A sewage on-line monitoring system based on parallel data flow and a monitoring method thereof

Abstract

The application discloses a sewage online monitoring system based on parallel data flow and a monitoring method thereof, wherein the monitoring system comprises a data input module, a model generation module, a data acquisition module, a data matching module and a data interaction module. Through the application, a user can more intuitively master the sewage treatment condition, remote monitoring of a sewage treatment plant is realized, and the user can master the sewage treatment condition of the sewage treatment plant without going to a site of the sewage treatment plant.

Description

Technical Field

[0001] This invention relates to the field of wastewater treatment technology, and in particular to an online wastewater monitoring system and method based on parallel data streams. Background Technology

[0002] Currently, most wastewater treatment plants treat wastewater based on its composition, employing methods such as sedimentation, aeration, aeration, anaerobic treatment, and chemical treatment. In practice, wastewater treatment plants often divide their jurisdiction into factory areas, residential areas, and office areas, and then allocate discharge periods for each area. This allows different areas to discharge wastewater independently within their designated time periods, with maximum discharge limits set for each period. This approach enables wastewater treatment plants to treat wastewater more effectively and systematically, thereby improving the compliance rate of wastewater treatment.

[0003] However, existing wastewater treatment operation records are all based on paper records and self-made electronic spreadsheets, which cannot achieve real-time data collection and viewing. Most information collection and processing still need to be done manually, or require going to the wastewater treatment plant to understand the situation, which wastes a lot of human and material resources. Summary of the Invention

[0004] Therefore, to address the aforementioned shortcomings, this invention provides an online wastewater monitoring system. The system includes a data input module for acquiring wastewater treatment process design data from the wastewater treatment plant to be monitored, and simultaneously configuring parameter standards and monitoring accuracy for the process; a model generation module for generating a wastewater treatment process benchmark model by combining the parameter standards, monitoring accuracy, and process design data; a data acquisition module connecting the wastewater treatment plant's data acquisition device to the wastewater treatment site to read real-time on-site monitoring data; a data analysis module receiving the on-site monitoring data and analyzing on-site monitoring data uploaded by multiple data acquisition modules in parallel, thereby analyzing real-time process parameters based on the on-site monitoring data to obtain real-time process parameters; a data matching module matching the real-time process parameters to the wastewater treatment process benchmark model; and a data interaction module setting a data interaction window within which data interaction is performed between the monitoring sensors and the real-time process parameters, based on the process benchmark model, to obtain data interaction results.

[0005] On the other hand, the present invention also provides a wastewater online monitoring method based on parallel data streams, including interactively obtaining wastewater treatment process design data of the wastewater treatment plant to be monitored, and simultaneously configuring the parameter standards and monitoring accuracy of the process to be monitored; combining the parameter standards, monitoring accuracy, and process design data to generate a wastewater treatment process benchmark model; connecting the data acquisition device with the wastewater treatment site to read the site monitoring data in real time, and analyzing the real-time process parameters in parallel based on the site monitoring data to obtain the real-time process parameters; matching the real-time process parameters into the wastewater treatment process benchmark model; setting a data interaction window, and performing data interaction between the process benchmark model and the real-time process parameters within the data interaction window to obtain the data interaction result.

[0006] The present invention has the following advantages:

[0007] The aforementioned wastewater online monitoring system and method based on parallel data streams solves the technical problem of existing technologies being unable to collect and view wastewater treatment process parameters in real time. This invention collects process data and on-site data from wastewater treatment plants in real time and directly incorporates this data into the wastewater treatment process model. Users can interact with the model to view real-time process and on-site data, as well as the wastewater treatment plant's process standard data. This allows users to more intuitively understand the wastewater treatment status, enabling remote monitoring of wastewater treatment plants without needing to visit the site. Furthermore, the parallel data processing method effectively improves data processing speed, thereby increasing data response efficiency. Attached Figure Description

[0008] Figure 1 This is a schematic diagram of the structure of an online wastewater monitoring system based on parallel data streams;

[0009] Figure 2 This is a flowchart illustrating a wastewater online monitoring method based on parallel data streams.

[0010] Figure 3 This is a schematic diagram of the alarm process implemented based on the above online monitoring method;

[0011] Figure 4 This is a schematic diagram of the early warning process based on the above online monitoring method;

[0012] Figure 5 This is a flowchart illustrating the data prediction process in the aforementioned early warning procedure. Detailed Implementation

[0013] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0014] In this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, without necessarily requiring or implying any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus.

