Generation method of pollution source water quality fingerprint database, fingerprint database and application thereof

Abstract

The invention discloses a pollution source water quality fingerprint database generation method, a fingerprint database and application thereof, and belongs to the technical field of big data analysis, and the method comprises the following steps: S1, forming a water combination basic database and each water diversion basic database; s2, establishing association between each water distribution basic database and the water combination basic database; s3, collecting combined water pollution information and separated water pollution information obtained by online monitoring, and comparing the information with the threshold values in S2; s4, reading in an intelligent learning server for learning; s5, forming a learning database V0; s6, real-time on-line obtaining of water pollution information; s7, perfecting the water-combining abnormal database C2 and each water-dividing abnormal database in the learning database V0 to form a new learning database V1; s8, continuously repeating the steps S6-S7; s9, through continuous learning and improvement, a pollution source water quality fingerprint database is finally formed; n is an integer greater than 5. According to the method and the system, the source of super-emission, super-concentration emission or super-frequency emission can be traced to which enterprises specifically refer to.

Description

Technical Field

[0001] The present invention relates to the technical field of big data analysis, and in particular to a method for generating a pollution source water quality fingerprint database, a fingerprint database and an application thereof. Background Art

[0002] With the acceleration of industrialization and urbanization and the rapid growth of industrialization, the total amount of industrial wastewater discharge has increased. Some rivers, lakes and reservoirs have been polluted by industrial wastewater discharge and the ecological environment has been damaged. In order to protect the water environment, the environmental protection department requires industrial enterprises to treat the wastewater in the production process before discharging it. In order to protect the water environment, the environmental protection department will arrange environmental law enforcement personnel to supervise whether the enterprise's sewage treatment equipment is turned on through manual inspections, and sample and analyze the water quality of the waters near the sewage discharge pipeline, so as to realize the monitoring of sewage discharge.

[0003] In the process of sewage discharge monitoring, since environmental law enforcement personnel cannot monitor whether the sewage treatment equipment of enterprises is turned on at all times, and real-time monitoring cannot be achieved through sampling and analysis, some small and medium-sized sewage enterprises have the following operating methods that may pollute the water environment and affect the environment in order to save costs and energy consumption of sewage treatment equipment: ⑴ Excessive discharge: sewage enterprises discharge in excess of the registered permitted amount (within the permitted discharge period).

[0004] ⑵ Excessive concentration discharge: sewage enterprises discharge the generated wastewater without treatment or incomplete treatment (within the permitted discharge time).

[0005] ⑶ Discharge outside the permitted discharge period.

[0006] How to ensure that enterprises discharge wastewater within the registered permitted discharge volume, concentration and permitted discharge time has become the core concern of the regulatory authorities, and the existing technology lacks effective monitoring methods.

[0007] The above background technology is for facilitating the understanding of the present invention and is not a known technology disclosed to the general public before the application of the present invention. Summary of the invention

[0008] In view of the above-mentioned defects, the present invention provides a method for generating a pollution source water quality fingerprint database, which aims to improve at least one of the problems mentioned in the background technology.

[0009] The technical solution is: a method for generating a pollution source water quality fingerprint database, which is used for artificial intelligence monitoring of sewage discharge, and the generation method includes the following steps: S1, forming a combined water basic database C1 and a water distribution basic database D1...water distribution basic database Dn; S2, establish association between each water distribution basic database and the combined water basic database C1, establish the emission threshold of each enterprise under normal discharge, the combined water emission threshold and the key fingerprint information of each water distribution pollution source in the combined water; S3, continue to collect the combined water pollution information and the water separation pollution information obtained by online monitoring and compare them with the threshold value of S2, send the pollution information exceeding the threshold value to the combined water anomaly database C2, the water separation anomaly database E1...the water separation anomaly database En, and send the pollution information within the threshold value to each water separation basic database and the combined water basic database C1; S4, read the combined water basic database C1 and the divided water basic database D1 ... divided water basic database Dn, the combined water abnormality database C2, the divided water abnormality database E1 ... divided water abnormality database En into the intelligent learning server, and the intelligent learning server performs learning; S5, forming a learning database V0; S6, real-time online acquisition of water pollution information, inputting the online acquired water pollution information into the intelligent learning server, which determines whether the discharge is compliant or non-compliant. When non-compliant discharge exists, it determines which company or companies have carried out excessive discharge, excessive concentration or excessive frequency discharge; S7, through supervision and inspection, regulatory reports, 12345 complaints, 12369 complaints, and online public opinion, improve the combined water anomaly database C2, water distribution anomaly database E1...water distribution anomaly database En in the learning database V0 to form a new learning database V1; S8, repeat S6-S7 continuously; S9, through continuous learning and improvement, a water quality fingerprint database of pollution sources is finally formed; n is an integer greater than 5.

