A sewage detection data aggregation and analysis early warning method

Abstract

The invention relates to the technical field of electronic digital data processing, and in particular to a sewage detection data aggregation and analysis early warning method, the method comprising: S1. performing regional division, obtaining environmental characteristic values ​​of each target area through processing, and deploying sewage detection points; S2. obtaining reference indicators for evaluating the content of toxic metabolites at sewage detection points in each target area according to matching of the environmental characteristic values ​​of each target area; S3. acquiring sewage detection data and equipment operation data of each sewage detection point in each target area; S4. obtaining equipment operation abnormality risk assessment values ​​of each sewage detection point in each target area through processing and performing threshold matching; S5. obtaining toxic metabolite assessment parameters of each sewage detection point in each target area through processing and performing evaluation and early warning on each target area. The invention can help reduce the pollution of sewage and toxic substances to the environment by providing a sewage detection data aggregation and analysis early warning method, and is conducive to promoting regional sustainable development.

Description

Technical Field

[0001] The invention relates to the technical field of electronic digital data processing, and in particular to a sewage detection data aggregation and analysis early warning method. Background Art

[0002] The abuse of toxic substances has become a global problem, posing a serious threat to human health and social public safety. In order to effectively monitor and evaluate the toxic situation, countries have adopted advanced scientific and technological means. Sewage toxicity analysis, as a non-invasive monitoring method, has received widespread attention and application in recent years. However, the existing sewage toxicity analysis methods still have many challenges in data collection, processing and analysis. Therefore, it is particularly important to develop an efficient and accurate sewage detection data aggregation and analysis early warning method.

[0003] For example, the invention patent with announcement number: CN117312617B is a real-time sewage treatment method and system based on sewage data monitoring, including: obtaining local segments, first sewage monitoring real-time data and adjacent sewage monitoring real-time data; obtaining the noise degree of sewage monitoring real-time data according to local segments; obtaining the anomaly coefficient of the data type; obtaining the adjusted K-neighborhood distance of the first sewage monitoring real-time data, performing anomaly detection on the first sewage monitoring real-time data and adjacent sewage monitoring real-time data, obtaining local outlier factors, marking abnormal sewage data according to the local outlier factors, and realizing real-time sewage treatment monitoring.

[0004] For example, the invention patent with announcement number: CN118709065B is a sewage treatment anomaly detection and early warning system based on big data analysis, including a data analysis module for dividing multiple data indicators obtained within a preset time period into at least one category; a data processing module for constructing a scatter plot for any category, obtaining the initial K value of the KNN algorithm, and obtaining the degree of abnormality of each data point in the scatter plot according to the initial K value; a parameter acquisition module for obtaining abnormal points according to the degree of abnormality of each data point, and adaptively obtaining the optimal K value of each data point in the scatter plot according to the abnormal point and the initial K value; an anomaly detection module for applying the optimal K value in the KNN algorithm to detect the data points of each category and complete the abnormal early warning of sewage treatment. Under the optimal K value, the interference caused by the data deviation point during the operation of the KNN algorithm is eliminated, and the accuracy of data point detection is improved.

[0005] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the present application discovered that the above-mentioned technology has at least the following technical problems: the existing sewage detection data analysis and early warning system has limited data processing and analysis capabilities, low integration and automation levels, inadequate emergency response plans, and lacks the ability to quickly respond to pollution incidents, resulting in limited efficiency and accuracy of the early warning system. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention provides a sewage detection data aggregation and analysis early warning method, which can effectively solve the problems involved in the above-mentioned background technology.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: The present invention provides a sewage detection data aggregation and analysis early warning method, including: S1. Divide the sewage detection area into regions, mark them as target areas, obtain basic data of each target area, obtain environmental characteristic values ​​of each target area after processing, and deploy sewage detection points according to the environmental characteristic values ​​of each target area, and mark them as sewage detection points in each target area.

[0008] S2. According to the matching of the environmental characteristic values ​​of each target area, the reference indicators for evaluating the content of toxic metabolites in the sewage detection points of each target area are obtained.

[0009] S3. Obtain the sewage detection data of each sewage detection point in each target area and the equipment operation data of each sewage detection point in each target area.

[0010] S4. Based on the environmental characteristic values ​​of each target area and the equipment operation data of each sewage detection point in each target area, the equipment operation abnormality risk assessment value of each sewage detection point in each target area is processed, and the toxic metabolite content assessment reference index of each sewage detection point in each target area is corrected according to the equipment operation abnormality risk assessment value of each sewage detection point in each target area to obtain the toxic metabolite content assessment threshold of each sewage detection point in each target area.

[0011] S5. Based on the sewage detection data of each sewage detection point in each target area, the evaluation parameters of toxic metabolites at each sewage detection point in each target area are obtained through processing, and based on the evaluation threshold of toxic metabolites content at each sewage detection point in each target area and the evaluation parameters of toxic metabolites at each sewage detection point in each target area, each target area is evaluated and warned, and the sewage detection historical data of each sewage detection point in each target area is obtained. Based on the abnormal equipment operation risk assessment value of each sewage detection point in each target area, a comprehensive analysis is performed to obtain the detection effect evaluation index of each sewage detection point in each target area, and feedback is given to the warning effect.

[0012] As a further method, the environmental characteristic values ​​of each target area are obtained through processing, and the specific process is: the basic data of each target area includes: the altitude and terrain slope of each environmental monitoring point, the number of residential areas in each target area, and the population density of each residential area in each target area.

[0013] The average altitude, average terrain slope, number of critical residential areas and population density of critical residential areas in the sewage detection area were extracted from the regional sewage detection system database.

[0014] According to the basic data of each target area, the environmental characteristic values ​​of each target area are processed to obtain the environmental characteristic values ​​of each target area, which are used to quantitatively evaluate the influence of the basic environmental characteristics of each target area on the regional sewage collection and the metabolism of toxic substances in the sewage, and provide a basis for matching the reference indicators for evaluating the content of toxic metabolic substances in the sewage detection points of each target area.

