Industrial wastewater treatment pollutant discharge monitoring method and system

Abstract

The invention provides an industrial wastewater treatment pollutant discharge monitoring method and system, and relates to the technical field of industrial wastewater treatment, pollutant discharge monitoring and environmental risk management, and the method comprises the steps: carrying out the preprocessing operation after screening an original data set, obtaining a real-time effective data set, introducing two different judgment logics, and obtaining a real-time effective data set; one logic is used for judging persistent pollution, the other logic is used for judging instantaneous pollution, when the instantaneous pollution exists, instantaneous standard exceeding events are generated, parameters are recorded, a supervision risk event record book is generated in an integrated mode, and the supervision risk event record book is obtained by inquiring the parameters and the number of the instantaneous standard exceeding events in the supervision risk event record book in a timed mode. And setting a risk condition, and when the risk condition is met, sending a first risk report to execute an audible and visual alarm operation. The method has the advantages that the'false compliance 'emission risk caused by internal monitoring logic blind areas and external monitoring sampling mode mismatching in the prior art is effectively recognized and early warned, and unnecessary punishment and loss of enterprises are avoided.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of industrial wastewater treatment, pollutant emission monitoring and environmental risk management, in particular to an industrial wastewater treatment pollutant emission monitoring method and system. BACKGROUND

[0002] In industrial production activities, the compliance of wastewater treatment and pollutant emission is an important challenge faced by enterprises. In order to balance production efficiency and environmental protection, enterprises usually deploy online monitoring systems and develop corresponding emission control strategies. Under certain specific production processes, the characteristics of wastewater discharge may exhibit a short-time, high-concentration pulse feature. When the "blind area" of the monitoring logic and the "instant sampling" mode of the external regulatory agency do not match, even if the internal system of the enterprise shows that everything is normal, it may face the risk of being judged by the outside as exceeding the standard emission, thereby causing economic losses and production suspension.

[0003] The wastewater treatment station supporting the park has deployed continuous automatic monitoring equipment for multiple indicators. In order to ensure emission compliance, a very cautious operation mode is set, and when the real-time monitoring value of the key pollutant reaches the preset limit value, an alarm is triggered and the enhanced treatment program is linked, and the production line is reduced. Another operation mode is: the system does not make immediate response to the instantaneous over-limit data points, starts a timing observation window, and only when the pollutant concentration value is continuously and stably above the preset limit value for a certain period of time, it is determined as a "persistent emission risk" that needs to be intervened, and the enhanced treatment program is started. When high-concentration wastewater passes through, record the concentration peak, which is far above the legal limit, but due to the insufficient duration, the system classifies it as "short-term fluctuation without intervention", and does not trigger any alarm or intervention measures.

[0004] The prior art has deficiencies in identifying and warning the "pseudo-compliance" emission risk caused by the mismatch between the internal monitoring logic blind area and the external regulatory sampling mode.

[0005] Therefore, it is an urgent problem for those skilled in the art to provide an industrial wastewater treatment pollutant emission monitoring method and system for solving the above problems. SUMMARY

[0006] The purpose of the present application is to provide an industrial wastewater treatment pollutant emission monitoring method, which has the advantages of being able to effectively identify and warn the "pseudo-compliance" emission risk caused by the mismatch between the internal monitoring logic blind area and the external regulatory sampling mode in the prior art, and avoiding unnecessary penalties and losses faced by enterprises.

[0007] In order to achieve the above purpose, the technical scheme provided by the present application is as follows: An industrial wastewater treatment pollutant emission monitoring method applied to a chemical industry park wastewater treatment scene, comprising the following steps: obtain pollution concentration data corresponding to a plurality of pollutants in industrial wastewater, and upload the pollution concentration data as real-time original data sets after a first preset time period; perform a preprocessing operation on the real-time original data sets, obtain a preprocessed real-time effective data set, and deliver the preprocessed real-time effective data set; According to the preprocessed real-time effective data set, respectively, first determine whether the pollution concentration data of any of the pollutants in a preset sliding time window is greater than a preset first pollution concentration threshold, if all the first determination results are yes, define as persistent pollution, and perform pollution treatment enhancement operation according to the corresponding pollutants; According to the preprocessed real-time effective data set, respectively, secondly determine whether the pollution concentration data of any of the pollutants in each of the first preset time period is greater than a preset second pollution concentration threshold, if any of the second determination results is yes, define as transient pollution, generate transient over-standard event and record transient over-standard event parameter, integrate all the transient over-standard events into a regulatory risk event record book; Query the regulatory risk event record book regularly, thirdly determine whether the preset risk condition is met according to the transient over-standard event parameter and the number of all the transient over-standard events, if the third determination result is yes, send a first risk report and perform a sound and light alarm operation.

[0008] Through the above scheme, after the preprocessing operation on the original data set, the real-time effective data set is obtained, two different judgment logics are introduced, one of which is the judgment of persistent pollution, and the other is the judgment of transient pollution. When there is transient pollution, the transient over-standard event is generated and the parameter is recorded, and the regulatory risk event record book is integrated. By regularly querying the transient over-standard event parameter and the number of transient over-standard events in the regulatory risk event record book, the risk condition is set, and when the risk condition is met, the first risk report is sent and the sound and light alarm operation is performed.

[0009] Preferably, after the first determination result is no and the regulatory risk event record book is obtained, the following steps are further included: Statistical pollution concentration data when the first determination result is no, generate a pollutant concentration curve; Obtain the sliding average of the pollution concentration data in a second preset time period; According to the visual display of the pollutant concentration curve, the sliding average of the pollution concentration data in the second preset time period, the transient over-standard event parameter and the number of all the transient over-standard events, send a second risk report.

[0010] Through the above scheme, after the pollution concentration data when the first judgment result is false is counted, the pollution concentration curve is generated, and the sliding average of the pollution concentration data in the second preset time period is obtained, the man-machine interaction device is introduced, and the above contents are displayed side by side on the display screen of the man-machine interaction device. When the management personnel see "running stably" on the left side, "X times of external instantaneous over-standard events have occurred today" is prompted on the right side. Further introduction of the visualization and reporting mechanism enables the management personnel to more comprehensively understand the emission condition, assists decision-making, and reduces potential risks.

[0011] Preferably, the pre-processing operation is performed after the real-time raw data set is screened, a pre-processed real-time effective data set is obtained and issued, and the following steps are included: According to whether the real-time raw data set is complete, whether the numerical range of the pollution concentration data is abnormal, and whether the pollution concentration data conforms to the historical trend analysis result, the invalid data in the real-time raw data set is removed, and the effective data is retained as a real-time effective data set; The real-time effective data set is sequentially subjected to unit conversion and formatting processing, and the pre-processed real-time effective data set is obtained and issued.

[0012] Through the above scheme, by designing various screening conditions: judging whether the issued implementation raw data set is complete; judging whether the numerical range of the pollution concentration data is abnormal; judging whether the pollution concentration data conforms to the historical trend analysis result, the raw data set is screened, after the screening is completed, unit conversion and formatting processing are performed, and the pre-processed real-time effective data set with consistent data structure of all monitoring parameters is obtained and issued. The data preprocessing process is refined, the accuracy and effectiveness of the data relied on subsequent judgment are ensured, and the reliability of monitoring is improved.

[0013] Preferably, the first judgment is performed on whether the pollution concentration data of any of the pollutants in the preset sliding time window is greater than a preset first pollution concentration threshold value according to the pre-processed real-time effective data set, and the following steps are included: A plurality of pre-processed real-time effective data sets are obtained in a preset sliding time window; The pollution concentration data of any of the pollutants in each of the pre-processed real-time effective data sets is respectively first judged whether it is greater than a preset first concentration threshold value.

[0014] By the above scheme, a sliding window is introduced, and by setting the sliding window, a time range is circumscribed. A plurality of preprocessed real-time effective data sets are acquired in the sliding time window. First judgment is performed on each preprocessed real-time effective data set. It is judged whether the pollution concentration data of any one of the pollutants is greater than the preset first concentration threshold. When all the first judgment results are yes, it is defined as persistent pollution, and the corresponding pollution treatment enhancement operation is performed according to the pollutant. The judgment logic of persistent pollution is defined, and the accurate identification of long-term stable over-standard situation is ensured.

[0015] Preferably, according to the preprocessed real-time effective data set, whether the pollution concentration data of any one of the pollutants in each of the first preset time periods is greater than the preset second pollution concentration threshold is second judged respectively. If any second judgment result is yes, it is defined as transient pollution, a transient over-standard event is generated, and transient over-standard event parameters are recorded, including the following steps: A timestamp is generated according to the first preset time period; The preprocessed real-time effective data set corresponding to each of the timestamps is acquired; Whether the pollution concentration data of any one of the pollutants in the preprocessed real-time effective data set corresponding to each of the timestamps is greater than the preset second pollution concentration threshold is second judged respectively; If any second judgment result is yes, it is defined as transient pollution, a transient over-standard event is generated, and the timestamp and duration corresponding to the transient over-standard event, the over-standard pollutant type and the over-standard pollution concentration data are recorded; The transient over-standard event parameters include the timestamp corresponding to the occurrence of the transient over-standard event, the duration of the transient over-standard event, the timestamp corresponding to the end of the transient over-standard event, the over-standard pollutant type and the over-standard pollution concentration data.