[0015] As described in the background section, existing data monitoring methods cannot achieve real-time data collection and viewing. Most information collection and processing rely on manual labor or require on-site visits to sewage treatment plants to understand the situation, resulting in a significant waste of human and material resources.

[0016] Example 1:

[0017] In view of the above-mentioned technical deficiencies, this law proposes an online wastewater monitoring system, which includes...

[0018] The data input module 10 acquires the wastewater treatment process design data of the wastewater treatment plant to be monitored and simultaneously configures the parameter standards and monitoring accuracy of the process. Users can use this module to input process design drawings, basic data, design parameter standards for each stage of the wastewater treatment process, the accuracy of parameter fluctuations during monitoring, and even alarm level standards into the system. Furthermore, this data input module connects to a database, allowing it to retrieve pre-stored process design drawings, basic data, design parameter standards for each stage of the wastewater treatment process, the accuracy of parameter fluctuations during monitoring, and even alarm level standards from the database for use by other modules.

[0019] Model generation module 9, which can combine the parameter standards, monitoring accuracy and process design data to generate a wastewater treatment process benchmark model;

[0020] Data acquisition module 1 connects the data acquisition device of the sewage treatment plant with the sewage treatment site to read on-site monitoring data in real time;

[0021] Data analysis module 4 receives the above-mentioned field monitoring data and analyzes the field monitoring data uploaded by multiple data acquisition modules in parallel, thereby analyzing the real-time process parameters based on the field monitoring data to obtain the real-time process parameters.

[0022] Data matching module 5, which matches real-time process parameters to the aforementioned wastewater treatment process baseline model; and

[0023] The data interaction module 8 sets a data interaction window, and within the data interaction window, the data of the monitoring sensors are interacted with based on the above-mentioned process reference model and real-time process parameters to obtain the data interaction results.

[0024] Users input design data for wastewater treatment processes, including but not limited to drawings, process design standards, and basic data. Based on this data, a wastewater treatment process model is generated. Then, the user-input parameter standards (including but not limited to water volume, COD, TP, TN, etc., which are the data that the wastewater treatment process should achieve during design and operation) and monitoring accuracy (i.e., the upper and lower fluctuation accuracy of each parameter value) are matched into the wastewater treatment process model to generate a wastewater treatment process benchmark model.

[0025] The system communicates with data acquisition devices at wastewater treatment plants to establish a connection. These data acquisition devices include, but are not limited to, sensors installed at key stages of the wastewater treatment process, sensors in operating equipment, instruments, valves, and on-site monitoring equipment. These devices collect wastewater treatment parameters, equipment parameters, and on-site data, which are then uploaded to the system in real time. Parallel processing of the uploaded data—that is, processing data from multiple data acquisition devices simultaneously—improves data processing and response speed. The system outputs the analyzed real-time process parameters after parallel analysis. These real-time process parameters represent the current wastewater treatment process data, enabling real-time data monitoring.

[0026] The real-time process parameters output above are matched to the corresponding positions in the above process baseline model according to the type of the parameters themselves, so that the real-time process parameters correspond to the corresponding links in the process baseline model.

[0027] For example, regarding the influent flow data in the sedimentation stage, the aforementioned data acquisition device collects and uploads relevant data for analyzing the influent flow in this stage. After processing and analyzing the aforementioned relevant data, the real-time water flow parameters of the sedimentation stage are obtained, and these real-time water flow parameters are matched to the sedimentation stage in the aforementioned process reference model.

[0028] The aforementioned wastewater treatment process benchmark model and the real-time process parameters matched to the model are transmitted to the data interaction window. Users can interact with the wastewater treatment process benchmark model in this interaction window to obtain interactive content, including process parameter standards, monitoring accuracy, real-time parameters, and on-site monitoring images.

[0029] This system solves the technical problem of existing technologies being unable to collect and view wastewater treatment process parameters in real time. It collects process data and on-site data from wastewater treatment plants in real time and directly reflects this data in the wastewater treatment process model. Users can interact with the model to view real-time process and on-site data, as well as the plant's process standard data. This allows users to more intuitively understand the wastewater treatment status, enabling remote monitoring of wastewater treatment plants without needing to visit the site. Furthermore, the parallel data processing method employed in this approach effectively improves data processing speed and thus data response efficiency.

