characterized in that, The real-time integration method during the overflow period is as follows: the instantaneous flow rate and the instantaneous pollutant concentration corresponding to each high-frequency sampling point are multiplied, the product is multiplied by the corresponding sampling interval duration, and finally the calculation results of all sampling points are accumulated and integrated over the entire overflow duration.

7. The method for calculating the pollution load of a large overflow outlet according to claim 1, characterized in that, It also includes calibration and verification steps: periodically using standard solutions to perform on-site calibration of the sensors in the robust multimodal sensor array; periodically manually sampling and sending samples to the laboratory for analysis, comparing the laboratory analysis results with the online monitoring data, and verifying and correcting the online monitoring data.

8. The method for calculating the pollution load of a large overflow outlet according to claim 1, characterized in that, Pollutant concentration data include at least one of chemical oxygen demand, ammonia nitrogen, and total phosphorus; The time-weighted average method during normal periods is as follows: within each sampling interval, the product of flow rate and pollutant concentration is multiplied by the duration of that interval, and then the calculation results for all sampling intervals are summed.

9. The method for calculating the pollution load of a large overflow outlet according to claim 1, characterized in that, The dynamic adjustment of data acquisition frequency adopts a tiered frequency conversion strategy, specifically including: When the real-time flow reaches the preset overflow threshold or the flow rate exceeds the preset change rate threshold, and the pollutant concentration change rate is ≥20% within 5 minutes, it is determined to be the initial stage of overflow. The data acquisition frequency is switched to ultra-high frequency mode, and the sampling interval of ultra-high frequency mode is 10 seconds to 30 seconds. When the flow rate is stable above the preset overflow threshold and the fluctuation range is ≤10%, and the pollutant concentration change rate is <10% within 5 minutes, it is determined to be the overflow peak period, and the data collection frequency is switched to high frequency mode. The sampling interval of high frequency mode is 1 minute to 2 minutes. When the flow rate starts to decrease from the peak and the rate of decrease is ≥5% / minute, or when the pollutant concentration continues to decrease and the rate of decrease is ≥15% / 30 minutes, it is determined to be the overflow drainage period. The data acquisition frequency is switched to medium-high frequency mode, and the sampling interval of medium-high frequency mode is 3 minutes to 5 minutes. When the flow rate drops below the preset overflow threshold and remains below it for more than 30 minutes, the data collection frequency returns to the normal baseline frequency.

10. A pollution load calculation system for a large overflow outlet, characterized in that, include: A multimodal sensor array is deployed directly inside a large overflow outlet; Including online flow sensors and online pollutant concentration sensors: Choose an ultrasonic flow meter with ultrasonic vibration anti-adhesion function. Choose optical or electrochemical water quality sensors; some are equipped with dual probes. It features self-cleaning and redundant calibration functions; Based on the hydraulic characteristics and cross-sectional dimensions of the outlet, select areas where the water flow is well mixed and the data is highly representative, or deploy several sensors to perform weighted averaging of data for complex flow patterns; Real-time and synchronous collection of flow data and pollutant concentration data provides basic measured data for subsequent calculations; The data acquisition and control module is directly electrically connected to the robust multimodal sensor array; It receives raw flow and concentration data collected by the sensor array and performs initial storage; it has a built-in adaptive algorithm to dynamically adjust the data acquisition frequency of the sensor array based on real-time monitored flow data or flow change rate; it initially filters out obviously abnormal data to ensure the validity of transmitted data. The data transmission module is located between the data acquisition and control module and the data processing module; it uses wireless network transmission and partially supports primary and backup dual-link switching; it transmits the effective data processed by the data acquisition and control module to the cloud data processing center or local server in real time. The data processing module, located on a cloud server or local computer, comprises several sub-units, including: Period identification unit: Based on the received flow data, automatically identify the normal period and overflow period within the monitoring cycle; Load calculation unit: Adapts to different algorithms based on period type, including: Normal period: Time-weighted average method is used; Overflow period: Real-time integration method based on dynamic coupling relationship of real-time measurement value is adopted; Load accumulation unit: The pollution load of all normal periods and each overflow period is superimposed to obtain the total annual pollution load; Reduce reliance on theoretical model parameters and drive calculations entirely based on measured data.

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