[0016] By the above scheme, a timestamp is introduced, and the preprocessed real-time effective data set corresponding to each timestamp is acquired. Second judgment is performed on each preprocessed real-time effective data set. When one of the second judgment results is yes, it is defined as transient pollution, a transient over-standard event is generated, and the timestamp and duration corresponding to the transient over-standard event, the over-standard pollutant type and the over-standard pollution concentration data are recorded. Each time one of the second judgment results is yes, a transient over-standard event is recorded. The judgment and event recording mechanism of transient pollution is defined in detail, which provides a basis for accurate identification and tracing of short-time high-concentration emission events.

[0017] Preferably, the timing query is performed on the regulatory risk event record book, and the third determination is performed on whether a preset risk condition is met according to the instantaneous over-standard event parameter and the number of all the instantaneous over-standard events. The third determination is performed on whether the number of all the instantaneous over-standard events within a third preset time period is greater than a preset number threshold. Or, The third determination is performed on whether the cumulative duration of the plurality of instantaneous over-standard events within a fourth preset time period is greater than a preset over-standard time threshold. If any of the third determinations is yes, it is defined that the preset risk condition is met.

[0018] According to the above scheme, the regulatory risk event record book is queried at a timing, and the corresponding determination condition is set according to the instantaneous over-standard event parameter and the number of all the instantaneous over-standard events. When any determination result meets the determination condition, it is defined that the preset risk condition is met. Multiple risk determination conditions are provided, so that the system can more flexibly and comprehensively evaluate the cumulative risk of the instantaneous over-standard event, and the accuracy of the early warning is improved.

[0019] Preferably, after the instantaneous over-standard event is generated and the time stamp and duration, over-standard pollutant type and over-standard pollution concentration data corresponding to the instantaneous over-standard event are recorded, the method further comprises the following steps: Requesting to obtain production activity information of all production lines within a first preset time window before and after the time stamp corresponding to the occurrence of the instantaneous over-standard event; If the request is responded to, according to a preset production activity plan and real-time working conditions, production batch information, a current process stage and a product type matched with the time stamp corresponding to the instantaneous over-standard event are fed back as process source identification of the instantaneous over-standard event; If the request is not responded to, an unknown source identification is added for the instantaneous over-standard event; The production activity information includes the production batch information, the current process stage and the product type.

[0020] According to the above scheme, after the instantaneous over-standard event is generated, the production activity information of all production lines is requested to be obtained, and the process source identification of the actual over-standard event is determined in combination with the preset production activity plan and real-time working conditions. If the request is not responded to, an unknown source identification is added. The process source of the instantaneous over-standard event is traced, which helps enterprises to quickly locate the problem source, optimize the production process, and fundamentally solve the emission problem.

[0021] Preferably, after defining the instantaneous pollution as the transient pollution, generating the transient over-standard event and recording the time stamp, duration, over-standard pollutant type and over-standard pollution concentration data corresponding to the transient over-standard event, the method further comprises the following steps: According to the real-time working condition, the product type and the current process stage of each production line are obtained, which are classified as low-risk processes and high-risk processes, and the planned start time stamp of the high-risk process is obtained according to the preset production activity plan; The wastewater discharge delay time of each production line is obtained; According to the wastewater discharge delay time of each production line, the low-risk process and the corresponding production line matched with the time stamp corresponding to the transient over-standard event are determined as the low-risk source identification of the transient over-standard event; According to the time stamp corresponding to the transient over-standard event and the maximum wastewater discharge delay time, an expected wastewater discharge time stamp is obtained; The fourth determination is whether the planned start time stamp of the high-risk process falls within a second preset time window after the expected wastewater discharge time stamp; If yes, the low-risk source identification is updated to a potential composite high-risk identification, and a third risk report is sent.

[0022] Through the above scheme, the product type and the current process stage of each production line are classified as low-risk processes and high-risk processes by combining the real-time working condition and the preset production activity plan, and the original low-risk source identification is updated to a composite high-risk identification by combining the wastewater discharge delay time. The update mechanism from low-risk source to potential composite high-risk is introduced, which can early warn the potential composite high-risk emission event and provide more forward-looking risk management for enterprises.

[0023] Preferably, after updating the low-risk source identification to the potential composite high-risk identification, the method further comprises the following steps: According to the planned start time stamp of the high-risk process and the wastewater discharge delay time of the production line corresponding to the high-risk process, a high-risk wastewater discharge time stamp is obtained; The pollution concentration data of any of the pollutants in the high-risk process in the time period of the time stamp corresponding to the transient over-standard event and the high-risk wastewater discharge time stamp are obtained in real time, and a high-risk actual concentration decay trend curve is generated by fitting; The high-risk actual concentration decay trend curve is compared with a preset low-risk theoretical concentration decay trend curve at the high-risk wastewater discharge time stamp, and the fourth determination is whether the high-risk actual concentration decay trend curve has any preset risk feature; If the fourth determination result is yes, the potential high-risk composite event is updated to a confirmed high-risk composite event, and a fourth risk report is sent; The preset risk characteristics include a significant slowdown in the falling rate, a re-increase after falling, and a sustained high level.

[0024] Through the above scheme, the high-risk wastewater discharge timestamp is introduced, and the high-risk actual concentration decay trend curve generated by fitting the pollution concentration data obtained in the time period is compared with the preset low-risk theoretical concentration decay trend curve at the timestamp, further updating the potential high-risk composite event to a confirmed high-risk composite event, improving the accuracy and reliability of risk identification, and providing a basis for taking targeted measures.

[0025] An industrial wastewater treatment pollutant discharge monitoring system is applied to a chemical industry park wastewater treatment scene, and includes: An acquisition module is configured to acquire pollution concentration data corresponding to multiple pollutants in industrial wastewater, and upload the pollution concentration data as real-time original data sets after a first preset time period. A preprocessing module is configured to filter and preprocess the real-time original data sets to obtain real-time effective data sets after preprocessing and issue the real-time effective data sets. A first determination module is configured to determine, according to the real-time effective data sets after preprocessing, whether the pollution concentration data of any of the pollutants in a preset sliding time window is greater than a preset first pollution concentration threshold, and if all the determination results are yes, define it as persistent pollution and perform a pollution treatment enhancement operation according to the pollutants. A second determination module is configured to determine, according to the real-time effective data sets after preprocessing, whether the pollution concentration data of any of the pollutants in each of the first preset time periods is greater than a preset second pollution concentration threshold, and if any of the determination results is yes, define it as instantaneous pollution, generate an instantaneous over-standard event and record instantaneous over-standard event parameters, and integrate all the instantaneous over-standard events into a regulatory risk event record book. A third determination and alarm module is configured to query the regulatory risk event record book at regular intervals, determine, according to the instantaneous over-standard event parameters and the number of all the instantaneous over-standard events, whether a preset risk condition is met, and if the determination result is yes, send a first risk report and perform a sound and light alarm operation.

[0026] The application also provides an industrial wastewater treatment pollutant discharge monitoring system, which, due to the same technical concept and the same technical problems as the method, should have the same beneficial effects, and will not be described here.

[0027] In summary, the industrial wastewater treatment pollutant emission monitoring method and system provided by the application effectively solves the "pseudo-compliance" emission risk caused by the internal monitoring logic blind area and the external supervision sampling mode mismatch in the prior art by introducing the identification, recording and risk assessment mechanism of transient pollution, has the advantages of being able to effectively identify and warn the "pseudo-compliance" emission risk caused by the internal monitoring logic blind area and the external supervision sampling mode mismatch in the prior art, and avoiding unnecessary punishment and loss faced by enterprises BRIEF DESCRIPTION OF DRAWINGS

[0028] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0029] Figure 1 The flowchart of the industrial wastewater treatment pollutant emission monitoring method provided by the embodiment of the present application is shown in the figure. Figure 2 The flowchart after the first judgment result is no in step S31 and the supervision risk event record book is obtained in step S32 provided by the embodiment of the present application is shown in the figure. Figure 3 The flowchart of step S32 provided by the embodiment of the present application is shown in the figure. Figure 4 The flowchart after the transient over-standard event is generated and the transient over-standard event parameters are recorded provided by the embodiment of the present application is shown in the figure. Figure 5 The flowchart after the potential composite high-risk identification is updated provided by the embodiment of the present application is shown in the figure. Figure 6 The structural schematic diagram of the industrial wastewater treatment pollutant emission monitoring system provided by the embodiment of the present application is shown in the figure. DETAILED DESCRIPTION

[0030] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0031] The embodiments of the present application are written in a progressive manner.

[0032] In the face of the technical problems presented in the background art, the present application introduces a mechanism to specifically identify and manage transient high-concentration emission events while maintaining effective monitoring of persistent pollution, without overreacting. At the same time, for transient over-standard events, it is necessary to record and accumulate them in order to assess their potential risks from a macro perspective, rather than making judgments based on single events. In this way, it is possible to avoid taking high-cost enhanced treatment immediately for every transient over-standard, but to give warnings and responses according to the accumulated risk level.

