Wastewater detection and monitoring treatment method, system and medium based on big data

Abstract

The present application provides a wastewater detection and monitoring processing method, system and medium based on big data, which belongs to the field of wastewater detection and big data technology. The method includes: obtaining water quality monitoring information and extracting detection reagent raw material information and wastewater sampling detection information, respectively extracting and processing data, obtaining the physical indicator turbidity index, chemical indicator solubility index and biological indicator diversity index, further processing to obtain the wastewater pollution index, correcting the wastewater pollution index according to the average index of wastewater pollution in multiple time periods in a preset area, obtaining the wastewater pollution correction index, and finally comparing it with the local water quality monitoring index to determine the degree of impact of wastewater on local water quality and obtain the wastewater pollution level. This application conducts a multi-dimensional comprehensive evaluation of the degree of wastewater pollution through the physical, chemical, and biological indicators of water quality in preset areas and time periods and the corresponding reagent raw material quality, improves the accuracy and efficiency of wastewater detection, and clarifies the degree of pollution.

Description

Technical Field

[0001] The present application relates to the field of wastewater detection and big data technology, and more specifically, to a wastewater detection and monitoring processing method, system and medium based on big data. Background Art

[0002] Traditional wastewater testing technologies generally have discrete testing ranges and testing periods, which cannot form a continuous data sequence. The testing items are often relatively simple, and no comprehensive and systematic testing results are formed. Moreover, there is no good correlation between the testing items, which can not only reflect the overall degree of wastewater pollution, but also cannot accurately reflect the impact of wastewater on local water quality.

[0003] At present, there are many deficiencies in the multi-dimensional and accurate detection of wastewater pollution levels and the assessment of its impact based on local water quality. There is a lack of a comprehensive and multi-dimensional wastewater detection and monitoring method to achieve scientific and accurate wastewater pollution detection and provide more accurate and comprehensive technical support for wastewater treatment.

[0004] In view of the above problems, effective technical solutions are currently awaited. Summary of the invention

[0005] The purpose of this application is to provide a wastewater detection and monitoring treatment method, system and medium based on big data. It can obtain water quality monitoring information and extract detection reagent raw material information and wastewater sampling detection information. After data extraction and processing, the physical indicator turbidity index, chemical indicator solubility index and biological indicator diversity index are obtained. The wastewater pollution index is further processed to obtain the wastewater pollution index. The wastewater pollution index is corrected according to the average wastewater pollution index of multiple time periods in a preset area to obtain the wastewater pollution correction index. Finally, it is compared with the local water quality monitoring index to determine the degree of impact of wastewater on local water quality and obtain the wastewater pollution level. This application conducts a multi-dimensional comprehensive evaluation of the degree of wastewater pollution through the physical, chemical, and biological indicators of water quality in preset areas and time periods and the corresponding reagent raw material quality, improves the accuracy and efficiency of wastewater detection, and clarifies the degree of pollution.

[0006] The present application provides a wastewater detection and monitoring treatment method based on big data, which is characterized by comprising the following steps:

[0007] Obtain multiple wastewater quality monitoring information for multiple time periods in a preset area, extract detection reagent raw material information and wastewater sampling detection information;

[0008] Processing the raw material information of the detection reagent through a preset raw material quality evaluation model to obtain a raw material quality stability index;

[0009] Extracting physical indicator detection data, chemical indicator detection data and biological indicator detection data according to the wastewater sampling detection information;

[0010] Processing the physical indicator detection data to obtain a physical indicator turbidity index;

[0011] Processing the chemical indicator detection data and the raw material quality stability index to obtain a chemical indicator solubility index;

[0012] Processing the biological indicator detection data and the raw material quality stability index to obtain a biological indicator diversity index;

[0013] Processing is performed according to the physical indicator turbidity index, the chemical indicator solubility index and the biological indicator diversity index to obtain a wastewater pollution index;

[0014] Obtaining an average wastewater pollution index corresponding to a plurality of wastewater quality monitoring information in a plurality of time periods in the preset area, and correcting the wastewater pollution index according to the average wastewater pollution index to obtain a wastewater pollution correction index;

[0015] The wastewater pollution correction index is compared with the local water quality monitoring index of the preset area to determine the impact of the wastewater on the local water quality and obtain the wastewater pollution level.

[0016] Among them, in the wastewater detection and monitoring treatment method based on big data described in the present application, it is characterized in that the raw material information of the detection reagent is processed through a preset raw material quality evaluation model to obtain a raw material quality stability index, specifically:

[0017] Extracting detection reagent raw material data according to the detection reagent raw material information, including intra-batch quality difference data, inter-batch quality difference data, physical form integrity data and chemical property purity data;

[0018] The raw material quality stability index is obtained by processing the intra-batch quality difference data, the inter-batch quality difference data, the physical form integrity data and the chemical property purity data through a preset raw material quality evaluation model.

[0019] Among them, in the wastewater detection and monitoring treatment method based on big data described in the present application, it is characterized in that the physical indicator turbidity index is obtained by processing the physical indicator detection data, specifically:

[0020] Extracting transmittance data and suspended particle concentration data according to the physical indicator detection data;

[0021] The transmittance data and the suspended particle concentration data are processed by a preset water quality physical index evaluation model to obtain a physical index turbidity index.

[0022] Among them, in the wastewater detection and monitoring treatment method based on big data described in the present application, it is characterized in that the chemical indicator solubility index is obtained by processing the chemical indicator detection data and the raw material quality stability index, specifically:

[0023] Extracting pH data, oxygen content data and heavy metal content data according to the chemical indicator detection data;

[0024] The pH data, oxygen content data and heavy metal content data are combined with the raw material quality stability index and processed through a preset water quality chemical index evaluation model to obtain a chemical index solubility index.

[0025] Among them, in the wastewater detection and monitoring treatment method based on big data described in the present application, it is characterized in that the biological indicator detection data and the raw material quality stability index are processed to obtain the biological indicator diversity index, which is specifically:

[0026] Extracting total bacteria percentage data, coliform group content data and biological toxicity detection data based on the biological indicator detection data;

[0027] The biological indicator diversity index is obtained by processing the total bacteria proportion data, the coliform group content data and the biological toxicity detection data in combination with the raw material quality stability index.

[0028] Among them, in the wastewater detection and monitoring treatment method based on big data described in the present application, it is characterized in that the wastewater pollution index is obtained by processing according to the physical indicator turbidity index, the chemical indicator solubility index and the biological indicator diversity index, specifically:

[0029] The wastewater pollution index is obtained by processing the physical indicator turbidity index, the chemical indicator solubility index and the biological indicator diversity index through a preset water quality pollution evaluation model.