[0030] Example 2:

[0031] Current technology is unable to provide real-time online alerts for abnormal wastewater treatment data.

[0032] Therefore, in order to solve the above-mentioned technical problems, such as Figure 1 As shown, the monitoring system in this embodiment also includes an alarm module 7. The alarm module 7 can perform alarm analysis and calculation based on the above-mentioned real-time process parameters and parameter standards to obtain alarm analysis and calculation results. Based on the above-mentioned alarm analysis and calculation results, it can perform alarm level matching analysis in combination with alarm level standards to obtain alarm level matching results and output alarm level matching results.

[0033] The real-time process parameters are compared with the parameter standards to obtain the first difference calculation result. This second difference calculation result is then compared with the monitoring accuracy to obtain the second difference calculation result. The second difference calculation result is then compared with the corresponding standard in the alarm level standard list. If the second difference calculation result falls into the corresponding data area in the alarm level standard list, the alarm level is determined based on the data area it falls into. Finally, the matched alarm level result is output to the interactive window.

[0034] This embodiment enables real-time alarms for data exceeding limits during monitoring, thereby facilitating monitoring personnel to maintain and repair the processes corresponding to the current alarm parameters.

[0035] Example 3

[0036] To achieve over-limit early warning, this embodiment is optimized based on the above embodiment 2, such as... Figure 1 As shown, the monitoring system in this embodiment also includes a data prediction module 6, which performs predictive analysis on process parameters based on the on-site monitoring data to obtain prediction analysis results.

[0037] The data prediction module 6 includes:

[0038] The flow calculation module acquires the valve opening data, calculates the valve flow rate based on the opening data, and obtains the valve flow rate calculation result.

[0039] The water volume prediction module performs a water volume prediction calculation based on the valve flow calculation results and the time data, and obtains the water volume prediction calculation result.

[0040] This embodiment is applicable to early warning of excessive water volume. Since the valve opening process is a gradual process from 0 to Kmax, where Kmax is the preset valve opening, the same applies to the valve closing process, which is from Kmax to 0. During this process, liquid will still pass through. Therefore, in addition to calculating the water volume when the valve opening reaches Kmax, it is also necessary to calculate the water volume passing through during the valve opening or closing process. Based on the water volume calculation result when the valve is open, i.e., from opening 0 to opening Kmax, the water volume passing through when the valve is closed is predicted. At the same time, the flow rate when the valve opening reaches the preset opening Kmax is calculated. After obtaining the flow rate result, the water volume calculation analysis is performed based on the flow rate result and the duration of the state. The duration is configured by the user. The quantity calculation analysis result of the state is obtained. Then, the water volume calculation results of the opening state, the Kmax state, and the predicted closing state are combined to analyze the predicted water volume.

[0041] After obtaining the above water volume prediction and analysis results, the difference between the prediction and analysis results and the parameter standards is calculated to obtain the first water volume difference calculation result. Then, the difference calculation result is calculated again with the monitoring accuracy to obtain the second water volume difference calculation result. The second water volume difference calculation result is then compared and analyzed with the corresponding standard in the alarm level standard list. The analysis determines whether the second quantity difference calculation result falls into the corresponding data area in the alarm level standard list, and the alarm level is determined based on the data area it falls into. Finally, the matched alarm level result is output to the above interactive window.

[0042] This embodiment enables early warning of water volume exceeding limits, allowing users to take preventative measures and avoid losses or consequences caused by defects.

[0043] Example 4

[0044] To achieve timely handling of defects at wastewater treatment sites, this embodiment is further optimized based on the above embodiments, such as... Figure 1 As shown, the monitoring system also includes an inspection module 3. This module acquires inspection data recorded by the handheld inspection device 2, performs parallel analysis of process defects based on the inspection data, and obtains defect analysis results. If the defect analysis results indicate the existence of a defect, a defect work order is generated based on the defect analysis results and the inspection analysis results. The system also interacts with the data interaction module 8 to obtain defect processing results, and generates inspection results based on these results and the defect work order.