[0033] As shown in Figure 1 An industrial wastewater treatment pollutant emission monitoring method applied to a chemical industry park wastewater treatment scene, comprising the following steps: S1. Obtain the pollution concentration data corresponding to a plurality of pollutants in industrial wastewater, and upload the pollution concentration data as real-time original data set after preprocessing according to a first preset time period; S2. Screen the real-time original data set for preprocessing operation to obtain the preprocessed real-time effective data set and issue it; S31. According to the preprocessed real-time effective data set, respectively, first determine whether the pollution concentration data of any pollutant in the preset sliding time window is greater than the preset first pollution concentration threshold value, if all the first determination results are yes, define it as persistent pollution, and execute pollution treatment enhancement operation according to the pollutant; S32. According to the preprocessed real-time effective data set, respectively, secondly determine whether the pollution concentration data of any pollutant in each first preset time period is greater than the preset second pollution concentration threshold value, if any second determination result is yes, define it as transient pollution, generate a transient over-standard event and record the transient over-standard event parameters, and integrate all transient over-standard events into a regulatory risk event record book; S4. Query the regulatory risk event record book regularly, according to the transient over-standard event parameters and the number of all transient over-standard events, thirdly determine whether the preset risk condition is met, if the third determination result is yes, send a first risk report and execute a sound and light alarm operation.

[0034] Among them, the first preset time period in step S1 refers to the time interval of data collection and uploading, which can adopt a fixed time interval; The preprocessing operation in step S2 refers to the process of quality control and standardization of the original pollution concentration data, which can be realized by using data cleaning, missing value filling, outlier rejection, unit conversion and formatting processing, etc. The preset sliding time window in step S31 refers to a continuous time range for evaluating whether the pollutant concentration is continuously over-standard, which can adopt a fixed time window such as one hour, two hours or more. The preset first pollutant concentration threshold refers to the concentration standard for judging persistent pollution, which can adopt a specific percentage of the national or local emission standard, such as 70% or 80% of the limit value. The pollution treatment enhancement operation refers to the intensified wastewater treatment measures taken for persistent pollution, which can be realized by increasing the dosage of chemical agents, improving the aeration intensity, adjusting the treatment process parameters, etc.

[0035] The preset second pollutant concentration threshold in step S32 refers to the concentration standard for judging transient pollution, which can adopt the limit value of the national or local emission standard, such as 100% of the limit value, or a specific value higher than the first threshold. The transient over-standard event refers to the emission event in which the pollutant concentration exceeds the preset second pollutant concentration threshold within a short time, which can be generated in the form of automatic recognition and recording by the system. The transient over-standard event parameter refers to the data set describing the specific situation of the transient over-standard event, which can include the timestamp, duration, over-standard pollutant type and over-standard pollutant concentration data, etc. The regulatory risk event record book refers to the database or log system for storing all transient over-standard events and their parameters, which can be realized by using a relational database, a non-relational database or a file system.

[0036] The preset risk condition in step S4 refers to the judgment rule for comprehensively evaluating whether the transient over-standard event constitutes an overall risk, which can be set based on the number of transient over-standard events, the cumulative duration or the specific pollutant type, etc.

[0037] Steps S1 to S4 are to build a multi-dimensional and hierarchical industrial wastewater treatment pollutant emission monitoring system, aiming to comprehensively cover and accurately respond to different types of pollution emission conditions. The system continuously acquires real-time pollutant concentration data of multiple pollutants in industrial wastewater, and uploads these data according to the first preset time period to form a real-time raw data set. The system performs strict preprocessing operations on the real-time raw data set to obtain a preprocessed real-time effective data set and issues it. A double judgment mechanism is introduced to deal with different types of pollution emissions.

[0038] On the one hand, the system performs a first judgment to continuously monitor whether the pollutant concentration data of any pollutant is greater than the preset first pollutant concentration threshold within the preset sliding time window. This judgment logic based on the time window effectively avoids false positives due to transient data fluctuations. Only when the pollutant concentration is stable at a high level for a long time, it is defined as persistent pollution, and the pollution treatment enhancement operation is triggered immediately to ensure effective control of long-term and stable over-standard.

[0039] On the other hand, the system simultaneously performs a second judgment, i.e., whether the pollution concentration data of any pollutant is greater than a preset second pollution concentration threshold in each first preset time period. Once any instantaneous over-standard is detected, even if its duration is not enough to trigger the first judgment, the system immediately defines it as an instantaneous pollution and generates a detailed instantaneous over-standard event, records its key parameters, and then integrates all such events into the regulatory risk event record book. This mechanism ensures that even short-term, easily overlooked high-concentration emissions can be captured and recorded.

[0040] The system will regularly query the regulatory risk event record book. By comprehensively analyzing the instantaneous over-standard event parameters and the number of all instantaneous over-standard events, the system performs a third judgment to assess whether the preset risk condition is met. Once the judgment result is that the preset risk condition is met, the system will immediately send a first risk report and perform a sound and light alarm operation.

[0041] This series of steps forms a closed loop from data collection, preprocessing, double pollution identification to risk assessment and early warning, enabling enterprises to actively identify and respond to pseudo-compliant emission risks that may lead to external regulatory penalties, thereby effectively improving the fine level and risk response capability of environmental compliance management while ensuring production efficiency.

[0042] In some preferred embodiments, the application is implemented as follows. In the scenario of chemical industrial park wastewater treatment, by deploying online monitoring equipment such as multi-parameter water quality analyzer, the pollution concentration data of various pollutants such as chemical oxygen demand (COD), ammonia nitrogen, total phosphorus, and total nitrogen in industrial wastewater are obtained in real time. These data are uploaded to the central monitoring platform by the data acquisition unit every five minutes as the first preset time period to form a real-time raw data set. Subsequently, the data preprocessing module of the central monitoring platform processes the received real-time raw data set. The valid data retained are converted into units, such as milligrams per liter to grams per cubic meter, and formatted, and finally the preprocessed real-time valid data set is obtained and delivered to the subsequent analysis module. According to the preprocessed real-time valid data set, the system executes two kinds of judgment logic in parallel. For the judgment of persistent pollution, the system sets a two-hour preset sliding time window and sets the preset first pollution concentration threshold to 70% of the legal emission standard. The system continuously monitors, and if in any two-hour sliding window, the pollution concentration data of any monitored pollutant is greater than the threshold of 70%, the system determines that it is persistent pollution. At this time, the system will automatically link the central control system of the wastewater treatment station to perform pollution treatment enhancement operation. At the same time, for the judgment of instantaneous pollution, the system sets the preset second pollution concentration threshold to 100% of the legal emission standard. In each five-minute first preset time period, the system judges whether the pollution concentration data of any pollutant is greater than the threshold of 100%. If any pollutant is detected to be over standard in any five-minute period, the system immediately defines it as instantaneous pollution and generates an instantaneous over-standard event. The event records detailed instantaneous over-standard event parameters, and all generated instantaneous over-standard events are integrated and stored in a regulatory risk event record book, which can be a dedicated database table. The system queries the regulatory risk event record book every hour. According to the instantaneous over-standard event parameters stored in the record book and the number of all instantaneous over-standard events, the system makes a third judgment to assess whether the preset risk condition is met. If any condition is met, the system determines that the preset risk condition is met, and immediately sends a first risk report to the email addresses of the environmental protection management department and the park management personnel, and triggers the sound and light alarm operation of the wastewater treatment station control room to remind the on-site personnel to take emergency measures.

[0043] As Figure 2 shown, preferably, after the first judgment result is no and the regulatory risk event record book is obtained, the following steps are included: A1. Statistics of pollution concentration data when the first judgment result is no, generating a pollutant concentration curve; A2. Obtain the moving average of the pollution concentration data in the second preset time period; A3. According to the visualized pollutant concentration curve, the sliding average of the pollutant concentration data in the second preset time period, the instantaneous exceeding event parameter and the number of all instantaneous exceeding events, a second risk report is sent.

[0044] Steps A1 to A3 are specific implementation details after the first judgment result in step S31 is no and the supervision risk event record book is obtained in step S32. By counting the pollutant concentration data and generating the pollutant concentration curve, the trend of the pollutant concentration over time can be observed intuitively, so as to find potential abnormal fluctuations. Further, the sliding average of the pollutant concentration data is obtained. In combination with the visualized pollutant concentration curve, the sliding average, the instantaneous exceeding event parameter and the number of all instantaneous exceeding events, a second risk report is sent, so that the risk assessment is no longer limited to a single exceeding event, but can be combined with historical trends and overall conditions for judgment, so as to realize more comprehensive and in-depth assessment and early warning of the pollution event, and effectively avoid compliance risks caused by instantaneous exceeding.

[0045] Among them, the sliding average in step A2 refers to a commonly used time series data smoothing technique, which eliminates short-term fluctuations by calculating the average value of data in a certain time window. Specifically, it can be calculated by moving window method, that is, a fixed length window is slid on the time series, the average value of the data in the window is calculated, and the average value is taken as the value of the current time point; the second preset time period refers to the time span for calculating the sliding average of the pollutant concentration data, which can be a few minutes, a few hours or a longer period of time, and its length can be flexibly configured according to actual monitoring requirements and pollutant characteristics; the visual display refers to presenting abstract pollutant concentration data and analysis results to users in graphical, tabular and other intuitive forms. Specifically, it can be drawn through a data chart library on a monitoring interface, such as a line chart, a column chart, etc., or presented through a special data visualization software.