[0030] Among them, in the wastewater detection and monitoring processing method based on big data described in the present application, it is characterized in that the wastewater pollution degree average index corresponding to the multiple wastewater quality monitoring information of the preset area in multiple time periods is obtained, and the wastewater pollution degree index is corrected according to the wastewater pollution degree average index to obtain the wastewater pollution degree correction index, specifically:

[0031] Obtaining an average wastewater pollution index corresponding to a plurality of wastewater quality monitoring information in a plurality of time periods in the preset area;

[0032] According to the wastewater pollution degree average index, the wastewater pollution degree index is corrected by a wastewater pollution degree correction model to obtain a wastewater pollution degree correction index;

[0033] The calculation formula of the wastewater pollution correction model is:

[0034] ;

[0035] in, is the wastewater pollution correction index, is the average index of wastewater pollution, is the wastewater pollution index, is the preset characteristic coefficient.

[0036] Among them, in the wastewater detection and monitoring treatment method based on big data described in the present application, it is characterized in that the wastewater pollution correction index is compared with the local water quality monitoring index of the preset area to determine the degree of impact of the wastewater on the local water quality and obtain the wastewater pollution level, specifically:

[0037] Comparing the wastewater pollution correction index with the local water quality monitoring index of the preset area to obtain an index deviation rate;

[0038] Comparing the exponential deviation rate with a preset first deviation rate threshold and a preset second deviation rate threshold, the first deviation rate threshold being less than the second deviation rate threshold;

[0039] If the index deviation rate is less than the first deviation rate threshold, the wastewater pollution level does not exceed the standard;

[0040] If the index deviation rate is greater than or equal to the first deviation rate threshold and less than the second deviation rate threshold, the wastewater light pollution level is obtained;

[0041] If the index deviation rate is greater than or equal to the second deviation rate threshold, the wastewater severe pollution level is obtained.

[0042] In a second aspect, the present application provides a wastewater detection and monitoring processing system based on big data, the system comprising: a memory and a processor, the memory comprising a program of a wastewater detection and monitoring processing method based on big data, the program of the wastewater detection and monitoring processing method based on big data being executed by the processor to implement the following steps:

[0043] Obtain multiple wastewater quality monitoring information for multiple time periods in a preset area, extract detection reagent raw material information and wastewater sampling detection information;

[0044] Processing the raw material information of the detection reagent through a preset raw material quality evaluation model to obtain a raw material quality stability index;

[0045] Extracting physical indicator detection data, chemical indicator detection data and biological indicator detection data according to the wastewater sampling detection information;

[0046] Processing the physical indicator detection data to obtain a physical indicator turbidity index;

[0047] Processing the chemical indicator detection data and the raw material quality stability index to obtain a chemical indicator solubility index;

[0048] Processing the biological indicator detection data and the raw material quality stability index to obtain a biological indicator diversity index;

[0049] Processing is performed according to the physical indicator turbidity index, the chemical indicator solubility index and the biological indicator diversity index to obtain a wastewater pollution index;

[0050] Obtaining an average wastewater pollution index corresponding to a plurality of wastewater quality monitoring information in a plurality of time periods in the preset area, and correcting the wastewater pollution index according to the average wastewater pollution index to obtain a wastewater pollution correction index;

[0051] The wastewater pollution correction index is compared with the local water quality monitoring index of the preset area to determine the impact of the wastewater on the local water quality and obtain the wastewater pollution level.

[0052] In the third aspect, the present application also provides a computer-readable storage medium, which includes a wastewater detection and monitoring processing method program based on big data. When the wastewater detection and monitoring processing method program based on big data is executed by a processor, the steps of the wastewater detection and monitoring processing method based on big data as described in any one of the above items are implemented.

[0053] As can be seen from the above, the wastewater detection and monitoring processing method, system and medium based on big data provided in the embodiment of the present application obtain multiple wastewater quality monitoring information of multiple time periods in a preset area, extract detection reagent raw material information and wastewater sampling detection information, and process the detection reagent raw material information through a preset raw material quality evaluation model to obtain a raw material quality stability index, extract physical indicator detection data, chemical indicator detection data and biological indicator detection data according to the wastewater sampling detection information, and obtain the physical indicator turbidity index, chemical indicator solubility index and biological indicator diversity index after processing respectively, and then process them through a preset water quality pollution evaluation model to obtain a wastewater pollution index, obtain the wastewater pollution degree average index corresponding to multiple wastewater quality monitoring information in multiple time periods in a preset area, correct the wastewater pollution degree index according to the wastewater pollution degree average index, and obtain a wastewater pollution degree correction index, compare the wastewater pollution degree correction index with the local water quality monitoring index of the preset area, judge the degree of influence of the wastewater on the local water quality and obtain the wastewater pollution level. This application not only considers the monitoring data of the three dimensions of physical, chemical and biological wastewater quality, but also ensures the quality stability of the raw materials of the detection reagents in advance, and then conducts a comprehensive evaluation of the wastewater pollution degree, thereby realizing a comprehensive and multi-angle evaluation of the wastewater quality. This multi-dimensional monitoring can more comprehensively reflect the pollution status of the wastewater and improve the accuracy and reliability of the evaluation. By obtaining multiple wastewater quality monitoring information of multiple time periods in a preset area, calculating the average index of wastewater pollution, correcting the wastewater pollution index, and obtaining the wastewater pollution correction index, this dynamic monitoring and correction mechanism can more accurately reflect the changing trend of wastewater pollution and improve the timeliness and accuracy of the evaluation. This application combines scientific theory and practical application needs, taking into account the complexity of wastewater quality and focusing on the practicality and operability of the evaluation results. By constructing a series of specific indicators and indexes, the evaluation results are more intuitive, easy to understand and apply.

[0054] Other features and advantages of the present application will be described in the following description, and partly become apparent from the description, or understood by practicing the embodiments of the present application. The purpose and other advantages of the present application can be realized and obtained by the structures specifically pointed out in the written description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0056] Figure 1A flowchart of a wastewater detection and monitoring method based on big data provided in an embodiment of the present application;

[0057] Figure 2 A flow chart of obtaining a raw material quality stability index for a wastewater detection and monitoring treatment method based on big data provided in an embodiment of the present application;

[0058] Figure 3 A flow chart of obtaining the physical indicator turbidity index of the wastewater detection and monitoring treatment method based on big data provided in an embodiment of the present application;

[0059] Figure 4 A flow chart of obtaining the solubility index of chemical indicators in the wastewater detection and monitoring treatment method based on big data provided in an embodiment of the present application;

[0060] Figure 5 A flow chart of obtaining a biological indicator diversity index for a wastewater detection and monitoring treatment method based on big data provided in an embodiment of the present application. DETAILED DESCRIPTION

[0061] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0062] It should be noted that similar numbers and letters represent similar items in the following figures, so once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance. It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data need to comply with relevant laws, regulations and standards of relevant countries and regions.