[0015] As a further method, sewage detection points are deployed according to the environmental characteristic values ​​of each target area and marked as sewage detection points in each target area. The specific process is: extracting the first threshold and the second threshold of the regional environmental characteristics from the regional sewage detection system database, comparing the environmental characteristic values ​​of each target area with the first threshold and the second threshold of the regional environmental characteristics, and if the environmental characteristic value of the target area is higher than or equal to the first threshold of the regional environmental characteristics, the target area is marked as a high-pollution area.

[0016] If the target area environmental characteristic value is higher than the second threshold of the regional environmental characteristic and lower than the first threshold, the target area is marked as a medium pollution area.

[0017] If the target area environmental characteristic value is lower than or equal to the second threshold of the regional environmental characteristic, the target area is marked as a low-pollution area.

[0018] Corresponding sewage detection points are deployed in high, medium and low pollution areas respectively, and marked as sewage detection points in each target area.

[0019] As a further method, the matching obtains reference indicators for evaluating the content of toxic metabolites in sewage detection points in each target area. The specific matching process is: extracting a mapping set between the environmental characteristic values ​​of each target area and the reference indicators for evaluating the content of toxic metabolites in sewage detection points in each target area from the regional sewage detection system database.

[0020] Input the real-time environmental characteristic values ​​of the target area, and obtain the corresponding reference indicators for evaluating the content of toxic metabolites in the sewage detection points according to the mapping set.

[0021] As a further method, the processing obtains the equipment operation abnormality risk assessment value of each sewage detection point in each target area. The specific process is: the equipment operation data of each sewage detection point in each target area includes: the operation time of each equipment within a preset monitoring period, the number of equipment failures, the data transmission rate of the equipment and the response time of the equipment.

[0022] The critical equipment operation time, critical equipment failure times, critical equipment data transmission rate and critical equipment response time were extracted from the regional sewage detection system database.

[0023] Based on the environmental characteristic values ​​of each target area and the equipment operation data of each sewage detection point in each target area, comprehensive processing is performed to obtain the equipment operation abnormality risk assessment value of each sewage detection point in each target area.

[0024] As a further method, the reference index for evaluating the content of toxic metabolites at each sewage detection point in each target area is corrected according to the risk assessment value of abnormal equipment operation at each sewage detection point in each target area to obtain an evaluation threshold value for the content of toxic metabolites at each sewage detection point in each target area. The specific process is as follows: according to the risk assessment value of abnormal equipment operation at each sewage detection point in each target area, a correction value for the content of toxic metabolites at each sewage detection point in each target area is obtained by matching the risk assessment value of abnormal equipment operation at each sewage detection point in each target area from the regional sewage detection system database.

[0025] The reference index for evaluating the content of toxic metabolites at sewage testing points in each target area is summed with the correction value of the content of toxic metabolites at each sewage testing point in each target area to obtain the evaluation threshold of the content of toxic metabolites at each sewage testing point in each target area.

[0026] As a further method, the processing obtains the evaluation parameters of toxic metabolites at each sewage detection point in each target area. The specific process is: the concentration of various toxic metabolites at each sewage detection point within a preset monitoring period.

[0027] The critical concentrations of various toxic metabolites were extracted from the regional sewage detection system database.

[0028] According to the sewage detection data of each sewage detection point in each target area, the toxic metabolite assessment parameters of each sewage detection point in each target area are processed. The toxic metabolite assessment parameters of each sewage detection point in each target area are used to quantitatively evaluate the content of toxic metabolites in each sewage detection point in each target area, so as to provide a basis for risk warning for the target area.

[0029] As a further method, the target areas are evaluated and warned according to the evaluation threshold of the toxic metabolite content of each sewage detection point in each target area and the evaluation parameter of the toxic metabolite content of each sewage detection point in each target area. The specific process is: the evaluation threshold of the toxic metabolite content of each sewage detection point in each target area is compared with the evaluation parameter of the toxic metabolite content of each sewage detection point in each target area. If the evaluation parameter of the toxic metabolite content of a sewage detection point in the target area is higher than or equal to the evaluation threshold of the toxic metabolite content of the sewage detection point in the target area, the sewage detection point is marked as a high-pollution detection point. If the evaluation parameter of the toxic metabolite content of a sewage detection point in the target area is lower than the evaluation threshold of the toxic metabolite content of the sewage detection point in the target area, the sewage detection point is marked as a low-pollution detection point.

[0030] Statistics of high-pollution detection points in each target area are collected for early warning.

[0031] As a further method, the risk assessment value of abnormal equipment operation at each sewage detection point in each target area is quantitative assessment data obtained by comprehensive analysis of the equipment's operating time, the number of equipment failures, the equipment's data transmission rate and the equipment's response time. It is used to quantitatively assess the risk level of abnormal equipment operation at each sewage detection point in each target area, and provide a basis for risk warning for the target area.

[0032] As a further method, the specific numerical expressions of the environmental characteristic values ​​of each target area are as follows:

[0033] ;

[0034] In the formula, represents the environmental characteristic value of the nth target area, n represents the number of each target area, , m represents the total number of target areas, It represents the altitude of the ith environmental monitoring point in the nth target area, i represents the number of each environmental monitoring point, , h represents the total number of environmental monitoring points, represents the terrain slope of the ith environmental monitoring point in the nth target area, represents the number of residential areas in the nth target area, represents the population density of the qth residential area in the nth target area, q represents the number of each residential area, , p represents the total number of residential areas, Indicates the average altitude of the sewage detection area, represents the average terrain slope of the sewage detection area, represents the number of critical residential areas, Represents the critical residential area population density.