[0046] In some preferred embodiments, the present application is implemented as follows. When the industrial wastewater treatment pollutant emission monitoring system determines that no persistent pollution is detected after performing the first determination, the system does not stop monitoring the concentration data of the relevant pollutants. The system continues to collect the pollution concentration data at this time, for example, the real-time concentration data of chemical oxygen demand COD, and uses these data to generate a pollutant concentration curve in real time on the monitoring interface, which can intuitively show the dynamic trajectory of the change of COD concentration over time. At the same time, the system obtains the moving average value of the pollution concentration data in the second preset time period, for example, a 30-minute sliding window can be set to calculate and display the average value of the COD concentration in the window. This moving average curve can be displayed together with the original concentration curve to smooth out short-term transient fluctuations. When the system detects a new transient exceedance event and records it in the regulatory risk event record book, or at the preset report generation time point, the system will generate and send a second risk report based on the pollutant concentration curve currently displayed, the moving average value of the pollution concentration data in the second preset time period, and the transient exceedance event parameters extracted from the regulatory risk event record book and the number of all transient exceedance events. For example, if the pollutant concentration curve shows that there have been three transient exceedances in the past hour, and the moving average curve shows a slow upward trend, even if no persistent pollution alarm is triggered, the system will generate a detailed second risk report containing the concentration curve, the moving average trend graph, the detailed list of recent transient exceedance events, and the total number of transient exceedance events, and send it to relevant management personnel, such as the head of the environmental protection department or the production scheduling supervisor, so that they can timely grasp the potential risk situation and take preventive measures.

[0047] Preferably, after screening the real-time raw data set, a pretreatment operation is performed to obtain a pretreated real-time effective data set and issue it, including the following steps: According to whether the real-time raw data set is complete, whether the value range of the pollution concentration data is abnormal, and whether the pollution concentration data conforms to the historical trend analysis result, respectively, the invalid data in the real-time raw data set is removed, and the valid data is retained as a real-time effective data set; The real-time effective data set is sequentially subjected to unit conversion and formatting processing to obtain a pretreated real-time effective data set and issue it.

[0048] The above steps are the specific implementation details of step S2: through the multi-dimensional screening mechanism including integrity check, numerical range abnormality judgment and historical trend analysis, it can be ensured that the data entering the subsequent analysis link is high-quality effective data, so as to avoid misjudgment caused by data quality problems. At the same time, through unit conversion and formatting processing, the consistency and usability of the data can be ensured, so that the subsequent pollution judgment and risk warning can be based on accurate and standardized data, which significantly improves the accuracy and reliability of the entire industrial wastewater treatment pollutant discharge monitoring system.

[0049] Wherein, whether the real-time raw data set is complete means checking each piece or each batch of pollution concentration data record received to determine whether it contains all expected data fields or whether it lacks key information, which can be specifically checking whether there are null values, missing fields or not conforming to the preset data structure in the data record; whether the numerical range of the pollution concentration data is abnormal means comparing the actual measurement value of the pollution concentration data with the preset reasonable numerical range to identify and mark or exclude data points obviously exceeding the normal fluctuation range, which can be specifically setting the maximum and minimum allowed concentration values of each pollutant, for example, the concentration range of COD is usually between 0 and 5000 mg / L, and any data point exceeding this range is considered abnormal; whether the pollution concentration data conforms to the historical trend analysis result means comparing the current real-time pollution concentration data with the historical data pattern, trend or statistical characteristics of the pollutant in the past period of time to judge whether the current data conforms to the normal fluctuation rule, which can be specifically calculating the moving average, standard deviation of historical data or establishing a prediction model, and then comparing the current data with these historical statistics, for example, if the historical data shows that the concentration of a certain pollutant is usually low at night, and the current night data suddenly appears an abnormal peak, it may be marked as not conforming to the historical trend.

[0050] Unit conversion means converting pollution concentration data collected from different sources or different sensors to the same unit of measurement, which can be specifically converting concentration expressed in ppm (parts per million) to mg / L (milligrams per liter), or calibrating measurement values at different temperatures to equivalent values at standard temperature; formatting processing means arranging and standardizing the real-time effective data set after screening and unit conversion according to the predetermined data structure, coding method or file type, which can be specifically converting data from the original text format to structured JSON, XML or CSV format, or arranging according to the specific field order and data type.

[0051] In some preferred embodiments, the present application is implemented as follows: when the industrial wastewater treatment system receives a real-time raw data set from the online monitoring device, for example, the data set may contain concentration values of multiple pollutants such as COD, ammonia nitrogen, total phosphorus, etc. and corresponding time stamps. First, the system will perform integrity checks on these raw data, for example, by checking whether each data record contains all expected fields such as pollutant type, concentration value and time stamp, if it is found that a record is missing a concentration value, the record will be marked as invalid data and discarded. Further, the system will perform numerical range anomaly judgment on the remaining data. For example, for COD concentration data, the system will preset a reasonable numerical range, such as 0 to 5000 mg / L, any data point outside this range, such as negative values or abnormally high values far exceeding the normal discharge limit, will be identified and discarded. In addition, the system will also perform historical trend analysis on the pollution concentration data. For example, by analyzing the historical data of the past 24 hours or 7 days, the system can establish the typical fluctuation pattern of the pollutant concentration in different time periods. If the COD concentration data at a certain time point is within the numerical range, but there is a significant, abnormal deviation compared to the historical data of the same period, for example, an abnormal peak appears in a period of usually low concentration, the data will also be marked as abnormal and discarded. After the above screening, the real-time valid data set is obtained. Subsequently, the system will sequentially perform unit conversion and formatting processing on these valid data. For example, if the ammonia nitrogen concentration collected by some sensors is in ppm units, while the system internal processing requires mg / L units, corresponding unit conversion will be performed. Then, the system will arrange all valid data in a unified format, for example, arrange the data fields of different pollutants in a predetermined order, and unify the data type, such as converting all concentration values to floating point number format, so that the subsequent automatic analysis module can efficiently read and process these data. Finally, these pre-processed real-time valid data sets will be issued to the subsequent judgment module for continuous pollution and instantaneous pollution identification.

[0052] Preferably, according to the pre-processed real-time valid data set, a first judgment is made on whether the pollution concentration data of any pollutant in a preset sliding time window is greater than a preset first pollution concentration threshold, including the following steps: Obtaining a plurality of pre-processed real-time valid data sets in a preset sliding time window; Respectively, a first judgment is made on whether the pollution concentration data of any pollutant in each pre-processed real-time valid data set is greater than a preset first concentration threshold.

[0053] The above steps are the specific implementation details of the first judgment process in step S31. By obtaining and comprehensively analyzing multiple pre-processed real-time effective data sets within a preset sliding window, accidental errors or transient fluctuations in the data collection process can be effectively filtered out, avoiding misjudgments caused by data "spikes". At the same time, by independently judging each data set within the sliding window, the pollution situation over a period of time can be more comprehensively reflected, avoiding missed judgments and ensuring the effectiveness and stability of industrial wastewater discharge monitoring.

[0054] wherein the preset sliding window refers to a dynamic data set with a fixed time length or data point quantity, which can move forward over time or with the arrival of new data; obtaining multiple pre-processed real-time effective data sets refers to continuously or periodically collecting and storing real-time effective data after pre-processing within the range of the preset sliding window, which can be specifically achieved by the data acquisition module pulling data from the data source at regular intervals and temporarily storing it in the memory or temporary database; and respectively judging whether the pollution concentration data of any pollutant in each pre-processed real-time effective data set is greater than the preset first concentration threshold refers to judging each independent pre-processed real-time effective data set obtained within the sliding window one by one to check whether the concentration data of any pollutant exceeds the preset first pollution concentration threshold, which can be specifically achieved by traversing the pollutant concentration values in each data set and comparing them with the corresponding threshold.

[0055] In some preferred embodiments, the present application is implemented as follows: assuming that the preset sliding window is configured as a window with a duration of 30 minutes, the system acquires a preprocessed real-time valid dataset every 1 minute. When a new dataset arrives, the oldest dataset will be removed from the window to maintain the dynamic nature of the window. Specifically, after the preprocessing module completes the screening, unit conversion and formatting processing of the real-time raw dataset, and issues the preprocessed real-time valid dataset, a data acquisition and storage unit continuously acquires these datasets within the preset sliding window. For example, this unit can be a data buffer that can store 30 preprocessed real-time valid datasets received every minute in the last 30 minutes. Subsequently, a judgment logic unit will perform a first judgment for each of the 30 datasets. For example, for each dataset, the judgment logic unit will traverse the concentration data of pollutants such as chemical oxygen demand (COD), ammonia nitrogen, total phosphorus, etc. contained therein. If the concentration data of any pollutant in a certain dataset, for example, the COD concentration, exceeds the preset first pollution concentration threshold (for example, the COD threshold is 100 mg / L), the dataset is marked as "over standard". Through the one-by-one judgment of all 30 datasets in the window, the system can obtain a detailed record of whether each time point in the past 30 minutes is over standard. If all 30 datasets are judged to be "over standard", the system can accurately identify that this is a persistent pollution event and trigger the corresponding pollution treatment enhancement operation.