[0010] Furthermore, the sewage discharge is the sewage discharge from an industrial park whose sewage pollution source is metal ions. In the industrial park, there are A1 enterprise, A2 enterprise, A3 enterprise, A4 enterprise, A5 enterprise, A6 enterprise, A7 enterprise, A8 enterprise...An enterprise. Among them, the metal ions in the wastewater discharged by A1 enterprise, A2 enterprise, A3 enterprise, A4 enterprise, A5 enterprise, A6 enterprise, A7 enterprise, A8 enterprise...An enterprise are different. Each enterprise is equipped with an artificial sampling port, and B is the online monitoring point before the wastewater in the park is collected and merged into the wastewater network.

[0011] Further, S1 comprises the following steps: S11, collecting the combined water pollution information obtained through online monitoring to form a combined water basic database C1, which is composed of continuous frames; S12, respectively collect water pollution information obtained through sampling and analysis from the artificial sampling ports of A1 enterprise...An enterprise in the same type of acquisition method as the combined water pollution information obtained by online monitoring in S11, and form water division basic databases D1...water division basic databases Dn respectively, wherein the water division basic database D1 corresponds to A1 enterprise,...water division basic database Dn corresponds to An enterprise; the water division basic databases D1...water division basic databases Dn are each composed of intermittent frames.

[0012] Furthermore, in S1, in the process of forming the combined water basic database C1 and the water division basic database D1 ... the water division basic database Dn, the pollution discharge of enterprises in the park is strictly monitored to ensure that the discharge of each enterprise is within the permitted range of registered discharges in the process of forming the combined water basic database C1 and the water division basic database D1 ... the water division basic database Dn.

[0013] Furthermore, in S2, when establishing the association, the information obtained from the sampling analysis at the sampling port is compared with the combined water pollution information obtained by online monitoring when the metal ion-containing wastewater flows from the sampling port to point B, so as to obtain key information on the impact of the enterprise's sewage discharge on the combined water.

[0014] Furthermore, in S3, when monitoring the combined water, the combined water pollution information obtained by real-time online monitoring is first compared with the threshold of S2 to see if it exceeds the threshold. If it exceeds the threshold, it is confirmed that there are enterprises in the park that fail to discharge wastewater in accordance with regulations. After confirming the information, the key fingerprint information of each water pollution source in the combined water formed in S2 is used to determine which specific enterprise or enterprises have committed excessive discharge, excessive concentration or excessive frequency of discharge.

[0015] Further, in S4, the intelligent learning server learns the pollution information features captured and read into the intelligent learning server, and respectively forms compliance standards, over-discharge standards, over-concentration emission standards or over-frequency standards, and sets the pollution information of the combined water to be monitored or the pollution information of each water branch to be compared with the formed standards. If the pollution information of the combined water to be monitored or the pollution information of each water branch is not within the compliance standard, it is determined that some enterprises have unqualified behavior. If it is within the compliance standard, it is determined that no enterprise has unqualified behavior. When some enterprises have unqualified behavior, the pollution information of the combined water to be monitored or the pollution information of each water branch is compared with the over-discharge standard, over-concentration emission standard or over-frequency standard to determine which specific enterprise or enterprises have carried out over-discharge, over-concentration or over-frequency emission.

[0016] Furthermore, the online monitoring to obtain the combined water pollution information and the manual sampling port sampling analysis to obtain the separate water pollution information are obtained through a three-dimensional fluorescence spectroscopy device.