[0035] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects:

[0036] (1) The present invention provides a sewage detection data aggregation and analysis early warning method, which accurately identifies the high-pollution sewage detection points in the target area, and provides risk warning and efficient treatment for them, which is conducive to reducing the pollution of sewage and toxic substances to the environment, reducing the impact of sewage and toxic substances on residents' lives, protecting public health, and promoting regional sustainable development.

[0037] (2) The present invention can help identify high-risk areas in the target area and guide the deployment of regional sewage detection points by comprehensively analyzing the altitude, terrain slope, number of residential areas and population density of the area. It can also help environmental management departments formulate more accurate management strategies and improve decision-making efficiency. It can also detect environmental changes in a timely manner and adjust management measures.

[0038] (3) The present invention can help establish a risk warning system by comprehensively analyzing the equipment's operating time, number of failures, data transmission rate, and response time, so as to timely detect equipment abnormalities and take measures. It can also help formulate reasonable maintenance plans to ensure that the equipment operates in the best condition and reduce failures and downtime. It can also help identify performance bottlenecks, guide the optimization of equipment or processes, and improve overall efficiency, thereby helping to extend the service life of the equipment and reduce the total cost of ownership.

[0039] (4) By monitoring the concentration of toxic metabolites at different sewage detection points, the present invention can help identify specific pollution sources and assess their potential impact on surrounding ecosystems and public health. It can also guide the risk classification of regional sewage detection points and give priority to areas with higher risks. It can also help guide the formulation of emergency response plans and take measures to reduce the spread of pollution. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0041] Figure 1 It is a schematic diagram of the method flow of the present invention.

[0042] Figure 2 The following is a business process diagram involved in an embodiment of the present invention. DETAILED DESCRIPTION

[0043] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0044] Reference Figure 1As shown, the present invention provides a sewage detection data aggregation and analysis early warning method, including: S1. Divide the sewage detection area into regions, mark them into target areas, obtain basic data of each target area, obtain environmental characteristic values ​​of each target area after processing, and deploy sewage detection points according to the environmental characteristic values ​​of each target area, and mark them as sewage detection points in each target area.

[0045] Specifically, the environmental characteristic values ​​of each target area are obtained through processing, and the specific process is as follows: the basic data of each target area includes: the altitude and terrain slope of each environmental monitoring point, the number of residential areas in each target area, and the population density of each residential area in each target area.

[0046] It needs to be explained that the terrain slope of the environmental monitoring point refers to the degree of inclination of the surface where the monitoring point is located, specifically the ratio of the surface height change (i.e. vertical distance) to the horizontal distance.

[0047] It should be explained that the altitude of a region can be obtained through satellite remote sensing technology, such as the global positioning system or elevation data in a geographic information system. Accurate terrain slope data can be obtained through field measurements and equipment such as topographs.

[0048] The average altitude, average terrain slope, number of critical residential areas and population density of critical residential areas in the sewage detection area were extracted from the regional sewage detection system database.

[0049] According to the basic data of each target area, the environmental characteristic value of each target area is processed, and the environmental characteristic value of each target area is used to quantitatively evaluate the impact of the basic environmental characteristics of each target area on the regional sewage collection and the metabolism of toxic substances in the sewage, and provide a basis for matching the reference indicators for evaluating the content of toxic metabolites in the sewage detection points of each target area. The toxic metabolites include heavy metal compounds such as chromium, cadmium, nickel, zinc, copper, gold and silver, cyanide hydrogen sulfide and methane, ammonia, carbon dioxide and other compounds that have adverse effects on animals and plants.

[0050] In a specific embodiment, the numerical expression of the environmental characteristic value of each target area is:

[0051] ;

[0052] In the formula, represents the environmental characteristic value of the nth target area, n represents the number of each target area, , m represents the total number of target areas, It represents the altitude of the ith environmental monitoring point in the nth target area, i represents the number of each environmental monitoring point, , h represents the total number of environmental monitoring points, represents the terrain slope of the ith environmental monitoring point in the nth target area, represents the number of residential areas in the nth target area, represents the population density of the qth residential area in the nth target area, q represents the number of each residential area, , p represents the total number of residential areas, Indicates the average altitude of the sewage detection area, represents the average terrain slope of the sewage detection area, represents the number of critical residential areas, Represents the critical residential area population density.

[0053] It needs to be explained that when the altitude and terrain slope are lower, the number of residential areas is greater, and the population density is denser, the corresponding environmental characteristic values ​​of the target area will be greater, indicating that the basic environmental characteristics of the target area have a greater impact on the regional sewage collection and the metabolism of toxic substances in the sewage.

[0054] It needs to be explained that the slope of the terrain is often related to the change in altitude. For example, in mountainous areas, places with large changes in altitude usually have larger slopes. The slope of the terrain may affect the number of residential areas. Generally, areas with larger slopes are not conducive to construction, so the number of residential areas may be smaller. Altitude may also affect the number of residential areas. High-altitude areas may have fewer residential areas due to factors such as climate and transportation. The number of residential areas and population density are related, but the relationship between them depends on the size of each residential area. Altitude and terrain slope may indirectly affect the population density of residential areas. Generally, flatter areas with moderate altitudes are more suitable for living, so the population density may be higher.

[0055] It should be explained that low-lying areas, i.e. areas with an altitude lower than the average altitude of the region and a slope lower than the average terrain slope of the region, are prone to water accumulation, so sewage and rainwater are easily collected. Analyzing the altitude and terrain slope of the target area can help identify which areas may become high-risk areas for sewage collection. Areas with dense residential areas and high population density have a large amount of sewage generated, and if the drainage system is not perfect, the sewage collection problem will be more serious. By analyzing the number of residential areas and population density, the amount of sewage generated can be predicted, so as to reasonably plan the scale and location of sewage treatment facilities. Combining altitude and terrain slope, the design of sewage pipe network can be optimized to reduce the risk of sewage collection and overflow. Densely populated areas may use more chemicals and produce more industrial and domestic toxic substances. These substances may enter the environment through sewage discharge. Altitude and terrain slope affect the migration and diffusion of toxic substances. For example, pollutants may accumulate in low-lying areas or flow rapidly downstream in areas with large slopes.