[0056] As shown in Figure 3 Preferably, according to the preprocessed real-time valid dataset, a second judgment is made on whether the pollution concentration data of any pollutant in each first preset time period is greater than the preset second pollution concentration threshold, and if any second judgment result is yes, it is defined as instantaneous pollution, an instantaneous over-standard event is generated and the instantaneous over-standard event parameters are recorded, including the following steps: B1. Generating a timestamp according to the first preset time period; B2. Obtaining the preprocessed real-time valid dataset corresponding to each timestamp; B3. Respectively judging whether the pollution concentration data of any pollutant in the preprocessed real-time valid dataset corresponding to each timestamp is greater than the preset second pollution concentration threshold; B4. If any second judgment result is yes, it is defined as instantaneous pollution, an instantaneous over-standard event is generated and the timestamp and duration corresponding to the instantaneous over-standard event, the over-standard pollutant type and the over-standard pollution concentration data are recorded; Wherein, the instantaneous over-standard event parameters include: the timestamp corresponding to the occurrence of the instantaneous over-standard event, the duration of the instantaneous over-standard event, the timestamp corresponding to the end of the instantaneous over-standard event, the over-standard pollutant type and the over-standard pollution concentration data.

[0057] Steps B1 to B4 are specific implementation details of step S32, which are to capture short-time and high-concentration pollutant emission peaks by making fine time granularity judgments on the pre-processed real-time effective data set, avoiding missing these key risks due to the time window limitations of traditional monitoring strategies. At the same time, the occurrence time, duration, over-standard pollutant type and over-standard pollutant concentration data of the instantaneous over-standard event are recorded comprehensively, providing accurate and sufficient data support for subsequent risk assessment, pollution tracing and emergency response, thereby improving the timeliness and effectiveness of pollution monitoring and reducing the risk of external penalties due to instantaneous over-standard.

[0058] In step B1, the first preset time period refers to the time interval for data sampling and event judgment, which can be set to seconds, minutes or shorter time units; the timestamp refers to the time mark generated at a specific time point, which can take the form of Unix timestamp, date and time string or serial number, etc.

[0059] The preset second pollutant concentration threshold in step B3 refers to the critical value for judging whether the pollutant concentration is over-standard, which can be set according to national or local emission standards, industry specifications or enterprise internal management requirements.

[0060] The instantaneous pollution in step B4 refers to the phenomenon that the pollutant concentration exceeds the preset second pollutant concentration threshold in a short time; the instantaneous over-standard event refers to the instantaneous pollution event recognized and recorded by the system; the instantaneous over-standard event parameters refer to the key information set for describing the instantaneous over-standard event, including the event occurrence time, duration, end time, over-standard pollutant type and over-standard concentration data.

[0061] In some preferred embodiments, the application is implemented as follows: the system can set the first preset time period to 1 minute, which means that every 1 minute, the system will generate a corresponding timestamp, for example, in Unix timestamp format, such as 1678886400 representing March 15, 2023 00:00:00. Then, the system will obtain the pre-processed real-time valid data set corresponding to each newly generated timestamp from the data storage module or real-time data stream. For example, at timestamp 1678886400, the system obtains the concentration data of COD, ammonia nitrogen, total phosphorus and other pollutants at that time, which have been cleaned and formatted. Subsequently, the system will make a second judgment on each pollutant concentration data in the data set, respectively. For example, for the COD pollutant, the system will judge whether its concentration data is greater than the preset second pollution concentration threshold, which can be set to 1.2 times the national emission standard COD limit value. If at a certain timestamp, for example 1678886460 (i.e. 00:01:00), the system judges that the COD concentration is 150 mg / L, and the preset second pollution concentration threshold is 100 mg / L, the judgment result is yes, and the system will immediately define this as an instantaneous pollution. At this time, the system will generate an instantaneous over-standard event and record it in the regulatory risk event record book. The record content includes the timestamp 1678886460 corresponding to the occurrence of the event, the duration of the event (for example, if the data of the next 1 minute is also over-standard, the duration is 2 minutes), the over-standard pollutant type (for example, COD) and the over-standard pollution concentration data (for example, 150 mg / L). The record of the instantaneous over-standard event parameters can be specifically an entry in the database, including fields such as: event occurrence timestamp (for example, 1678886460), duration (for example, 120 seconds), event end timestamp (for example, 1678886580), over-standard pollutant type (for example, COD), over-standard pollution concentration data (for example, 150 mg / L). In this way, the system can record each instantaneous over-standard event in detail and structure, facilitating subsequent query and analysis.

[0062] Preferably, the timing query regulatory risk event record book, according to the instantaneous over-standard event parameters and the number of all instantaneous over-standard events, makes a third judgment whether the preset risk condition is met, and if the third judgment result is yes, includes the following steps: The timing query regulatory risk event record book makes a third judgment whether the number of all instantaneous over-standard events within a third preset time period is greater than a preset number threshold; Or, The third judgment whether the cumulative duration of multiple instantaneous over-standard events within a fourth preset time period is greater than a preset over-standard time threshold; If any of the third judgment results is yes, it is defined that the preset risk condition is met.

[0063] The above steps are specific implementation details of determining whether the preset risk condition is met in step S4. By effectively utilizing the number or duration information of the instantaneous exceeding event and the corresponding number threshold or time threshold, the judgment process of meeting the preset risk condition is set, thereby avoiding one-sidedness of risk assessment and ensuring accurate identification and timely warning of potential emission risks.

[0064] The regulatory risk event record book refers to a database or data structure for centralized storage and management of all instantaneous exceeding event information, which can be implemented using a relational database, a non-relational database, or a distributed file system. The third preset time period refers to a time window for evaluating the frequency of instantaneous exceeding events, which can be set to hours, days, or weeks, etc. The preset number threshold refers to the upper limit value of the number of instantaneous exceeding events within the third preset time period, which can be set according to historical data analysis, industry standards, or regulatory requirements. The fourth preset time period refers to a time window for evaluating the cumulative duration of instantaneous exceeding events, which can be set to days, weeks, or months, etc.

[0065] The preset exceeding event threshold refers to the upper limit value of the cumulative duration of multiple instantaneous exceeding events within the fourth preset time period, which can be set according to the characteristics of pollutants, environmental carrying capacity, or risk level.

[0066] In some preferred embodiments, the application is implemented as follows. The system can be configured to query the regulatory risk event record book every 10 minutes to ensure that the latest transient over-standard event data is obtained. When making a risk judgment, the third preset time period can be set to 24 hours, and the preset number threshold can be set to 5 times. This means that if the total number of transient over-standard events in the past 24 hours exceeds 5 times, even if each over-standard duration is short, the system will immediately consider that there is a risk. At the same time, the fourth preset time period can be set to 7 days, and the preset over-standard time threshold can be set to 30 minutes. This means that if the cumulative duration of all transient over-standard events in the past 7 days exceeds 30 minutes, the system will also consider that there is a risk. For example, if a production line has 6 transient over-standard events in a day, each lasting 5 minutes, although the single duration is not long, since the number (6 times) exceeds the preset number threshold (5 times) within 24 hours, the system will immediately define that the preset risk condition is met. For another example, if a production line has only 3 transient over-standard events in three days, but one of them lasts for 15 minutes, and the other two each lasts for 10 minutes, the total duration is 35 minutes. At this time, although the number of events does not exceed the threshold within 24 hours, the cumulative duration (35 minutes) exceeds the preset over-standard time threshold (30 minutes) within 7 days, the system will also define that the preset risk condition is met. In this way, both high-frequency short-time over-standard and low-frequency long-time cumulative over-standard can be effectively identified, thereby triggering the corresponding alarm and processing procedures.

[0067] Preferably, if any of the second judgment results is yes, defining transient pollution, after generating a transient over-standard event and recording the timestamp and duration, over-standard pollutant type and over-standard pollution concentration data corresponding to the transient over-standard event, the following steps are further included: Requesting to obtain production activity information of all production lines within a first preset time window before and after the timestamp corresponding to the occurrence of the transient over-standard event; If in response to the request, feeding back production batch information, current process stage and product type matching the timestamp corresponding to the transient over-standard event as process source identification of the transient over-standard event according to the preset production activity plan and real-time working conditions; If the request is not responded, adding unknown source identification to the transient over-standard event; Wherein, the production activity information includes: production batch information, current process stage and product type.

[0068] The above step is a specific implementation detail after generating the instantaneous over-standard event and recording the instantaneous over-standard event parameters in step S32. By associating the instantaneous over-standard event with specific production activity information, the precise identification of the process source of the instantaneous over-standard event is achieved. This enables the enterprise to quickly locate the production link, batch, and process that caused the pollution, and then take targeted improvement measures to prevent and control pollution from the source. Even in the case where production information cannot be automatically obtained, the addition of the unknown source identifier can prompt management personnel to conduct manual investigation, avoiding the problem of being unable to trace the source and take effective measures after the occurrence of an instantaneous over-standard event, and improving the fine management level of industrial wastewater discharge monitoring and the response efficiency of pollution events.