[0045] Users formulate inspection plans and assign inspection tasks to inspection personnel. The inspection personnel record the inspection results during the inspection process and upload the records. By analyzing the inspection records, any abnormalities or defects found are identified. If defects are found, a defect list is generated. Based on the links with abnormal defects, response areas are determined, and the defect list is distributed to the response areas so that the maintenance personnel in those areas can obtain the defect list and carry out timely rectification, inspection, and maintenance.

[0046] Example 5

[0047] To gain a more intuitive understanding of the overall situation of multiple indicators, this embodiment is optimized based on the above embodiments. In addition to the modules described in the above embodiments, this embodiment also includes a statistical analysis module. This statistical analysis module obtains the statistical time period through user interaction, performs statistical calculations on the above real-time process parameters according to the statistical time period, and obtains statistical results. The statistical results have a mapping relationship with the time period, and a statistical set model of time and statistical results is generated according to the above mapping relationship.

[0048] By interacting with users to obtain time periods (year, month, day), the system calculates the sum of real-time process parameters based on these time periods, creating a set of sum calculation results. These results are then arranged sequentially according to preset rules within the aforementioned time periods, forming a statistical ensemble model. This ensemble model is uploaded to the interactive window, allowing users to more intuitively view the overall situation of multiple indicators across various stages of the wastewater treatment process. This facilitates user analysis, summarization, and the development of plans or solutions.

[0049] Example 6:

[0050] like Figures 2-5 As shown, this embodiment provides a wastewater online monitoring method based on the monitoring system described in the above embodiments, such as... Figure 2 As shown, the method includes

[0051] S100: Interact with the wastewater treatment process design data of the wastewater treatment plant to be monitored, and simultaneously configure the parameter standards and monitoring accuracy of the process to be monitored. Combine the parameter standards, monitoring accuracy and process design data to generate a wastewater treatment process benchmark model.

[0052] Specifically, the user inputs design data for the wastewater treatment process, including but not limited to drawings, process design standards, and basic data. Based on the above data, a wastewater treatment process model is generated. Then, the user-input parameter standards (including but not limited to water volume, COD, TP, TN, etc., which are the data that the wastewater treatment process should achieve during design and operation) and monitoring accuracy (i.e., the upper and lower fluctuation accuracy of each parameter value) are matched into the above wastewater treatment process model to generate a wastewater treatment process benchmark model.

[0053] For example, the baseline model is established by the model generation module after obtaining the design drawings of the wastewater treatment plant, using OpenFlows SewerGEMS, EnviroSim BioWin or other wastewater treatment process modeling software built into the module, based on the design drawings and corresponding design data.

[0054] S200: Connects the data acquisition device to the wastewater treatment site, reads the site monitoring data in real time, and analyzes the real-time process parameters in parallel based on the above site monitoring data to obtain the real-time process parameters;

[0055] Specifically, it communicates with the data acquisition devices of the wastewater treatment plant to achieve connection. These data acquisition devices include, but are not limited to, sensors installed in the wastewater treatment process, sensors in operating equipment, instruments, valves, and on-site monitoring equipment. The data acquisition devices collect wastewater treatment parameters, equipment parameters, and on-site data, and upload them to the system in real time. By processing the real-time uploaded data in parallel, that is, processing data uploaded by multiple data acquisition devices simultaneously, the data processing and response speed is improved. After parallel analysis, the real-time process parameters obtained from the analysis are output. These real-time process parameters are the real-time data of the current wastewater treatment process, realizing real-time data monitoring.

[0056] S300: Match the real-time process parameters to the above-mentioned wastewater treatment process baseline model;

[0057] Specifically, multiple real-time process parameters output above are matched to the corresponding positions in the above process reference model according to the type of the parameters themselves, so that the real-time process parameters correspond to the corresponding links in the process reference model.

[0058] For example, regarding the influent flow data in the sedimentation stage, the aforementioned data acquisition device collects and uploads relevant data for analyzing the influent flow in this stage. After processing and analyzing the aforementioned relevant data, the real-time water flow parameters of the sedimentation stage are obtained, and these real-time water flow parameters are matched to the sedimentation stage in the aforementioned process reference model.

[0059] S400: Set up a data interaction window. Within the data interaction window, perform data interaction with the above-mentioned process baseline model and real-time process parameters to obtain data interaction results.