[0056] It should be explained that this embodiment can help identify high-risk areas in the target area, help guide the deployment of regional sewage detection points, and help environmental management departments formulate more accurate management strategies and improve decision-making efficiency by comprehensively analyzing the altitude, terrain slope, number of residential areas and population density of the area. It can also detect environmental changes in a timely manner and adjust management measures. This helps to reduce the pollution of sewage and toxic substances to the environment, reduce the impact of sewage and toxic substances on residents' lives, and protect public health.

[0057] Furthermore, sewage detection points are deployed according to the environmental characteristic values ​​of each target area and marked as sewage detection points in each target area. The specific process is: extract the first threshold and the second threshold of the regional environmental characteristics from the regional sewage detection system database, and compare the environmental characteristic values ​​of each target area with the first threshold and the second threshold of the regional environmental characteristics. If the environmental characteristic value of the target area is higher than or equal to the first threshold of the regional environmental characteristics, the target area is marked as a high-pollution area.

[0058] If the target area environmental characteristic value is higher than the second threshold of the regional environmental characteristic and lower than the first threshold, the target area is marked as a medium pollution area.

[0059] If the target area environmental characteristic value is lower than or equal to the second threshold of the regional environmental characteristic, the target area is marked as a low-pollution area.

[0060] Corresponding sewage detection points are deployed in high, medium and low pollution areas respectively, and marked as sewage detection points in each target area.

[0061] In a specific embodiment, 20 sewage detection points may be deployed in high-pollution areas.

[0062] S2. According to the matching of the environmental characteristic values ​​of each target area, the reference indicators for evaluating the content of toxic metabolites in the sewage detection points of each target area are obtained.

[0063] Specifically, reference indicators for evaluating the content of toxic metabolites in sewage detection points in each target area are matched, and the specific matching process is: a mapping set between environmental characteristic values ​​of each target area and reference indicators for evaluating the content of toxic metabolites in sewage detection points in each target area is extracted from the regional sewage detection system database.

[0064] Input the real-time environmental characteristic values ​​of the target area, and obtain the corresponding reference indicators for evaluating the content of toxic metabolites in the sewage detection points according to the mapping set.

[0065] It should be added that the mapping relationship of the above mapping sets is a one-to-one correspondence.

[0066] S3. Obtain the sewage detection data of each sewage detection point in each target area and the equipment operation data of each sewage detection point in each target area.

[0067] Specifically, the sewage detection data of each sewage detection point in each target area includes: the concentrations of various toxic metabolites at each sewage detection point within a preset monitoring period.

[0068] The equipment operation data of each sewage detection point in each target area includes: each operation time of the equipment within a preset monitoring period, the number of equipment failures, the data transmission rate of the equipment and the response time of the equipment.

[0069] It should be explained that, in this embodiment, the operation time of each device refers to the continuous normal operation time of the device within the preset monitoring period. The data transmission rate of the device refers to the speed at which the device transmits data. The response time of the device refers to the time from the device receiving a detection request to the device completing the request and giving feedback.

[0070] It is important to explain that the running time of a device can be recorded in real time by testing the device's built-in timer or logging function. The number of device failures can be tracked through maintenance logs or service records. The data transmission rate of a device can be measured using network monitoring tools. The data transmission rate can also be obtained through the device's built-in performance testing function or third-party testing software. The system log can record the device's response time. The response time of a device can also be tested in real time or periodically using performance monitoring tools.

[0071] It should be added that, in this embodiment, one sewage detection point corresponds to one detection device.

[0072] S4. Based on the environmental characteristic values ​​of each target area and the equipment operation data of each sewage detection point in each target area, the equipment operation abnormality risk assessment value of each sewage detection point in each target area is processed, and the toxic metabolite content assessment reference index of each sewage detection point in each target area is corrected according to the equipment operation abnormality risk assessment value of each sewage detection point in each target area to obtain the toxic metabolite content assessment threshold of each sewage detection point in each target area.

[0073] Specifically, the equipment operation abnormality risk assessment value of each sewage detection point in each target area is processed and obtained. The specific process is: extracting the critical equipment operation time, critical equipment failure number, critical equipment data transmission rate and critical equipment response time from the regional sewage detection system database.

[0074] According to the environmental characteristic values ​​of each target area and the equipment operation data of each sewage detection point in each target area, comprehensive processing is performed to obtain the equipment operation abnormality risk assessment value of each sewage detection point in each target area. The equipment operation abnormality risk assessment value of each sewage detection point in each target area is used to quantitatively assess the risk degree of equipment operation abnormality of each sewage detection point in each target area, so as to provide a basis for risk warning for the target area.

[0075] In a specific embodiment, the numerical expression of the equipment operation abnormality risk assessment value of each sewage detection point in each target area is:

[0076] ;

[0077] In the formula, represents the risk assessment value of equipment operation abnormality at the sth sewage detection point in the nth target area, represents the environmental characteristic value of the nth target area, s represents the number of each sewage detection point, , r represents the total number of sewage detection points, t represents the time variable, , Indicates the current time point. Indicates the monitoring start time point, It represents the kth operation time of the equipment at the sth sewage detection point in the nth target area, where k represents the number of each operation of the equipment. , g represents the total number of times the device runs, Indicates the number of failures of the sth sewage detection point equipment in the nth target area within the preset monitoring period, represents the data transmission rate of the sth sewage detection point equipment in the nth target area at time t, It represents the response time of the equipment at the sth sewage detection point in the nth target area at time t, Indicates the critical equipment operation time, represents the number of critical equipment failures, Indicates the critical device data transfer rate, Indicates the critical device response time, Indicates the target area equipment operation abnormality risk correction factor corresponding to the preset target area environmental characteristic value.