[0069] The first preset time window refers to a time range set before and after the time point of the occurrence of the instantaneous over-standard event, which can be one hour, half an hour, or other appropriate lengths of time, and is used to cover the possible delay of wastewater from the production link to the discharge monitoring, as well as the buffering effect of wastewater in the treatment system. The production activity information refers to various types of data related to the production process, which can specifically include production batch information, current process stage, and product type.

[0070] The preset production activity plan refers to the production arrangement and process set by the enterprise in advance, which can specifically include the start and end time of each production batch, the planned duration of each process, and the product type corresponding to the production. The real-time working condition refers to the current actual operating state of the production line, which can specifically include equipment operating parameters, material addition amount, reaction temperature, pressure, and actual production progress.

[0071] In some preferred embodiments, the present application is implemented as follows. Assume that in a chemical industrial park, the wastewater treatment system continuously monitors the water quality at the discharge outlet. When the system detects a transient exceedance event, e.g., the total organic carbon concentration instantaneously spikes to 500 mg / L at 10:30 am and lasts for 20 minutes, within a certain first preset time period (e.g., every 5 minutes) according to a preset second pollution concentration threshold, the system will immediately generate a transient exceedance event record containing 10:30 as the timestamp of the event occurrence, 20 minutes of duration, total organic carbon as the type of the exceedance pollutant, and 500 mg / L of the exceedance concentration data. Subsequently, the system will start the process source tracing process. It will request to obtain the production activity information of all production lines within a first preset time window (e.g., set to 30 minutes before and after, i.e., from 10:00 to 11:00) around the timestamp of 10:30 am. These information can be obtained from the manufacturing execution system or enterprise resource planning system of the park. If the manufacturing execution system successfully responds to the request, the system will feedback the production batch information (P20230915-003), the current process stage (cleaning), and the product type (special resin A) that match the timestamp of 10:30 am according to the preset production activity plan (e.g., the production schedule shows that production line No. 3 is performing the "cleaning" process of special resin A from 10:15 to 10:55, with production batch No. P20230915-003) and real-time operating data (e.g., the manufacturing execution system shows that production line No. 3 is indeed in the "cleaning" stage at 10:30, with normal cleaning agent dosage). These information are then marked by the system as the process source identification of the transient exceedance event. In this way, the management personnel can quickly understand that this total organic carbon exceedance is likely related to the "cleaning" process of special resin A started by production line No. 3 at 10:15. If the manufacturing execution system fails to respond to the request, e.g., due to network failure or data interface abnormality, the system will add an unknown source identification to the transient exceedance event. At this time, although the source cannot be automatically located, the identification will trigger a manual intervention process, e.g., the system will send a notification to the relevant responsible person, prompting the need to manually check the production records in this time period to identify the cause of the exceedance.

[0072] As shown in Figure 4 , preferably, after defining the transient pollution as any one of the second determination results is yes, generating a transient exceedance event and recording the timestamp and duration of the transient exceedance event, the type of the exceedance pollutant, and the exceedance pollution concentration data, the following steps are further included: C1. According to the real-time operating conditions, obtain the product type and the current process stage of each production line, and correspondingly classify them into low-risk processes and high-risk processes, and according to the preset production activity plan, obtain the planned start timestamp of the high-risk processes; C2. Obtain the wastewater discharge delay time of each production line; C3. According to the wastewater discharge delay time of each production line, determine the low-risk process and the corresponding production line matched with the time stamp corresponding to the instantaneous over-standard event as the low-risk source identification of the instantaneous over-standard event; C4. According to the time stamp corresponding to the instantaneous over-standard event and the maximum wastewater discharge delay time, obtain the expected wastewater discharge time stamp; C5. Fourthly, determine whether the planned start time stamp of the high-risk process falls within the second preset time window after the expected wastewater discharge time stamp; C6. If yes, update the low-risk source identification to the potential composite high-risk identification, and send the third risk report.

[0073] Steps C1 to C6 are specific implementation details after generating the instantaneous over-standard event and recording the instantaneous over-standard event parameters in step S32. By comprehensively considering the process risk level of the production line, the wastewater discharge delay time, and the planned start time of the high-risk process, the scheme can identify potential composite high-risk events, avoiding misjudgment caused by relying solely on time stamp matching. This improves the accuracy and reliability of pollution source identification, enabling enterprises to respond more timely and comprehensively to potential composite pollution risks, thereby effectively avoiding external regulatory penalties due to instantaneous over-standard.

[0074] The real-time working condition in step C1 refers to the real-time data of the current running state of the production site, which can be information about production line operation, equipment status, material input, process parameters, etc. obtained through sensors, automation control systems or manual input, for providing an instant view of the production process to accurately classify process risks and match time stamps; the low-risk process refers to a production link or process step with low pollution risk to the environment under normal operating conditions, which can be defined through historical data analysis, process characteristic evaluation or industry standards; the high-risk process refers to a production link or process step with high pollution risk to the environment under normal operation or specific operation (such as cleaning, emptying), which can be identified by characteristics such as use of specific chemicals, high-concentration wastewater generation or intermittent discharge; the preset production activity plan refers to pre-prepared and stored data such as production scheduling, process flow, batch information, and planned start and end time of each process, which can be maintained through production management systems or enterprise resource planning systems; the planned start time stamp refers to the precise time point when the high-risk process is scheduled to start execution in the preset production activity plan, which can be recorded through production scheduling systems or automation control systems.

[0075] The wastewater discharge delay time in step C2 refers to the time required for wastewater to reach the final discharge monitoring point from the production line discharge point, which can be determined by flow meter, pipe length, flow rate calculation or tracer experiment, etc.

[0076] The maximum wastewater discharge delay time in step C4 refers to the longest delay time required for wastewater from all production lines to reach the final discharge monitoring point from the discharge point, which can be determined by statistical analysis of the wastewater discharge delay times of all production lines.

[0077] The expected wastewater discharge timestamp in step C5 refers to the time point when the wastewater corresponding to the instantaneous exceedance event is expected to reach the discharge monitoring point after considering the wastewater discharge delay, which can be calculated by adding the time stamp of the instantaneous exceedance event to the maximum wastewater discharge delay time; the second preset time window refers to a pre-set time range for determining whether the planned start timestamp of the high-risk process is associated with the expected wastewater discharge timestamp, which can be determined by empirical value, historical data analysis or expert evaluation.

[0078] The potential composite high-risk identification in step C6 refers to the risk status mark identified by the system that the instantaneous exceedance event may be caused by the joint action of low-risk processes and high-risk processes, which can be represented by adding a composite risk attribute to the low-risk source identification; the third risk report refers to the warning information or data report generated and sent for potential composite high-risk events, which can be sent by email, SMS, system notification or integrated into the risk management platform.

[0079] In some preferred embodiments, the present application is implemented as follows. When the system detects a certain instantaneous over-standard event through the second judging step, for example, the COD concentration of the discharge port is monitored to be instantaneously over-standard at 10:00 am, and the time stamp corresponding to the instantaneous over-standard event is recorded as 10:00:00. At this time, the system will immediately obtain the product types and current process stages of all production lines in the park according to the real-time working conditions. For example, production line A is performing the rectification process of product X and is classified as a low-risk process; production line B is performing the reaction kettle cleaning process of product Y and is classified as a high-risk process. At the same time, the system will query the preset production activity plan to obtain the planned start time stamp of the high-risk process (reaction kettle cleaning) of production line B, for example, 09:45:00. Then, the system obtains the wastewater discharge delay time of each production line. For example, the wastewater discharge delay time of production line A is 10 minutes, and the wastewater discharge delay time of production line B is 15 minutes. According to the wastewater discharge delay time of 10 minutes of production line A, the system determines that the low-risk process matched with the time stamp 10:00:00 corresponding to the instantaneous over-standard event is the rectification process of production line A, and takes it as the low-risk source identification of the instantaneous over-standard event. Subsequently, the system calculates the expected wastewater discharge time stamp according to the time stamp 10:00:00 corresponding to the instantaneous over-standard event and the maximum wastewater discharge delay time of all production lines in the park (assuming 15 minutes, i.e. the delay time of production line B), i.e. 10:00:00 + 15 minutes = 10:15:00. Finally, the system fourthly judges whether the planned start time stamp 09:45:00 of the high-risk process (reaction kettle cleaning) of production line B falls within the second preset time window after the expected wastewater discharge time stamp 10:15:00. Assuming that the second preset time window is 10 minutes, i.e. judging whether 09:45:00 falls between 10:15:00 and 10:25:00. If the judgment result is yes (for example, if the start time of the high-risk process is after considering the delay, its wastewater discharge may overlap with the time window of the over-standard event), the system will update the originally determined low-risk source identification (the rectification process of production line A) to a potential composite high-risk identification, and immediately send a third risk report to the relevant management personnel, prompting that the instantaneous over-standard event may not only be a problem of the low-risk process, but also may be related to the potential influence of the high-risk process, which needs to be further investigated.