[0017] The present invention also provides a pollution source water quality fingerprint database.

[0018] The technical solution is: a pollution source water quality fingerprint database, which is generated by the above-mentioned generation method.

[0019] The present invention also provides an application of a pollution source water quality fingerprint database.

[0020] The technical solution is: an application of a pollution source water quality fingerprint database, which is the above-mentioned pollution source water quality fingerprint database. During the monitoring process, the combined water pollution information is obtained online in real time, and the combined water pollution information obtained online is input into an intelligent learning server with the above-mentioned pollution source water quality fingerprint database to determine whether it is compliant discharge or non-compliant discharge. When there is non-compliant discharge, determine which specific enterprise or enterprises have committed excessive discharge, excessive concentration or excessive frequency discharge. At the same time, through supervision and inspection, regulatory broadcasts, 12345 complaints, 12369 complaints, and online public opinion, the combined water anomaly database C2, water division anomaly database E1...water division anomaly database En in the pollution source water quality fingerprint database are improved to form a new pollution source water quality fingerprint database.

[0021] Compared with the prior art, the present invention has the following beneficial effects: Aiming at the specificity of the metal sewage industrial park, the present invention sets an online monitoring point at the sewage system collection point of the metal sewage industrial park, and forms a continuously improved pollution source water quality fingerprint database through the information collected by the online monitoring point and the information obtained by sampling and analyzing each sewage-producing enterprise. Through the continuously improved pollution source water quality fingerprint database and the information obtained by the online monitoring point, it is possible to determine in real time whether there are enterprises in the park that have excessive discharge, excessive concentration discharge or excessive frequency discharge. Furthermore, the source of excessive discharge, excessive concentration discharge or excessive frequency discharge can be traced to which specific enterprise.

[0022] Other features and advantages of the present invention will be set forth in the following description, or some features and advantages may be inferred or unambiguously determined from the description, or may be learned by implementing the above-mentioned technology of the present invention.

[0023] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are specifically listed below and described in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a schematic diagram of the scene of the present invention. DETAILED DESCRIPTION

[0025] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0026] For the purpose of unified management, industrial layout is now increasingly distributed and arranged according to certain characteristics or functions, such as logistics industrial parks, pharmaceutical industrial parks, etc. Among the various industrial parks, there is a type of industrial park whose wastewater pollution source contains metal ions, and the metal ion content is one of the key indicators of water quality control.

[0027] The inventors found in their research that for the pollution source enterprises A1, A2, A3, A4, A5, A6, A7, A8, An, etc. that produce metal ion wastewater in the park, the metal ions in their respective wastewaters are different. For example, the wastewater of A1 may contain Ca 2+ Mg may be contained in the wastewater of A2 enterprise 2 + , the wastewater of A3 enterprise may contain Cu 2+ On this basis, the present invention forms a pollution source water quality fingerprint database.

[0028] Please refer to Figure 1 , Figure 1 This is a schematic diagram of the scene of the present invention. Figure 1 There are A1 enterprise, A2 enterprise, A3 enterprise, A4 enterprise, A5 enterprise, A6 enterprise, A7 enterprise, A8 enterprise...An enterprise distributed in the park. Among them, the metal ions in the wastewater discharged by A1 enterprise, A2 enterprise, A3 enterprise, A4 enterprise, A5 enterprise, A6 enterprise, A7 enterprise, A8 enterprise...An enterprise are different. Each enterprise is equipped with an artificial sampling port. B is the online monitoring point before the wastewater in the park is collected and merged into the wastewater network.

[0029] A method for generating a pollution source water quality fingerprint database comprises the following steps: S1, forming a combined water basic database C1 and a water distribution basic database D1 ... water distribution basic database Dn, including the following steps: S11, collecting the combined water pollution information obtained through online monitoring to form a combined water basic database C1, which is composed of continuous frames.

[0030] S12, respectively collect the water pollution information obtained from the artificial sampling ports of A1 enterprise...An enterprise in the same way as the combined water pollution information obtained by online monitoring in S11, and form water division basic databases D1...water division basic databases Dn, where water division basic database D1 corresponds to A1 enterprise,...water division basic database Dn corresponds to An enterprise. Since the sampling at the artificial sampling port is not online monitoring, but intermittent sampling, each water division basic database is not a continuous frame database.