[0078] It needs to be explained that the shorter the equipment operation time, the more equipment failures, the slower the equipment data transmission rate, and the longer the equipment response time, the greater the corresponding equipment operation abnormality risk assessment value, indicating that the risk of equipment operation abnormality is greater.

[0079] It should be explained that in this embodiment It represents the target area equipment operation abnormal risk correction factor corresponding to the preset target area environmental characteristic value. The value of the correction factor represents the degree of influence of the target area environmental characteristic value on the target area detection equipment operation abnormal risk. When used, the correction factor can be directly obtained from the regional sewage detection system database. The value of the correction factor is preset in the regional sewage detection system database, and the target area environmental characteristic value and the correction factor preset in the regional sewage detection system database form a mapping set. For example, by inputting the real-time target area environmental characteristic value into the mapping set, the corresponding target area equipment operation abnormal risk correction factor can be obtained. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship. The value range of the correction factor is between 0 and 1, indicating the degree from no impact to maximum impact.

[0080] It should be explained that the longer the normal operation time of the equipment, the fewer times the equipment fails within the preset detection cycle. The faster the data transmission rate of the equipment, the shorter the waiting time for data processing, thereby reducing the response time. The shorter the response time of the equipment, the faster the system processes data and the better the user experience. The fewer the equipment failures and the longer the operation time, the more stable the system and the shorter the response time. If the equipment fails frequently, it may affect data transmission, which in turn increases the response time.

[0081] It should be explained that this embodiment can help establish a risk warning system by comprehensively analyzing the operation time of each device, the number of device failures, the data transmission rate of the device, and the response time of the device, so as to timely detect abnormal conditions of the device and take measures. It is helpful to formulate a reasonable maintenance plan to ensure that the equipment operates in the best state and reduce failures and downtime. It can also help identify performance bottlenecks, guide the optimization of equipment or processes, and improve overall efficiency. It can also guide preventive maintenance, thereby helping to reduce emergency repair costs and extend the service life of equipment.

[0082] Furthermore, according to the abnormal equipment operation risk assessment value of each sewage detection point in each target area, the reference index for toxic metabolite content assessment at the sewage detection point in each target area is corrected to obtain the toxic metabolite content assessment threshold of each sewage detection point in each target area. The specific process is: according to the abnormal equipment operation risk assessment value of each sewage detection point in each target area, the toxic metabolite content correction value of each sewage detection point in each target area is matched from the regional sewage detection system database.

[0083] The reference index for evaluating the content of toxic metabolites at sewage testing points in each target area is summed with the correction value of the content of toxic metabolites at each sewage testing point in each target area to obtain the evaluation threshold of the content of toxic metabolites at each sewage testing point in each target area.

[0084] S5. Based on the sewage detection data of each sewage detection point in each target area, the evaluation parameters of toxic metabolites at each sewage detection point in each target area are obtained through processing, and based on the evaluation threshold of toxic metabolites content at each sewage detection point in each target area and the evaluation parameters of toxic metabolites at each sewage detection point in each target area, each target area is evaluated and warned, and the sewage detection historical data of each sewage detection point in each target area is obtained. Based on the abnormal equipment operation risk assessment value of each sewage detection point in each target area, a comprehensive analysis is performed to obtain the detection effect evaluation index of each sewage detection point in each target area, and feedback is given to the warning effect.

[0085] Specifically, the evaluation parameters of toxic metabolites at each sewage detection point in each target area are obtained through processing. The specific process is: critical concentrations of various toxic metabolites are extracted from the regional sewage detection system database.

[0086] According to the sewage detection data of each sewage detection point in each target area, the toxic metabolite assessment parameters of each sewage detection point in each target area are processed. The toxic metabolite assessment parameters of each sewage detection point in each target area are used to quantitatively evaluate the content of toxic metabolites in each sewage detection point in each target area, so as to provide a basis for risk warning for the target area.

[0087] In a specific embodiment, the numerical expression of the evaluation parameter of the toxic metabolites at each sewage detection point in each target area is:

[0088] ;

[0089] In the formula, represents the evaluation parameter of toxic metabolites at the sth sewage detection point in the nth target area, e represents a natural constant, represents the concentration of the yth toxic metabolite at the sth sewage detection point in the nth target area, where y represents the number of each toxic metabolite. , x represents the total number of toxic metabolites, represents the critical concentration of the yth toxic metabolite, It represents the influence characteristic factor of the toxic metabolite content corresponding to the preset y-th toxic metabolite concentration.

[0090] It should be added that in sewage toxicity monitoring, although in theory the total amount of toxic metabolites can be obtained by simply adding up the contents of each toxic substance, in fact, it is a more accurate and scientific method to assign weights to the content of each toxic metabolite and design a formula to quantify it. Some toxic metabolites are relatively stable in sewage, while others may decrease rapidly due to adsorption, degradation, etc. At the same time, different toxic metabolites have different levels of importance in sewage toxicity monitoring. By designing different weights for each toxic metabolite, their actual concentration and relative importance in sewage can be more accurately reflected. For example, polychlorinated biphenyls can remain in natural water bodies for a long time and are difficult to be biodegraded, so their weight is set to 0.8.

[0091] It needs to be explained that the higher the concentration of various toxic metabolites at the sewage testing point, the larger the corresponding evaluation parameter of the toxic metabolites at the sewage testing point, indicating that the content of toxic metabolites at the sewage testing point is higher.