[0080] As Figure 5 shown, preferably, after updating the low-risk source identification to the potential composite high-risk identification, the following steps are further included: D1. obtaining the high-risk wastewater discharge time stamp according to the planned start time stamp of the high-risk process and the wastewater discharge delay time of the production line corresponding to the high-risk process; D2. In the time period between the time stamp corresponding to the instantaneous over-standard event and the time stamp of the high-risk wastewater discharge, the pollution concentration data of any pollutant in the high-risk process is obtained in real time, and a high-risk actual concentration decay trend curve is generated by fitting; D3. The high-risk actual concentration decay trend curve is compared with the preset low-risk theoretical concentration decay trend curve at the time stamp of the high-risk wastewater discharge, and it is determined whether the high-risk actual concentration decay trend curve has any preset risk characteristics; D4. If the fourth determination result is yes, the potential composite high-risk identifier is updated to a confirmed high-risk composite event, and a fourth risk report is sent; Wherein, the preset risk characteristics include: significantly slowing down, rising again after falling and maintaining a high level.

[0081] Steps D1 to D4 are specific implementation details after the potential composite high-risk identifier is updated, which is a precise secondary confirmation of the potential composite high-risk event. By obtaining the high-risk wastewater discharge time stamp and monitoring and fitting the actual pollutant concentration decay trend curve of the high-risk process in real time within this time period, and then comparing it with the preset low-risk theoretical decay trend curve and determining whether there is a specific risk characteristic, the risk of misjudgment caused by only relying on time correlation is avoided. This enables the system to accurately identify the true high-risk composite event, reduces unnecessary risk reports and processing, improves the accuracy and reliability of risk warning, and effectively avoids resource waste and production interference caused by misjudgment.

[0082] Wherein, the high-risk wastewater discharge time stamp in step D1 refers to the time point when the wastewater generated by the high-risk process is expected or actually discharged to the wastewater treatment system, which can be calculated by adding the wastewater discharge delay time of the production line corresponding to the high-risk process to the planned start time stamp of the high-risk process.

[0083] The high-risk actual concentration decay trend curve in step D2 refers to the actual trend of the concentration of pollutants discharged by the high-risk process changing with time within a certain period of time, which can be generated by mathematical fitting of the real-time obtained pollutant concentration data, such as using polynomial regression, exponential decay model or spline interpolation method.

[0084] The preset low-risk theoretical concentration decay trend curve in step D3 refers to the expected decay pattern of the pollutant concentration over time without the influence of high-risk processes or under normal low-risk conditions, which can be established by statistical analysis based on historical data, physical and chemical model simulation, or expert experience setting, etc. The preset risk feature refers to a specific pattern or behavior in the pollutant concentration decay trend that indicates the presence of a high-risk composite event, which can be identified by a predefined mathematical condition or pattern recognition algorithm, such as by calculating the slope change, local extreme value, or sustained high concentration interval of the curve.

[0085] The fourth risk report in step D4 refers to the highest level of emergency alert issued by the system, which explicitly indicates that the current exceedance event contains high-risk process emissions and provides detailed information on the event time, the exceeding pollutant, the current concentration, and the confirmed high-risk source.

[0086] In some preferred embodiments, the application is implemented as follows: Assuming that in a chemical industrial park, a production line is performing a "cleaning of the reactor" process, the system has marked a transient exceedance event as a potential composite high-risk identifier according to previous judgment logic. To further confirm, the system first obtains the planned start timestamp of the high-risk process from the production plan management system, for example, at 10:00 am. At the same time, according to the historical operation data or physical model of the production line, it determines that there is a fixed delay time of 30 minutes from the reaction kettle to the monitoring point. Based on this, the system calculates the high-risk wastewater discharge timestamp as 10:30 am. Subsequently, the system obtains the pollutant concentration data of the specific pollutant (e.g., COD) involved in the high-risk process through online monitoring equipment in the time period between the transient exceedance event occurrence timestamp (e.g., 10:15 am) and the high-risk wastewater discharge timestamp (10:30 am). After collecting these real-time data points, the system uses the data processing unit to fit the concentration data using an exponential decay model or a polynomial regression algorithm, thereby generating a high-risk actual concentration decay trend curve. At the same time, the system internally pre-stores a preset low-risk theoretical concentration decay trend curve, which is established based on the natural decay law of the pollutant concentration after transient exceedance under normal production conditions in the park. When the high-risk wastewater discharge timestamp arrives, the system compares the high-risk actual concentration decay trend curve generated in real time with the preset low-risk theoretical concentration decay trend curve at that timestamp.

[0087] During the comparison process, the system will make a fourth determination as to whether the high-risk actual concentration decay trend curve has a preset risk feature. For example, the system can calculate the average decline rate of the actual curve in the comparison period and compare it with the decline rate of the theoretical curve. If the actual decline rate is significantly lower than the theoretical decline rate, it is determined that the "decline rate is significantly slowed down". The system can also monitor whether there is a local minimum value in the actual curve during the decline process and then rises again. If there is, it is determined that "it rises again after declining". Alternatively, the system can determine whether the actual curve has been continuously maintained at a concentration level higher than a preset threshold for a period of time. If the condition is met, it is determined that "it is continuously maintained at a high level".

[0088] If the fourth determination result is yes, that is, the actual concentration decay trend exhibits any of the preset risk features, the system will update the previously marked potential high-risk composite event to a confirmed high-risk composite event. Subsequently, the system will immediately send a fourth risk report, for example, sending a detailed risk report to relevant management personnel and environmental protection departments through a short message, an email or a system alarm interface, and can also start a higher level of emergency response measures, for example, automatically adjusting the wastewater treatment process parameters or notifying the production line to adjust the load, to cope with the confirmed high-risk composite event.

[0089] As shown in Figure 6 An industrial wastewater treatment pollutant emission monitoring system applied to a chemical industry park wastewater treatment scene, comprising: An acquisition module is configured to acquire pollutant concentration data corresponding to multiple pollutants in industrial wastewater, and upload the pollutant concentration data as a real-time original data set according to a first preset time period. A preprocessing module is configured to filter the real-time original data set and perform a preprocessing operation to obtain a preprocessed real-time effective data set and deliver the preprocessed real-time effective data set. A first determination module is configured to determine, according to the preprocessed real-time effective data set, whether the pollutant concentration data of any pollutant in a preset sliding time window is greater than a preset first pollutant concentration threshold. If all the first determination results are yes, it is defined as persistent pollution, and a pollution treatment enhancement operation is performed according to the pollutant. A second determination module is configured to determine, according to the preprocessed real-time effective data set, whether the pollutant concentration data of any pollutant in each first preset time period is greater than a preset second pollutant concentration threshold. If any of the second determination results is yes, it is defined as instantaneous pollution, an instantaneous over-standard event is generated, and an instantaneous over-standard event parameter is recorded. All the instantaneous over-standard events are integrated into a regulatory risk event record book. The third judging and alarming module is configured to query the supervision risk event record book at a regular time, judge whether the preset risk condition is met according to the instantaneous over-standard event parameter and the number of all instantaneous over-standard events, and send a first risk report and perform a sound and light alarming operation if the third judging result is yes.

[0090] The scheme provided in the application can effectively and reliably execute the industrial wastewater treatment pollutant emission monitoring method by embodying each logical step in the industrial wastewater treatment pollutant emission monitoring method as an independent system module, and distributing data acquisition, preprocessing, first judging, second judging and third judging and alarming functions to different units through modular design.

[0091] In the embodiments provided in the application, it should be understood that the disclosed method and system can be implemented in other manners. The above-described system embodiments are only schematic; for example, the division of the modules is only a logical function division, and there can be another division manner in actual implementation; for example, a plurality of modules or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the above-described components can be indirect coupling or communication connection through some interfaces, devices or modules, and can be electrical, mechanical or in other forms.

[0092] In addition, all the function modules in each embodiment of the application can be integrated in one processor, or each module can be a separate device, or two or more modules can be integrated in one device; each function module in each embodiment of the application can be realized in the form of hardware or in the form of hardware plus software function unit.

[0093] Those skilled in the art can understand that all or part of the steps of the above method embodiments can be completed by program instructions and related hardware, and the above program instructions can be stored in a computer readable storage medium, and the program instructions are executed to perform the steps of the above method embodiments; and the above storage medium includes mobile storage devices, read-only memories (ROM), magnetic discs or optical discs and various storage media that can store program codes.

[0094] Hereinafter, the terms "first" and "second" are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined with "first" and "second" can explicitly or implicitly include one or more of the features.

[0095] If a flow diagram is used, the flow diagram is used to illustrate the operations according to embodiments of the present application. It should be understood that the operations in the flow diagram do not necessarily have to be performed in the order shown. Rather, various steps can be handled in reverse order or simultaneously. Additionally, other operations can be added or removed depending on the specifics of the process.