[0031] In this step, in the process of forming the combined water basic database C1 and the water division basic database D1...the water division basic database Dn, the pollution discharge of enterprises in the park is strictly monitored to ensure that in the process of forming the combined water basic database C1 and the water division basic database D1...the water division basic database Dn, the emissions of each enterprise are within the permitted range of registered emissions, that is, the emission amount, emission frequency and emission concentration are all within the permitted range of registered emissions.

[0032] S2, establish association between each water distribution basic database and the combined water basic database C1, and establish the emission threshold of each enterprise under normal discharge, the combined water emission threshold and the key fingerprint information of each water distribution pollution source in the combined water.

[0033] When establishing the association, the information obtained from the sampling analysis at the sampling port is compared with the combined water pollution information obtained by online monitoring when the metal ion-containing wastewater flows from the sampling port to point B, so as to obtain key information on the impact of the enterprise's sewage discharge on the combined water. Since the sampling time of each sampling port may be different, the collection time of the combined water pollution information of the combined water basic database C1 may be different when the association between each water distribution basic database and the combined water basic database C1 is established.

[0034] In one or more specific embodiments of the present invention, online monitoring to obtain combined water pollution information and manual sampling port sampling and analysis to obtain separate water pollution information are obtained through three-dimensional fluorescence spectroscopy equipment. Different metal ions each have their own unique characteristic spectral lines, and these characteristic spectral lines are similar to human fingerprints, and these different characteristic spectral lines are reflected in the fluorescence spectrum of the combined water.

[0035] S3, continue to collect the combined water pollution information and the divided water pollution information obtained by online monitoring and compare it with the threshold value of S2, and send the pollution information exceeding the threshold value to the combined water anomaly database C2, the divided water anomaly database E1...the divided water anomaly database En respectively, and send the pollution information within the threshold value to each divided water basic database and the combined water basic database C1.

[0036] In this step, when monitoring the combined water, first compare the combined water pollution information collected in real time through online monitoring with the threshold of S2 to see if it exceeds the threshold. If so, it is confirmed that there are enterprises in the park that fail to discharge wastewater in accordance with regulations. After confirming the information, determine which specific enterprise or enterprises have committed over-discharge, over-concentration or over-frequency discharge based on the key fingerprint information of each water pollution source formed in S2 in the combined water.

[0037] S4, read the combined water basic database C1 and the divided water basic database D1 ... the divided water basic database Dn, the combined water abnormality database C2, the divided water abnormality database E1 ... the divided water abnormality database En into the intelligent learning server, and the intelligent learning server performs learning.

[0038] The intelligent learning server learns the pollution information features that are captured and read by the intelligent learning server, and forms compliance standards, over-discharge standards, over-concentration discharge standards or over-frequency standards respectively, and sets the pollution information of the combined water to be monitored or the pollution information of each water branch to be compared with the formed standards. If the pollution information of the combined water to be monitored or the pollution information of each water branch is not within the compliance standard, it is determined that some enterprises have unqualified behavior. If it is within the qualified standard, it is determined that no enterprise has unqualified behavior. When an enterprise has unqualified behavior, the pollution information of the combined water to be monitored or the pollution information of each water branch is compared with the over-discharge standard, over-concentration discharge standard or over-frequency standard to determine which specific enterprise or enterprises have carried out over-discharge, over-concentration or over-frequency discharge.

[0039] S5, forming a learning database V0.

[0040] S6, real-time online acquisition of water pollution information, inputting the online acquired water pollution information into the intelligent learning server, which will determine whether it is compliant discharge or non-compliant discharge. When non-compliant discharge exists, it will determine which specific enterprise or enterprises have carried out excessive discharge, excessive concentration or excessive frequency discharge.

[0041] S7, through supervision and inspection, regulatory broadcasts, 12345 complaints, 12369 complaints, online public opinion and other methods, improve the combined water anomaly database C2, water distribution anomaly database E1...water distribution anomaly database En in the learning database V0 to form a new learning database V1.