[0092] It should be explained that in this embodiment It represents the influencing characteristic factor of the toxic metabolite content corresponding to the preset concentration of the yth toxic metabolite. The value of the influencing characteristic factor represents the degree of influence of the concentration of various toxic metabolites at the sewage detection point on the content of toxic metabolites in the target area. When used, the influencing characteristic factor can be directly obtained from the regional sewage detection system database. The value of the influencing characteristic factor is preset in the regional sewage detection system database. The concentration of various toxic metabolites at the sewage detection point and the influencing characteristic factors preset in the regional sewage detection system database form a mapping set. For example, the real-time concentration of toxic metabolites at the sewage detection point is input into the mapping set to obtain the corresponding influencing characteristic factor of the toxic metabolite content. The mapping relationship can be one-to-one or many-to-one. The value range of the influencing characteristic factor is between 0 and 1, indicating the degree from no influence to maximum influence.

[0093] It should be explained that this embodiment can help identify specific pollution sources by monitoring the concentration of toxic metabolites at different sewage detection points, and also help assess their potential impact on surrounding ecosystems and public health. It can also guide the risk level classification of regional sewage detection points and give priority to areas with higher risks. It can also help guide the formulation of emergency response plans and take measures to reduce the spread of pollution.

[0094] Furthermore, based on the evaluation threshold of the toxic metabolite content of each sewage detection point in each target area and the evaluation parameter of the toxic metabolite content of each sewage detection point in each target area, each target area is evaluated and warned. The specific process is: the evaluation threshold of the toxic metabolite content of each sewage detection point in each target area is compared with the evaluation parameter of the toxic metabolite content of each sewage detection point in each target area. If the evaluation parameter of the toxic metabolite content of a sewage detection point in the target area is higher than or equal to the evaluation threshold of the toxic metabolite content of the sewage detection point in the target area, the sewage detection point is marked as a high-pollution detection point. If the evaluation parameter of the toxic metabolite content of a sewage detection point in the target area is lower than the evaluation threshold of the toxic metabolite content of the sewage detection point in the target area, the sewage detection point is marked as a low-pollution detection point.

[0095] Count the high-pollution detection points in each target area and notify the preset personnel for early warning feedback.

[0096] For example, if there is only a single high-pollution detection point in the target area, the specific early warning feedback process is: U1. First, the accuracy of the monitoring data should be confirmed to ensure that the data comes from reliable monitoring equipment and detection methods. If necessary, data review or re-testing can be carried out.

[0097] U2. Analyze the causes: Analyze the possible causes of high concentrations based on local pollution sources, water quality background, meteorological conditions and other factors. Determine whether there are any illegal discharges or excessive discharges.

[0098] U3. Timely reporting: The monitoring results and preliminary analysis of the reasons shall be reported to the local environmental protection department or relevant regulatory agencies in a timely manner. The report shall include the monitoring data, the degree of exceeding the standard, the possible reasons and the recommended response measures.

[0099] U4. Assist in investigation: Cooperate with environmental protection departments or relevant regulatory agencies to conduct on-site investigations and provide necessary monitoring data and information. If necessary, assist in tracing and investigating pollution sources.

[0100] For example, if there are multiple high-pollution detection points in the target area, the specific early warning feedback process is as follows: V1. Conduct a comprehensive assessment to determine whether there is a regional pollution problem. The assessment should include aspects such as the degree of pollution, scope of impact, and potential hazards.

[0101] V2. Emergency Report: Report the comprehensive assessment results to the higher-level environmental protection department or relevant regulatory agency in a timely manner, and recommend the activation of the emergency response mechanism. The report should emphasize the urgency and severity of the problem, as well as the recommended emergency measures.

[0102] V3. Strengthen monitoring: Increase the monitoring frequency and monitoring points in the affected area to obtain more comprehensive and accurate monitoring data to monitor water quality changes in real time and promptly detect and report new pollution situations.

[0103] V4. Collaborative response: Communicate and coordinate with local environmental protection departments, other relevant departments and affected enterprises and institutions to jointly formulate response measures.

[0104] V5. Public notification: Under the premise of ensuring information security, inform the public of pollution conditions and response measures through media, announcements, etc. Encourage the public to participate in environmental protection and raise environmental awareness.

[0105] V6. Follow-up: Follow up and evaluate the effectiveness of the implementation of the response measures, and adjust the response measures according to the evaluation results until the pollution problem is effectively resolved.

[0106] It should be explained that this embodiment can guide the rational planning of sewage treatment facilities, improve sewage treatment efficiency, and reduce operating costs by accurately identifying high-pollution areas and conducting risk warnings and treatments. At the same time, it can promote regional sustainable development through scientific management of sewage and toxic substances.

[0107] Specifically, a comprehensive analysis is performed to obtain a detection effect evaluation index for each sewage detection point in each target area. The specific process is as follows: the sewage detection historical data of each sewage detection point in each target area includes: the concentrations of various toxic metabolites at each sewage detection point within each preset monitoring period.

[0108] Based on the historical data of sewage detection at each sewage detection point in each target area, the evaluation parameters of toxic metabolites at each sewage detection point in each target area for each preset monitoring period are processed.

[0109] Based on the toxic metabolite assessment parameters of each sewage detection point in each target area in each preset monitoring period and the equipment operation abnormality risk assessment value of each sewage detection point in each target area, a comprehensive analysis is conducted to obtain the detection effect evaluation index of each sewage detection point in each target area. The detection effect evaluation index of each sewage detection point in each target area is used to quantitatively evaluate the sewage toxicity detection effect of each sewage detection point in each target area, so as to provide a basis for judging whether the early warning is incorrect.