[0063] Please refer to Figure 1 , Figure 1The following is a flowchart of a wastewater detection and monitoring processing method based on big data in some embodiments of the present application. The wastewater detection and monitoring processing method based on big data is used in terminal devices, such as computers, mobile terminals, etc. The wastewater detection and monitoring processing method based on big data includes the following steps:

[0064] S101, obtaining multiple wastewater quality monitoring information of multiple time periods in a preset area, extracting detection reagent raw material information and wastewater sampling detection information;

[0065] S102, processing the detection reagent raw material information through a preset raw material quality evaluation model to obtain a raw material quality stability index;

[0066] S103, extracting physical indicator detection data, chemical indicator detection data and biological indicator detection data according to the wastewater sampling detection information;

[0067] S104, processing the physical indicator detection data to obtain a physical indicator turbidity index;

[0068] S105, processing the chemical indicator detection data and the raw material quality stability index to obtain a chemical indicator solubility index;

[0069] S106, processing the biological indicator detection data and the raw material quality stability index to obtain a biological indicator diversity index;

[0070] S107, performing processing according to the physical indicator turbidity index, the chemical indicator solubility index and the biological indicator diversity index to obtain a wastewater pollution index;

[0071] S108, obtaining an average wastewater pollution index corresponding to a plurality of wastewater quality monitoring information in a plurality of time periods in the preset area, and correcting the wastewater pollution index according to the average wastewater pollution index to obtain a wastewater pollution correction index;

[0072] S109: Compare the wastewater pollution correction index with the local water quality monitoring index of the preset area to determine the impact of the wastewater on the local water quality and obtain the wastewater pollution level.

[0073] Among them, the present application obtains multiple wastewater quality monitoring information of multiple time periods in a preset area, extracts detection reagent raw material information and wastewater sampling detection information, processes the detection reagent raw material information through a preset raw material quality evaluation model, and obtains a raw material quality stability index, extracts physical indicator detection data, chemical indicator detection data and biological indicator detection data according to the wastewater sampling detection information, and obtains a physical indicator turbidity index, a chemical indicator solubility index and a biological indicator diversity index after processing respectively, and then processes them through a preset water quality pollution evaluation model to obtain a wastewater pollution index, obtains the average wastewater pollution index corresponding to multiple wastewater quality monitoring information of multiple time periods in the preset area, corrects the wastewater pollution index according to the average wastewater pollution index, and obtains a wastewater pollution correction index, compares the wastewater pollution correction index with the local water quality monitoring index of the preset area, judges the degree of influence of the wastewater on the local water quality and obtains the wastewater pollution level. This application not only considers the monitoring data of the three dimensions of physical, chemical and biological wastewater quality, but also ensures the quality stability of the raw materials of the detection reagents in advance, and then conducts a comprehensive evaluation of the wastewater pollution degree, thereby realizing a comprehensive and multi-angle evaluation of the wastewater quality. This multi-dimensional monitoring can more comprehensively reflect the pollution status of the wastewater and improve the accuracy and reliability of the evaluation. By obtaining multiple wastewater quality monitoring information of multiple time periods in a preset area, calculating the average index of wastewater pollution, correcting the wastewater pollution index, and obtaining the wastewater pollution correction index, this dynamic monitoring and correction mechanism can more accurately reflect the changing trend of wastewater pollution and improve the timeliness and accuracy of the evaluation. This application combines scientific theory and practical application needs, taking into account the complexity of wastewater quality and focusing on the practicality and operability of the evaluation results. By constructing a series of specific indicators and indexes, the evaluation results are more intuitive, easy to understand and apply.

[0074] Please refer to Figure 2 , Figure 2 It is a flow chart of obtaining the raw material quality stability index of the wastewater detection and monitoring treatment method based on big data in some embodiments of the present application. According to an embodiment of the present invention, the raw material information of the detection reagent is processed through a preset raw material quality evaluation model to obtain the raw material quality stability index, specifically:

[0075] S201, extracting detection reagent raw material data according to the detection reagent raw material information, including intra-batch quality difference data, inter-batch quality difference data, physical form integrity data and chemical property purity data;

[0076] S202, processing the intra-batch quality difference data, inter-batch quality difference data, physical form integrity data and chemical property purity data through a preset raw material quality evaluation model to obtain a raw material quality stability index.

[0077] Among them, in order to grasp the quality of water quality testing reagents, testing reagent raw material data are extracted according to the testing reagent raw material information, including intra-batch quality difference data, inter-batch quality difference data, physical form integrity data and chemical property purity data. The intra-batch quality difference data reflects the quality difference between different testing reagent raw materials in the same batch, the inter-batch quality difference data reflects the quality difference between different batches of testing reagent raw materials, the physical form integrity data describes whether the physical form of the testing reagent raw materials is complete, and the chemical property purity data reflects the purity of the target compound in the testing reagent raw materials. High-purity reagents can reduce interference in the analysis process and improve the accuracy of monitoring results. The intra-batch quality difference data, inter-batch quality difference data, physical form integrity data and chemical property purity data are processed through a preset raw material quality evaluation model to obtain a raw material quality stability index;

[0078] The calculation formula of the raw material quality evaluation model is:

[0079] ;

[0080] in, is the raw material quality stability index, They are intra-batch quality variability data, inter-batch quality variability data, physical form integrity data and chemical property purity data. It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset water quality monitoring database).

[0081] Please refer to Figure 3 , Figure 3 The flowchart of obtaining the physical indicator turbidity index of the wastewater detection and monitoring treatment method based on big data in some embodiments of the present application. According to an embodiment of the present invention, the physical indicator turbidity index is obtained by processing the physical indicator detection data, specifically:

[0082] S301, extracting transmittance data and suspended particle concentration data according to the physical indicator detection data;

[0083] S302: Process the transmittance data and the suspended particle concentration data through a preset water quality physical index evaluation model to obtain a physical index turbidity index.