[0042] S8, repeat S6-S7 continuously.

[0043] S9, through continuous learning and improvement, a water quality fingerprint database of pollution sources will eventually be formed.

[0044] After the pollution source water quality fingerprint database has been running for a long time, since the samples in the combined water anomaly database C2 in the database are sufficient, and since each metal ion has its own unique characteristic spectrum, it is possible to determine whether the discharge is compliant or whether there is unqualified discharge simply by comparing the obtained combined water pollution information with the combined water anomaly database C2. At the same time, it is also possible to determine which specific company or companies have committed excessive discharge, excessive concentration or excessive frequency discharge based on the combined water pollution information. It is no longer necessary to manually take samples from the company's sampling port for analysis or to manually go to the company for inspection. Only one monitoring point and the pollution source water quality fingerprint database can be used to identify whether each company has non-compliant discharge behavior.

[0045] The present invention also provides an artificial intelligence method for monitoring sewage discharge, which uses the above-mentioned pollution source water quality fingerprint database.

[0046] In the process of artificial intelligence monitoring of sewage discharge, the combined water pollution information is obtained online in real time, and the combined water pollution information obtained online is input into the intelligent learning server with the above-mentioned pollution source water quality fingerprint database to determine whether it is compliant discharge or non-compliant discharge. When there is non-compliant discharge, it is determined which specific enterprise or enterprises have committed excessive discharge, excessive concentration or excessive frequency discharge. At the same time, through supervision and inspection, regulatory reports, 12345 complaints, 12369 complaints, online public opinion, etc., the combined water anomaly database C2, water division anomaly database E1...water division anomaly database En in the pollution source water quality fingerprint database are improved to form a new pollution source water quality fingerprint database.

[0047] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for generating a pollution source water quality fingerprint database, which is used for artificial intelligence monitoring of sewage discharge, characterized in that: The generation method The following steps are involved: S1, forming a combined water basic database C1 and a water distribution basic database D1...water distribution basic database Dn; S2, establish association between each water distribution basic database and the combined water basic database C1, establish the emission threshold of each enterprise under normal discharge, the combined water emission threshold and the key fingerprint information of each water distribution pollution source in the combined water; S3, continue to collect the combined water pollution information and the water separation pollution information obtained by online monitoring and compare them with the threshold value of S2, send the pollution information exceeding the threshold value to the combined water anomaly database C2, the water separation anomaly database E1...the water separation anomaly database En, and send the pollution information within the threshold value to each water separation basic database and the combined water basic database C1; S4, read the combined water basic database C1 and the divided water basic database D1 ... divided water basic database Dn, the combined water abnormality database C2, the divided water abnormality database E1 ... divided water abnormality database En into the intelligent learning server, and the intelligent learning server performs learning; S5, forming a learning database V0; S6, real-time online acquisition of water pollution information, inputting the online acquired water pollution information into the intelligent learning server, which determines whether the discharge is compliant or non-compliant. When non-compliant discharge exists, it determines which company or companies have carried out excessive discharge, excessive concentration or excessive frequency discharge; S7, through supervision and inspection, regulatory reports, 12345 complaints, 12369 complaints, and online public opinion, improve the combined water anomaly database C2, water distribution anomaly database E1...water distribution anomaly database En in the learning database V0 to form a new learning database V1; S8, repeat S6-S7 continuously; S9, through continuous learning and improvement, a water quality fingerprint database of pollution sources is finally formed; n is an integer greater than 5.

2. The method for generating a pollution source water quality fingerprint database according to claim 1, characterized in that: The sewage discharge is the sewage discharge from an industrial park whose sewage pollution source is metal ions. In the industrial park, there are A1 enterprise, A2 enterprise, A3 enterprise, A4 enterprise, A5 enterprise, A6 enterprise, A7 enterprise, A8 enterprise...An enterprise. Among them, the metal ions in the wastewater discharged by A1 enterprise, A2 enterprise, A3 enterprise, A4 enterprise, A5 enterprise, A6 enterprise, A7 enterprise, A8 enterprise...An enterprise are different. Each enterprise is equipped with an artificial sampling port. Point B is the online monitoring point before the wastewater in the park is collected and merged into the wastewater network.