[0110] In a specific embodiment, the numerical expression of the detection effect evaluation index of each sewage detection point in each target area is:

[0111] ;

[0112] In the formula, It represents the detection effect evaluation index of the sth sewage detection point in the nth target area. represents the evaluation parameter of toxic metabolites at the sth sewage detection point in the nth target area in the fth preset monitoring cycle, where f represents the number of each preset monitoring cycle, , j represents the total number of preset monitoring cycles, represents the risk assessment value of equipment operation abnormality at the sth sewage detection point in the nth target area, It indicates the detection effect correction factor corresponding to the evaluation parameter of toxic metabolites at the preset sewage detection point. It represents the detection effect correction factor corresponding to the risk assessment value of equipment operation abnormality at the sewage detection point.

[0113] It needs to be explained that when the difference between the toxic metabolite assessment parameters of the sewage detection point in the preset monitoring period and the average value is smaller, and the equipment operation abnormality risk assessment value of the sewage detection point is also smaller, the corresponding sewage detection point detection effect evaluation index is larger, indicating that the sewage toxicity detection effect of the sewage detection point is better.

[0114] It should be explained that in this embodiment It indicates the detection effect correction factor corresponding to the evaluation parameter of toxic metabolites at the preset sewage detection point. The detection effect correction factors corresponding to the equipment operation abnormality risk assessment values ​​of the sewage detection points are represented. The values ​​of these correction factors respectively represent the influence of the toxic metabolite assessment parameters of the sewage detection points and the equipment operation abnormality risk assessment values ​​of the sewage detection points on the sewage detection effect. When used, these correction factors can be directly obtained from the regional sewage detection system database. The values ​​of these correction factors are preset in the regional sewage detection system database. The toxic metabolite assessment parameters of the sewage detection points and the equipment operation abnormality risk assessment values ​​of the sewage detection points form a mapping set with the correction factors preset in the regional sewage detection system database. For example, the real-time toxic metabolite assessment parameters of the sewage detection points and the equipment operation abnormality risk assessment values ​​of the sewage detection points are input into the mapping set to obtain the corresponding detection effect correction factors. The mapping relationship can be one-to-one or many-to-one. The value range of these correction factors is between 0 and 1, indicating the degree from no influence to maximum influence.

[0115] It should be explained that this embodiment can improve the detection accuracy by comprehensively analyzing the evaluation parameters of toxic metabolites and abnormal equipment operation. Through accurate evaluation, the reasons for poor detection results can be found, and measures can be taken to improve the detection accuracy. According to the evaluation results, the detection equipment can be maintained and upgraded in a targeted manner to improve the detection efficiency. It is also possible to promptly detect abnormal equipment operation and excessive toxic metabolites, and provide early warnings for environmental protection departments and enterprises. The evaluation of sewage detection points will help strengthen the supervision of toxic metabolites, thereby improving environmental quality. The evaluation results can also serve as a basis for corporate management decision-making, which is conducive to improving the level of environmental management.

[0116] In a specific embodiment, the regional sewage detection system database is used to store relevant data in the process of regional sewage detection, including: the average altitude of the sewage detection area, the average terrain slope, the number of critical residential areas, the population density of critical residential areas, the operating time of critical equipment, the number of critical equipment failures, the data transmission rate of critical equipment and the response time of critical equipment, as well as the data extracted from the regional sewage detection system database in the above embodiments. The various indicator data of sewage samples can be collected in real time or regularly through automatic monitoring instruments installed at each sewage detection point, such as water quality analysis instruments, flow meters, sensors, etc., and then the monitoring data can be transmitted to the database using wireless communication technology (such as GPRS, 3G / 4G / 5G, Wi-Fi, satellite communication, etc.).

[0117] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or do not exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. A sewage detection data aggregation and analysis early warning method, characterized in that: include: S1. Divide the sewage detection area into regions, mark them into target regions, obtain basic data of each target region, obtain environmental characteristic values ​​of each target region after processing, and deploy sewage detection points according to the environmental characteristic values ​​of each target region, marking them as sewage detection points in each target region; S2. Obtain reference indicators for evaluating the content of toxic metabolites at sewage detection points in each target area based on matching of environmental characteristic values ​​of each target area; S3. Obtaining sewage detection data of each sewage detection point in each target area and equipment operation data of each sewage detection point in each target area; S4. According to the environmental characteristic values ​​of each target area and the equipment operation data of each sewage detection point in each target area, the equipment operation abnormality risk assessment value of each sewage detection point in each target area is processed, and the toxic metabolite content assessment reference index of each sewage detection point in each target area is corrected according to the equipment operation abnormality risk assessment value of each sewage detection point in each target area, so as to obtain the toxic metabolite content assessment threshold of each sewage detection point in each target area; S5. According to the sewage detection data of each sewage detection point in each target area, the evaluation parameters of toxic metabolites at each sewage detection point in each target area are processed, and according to the evaluation threshold of the toxic metabolites content at each sewage detection point in each target area and the evaluation parameters of toxic metabolites at each sewage detection point in each target area, each target area is evaluated and warned, and the sewage detection historical data of each sewage detection point in each target area is obtained. According to the equipment operation abnormality risk assessment value of each sewage detection point in each target area, the detection effect evaluation index of each sewage detection point in each target area is obtained through comprehensive analysis, and feedback is given on the warning effect; The basic data of each target area include: the altitude and terrain slope of each environmental monitoring point, the number of residential areas in each target area, and the population density of each residential area in each target area; The average altitude, average terrain slope, number of critical residential areas and population density of critical residential areas in the sewage detection area were extracted from the regional sewage detection system database; According to the basic data of each target area, the environmental characteristic values ​​of each target area are processed to obtain the environmental characteristic values ​​of each target area, which are used to quantitatively evaluate the influence of the basic environmental characteristics of each target area on the regional sewage collection and the metabolism of toxic substances in the sewage, and provide a basis for matching the reference indicators for the evaluation of the content of toxic metabolites in the sewage detection points of each target area; The specific numerical expressions of the environmental characteristic values ​​of each target area are as follows: In the formula, τ n represents the environmental characteristic value of the nth target area, n represents the number of each target area, n = 1, 2, 3, ..., m, m represents the total number of target areas, HB ni represents the altitude of the ith environmental monitoring point in the nth target area, i represents the number of each environmental monitoring point, i=1, 2, 3, ..., h, h represents the total number of environmental monitoring points, PD ni represents the terrain slope of the ith environmental monitoring point in the nth target area, JM n represents the number of residential areas in the nth target area, JL nq represents the population density of the qth residential area in the nth target area, q represents the number of each residential area, q = 1, 2, 3, ..., p, p represents the total number of residential areas, Indicates the average altitude of the sewage detection area, represents the average terrain slope of the sewage detection area, represents the number of critical residential areas, Represents the critical residential area population density.