[0060] Specifically, the aforementioned wastewater treatment process benchmark model and the real-time process parameters matched to the model are transmitted to the data interaction window. Users can interact with the wastewater treatment process benchmark model in this interaction window to obtain interactive content, including process parameter standards, monitoring accuracy, real-time parameters, and on-site monitoring images.

[0061] For example, users can click on the sedimentation process stage of the process baseline model in the interactive window to generate an interactive command to obtain sedimentation process parameters. Based on this command, the user can obtain the corresponding interactive content, which includes various parameters of the sedimentation process stage, such as the influent flow rate, effluent flow rate, and images of the sedimentation tank area. These parameters are then output to the interactive window, allowing users to view the relevant parameters of the wastewater treatment process more intuitively.

[0062] The above method solves the technical problem of existing technologies being unable to collect and view wastewater treatment process parameters in real time. This invention collects process data and on-site data from wastewater treatment plants in real time and directly reflects this data in the wastewater treatment process model. Users can interact with the model to view real-time process data and on-site data, as well as the wastewater treatment plant's process standard data. This allows users to more intuitively understand the wastewater treatment status, enabling remote monitoring of wastewater treatment plants without needing to visit the site. Furthermore, the parallel data processing method employed in this approach effectively improves data processing speed, thereby enhancing data response efficiency.

[0063] like Figure 3 As shown, the monitoring methods described above also include:

[0064] S500: Perform alarm analysis and calculation based on the real-time process parameters and parameter standards to obtain alarm analysis and calculation results;

[0065] Specifically, the difference between the real-time process parameters and the parameter standard is calculated to obtain the first difference calculation result. Then, the difference calculation result is compared with the monitoring accuracy again to obtain the second difference calculation result.

[0066] S600: Interactively obtain alarm level standards, perform alarm level matching analysis based on the alarm analysis and calculation results above, and output alarm level matching results.

[0067] Specifically, the second difference calculation result is compared and analyzed with the corresponding standard in the alarm level standard list. The analysis shows that the second difference calculation result falls into the corresponding data area in the alarm level standard list, and the alarm level is determined based on the data area it falls into. Then, the matched alarm level result is output to the interactive window.

[0068] The above method enables real-time alarms for data exceeding limits during the monitoring process, thereby facilitating monitoring personnel to maintain and repair the processes corresponding to the current alarm parameters.

[0069] like Figure 4 As shown, the online wastewater monitoring method also includes

[0070] S700: Based on the on-site monitoring data, predictive analysis is performed on the process parameters to obtain the predictive analysis results;

[0071] S800: Based on the predicted analysis results and the matching parameter standards, perform alarm analysis calculations to obtain alarm analysis calculation results;

[0072] S900: Based on the alarm analysis and calculation results above, and combined with the alarm level standards, perform alarm level matching analysis to obtain alarm level matching results and output the level matching results.

[0073] Among them, such as Figure 5 As shown, S700 above: Based on the on-site monitoring data, predictive analysis is performed on the process parameters to obtain the predictive analysis results, including...

[0074] S710: Obtain valve opening data, calculate valve flow rate based on the above opening data, and obtain valve flow rate calculation results;

[0075] S710: Based on the valve flow calculation results above and combined with the time data, perform a prediction calculation of water volume to obtain the prediction calculation result of water volume.

[0076] This process is for early warning of excessive water volume. Since the valve opening process is a gradual process from 0 to Kmax, where Kmax is the preset valve opening, the process is similarly gradual. Similarly, the valve closing process is a process from Kmax to 0. During this process, liquid will still pass through. Therefore, in addition to calculating the water volume when the valve opening reaches Kmax, it is also necessary to calculate the water volume passing through during the valve opening or closing process. Based on the water volume calculation results when the valve is open, i.e., from opening 0 to opening Kmax, the water volume passing through when the valve is closed is predicted. At the same time, the flow rate when the valve opening reaches the preset opening Kmax is calculated. After obtaining the flow rate result, the water volume calculation analysis is performed based on the flow rate result and the duration of this state. The duration is configured by the user. The quantity calculation analysis results for this state are obtained. Then, combined with the water volume calculation results of the opening state, the water volume calculation results of the Kmax state, and the predicted water volume calculation results of the closing state, the predicted water volume analysis results are obtained.