3. The method for generating a pollution source water quality fingerprint database according to claim 2, characterized in that: S1 includes the following steps: S11, collecting the combined water pollution information obtained through online monitoring to form a combined water basic database C1, which is composed of continuous frames; S12, respectively collect water pollution information obtained through sampling and analysis from the artificial sampling ports of A1 enterprise...An enterprise in the same type of acquisition method as the combined water pollution information obtained by online monitoring in S11, and form water division basic databases D1...water division basic databases Dn respectively, wherein the water division basic database D1 corresponds to A1 enterprise,...water division basic database Dn corresponds to An enterprise; the water division basic databases D1...water division basic databases Dn are each composed of intermittent frames.

4. The method for generating a pollution source water quality fingerprint database according to claim 3, characterized in that: In S1, in the process of forming the combined water basic database C1 and the water division basic database D1...the water division basic database Dn, the pollution discharge of enterprises in the park is strictly monitored to ensure that the discharge of each enterprise is within the permitted range of registered discharges in the process of forming the combined water basic database C1 and the water division basic database D1...the water division basic database Dn.

5. The method for generating a pollution source water quality fingerprint database according to claim 1, characterized in that: In S2, when establishing the association, the information obtained from the sampling analysis at the sampling port is compared with the combined water pollution information obtained by online monitoring when the metal ion-containing wastewater flows from the sampling port to point B, so as to obtain key information on the impact of the enterprise's sewage discharge on the combined water.

6. The method for generating a pollution source water quality fingerprint database according to claim 1, characterized in that: In S3, when monitoring the combined water, the combined water pollution information collected in real time through online monitoring is first compared with the threshold of S2 to see if it exceeds the threshold. If so, it is confirmed that there are enterprises in the park that fail to discharge wastewater in accordance with regulations. After confirming the information, the key fingerprint information of each water pollution source in the combined water formed in S2 is used to determine which specific enterprise or enterprises have committed excessive discharge, excessive concentration or excessive frequency of discharge.

7. The method for generating a pollution source water quality fingerprint database according to claim 1, characterized in that: In S4, the intelligent learning server learns the pollution information features captured and read into the intelligent learning server, and respectively forms compliance standards, over-discharge standards, over-concentration emission standards or over-frequency standards, and sets the pollution information of the combined water to be monitored or the pollution information of each water branch to be compared with the formed standards. If the pollution information of the combined water to be monitored or the pollution information of each water branch is not within the compliance standard, it is determined that some enterprises have unqualified behavior. If it is within the compliance standard, it is determined that no enterprise has unqualified behavior. When some enterprises have unqualified behavior, the pollution information of the combined water to be monitored or the pollution information of each water branch is compared with the over-discharge standard, over-concentration emission standard or over-frequency standard to determine which specific enterprise or enterprises have carried out over-discharge, over-concentration or over-frequency emission.

8. The method for generating a pollution source water quality fingerprint database according to any one of claims 1 to 7, characterized in that: The online monitoring to obtain the combined water pollution information and the manual sampling port sampling analysis to obtain the separate water pollution information are obtained through three-dimensional fluorescence spectroscopy equipment.

9. A pollution source water quality fingerprint database, characterized in that: The pollution source water quality fingerprint database is generated by the generation method described in any one of claims 1-8.

10. An application of a pollution source water quality fingerprint database, characterized in that: The pollution source water quality fingerprint database is the pollution source water quality fingerprint database described in claim 9. During the monitoring process, the combined water pollution information is obtained online in real time, and the combined water pollution information obtained online is input into the intelligent learning server with the above-mentioned pollution source water quality fingerprint database to determine whether it is compliant discharge or non-compliant discharge. When there is non-compliant discharge, it is determined which specific enterprise or enterprises have carried out excessive discharge, excessive concentration or excessive frequency discharge. At the same time, through supervision and inspection, regulatory broadcasts, 12345 complaints, 12369 complaints, and online public opinion, the combined water anomaly database C2, water distribution anomaly database E1...water distribution anomaly database En in the pollution source water quality fingerprint database are improved to form a new pollution source water quality fingerprint database.

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