[0084] Among them, in order to grasp the physical indicators of water quality and turbidity, the transmittance data and suspended particle concentration data are extracted according to the physical indicator detection data. The transmittance data indicates the proportion of light remaining after being absorbed or scattered after passing through the water body. The suspended particle concentration data can be expressed in the number of particles per liter or mass concentration. These parameters can be obtained through professional equipment, such as optical sensors. According to the transmittance data and suspended particle concentration data, they are processed through the preset water quality physical indicator evaluation model to obtain the physical indicator turbidity index;

[0085] The calculation formula of the water quality physical index evaluation model is:

[0086] ;

[0087] in, It is the physical index turbidity index. is the transmittance data, is the suspended particle concentration data, It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset water quality monitoring database).

[0088] Please refer to Figure 4 , Figure 4 The flowchart of obtaining the chemical indicator solubility index of the wastewater detection and monitoring treatment method based on big data in some embodiments of the present application. According to an embodiment of the present invention, the chemical indicator detection data and the raw material quality stability index are processed to obtain the chemical indicator solubility index, specifically:

[0089] S401, extracting pH data, oxygen content data and heavy metal content data according to the chemical indicator detection data;

[0090] S402, processing the pH data, oxygen content data and heavy metal content data in combination with the raw material quality stability index through a preset water quality chemical index evaluation model to obtain a chemical index solubility index.

[0091] Among them, in order to grasp the water quality chemical indicators and various data of the indicators, pH data, oxygen content data and heavy metal content data are extracted according to the chemical indicator detection data. The pH data is expressed by the negative logarithm of the hydrogen ion concentration in the water, the oxygen content data refers to the amount of oxygen dissolved in the water, and the heavy metal content data refers to the concentration of various heavy metal elements in the water. The pH data, oxygen content data and heavy metal content data are combined with the raw material quality stability index through a preset water quality chemical indicator evaluation model to obtain a chemical indicator solubility index;

[0092] The calculation formula of the water quality chemical index evaluation model is:

[0093] ;

[0094] in, is the chemical indicator solubility index, They are pH data, oxygen content data and heavy metal content data. is the raw material quality stability index, It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset water quality monitoring database).

[0095] Please refer to Figure 5 , Figure 5 The flowchart of obtaining the biological indicator diversity index of the wastewater detection and monitoring treatment method based on big data in some embodiments of the present application. According to an embodiment of the present invention, the biological indicator detection data and the raw material quality stability index are processed to obtain the biological indicator diversity index, specifically:

[0096] S501, extracting total bacteria percentage data, coliform group content data and biological toxicity detection data according to the biological indicator detection data;

[0097] S502. The total bacteria percentage data, the coliform group content data and the biological toxicity detection data are processed in combination with the raw material quality stability index to obtain a biological indicator diversity index.

[0098] Among them, in order to grasp the situation of water quality biological indicators, the total bacteria proportion data, coliform group content data and biological toxicity detection data are extracted according to the biological indicator detection data. The total bacteria proportion data refers to the relative proportion of the total number of colonies in the water, the coliform group content data refers to the number of coliform groups in the water, and the biological toxicity detection data refers to the content or intensity of biological toxic substances in the water sample. The total bacteria proportion data, coliform group content data and biological toxicity detection data are processed in combination with the raw material quality stability index to obtain the biological indicator diversity index;

[0099] The calculation formula of the biological indicator evaluation model is:

[0100] ;

[0101] in, is the biodiversity index, They are the total bacterial proportion data, coliform group content data and biological toxicity detection data. is the raw material quality stability index, It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset water quality monitoring database).

[0102] According to an embodiment of the present invention, the wastewater pollution index is obtained by processing the physical indicator turbidity index, the chemical indicator solubility index and the biological indicator diversity index, specifically:

[0103] The wastewater pollution index is obtained by processing the physical indicator turbidity index, the chemical indicator solubility index and the biological indicator diversity index through a preset water quality pollution evaluation model.

[0104] Among them, in order to grasp the pollution degree of wastewater and intuitively reflect the state of water quality, the wastewater pollution degree index is obtained by processing according to the physical indicator turbidity index, chemical indicator solubility index and biological indicator diversity index through the preset water quality pollution degree evaluation model. The physical indicator turbidity index refers to the degree to which suspended matter in the water hinders the transmission of light, reflecting the cleanliness of the water body, the chemical indicator solubility index reflects the self-purification ability of the water body, and the biological indicator diversity index represents the relationship between the number and species of mixed biological communities composed of various organisms, reflecting a comprehensive indicator of species richness and uniformity. The wastewater pollution degree index comprehensively reflects the degree of water pollution from three aspects: physical indicators, chemical indicators and biological indicators of water quality;

[0105] The calculation formula of the water pollution evaluation model is:

[0106] ;

[0107] in, is the wastewater pollution index, They are the physical indicator turbidity index, the chemical indicator solubility index and the biological indicator diversity index. It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset water quality monitoring database).

[0108] According to an embodiment of the present invention, the wastewater pollution degree average index corresponding to the multiple wastewater quality monitoring information in multiple time periods of the preset area is obtained, and the wastewater pollution degree index is corrected according to the wastewater pollution degree average index to obtain the wastewater pollution degree correction index, specifically:

[0109] Obtaining an average wastewater pollution index corresponding to a plurality of wastewater quality monitoring information in a plurality of time periods in the preset area;

[0110] According to the wastewater pollution degree average index, the wastewater pollution degree index is corrected by a wastewater pollution degree correction model to obtain a wastewater pollution degree correction index;

[0111] The calculation formula of the wastewater pollution correction model is:

[0112] ;

[0113] in, is the wastewater pollution correction index, is the average index of wastewater pollution, is the wastewater pollution index, It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset water quality monitoring database).

[0114] Among them, in order to further improve the accuracy of the wastewater pollution index, the average wastewater pollution index corresponding to multiple wastewater quality monitoring information in multiple time periods in a preset area is obtained, and the wastewater pollution index is corrected by a wastewater pollution correction model according to the average wastewater pollution index to obtain the wastewater pollution correction index.

[0115] According to an embodiment of the present invention, the wastewater pollution correction index is compared with the local water quality monitoring index of the preset area to determine the impact of wastewater on local water quality and obtain the wastewater pollution level, specifically:

[0116] Comparing the wastewater pollution correction index with the local water quality monitoring index of the preset area to obtain an index deviation rate;

[0117] Comparing the exponential deviation rate with a preset first deviation rate threshold and a preset second deviation rate threshold, the first deviation rate threshold being less than the second deviation rate threshold;

[0118] If the index deviation rate is less than the first deviation rate threshold, the wastewater pollution level does not exceed the standard;

[0119] If the index deviation rate is greater than or equal to the first deviation rate threshold and less than the second deviation rate threshold, the wastewater light pollution level is obtained;

[0120] If the index deviation rate is greater than or equal to the second deviation rate threshold, the wastewater severe pollution level is obtained.