[0077] After obtaining the above water volume prediction and analysis results, the difference between these results and the parameter standards is calculated to obtain the first water volume difference calculation result. This second difference calculation result is then compared with the monitoring accuracy to obtain the second water volume difference calculation result. This second water volume difference calculation result is then compared with the corresponding standard in the alarm level standard list. If the second water volume difference calculation result falls within the corresponding data area in the alarm level standard list, the alarm level is determined based on the data area it falls into, and the matched alarm level result is then output to the interactive window. This achieves early warning of water volume exceeding limits, allowing users to take preventative measures and avoid losses or consequences caused by defects.

[0078] In addition, online wastewater monitoring methods also include:

[0079] Interactively acquire inspection data, and analyze process defects in parallel based on the inspection data to obtain defect analysis results;

[0080] If the defect analysis result indicates the existence of a defect, a defect work order will be generated based on the defect analysis result and the inspection analysis result.

[0081] The defect processing results are obtained interactively, and inspection results are generated based on these results and the defect work order.

[0082] Specifically, users formulate inspection plans and assign inspection tasks to inspection personnel. The inspection personnel record the inspection results during the inspection process and upload the records. By analyzing the inspection records, any abnormal defects found in the records are analyzed. If defects are found, a defect list is generated, and a response area is determined based on the links with abnormal defects. The defect list is then distributed to the response area so that the maintenance personnel in that response area can obtain the defect list and carry out timely rectification, inspection, and maintenance.

[0083] The above-mentioned online wastewater monitoring methods also include:

[0084] The statistical time period is obtained interactively, and the above real-time process parameters are statistically calculated based on the statistical time period to obtain statistical results.

[0085] There is a mapping relationship between statistical results and time periods. Based on the above mapping relationship, a statistical set model of time and statistical results is generated.

[0086] Specifically, the time period is obtained through user interaction. The time period includes year, month, and day. Based on the above time period, the real-time process parameters are summed to obtain the sum calculation results and form a set of sum calculation results. At the same time, the sum results are arranged in order according to the above time period and a preset rule to form a statistical set model.

[0087] The aforementioned ensemble model is uploaded to the interactive window, allowing users to more intuitively view the overall situation of multiple indicators in each stage of the wastewater treatment process, thus facilitating users to analyze, summarize, and specify plans or solutions.

[0088] Through the foregoing detailed description of an online wastewater monitoring system, those skilled in the art can clearly understand the online wastewater monitoring system and its monitoring method based on parallel data streams in this embodiment. As the method disclosed in the embodiment corresponds to the device disclosed in the embodiment, the description is relatively simple, and relevant parts can be referred to the method section description.

[0089] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A wastewater online monitoring system based on parallel data streams, characterized in that, The monitoring system includes The data input module acquires the wastewater treatment process design data of the wastewater treatment plant to be monitored, and simultaneously configures the parameter standards and monitoring accuracy of the process to be monitored. The model generation module, combining the parameter standards, monitoring accuracy, and process design data, generates a baseline model for the wastewater treatment process. The data acquisition module connects the data acquisition device of the sewage treatment plant to the sewage treatment site, and reads the on-site monitoring data in real time. The data analysis module receives the aforementioned field monitoring data and analyzes the field monitoring data uploaded by multiple data acquisition modules in parallel, thereby analyzing the real-time process parameters based on the field monitoring data to obtain the real-time process parameters. The data matching module matches real-time process parameters to the aforementioned wastewater treatment process baseline model. as well as The data interaction module sets up a data interaction window, and within the data interaction window, the data interaction of the monitoring sensors is performed based on the above-mentioned process reference model and real-time process parameters to obtain the data interaction results. The system also includes a data prediction module, which performs predictive analysis on process parameters based on the on-site monitoring data to obtain prediction analysis results; The system also includes an alarm module, which performs alarm analysis and calculation based on the real-time process parameters and parameter standards to obtain alarm analysis and calculation results. Based on the alarm analysis and calculation results, it performs alarm level matching analysis in conjunction with alarm level standards to obtain alarm level matching results and outputs alarm level matching results. The data prediction module includes: The flow calculation module acquires the valve opening data, calculates the valve flow rate based on the opening data, and obtains the valve flow rate calculation result. The water volume prediction module calculates the water volume based on the valve flow rate calculation results and time data, and obtains the predicted analysis results of the water volume. The alarm module obtains the predicted analysis results of water volume, calculates the difference between the predicted analysis results and the parameter standards to obtain the first water volume difference calculation result, and then calculates the difference between the first water volume difference calculation result and the monitoring accuracy to obtain the second water volume difference calculation result. The second water volume difference calculation result is then compared and analyzed with the corresponding standard in the alarm level standard list. The analysis shows that the second water volume difference calculation result falls into the corresponding data area in the alarm level standard list, and the alarm level is determined based on the data area it falls into. Finally, the matched alarm level result is output to the interactive window.