[0096] The industrial wastewater treatment pollutant emission monitoring method and system provided by the present application are described in detail above. The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to the embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for monitoring pollutant discharge from industrial wastewater treatment, applied to wastewater treatment scenarios in chemical industrial parks, characterized in that, Includes the following steps: Acquire pollution concentration data corresponding to multiple pollutants in industrial wastewater, and upload the pollution concentration data as a real-time raw dataset according to a first preset time period. After filtering the real-time raw dataset, preprocessing is performed to obtain the preprocessed real-time valid dataset, which is then distributed. Based on the preprocessed real-time effective dataset, it is first determined whether the pollution concentration data of any pollutant within a preset sliding time window is greater than a preset first pollution concentration threshold. If all the first determination results are yes, it is defined as persistent pollution, and pollution treatment enhancement operation is performed according to the pollutant. Based on the preprocessed real-time valid dataset, a second determination is made on whether the pollution concentration data of any pollutant within each first preset time period is greater than a preset second pollution concentration threshold. If any second determination result is yes, it is defined as transient pollution, a transient exceedance event is generated and the transient exceedance event parameters are recorded, and all the transient exceedance events are integrated into a regulatory risk event logbook. The regulatory risk event log is queried periodically. Based on the instantaneous exceedance event parameters and the number of all instantaneous exceedance events, a third determination is made as to whether the preset risk conditions are met. If the third determination result is yes, a first risk report is sent and an audible and visual alarm is executed.

2. The method for monitoring pollutant discharge from industrial wastewater treatment as described in claim 1, characterized in that, After the first judgment result is negative and the regulatory risk event logbook is obtained, the following steps are also included: Statistically analyze the pollution concentration data when the first judgment result is negative, and generate a pollutant concentration curve; Obtain the moving average value of the pollution concentration data within a second preset time period; A second risk report is sent based on the visualized pollutant concentration curve, the moving average of the pollutant concentration data within the second preset time period, the instantaneous exceedance event parameters, and the number of all instantaneous exceedance events.

3. The method for monitoring pollutant discharge from industrial wastewater treatment as described in claim 1, characterized in that, The process of preprocessing the real-time raw dataset after filtering it to obtain a preprocessed real-time valid dataset and then distributing it includes the following steps: Based on whether the real-time raw dataset is complete, whether the range of the pollution concentration data is abnormal, and whether the pollution concentration data conforms to the historical trend analysis results, invalid data in the real-time raw dataset is removed, and valid data is retained as the real-time valid dataset. The real-time valid dataset is sequentially subjected to unit conversion and formatting to obtain the preprocessed real-time valid dataset, which is then distributed.

4. The method for monitoring pollutant discharge from industrial wastewater treatment as described in claim 3, characterized in that, The step of determining, based on the preprocessed real-time valid dataset, whether the pollution concentration data of any pollutant within a preset sliding time window is greater than a preset first pollution concentration threshold includes the following steps: Multiple preprocessed real-time valid datasets are acquired within a preset sliding window; First, determine whether the pollution concentration data of any pollutant in each of the preprocessed real-time valid datasets is greater than a preset first concentration threshold.

5. The method for monitoring pollutant discharge from industrial wastewater treatment as described in claim 3, characterized in that, The step of determining, based on the preprocessed real-time valid dataset, whether the pollution concentration data of any pollutant within each first preset time period is greater than a preset second pollution concentration threshold, and defining it as transient pollution based on any second determination result, generating a transient exceedance event and recording the transient exceedance event parameters, includes the following steps: A timestamp is generated based on the first preset time period; Obtain the preprocessed real-time valid dataset corresponding to each timestamp; The second determination is made as to whether the pollution concentration data of any pollutant in the preprocessed real-time effective dataset corresponding to each timestamp is greater than the preset second pollution concentration threshold. If any of the second judgment results is yes, it is defined as transient pollution, a transient exceedance event is generated, and the timestamp and duration, the type of pollutant exceeding the standard and the concentration data of the pollutant exceeding the standard corresponding to the transient exceedance event are recorded; The parameters of the instantaneous exceedance event include: the timestamp corresponding to the occurrence of the instantaneous exceedance event, the duration of the instantaneous exceedance event, the timestamp corresponding to the end of the instantaneous exceedance event, the type of pollutant exceeding the standard, and the concentration data of the pollutant exceeding the standard.

6. The method for monitoring pollutant discharge from industrial wastewater treatment as described in claim 5, characterized in that, The third step, based on the instantaneous exceedance event parameters and the total number of all instantaneous exceedance events, determines whether a preset risk condition is met. If the third determination result is yes, the steps include the following: The regulatory risk event record book is queried periodically, and the third determination is whether the number of all the instantaneous exceeding events within the third preset time period is greater than a preset number threshold. or, The third determination is whether the cumulative duration of multiple instantaneous exceeding events within the fourth preset time period is greater than the preset exceeding time threshold. If any third judgment result is yes, then the pre-defined risk condition is satisfied.

7. The method for monitoring pollutant discharge from industrial wastewater treatment as described in claim 5, characterized in that, After defining any second judgment result as transient pollution, generating a transient exceedance event, and recording the timestamp and duration, the type of pollutant exceeding the standard, and the concentration data of the pollutant exceeding the standard corresponding to the transient exceedance event, the following steps are also included: The request is to obtain production activity information of all production lines within a first preset time window before and after the timestamp corresponding to the instantaneous exceedance event; If the request is responded to, the production batch information, current process stage and product type that match the timestamp corresponding to the instantaneous exceedance event are fed back according to the preset production activity plan and real-time operating conditions, as the process source identifier of the instantaneous exceedance event; If the request is not responded to, an unknown source identifier will be added to the instantaneous exceedance event; The production activity information includes: the production batch information, the current process stage, and the product type.

8. The method for monitoring pollutant discharge from industrial wastewater treatment as described in claim 5, characterized in that, After defining any second judgment result as transient pollution, generating a transient exceedance event, and recording the timestamp and duration, the type of pollutant exceeding the standard, and the concentration data of the pollutant exceeding the standard corresponding to the transient exceedance event, the following steps are also included: The product type and current process stage of each production line are obtained based on real-time operating conditions, and are classified into low-risk processes and high-risk processes. The planned start timestamp of the high-risk process is obtained according to the preset production activity plan. Obtain the wastewater discharge delay time for each production line; Based on the wastewater discharge delay time of each production line, the low-risk process and corresponding production line that match the timestamp of the instantaneous exceedance event are determined as the low-risk source identifier of the instantaneous exceedance event. Based on the timestamp corresponding to the instantaneous exceedance event and the maximum wastewater discharge delay time, obtain the expected wastewater discharge timestamp; Fourth, determine whether the planned start time stamp of the high-risk process falls within the second preset time window after the expected wastewater discharge time stamp; If so, the low-risk source identifier will be updated to a potential composite high-risk identifier, and a third risk report will be sent.

9. The method for monitoring pollutant discharge from industrial wastewater treatment as described in claim 8, characterized in that, After updating the low-risk source identifier to a potential composite high-risk identifier, the following steps are also included: Based on the planned start timestamp of the high-risk process and the wastewater discharge delay time of the production line corresponding to the high-risk process, obtain the high-risk wastewater discharge timestamp; During the time interval between the timestamp corresponding to the instantaneous exceedance event and the timestamp of the high-risk wastewater discharge, the pollution concentration data of any pollutant in the high-risk process is acquired in real time, and a high-risk actual concentration decay trend curve is generated by fitting. The high-risk actual concentration decay trend curve is compared with the preset low-risk theoretical concentration decay trend curve at the high-risk wastewater discharge timestamp, and then it is determined whether the high-risk actual concentration decay trend curve has any preset risk characteristics. If the fourth judgment result is yes, then the potential composite high-risk identifier will be updated to a confirmed high-risk composite event, and a fourth risk report will be sent. The preset risk characteristics include: a significant slowdown in the rate of decline, a subsequent rise after the decline, and a sustained high level.

10. An industrial wastewater treatment pollutant discharge monitoring system, applied to wastewater treatment scenarios in chemical industrial parks, characterized in that, include: The acquisition module is used to acquire pollution concentration data corresponding to multiple pollutants in industrial wastewater, and upload the pollution concentration data as a real-time raw dataset according to a first preset time period. The preprocessing module is used to filter the real-time raw dataset and perform preprocessing operations to obtain the preprocessed real-time valid dataset and distribute it. The first judgment module is used to determine, based on the preprocessed real-time effective dataset, whether the pollution concentration data of any pollutant within a preset sliding time window is greater than a preset first pollution concentration threshold. If all the first judgment results are yes, it is defined as persistent pollution, and pollution treatment enhancement operation is performed according to the pollutant. The second judgment module is used to determine, based on the preprocessed real-time effective dataset, whether the pollution concentration data of any pollutant within each first preset time period is greater than a preset second pollution concentration threshold. If any second judgment result is yes, it is defined as transient pollution, a transient exceedance event is generated and the transient exceedance event parameters are recorded, and all the transient exceedance events are integrated into a regulatory risk event logbook. The third judgment and alarm module is used to periodically query the regulatory risk event record book, and make a third judgment on whether the preset risk conditions are met based on the instantaneous exceedance event parameters and the number of all instantaneous exceedance events. If the third judgment result is yes, a first risk report is sent and an audible and visual alarm operation is executed.

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