[0121] Among them, in order to accurately reflect the degree of wastewater pollution and the degree of impact on the local water quality of the area, the wastewater pollution correction index is compared with the local water quality monitoring index of the preset area to obtain the index deviation rate. The local water quality monitoring index can be queried through a preset water quality monitoring database, and the index deviation rate is compared with a preset first deviation rate threshold and a preset second deviation rate threshold. The first deviation rate threshold is less than the second deviation rate threshold. If the index deviation rate is less than the first deviation rate threshold, the wastewater pollution degree does not exceed the standard. If the index deviation rate is greater than or equal to the first deviation rate threshold and less than the second deviation rate threshold, the wastewater light pollution level is obtained. If the index deviation rate is greater than or equal to the second deviation rate threshold, the wastewater heavy pollution level is obtained.

[0122] According to an embodiment of the present invention, after the raw material information of the detection reagent is processed by a preset raw material quality evaluation model to obtain the raw material quality stability index, the method further includes:

[0123] Comparing the raw material quality stability index with a preset stability index threshold to obtain a stability index deviation rate;

[0124] comparing the stability index deviation rate with a preset stability index deviation rate threshold;

[0125] If the stability index deviation rate is greater than or equal to the stability index deviation rate threshold, the raw material quality stability does not meet the requirements;

[0126] If the stability index deviation rate is less than the stability index deviation rate threshold, the raw material quality stability meets the requirements.

[0127] Among them, in order to improve the quality and stability of raw materials, the raw material quality stability index is compared with the preset stability index threshold to obtain the stability index deviation rate, and the stability index deviation rate is compared with the preset stability index deviation rate threshold. If the stability index deviation rate is greater than or equal to the stability index deviation rate threshold, the raw material quality stability does not meet the requirements; if the stability index deviation rate is less than the stability index deviation rate threshold, the raw material quality stability meets the requirements.

[0128] The present invention also discloses a wastewater detection and monitoring processing system based on big data, including a memory and a processor, wherein the memory includes a wastewater detection and monitoring processing method program based on big data, and when the wastewater detection and monitoring processing method program based on big data is executed by the processor, the following steps are implemented:

[0129] Obtain multiple wastewater quality monitoring information for multiple time periods in a preset area, extract detection reagent raw material information and wastewater sampling detection information;

[0130] Processing the raw material information of the detection reagent through a preset raw material quality evaluation model to obtain a raw material quality stability index;

[0131] Extracting physical indicator detection data, chemical indicator detection data and biological indicator detection data according to the wastewater sampling detection information;

[0132] Processing the physical indicator detection data to obtain a physical indicator turbidity index;

[0133] Processing the chemical indicator detection data and the raw material quality stability index to obtain a chemical indicator solubility index;

[0134] Processing the biological indicator detection data and the raw material quality stability index to obtain a biological indicator diversity index;

[0135] Processing is performed according to the physical indicator turbidity index, the chemical indicator solubility index and the biological indicator diversity index to obtain a wastewater pollution index;

[0136] Obtaining an average wastewater pollution index corresponding to a plurality of wastewater quality monitoring information in a plurality of time periods in the preset area, and correcting the wastewater pollution index according to the average wastewater pollution index to obtain a wastewater pollution correction index;

[0137] The wastewater pollution correction index is compared with the local water quality monitoring index of the preset area to determine the impact of the wastewater on the local water quality and obtain the wastewater pollution level.

[0138] Among them, the present application obtains multiple wastewater quality monitoring information of multiple time periods in a preset area, extracts detection reagent raw material information and wastewater sampling detection information, processes the detection reagent raw material information through a preset raw material quality evaluation model, and obtains a raw material quality stability index, extracts physical indicator detection data, chemical indicator detection data and biological indicator detection data according to the wastewater sampling detection information, and obtains a physical indicator turbidity index, a chemical indicator solubility index and a biological indicator diversity index after processing respectively, and then processes them through a preset water quality pollution evaluation model to obtain a wastewater pollution index, obtains the average wastewater pollution index corresponding to multiple wastewater quality monitoring information of multiple time periods in the preset area, corrects the wastewater pollution index according to the average wastewater pollution index, and obtains a wastewater pollution correction index, compares the wastewater pollution correction index with the local water quality monitoring index of the preset area, judges the degree of influence of the wastewater on the local water quality and obtains the wastewater pollution level. This application not only considers the monitoring data of the three dimensions of physical, chemical and biological wastewater quality, but also ensures the quality stability of the raw materials of the detection reagents in advance, and then conducts a comprehensive evaluation of the wastewater pollution degree, thereby realizing a comprehensive and multi-angle evaluation of the wastewater quality. This multi-dimensional monitoring can more comprehensively reflect the pollution status of the wastewater and improve the accuracy and reliability of the evaluation. By obtaining multiple wastewater quality monitoring information of multiple time periods in a preset area, calculating the average index of wastewater pollution, correcting the wastewater pollution index, and obtaining the wastewater pollution correction index, this dynamic monitoring and correction mechanism can more accurately reflect the changing trend of wastewater pollution and improve the timeliness and accuracy of the evaluation. This application combines scientific theory and practical application needs, taking into account the complexity of wastewater quality and focusing on the practicality and operability of the evaluation results. By constructing a series of specific indicators and indexes, the evaluation results are more intuitive, easy to understand and apply.

[0139] According to an embodiment of the present invention, the raw material information of the detection reagent is processed by a preset raw material quality evaluation model to obtain a raw material quality stability index, specifically:

[0140] Extracting detection reagent raw material data according to the detection reagent raw material information, including intra-batch quality difference data, inter-batch quality difference data, physical form integrity data and chemical property purity data;

[0141] The raw material quality stability index is obtained by processing the intra-batch quality difference data, the inter-batch quality difference data, the physical form integrity data and the chemical property purity data through a preset raw material quality evaluation model.