2. The wastewater online monitoring system based on parallel data stream according to claim 1, characterized in that, The system also includes an inspection module, which acquires inspection data, analyzes process defects in parallel based on the inspection data, and obtains defect analysis results. If the defect analysis results indicate the existence of defects, a defect work order is generated based on the defect analysis results and the inspection analysis results. The system then interactively obtains defect processing results and generates inspection results based on the defect processing results and the defect work order.

3. The wastewater online monitoring system based on parallel data stream according to claim 1, characterized in that, The system also includes a statistical analysis module, which interactively obtains statistical time periods, performs statistical calculations on the real-time process parameters based on the statistical time periods, obtains statistical results, and establishes a mapping relationship between the statistical results and the time periods. Based on the mapping relationship, a statistical set model of time and statistical results is generated.

4. A wastewater online monitoring method based on parallel data streams, characterized in that, The method uses the monitoring system described in any one of claims 1 to 3, and the method includes... The wastewater treatment process design data of the wastewater treatment plant to be monitored is obtained interactively, and the parameter standards and monitoring accuracy of the process to be monitored are configured simultaneously. The wastewater treatment process benchmark model is generated by combining the parameter standards, monitoring accuracy and process design data. Connect the data acquisition device to the wastewater treatment site, read the on-site monitoring data in real time, and analyze the real-time process parameters in parallel based on the on-site monitoring data to obtain the real-time process parameters; The real-time process parameters are matched to the above-mentioned wastewater treatment process benchmark model; A data interaction window is set up. Within the data interaction window, data interaction is performed based on the aforementioned process baseline model and real-time process parameters to obtain data interaction results.

5. The wastewater online monitoring method based on parallel data stream according to claim 4, characterized in that, The method also includes Alarm analysis and calculation are performed based on the real-time process parameters and parameter standards to obtain the alarm analysis and calculation results; The alarm level standard is obtained interactively. Based on the alarm analysis and calculation results above, alarm level matching analysis is performed in combination with the alarm level standard to obtain alarm level matching results, and the alarm level matching results are output.

6. The wastewater online monitoring method based on parallel data stream according to claim 4, characterized in that, The method also includes Based on the on-site monitoring data, predictive analysis is performed on the process parameters to obtain the predictive analysis results; Based on the predicted analysis results and the matching parameter standards, alarm analysis calculations are performed to obtain alarm analysis calculation results; Based on the alarm analysis and calculation results above, alarm level matching analysis is performed in conjunction with alarm level standards to obtain alarm level matching results, and the level matching results are output.

7. The wastewater online monitoring method based on parallel data stream according to claim 6, characterized in that, Based on the aforementioned on-site monitoring data, predictive analysis is performed on the process parameters to obtain the predictive analysis results, including... Obtain the valve opening data, calculate the valve flow rate based on the opening data, and obtain the valve flow rate calculation result; Based on the valve flow calculation results and the time data, a water volume prediction calculation is performed to obtain the water volume prediction result.

8. The wastewater online monitoring method based on parallel data stream according to claim 4, characterized in that, The method also includes Interactively acquire inspection data, and analyze process defects in parallel based on the inspection data to obtain defect analysis results; If the defect analysis result indicates the existence of a defect, a defect work order will be generated based on the defect analysis result and the inspection analysis result. The defect processing results are obtained interactively, and inspection results are generated based on these results and the defect work order.

9. The wastewater online monitoring method based on parallel data stream according to claim 4, characterized in that, The method also includes The statistical time period is obtained interactively, and the above real-time process parameters are statistically calculated based on the statistical time period to obtain statistical results. There is a mapping relationship between statistical results and time periods. Based on the above mapping relationship, a statistical set model of time and statistical results is generated.

Images