2. A sewage detection data aggregation and analysis early warning method according to claim 1, characterized in that: The sewage detection points are deployed according to the environmental characteristic values ​​of each target area and marked as sewage detection points in each target area. The specific process is as follows: Extracting the first threshold and the second threshold of regional environmental characteristics from the regional sewage detection system database, comparing the environmental characteristic value of each target area with the first threshold and the second threshold of regional environmental characteristics, and marking the target area as a high-pollution area if the environmental characteristic value of the target area is higher than or equal to the first threshold of regional environmental characteristics; If the target area environmental characteristic value is higher than the second threshold of the regional environmental characteristic and lower than the first threshold, the target area is marked as a medium pollution area; If the target area environmental characteristic value is lower than or equal to the second threshold of the regional environmental characteristic, the target area is marked as a low pollution area; Corresponding sewage detection points are deployed in high, medium and low pollution areas respectively, and marked as sewage detection points in each target area.

3. The sewage detection data aggregation and analysis early warning method according to claim 1 is characterized by: The matching obtains the reference index for evaluating the content of toxic metabolites at the sewage detection points in each target area. The specific matching process is as follows: Extracting from the regional sewage detection system database, a mapping set between the environmental characteristic values ​​of each target area and the reference indicators for evaluating the content of toxic metabolites at each target area sewage detection point is obtained; Input the real-time environmental characteristic values ​​of the target area, and obtain the corresponding reference indicators for evaluating the content of toxic metabolites in the sewage detection points according to the mapping set.

4. The sewage detection data aggregation and analysis early warning method according to claim 1 is characterized by: The processing obtains the equipment operation abnormality risk assessment value of each sewage detection point in each target area, and the specific process is as follows: The equipment operation data of each sewage detection point in each target area includes: each operation time of the equipment within a preset monitoring period, the number of equipment failures, the data transmission rate of the equipment and the response time of the equipment; The critical equipment operation time, critical equipment failure times, critical equipment data transmission rate and critical equipment response time are extracted from the regional sewage detection system database; Based on the environmental characteristic values ​​of each target area and the equipment operation data of each sewage detection point in each target area, comprehensive processing is performed to obtain the equipment operation abnormality risk assessment value of each sewage detection point in each target area.

5. A sewage detection data aggregation and analysis early warning method according to claim 4, characterized in that: The toxic metabolite content assessment reference index of each target area sewage detection point is corrected according to the equipment operation abnormality risk assessment value of each sewage detection point in each target area to obtain the toxic metabolite content assessment threshold of each sewage detection point in each target area. The specific process is as follows: According to the risk assessment value of equipment operation abnormality at each sewage detection point in each target area, the correction value of the content of toxic metabolites at each sewage detection point in each target area is matched from the regional sewage detection system database; The reference index for evaluating the content of toxic metabolites at sewage testing points in each target area is summed with the correction value of the content of toxic metabolites at each sewage testing point in each target area to obtain the evaluation threshold of the content of toxic metabolites at each sewage testing point in each target area.

6. The sewage detection data aggregation and analysis early warning method according to claim 1 is characterized by: The processing obtains the evaluation parameters of toxic metabolites at each sewage detection point in each target area, and the specific process is as follows: The sewage detection data of each sewage detection point in each target area includes: the concentration of various toxic metabolites at each sewage detection point within a preset monitoring period; The critical concentrations of various toxic metabolites were extracted from the regional sewage detection system database; According to the sewage detection data of each sewage detection point in each target area, the toxic metabolite assessment parameters of each sewage detection point in each target area are processed. The toxic metabolite assessment parameters of each sewage detection point in each target area are used to quantitatively evaluate the content of toxic metabolites in each sewage detection point in each target area, so as to provide a basis for risk warning for the target area.

7. A sewage detection data aggregation and analysis early warning method according to claim 6, characterized in that: According to the evaluation threshold of the toxic metabolite content of each sewage detection point in each target area and the evaluation parameter of the toxic metabolite of each sewage detection point in each target area, each target area is evaluated and warned. The specific process is as follows: The toxic metabolite content assessment threshold of each sewage detection point in each target area is compared with the toxic metabolite assessment parameter of each sewage detection point in each target area. If the toxic metabolite assessment parameter of a sewage detection point in the target area is higher than or equal to the toxic metabolite content assessment threshold of the sewage detection point in the target area, the sewage detection point is marked as a high-pollution detection point. If the toxic metabolite assessment parameter of a sewage detection point in the target area is lower than the toxic metabolite content assessment threshold of the sewage detection point in the target area, the sewage detection point is marked as a low-pollution detection point. Statistics of high-pollution detection points in each target area are collected for early warning.

8. The sewage detection data aggregation and analysis early warning method according to claim 4 is characterized by: The equipment operation abnormality risk assessment value of each sewage detection point in each target area is a quantitative assessment data obtained by comprehensively analyzing the equipment's operation time, the number of equipment failures, the equipment's data transmission rate and the equipment's response time. It is used to quantitatively assess the risk level of equipment operation abnormality at each sewage detection point in each target area, and provide a basis for risk warning for the target area.

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