[0142] Among them, in order to grasp the quality of water quality testing reagents, testing reagent raw material data are extracted according to the testing reagent raw material information, including intra-batch quality difference data, inter-batch quality difference data, physical form integrity data and chemical property purity data. The intra-batch quality difference data reflects the quality difference between different testing reagent raw materials in the same batch, the inter-batch quality difference data reflects the quality difference between different batches of testing reagent raw materials, the physical form integrity data describes whether the physical form of the testing reagent raw materials is complete, and the chemical property purity data reflects the purity of the target compound in the testing reagent raw materials. High-purity reagents can reduce interference in the analysis process and improve the accuracy of monitoring results. The intra-batch quality difference data, inter-batch quality difference data, physical form integrity data and chemical property purity data are processed through a preset raw material quality evaluation model to obtain a raw material quality stability index;

[0143] The calculation formula of the raw material quality evaluation model is:

[0144] ;

[0145] in, is the raw material quality stability index, They are intra-batch quality variability data, inter-batch quality variability data, physical form integrity data and chemical property purity data. It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset water quality monitoring database).

[0146] According to an embodiment of the present invention, the physical indicator turbidity index is obtained by processing the physical indicator detection data, specifically:

[0147] Extracting transmittance data and suspended particle concentration data according to the physical indicator detection data;

[0148] The transmittance data and the suspended particle concentration data are processed by a preset water quality physical index evaluation model to obtain a physical index turbidity index.

[0149] Among them, in order to grasp the physical indicators of water quality and turbidity, the transmittance data and suspended particle concentration data are extracted according to the physical indicator detection data. The transmittance data indicates the proportion of light remaining after being absorbed or scattered after passing through the water body. The suspended particle concentration data can be expressed in the number of particles per liter or mass concentration. These parameters can be obtained through professional equipment, such as optical sensors. According to the transmittance data and suspended particle concentration data, they are processed through the preset water quality physical indicator evaluation model to obtain the physical indicator turbidity index;

[0150] The calculation formula of the water quality physical index evaluation model is:

[0151] ;

[0152] in, It is the physical index turbidity index. is the transmittance data, is the suspended particle concentration data, It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset water quality monitoring database).

[0153] According to an embodiment of the present invention, the chemical indicator solubility index is obtained by processing the chemical indicator detection data and the raw material quality stability index, specifically:

[0154] Extracting pH data, oxygen content data and heavy metal content data according to the chemical indicator detection data;

[0155] The pH data, oxygen content data and heavy metal content data are combined with the raw material quality stability index and processed through a preset water quality chemical index evaluation model to obtain a chemical index solubility index.

[0156] Among them, in order to grasp the water quality chemical indicators and various data of the indicators, pH data, oxygen content data and heavy metal content data are extracted according to the chemical indicator detection data. The pH data is expressed by the negative logarithm of the hydrogen ion concentration in the water, the oxygen content data refers to the amount of oxygen dissolved in the water, and the heavy metal content data refers to the concentration of various heavy metal elements in the water. The pH data, oxygen content data and heavy metal content data are combined with the raw material quality stability index through a preset water quality chemical indicator evaluation model to obtain a chemical indicator solubility index;

[0157] The calculation formula of the water quality chemical index evaluation model is:

[0158] ;

[0159] in, is the chemical indicator solubility index, They are pH data, oxygen content data and heavy metal content data. is the raw material quality stability index, It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset water quality monitoring database).

[0160] According to an embodiment of the present invention, the biological indicator detection data and the raw material quality stability index are processed to obtain the biological indicator diversity index, which is specifically:

[0161] Extracting total bacteria percentage data, coliform group content data and biological toxicity detection data based on the biological indicator detection data;

[0162] The biological indicator diversity index is obtained by processing the total bacteria proportion data, the coliform group content data and the biological toxicity detection data in combination with the raw material quality stability index.

[0163] Among them, in order to grasp the situation of water quality biological indicators, the total bacteria proportion data, coliform group content data and biological toxicity detection data are extracted according to the biological indicator detection data. The total bacteria proportion data refers to the relative proportion of the total number of colonies in the water, the coliform group content data refers to the number of coliform groups in the water, and the biological toxicity detection data refers to the content or intensity of biological toxic substances in the water sample. The total bacteria proportion data, coliform group content data and biological toxicity detection data are processed in combination with the raw material quality stability index to obtain the biological indicator diversity index;

[0164] The calculation formula of the biological indicator evaluation model is:

[0165] ;

[0166] in, is the biodiversity index, They are the total bacterial proportion data, coliform group content data and biological toxicity detection data. is the raw material quality stability index, It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset water quality monitoring database).

[0167] According to an embodiment of the present invention, the wastewater pollution index is obtained by processing the physical indicator turbidity index, the chemical indicator solubility index and the biological indicator diversity index, specifically:

[0168] The wastewater pollution index is obtained by processing the physical indicator turbidity index, the chemical indicator solubility index and the biological indicator diversity index through a preset water quality pollution evaluation model.

[0169] Among them, in order to grasp the pollution degree of wastewater and intuitively reflect the state of water quality, the wastewater pollution degree index is obtained by processing according to the physical indicator turbidity index, chemical indicator solubility index and biological indicator diversity index through the preset water quality pollution degree evaluation model. The physical indicator turbidity index refers to the degree to which suspended matter in the water hinders the transmission of light, reflecting the cleanliness of the water body, the chemical indicator solubility index reflects the self-purification ability of the water body, and the biological indicator diversity index represents the relationship between the number and species of mixed biological communities composed of various organisms, reflecting a comprehensive indicator of species richness and uniformity. The wastewater pollution degree index comprehensively reflects the degree of water pollution from three aspects: physical indicators, chemical indicators and biological indicators of water quality;

[0170] The calculation formula of the water pollution evaluation model is:

[0171] ;

[0172] in, is the wastewater pollution index, They are the physical indicator turbidity index, the chemical indicator solubility index and the biological indicator diversity index. It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset water quality monitoring database).

[0173] According to an embodiment of the present invention, the wastewater pollution degree average index corresponding to the multiple wastewater quality monitoring information in multiple time periods of the preset area is obtained, and the wastewater pollution degree index is corrected according to the wastewater pollution degree average index to obtain the wastewater pollution degree correction index, specifically:

[0174] Obtaining an average wastewater pollution index corresponding to a plurality of wastewater quality monitoring information in a plurality of time periods in the preset area;

[0175] According to the wastewater pollution degree average index, the wastewater pollution degree index is corrected by a wastewater pollution degree correction model to obtain a wastewater pollution degree correction index;

[0176] The calculation formula of the wastewater pollution correction model is:

[0177] ;

[0178] in, is the wastewater pollution correction index, is the average index of wastewater pollution, is the wastewater pollution index, It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset water quality monitoring database).

[0179] Among them, in order to further improve the accuracy of the wastewater pollution index, the average wastewater pollution index corresponding to multiple wastewater quality monitoring information in multiple time periods in a preset area is obtained, and the wastewater pollution index is corrected by a wastewater pollution correction model according to the average wastewater pollution index to obtain the wastewater pollution correction index.

[0180] According to an embodiment of the present invention, the wastewater pollution correction index is compared with the local water quality monitoring index of the preset area to determine the impact of wastewater on local water quality and obtain the wastewater pollution level, specifically:

[0181] Comparing the wastewater pollution correction index with the local water quality monitoring index of the preset area to obtain an index deviation rate;

[0182] Comparing the exponential deviation rate with a preset first deviation rate threshold and a preset second deviation rate threshold, the first deviation rate threshold being less than the second deviation rate threshold;

[0183] If the index deviation rate is less than the first deviation rate threshold, the wastewater pollution level does not exceed the standard;

[0184] If the index deviation rate is greater than or equal to the first deviation rate threshold and less than the second deviation rate threshold, the wastewater light pollution level is obtained;

[0185] If the index deviation rate is greater than or equal to the second deviation rate threshold, the wastewater severe pollution level is obtained.

[0186] Among them, in order to accurately reflect the degree of wastewater pollution and the degree of impact on the local water quality of the area, the wastewater pollution correction index is compared with the local water quality monitoring index of the preset area to obtain the index deviation rate. The local water quality monitoring index can be queried through a preset water quality monitoring database, and the index deviation rate is compared with a preset first deviation rate threshold and a preset second deviation rate threshold. The first deviation rate threshold is less than the second deviation rate threshold. If the index deviation rate is less than the first deviation rate threshold, the wastewater pollution degree does not exceed the standard. If the index deviation rate is greater than or equal to the first deviation rate threshold and less than the second deviation rate threshold, the wastewater light pollution level is obtained. If the index deviation rate is greater than or equal to the second deviation rate threshold, the wastewater heavy pollution level is obtained.

[0187] According to an embodiment of the present invention, after the raw material information of the detection reagent is processed by a preset raw material quality evaluation model to obtain the raw material quality stability index, the method further includes:

[0188] Comparing the raw material quality stability index with a preset stability index threshold to obtain a stability index deviation rate;

[0189] comparing the stability index deviation rate with a preset stability index deviation rate threshold;

[0190] If the stability index deviation rate is greater than or equal to the stability index deviation rate threshold, the raw material quality stability does not meet the requirements;

[0191] If the stability index deviation rate is less than the stability index deviation rate threshold, the raw material quality stability meets the requirements.

[0192] Among them, in order to improve the quality and stability of raw materials, the raw material quality stability index is compared with the preset stability index threshold to obtain the stability index deviation rate, and the stability index deviation rate is compared with the preset stability index deviation rate threshold. If the stability index deviation rate is greater than or equal to the stability index deviation rate threshold, the raw material quality stability does not meet the requirements; if the stability index deviation rate is less than the stability index deviation rate threshold, the raw material quality stability meets the requirements.

[0193] The third aspect of the present invention provides a computer-readable storage medium, which includes a wastewater detection and monitoring processing method program based on big data. When the wastewater detection and monitoring processing method program based on big data is executed by a processor, the steps of the wastewater detection and monitoring processing method based on big data as described in any one of the above items are implemented.

[0194] The present invention discloses a wastewater detection and monitoring processing method, system and medium based on big data, which obtains a plurality of wastewater quality monitoring information of a preset area in a plurality of time periods, extracts detection reagent raw material information and wastewater sampling detection information, processes the detection reagent raw material information through a preset raw material quality evaluation model, obtains a raw material quality stability index, extracts physical indicator detection data, chemical indicator detection data and biological indicator detection data according to the wastewater sampling detection information, obtains a physical indicator turbidity index, a chemical indicator solubility index and a biological indicator diversity index after respective processing, and then processes the data through a preset water quality pollution degree evaluation model to obtain a wastewater pollution degree index, obtains a wastewater pollution degree average index corresponding to a plurality of wastewater quality monitoring information of a preset area in a plurality of time periods, corrects the wastewater pollution degree index according to the wastewater pollution degree average index, obtains a wastewater pollution degree correction index, compares the wastewater pollution degree correction index with the local water quality monitoring index of the preset area, judges the degree of influence of the wastewater on the local water quality and obtains the wastewater pollution level. This application not only considers the monitoring data of the three dimensions of physical, chemical and biological wastewater quality, but also ensures the quality stability of the raw materials of the detection reagents in advance, and then conducts a comprehensive evaluation of the wastewater pollution degree, thereby realizing a comprehensive and multi-angle evaluation of the wastewater quality. This multi-dimensional monitoring can more comprehensively reflect the pollution status of the wastewater and improve the accuracy and reliability of the evaluation. By obtaining multiple wastewater quality monitoring information of multiple time periods in a preset area, calculating the average index of wastewater pollution, correcting the wastewater pollution index, and obtaining the wastewater pollution correction index, this dynamic monitoring and correction mechanism can more accurately reflect the changing trend of wastewater pollution and improve the timeliness and accuracy of the evaluation. This application combines scientific theory and practical application needs, taking into account the complexity of wastewater quality and focusing on the practicality and operability of the evaluation results. By constructing a series of specific indicators and indexes, the evaluation results are more intuitive, easy to understand and apply.

[0195] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0196] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0197] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0198] A person of ordinary skill in the art can understand that: all or part of the steps of implementing the above-mentioned method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a readable storage medium, which, when executed, executes the steps of the above-mentioned method embodiment; and the aforementioned storage medium includes: mobile storage devices, read-only memories, random access memories, magnetic disks or optical disks, and other media that can store program codes.

[0199] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

Claims

1. A wastewater detection and monitoring treatment method based on big data, characterized in that: The following steps are involved: Obtain multiple wastewater quality monitoring information for multiple time periods in a preset area, extract detection reagent raw material information and wastewater sampling detection information; Processing the raw material information of the detection reagent through a preset raw material quality evaluation model to obtain a raw material quality stability index; Extracting physical indicator detection data, chemical indicator detection data and biological indicator detection data according to the wastewater sampling detection information; Processing the physical indicator detection data to obtain a physical indicator turbidity index; Processing the chemical indicator detection data and the raw material quality stability index to obtain a chemical indicator solubility index; Processing the biological indicator detection data and the raw material quality stability index to obtain a biological indicator diversity index; Processing is performed according to the physical indicator turbidity index, the chemical indicator solubility index and the biological indicator diversity index to obtain a wastewater pollution index; Obtaining an average wastewater pollution index corresponding to a plurality of wastewater quality monitoring information in a plurality of time periods in the preset area, and correcting the wastewater pollution index according to the average wastewater pollution index to obtain a wastewater pollution correction index; Compare the wastewater pollution correction index with the local water quality monitoring index of the preset area to determine the impact of the wastewater on the local water quality and obtain the wastewater pollution level; The physical indicator turbidity index is obtained as follows: Extracting transmittance data and suspended particle concentration data according to the physical indicator detection data; The transmittance data and the suspended particle concentration data are processed by a preset water quality physical index evaluation model to obtain a physical index turbidity index; The chemical indicator solubility index is obtained as follows: Extracting pH data, oxygen content data and heavy metal content data according to the chemical indicator detection data; The pH data, oxygen content data and heavy metal content data are combined with the raw material quality stability index and processed by a preset water quality chemical index evaluation model to obtain a chemical index solubility index; The biological indicator diversity index is obtained as follows: Extracting total bacteria percentage data, coliform group content data and biological toxicity detection data based on the biological indicator detection data; The biological indicator diversity index is obtained by processing the total bacteria proportion data, the coliform group content data and the biological toxicity detection data in combination with the raw material quality stability index; The wastewater pollution index is obtained as follows: According to the physical indicator turbidity index, chemical indicator solubility index and biological indicator diversity index, the wastewater pollution index is obtained by processing through a preset water quality pollution evaluation model; The wastewater pollution correction index is obtained as follows: Obtaining an average wastewater pollution index corresponding to a plurality of wastewater quality monitoring information in a plurality of time periods in the preset area; According to the wastewater pollution degree average index, the wastewater pollution degree index is corrected by a wastewater pollution degree correction model to obtain a wastewater pollution degree correction index; The calculation formula of the wastewater pollution correction model is: ； in, is the wastewater pollution correction index, is the average index of wastewater pollution, is the wastewater pollution index, is the preset characteristic coefficient.

2. The wastewater detection and monitoring treatment method based on big data according to claim 1 is characterized in that: The raw material information of the detection reagent is processed by a preset raw material quality evaluation model to obtain a raw material quality stability index, which is specifically: Extracting detection reagent raw material data according to the detection reagent raw material information, including intra-batch quality difference data, inter-batch quality difference data, physical form integrity data and chemical property purity data; The raw material quality stability index is obtained by processing the intra-batch quality difference data, the inter-batch quality difference data, the physical form integrity data and the chemical property purity data through a preset raw material quality evaluation model.

3. The wastewater detection and monitoring treatment method based on big data according to claim 1 is characterized in that: The wastewater pollution correction index is compared with the local water quality monitoring index of the preset area to determine the impact of the wastewater on the local water quality and obtain the wastewater pollution level, specifically: Comparing the wastewater pollution correction index with the local water quality monitoring index of the preset area to obtain an index deviation rate; Comparing the exponential deviation rate with a preset first deviation rate threshold and a preset second deviation rate threshold, the first deviation rate threshold being less than the second deviation rate threshold; If the index deviation rate is less than the first deviation rate threshold, the wastewater pollution level does not exceed the standard; If the index deviation rate is greater than or equal to the first deviation rate threshold and less than the second deviation rate threshold, the wastewater light pollution level is obtained; If the index deviation rate is greater than or equal to the second deviation rate threshold, the wastewater severe pollution level is obtained.

4. Wastewater detection and monitoring treatment system based on big data, characterized in that: The invention comprises a memory and a processor, wherein the memory comprises a wastewater detection and monitoring processing method program based on big data, and the wastewater detection and monitoring processing method program based on big data is executed by the processor to implement the following steps: Obtain multiple wastewater quality monitoring information for multiple time periods in a preset area, extract detection reagent raw material information and wastewater sampling detection information; Processing the raw material information of the detection reagent through a preset raw material quality evaluation model to obtain a raw material quality stability index; Extracting physical indicator detection data, chemical indicator detection data and biological indicator detection data according to the wastewater sampling detection information; Processing the physical indicator detection data to obtain a physical indicator turbidity index; Processing the chemical indicator detection data and the raw material quality stability index to obtain a chemical indicator solubility index; Processing the biological indicator detection data and the raw material quality stability index to obtain a biological indicator diversity index; Processing is performed according to the physical indicator turbidity index, the chemical indicator solubility index and the biological indicator diversity index to obtain a wastewater pollution index; Obtaining an average wastewater pollution index corresponding to a plurality of wastewater quality monitoring information in a plurality of time periods in the preset area, and correcting the wastewater pollution index according to the average wastewater pollution index to obtain a wastewater pollution correction index; Compare the wastewater pollution correction index with the local water quality monitoring index of the preset area to determine the impact of the wastewater on the local water quality and obtain the wastewater pollution level; The physical indicator turbidity index is obtained as follows: Extracting transmittance data and suspended particle concentration data according to the physical indicator detection data; The transmittance data and the suspended particle concentration data are processed by a preset water quality physical index evaluation model to obtain a physical index turbidity index; The chemical indicator solubility index is obtained as follows: Extracting pH data, oxygen content data and heavy metal content data according to the chemical indicator detection data; The pH data, oxygen content data and heavy metal content data are combined with the raw material quality stability index and processed by a preset water quality chemical index evaluation model to obtain a chemical index solubility index; The biological indicator diversity index is obtained as follows: Extracting total bacteria percentage data, coliform group content data and biological toxicity detection data based on the biological indicator detection data; The biological indicator diversity index is obtained by processing the total bacteria proportion data, the coliform group content data and the biological toxicity detection data in combination with the raw material quality stability index; The wastewater pollution index is obtained as follows: According to the physical indicator turbidity index, chemical indicator solubility index and biological indicator diversity index, the wastewater pollution index is obtained by processing through a preset water quality pollution evaluation model; The wastewater pollution correction index is obtained as follows: Obtaining an average wastewater pollution index corresponding to a plurality of wastewater quality monitoring information in a plurality of time periods in the preset area; According to the wastewater pollution degree average index, the wastewater pollution degree index is corrected by a wastewater pollution degree correction model to obtain a wastewater pollution degree correction index; The calculation formula of the wastewater pollution correction model is: ； in, is the wastewater pollution correction index, is the average index of wastewater pollution, is the wastewater pollution index, is the preset characteristic coefficient.

5. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a wastewater detection and monitoring processing method program based on big data. When the wastewater detection and monitoring processing method program based on big data is executed by a processor, the steps of the wastewater detection and monitoring processing method based on big data as described in any one of claims 1 to 3 are implemented.

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