CN116340980B - Water environment pollution analysis management system and method based on big data - Google Patents

Water environment pollution analysis management system and method based on big data Download PDF

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CN116340980B
CN116340980B CN202310349883.6A CN202310349883A CN116340980B CN 116340980 B CN116340980 B CN 116340980B CN 202310349883 A CN202310349883 A CN 202310349883A CN 116340980 B CN116340980 B CN 116340980B
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张笑
张海林
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Feixian Branch Of Linyi Municipal Bureau Of Ecological Environment
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Abstract

The invention discloses a water environment pollution analysis management system and method based on big data, and belongs to the field of water environment management. According to the invention, the microplastic pollution condition is traced by analyzing the microplastic content in the water environment, and the diffusion range is predicted by analyzing and monitoring the position pollution diffusion condition, so that the optimal cleaning position is predicted, the treatment of the water environment pollution is promoted, the waste of cleaning materials and pollution leakage are avoided, and the cleaning efficiency of related personnel on the microplastic pollution is improved.

Description

Water environment pollution analysis management system and method based on big data
Technical Field
The invention relates to the field of water environment management, in particular to a water environment pollution analysis management system and method based on big data.
Background
Along with the continuous development of economy, the environmental pollution problem is more and more serious, and the ecological environment is an essential material condition for human survival and development, is also the basis of the operation of an economic system, and is a necessary precondition for the economic development. For sustainable development of society and economy, the importance of water environment protection is undoubted, the awareness and the requirement of people on water environment protection are enhanced, and the method is a foundation for promoting sustainable development of human society. The river course is the important resource of people's production life, provides sufficient water source for the resident to be the main passageway of draining floods and draining floods, simultaneously, water environment is the important component of human living environment, and the water environment pollution degree aggravates not only influences people's water demand, still influences people's living environment, brings serious influence to social production life, has restricted social economic development, can say that water environment is the most important factor of human living environment.
Microplastic is a plastic particle with a diameter smaller than 5 mm, and is a main carrier causing pollution. The micro-plastic has small volume, the larger the specific surface area, the stronger the capability of adsorbed pollutants, a large amount of polychlorinated biphenyl, bisphenol A and other persistent organic pollutants exist in the environment, the organic pollutants are often hydrophobic, that is, the organic pollutants are not easy to dissolve in water and are not easy to be diluted by water, once the micro-plastic meets the pollutants, the micro-plastic just gathers to form an organic pollution sphere, and the micro-plastic is equivalent to riding as the pollutants, and can float around in the environment. The wandering micro-plastic is easy to be eaten by low-end food chain organisms such as mussels, zooplankton and the like, cannot be digested, can only exist in the stomach all the time, occupies space, and causes illness and even death of animals; if the microplastic with the organic pollutants is eaten, the pollutants are released under the action of enzymes in organisms, so that the illness state of the microplastic is aggravated. The living beings at the bottom end of the food chain such as mussels, zooplankton and the like can be eaten by upper animals, and the micro-plastics, even the micro-plastics and organic pollutants enter the upper animals, and the harmful substances in the lower animals are only 1 percent, but become 20 percent to the upper layer, so that a large number of living beings eating the micro-plastics can be sick or dead, the living beings at the top end of the food chain are human beings, a large number of micro-plastics can be accumulated in the human body under the enrichment effect, and the small particles which are difficult to digest generate unpredictable harm to the human body.
At present, the cleaning measures of the microplastic are to carry out physical interception through biodegradation and an adsorption film, however, the plastic is extremely dispersed in the environment and is difficult to be biodegraded in a large scale in situ, the consumption of manpower and material resources by regular dredging and film changing is not small, a large amount of manpower and material resources can be wasted due to overlarge installation range of the adsorption film, pollution leakage can be caused due to overlarge installation range of the adsorption film, and the water environment pollution management difficulty is increased.
It appears that it is necessary to trace the source of microplastic pollution in a water environment and to analyze the treatment area according to the spread of microplastic pollution. Therefore, a system and a method for analyzing and managing water environment pollution based on big data are needed.
Disclosure of Invention
The invention aims to provide a water environment pollution analysis management system and method based on big data, which are used for solving the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: a water environment pollution analysis management system based on big data, the pollution analysis management system includes: the system comprises a data acquisition module, a database, a pollution analysis module and an early warning and reminding module;
the output end of the data acquisition module is connected with the input end of the database, the output end of the database is connected with the input end of the pollution analysis module, the output end of the pollution analysis module is connected with the input end of the early warning reminding module, and the output end of the pollution analysis module is connected with the input end of the database; the system comprises a data acquisition module, a database, a pollution analysis module and an early warning reminding module, wherein the data acquisition module is used for acquiring basic data information and monitoring microplastic in a water environment in real time, the database is used for carrying out encryption storage on acquired data and analysis results, the pollution analysis module is used for carrying out analysis processing on the acquired data, and the early warning reminding module is used for carrying out early warning reminding on related personnel according to the analysis results.
Further, the data acquisition module comprises a basic data acquisition unit and a pollution monitoring unit, wherein the basic data acquisition unit is used for acquiring basic data information, the pollution monitoring unit monitors the content and the diffusion condition of microplastic in the water environment in real time through microplastic monitoring equipment, and monitors the water flow speed of the water environment through a water flow sensor.
Furthermore, the database comprises a data encryption unit and a data storage unit, the data encryption unit encrypts acquired data information and analysis results through an RSA encryption algorithm, so that the data security of the system is ensured, the occurrence of data leakage or data tampering is avoided, the RSA encryption is a public key cryptosystem, the so-called public key cryptosystem is a cryptosystem which uses different encryption keys and decryption keys and is a "computationally infeasible" cryptosystem for deriving the decryption keys from the known encryption keys, and the RSA algorithm security is based on the difficulty of large number decomposition. The difficulty of recovering plaintext from a public key and ciphertext is equivalent to decomposing the product of two large primes; in order to improve the confidentiality strength, the RSA key is at least 500 bits long, 1024 bits are generally recommended, and the key length of the current commercial RSA algorithm is 2048 bits; the RSA algorithm has better security than the symmetric encryption algorithm, but the encryption processing efficiency is not as high as that of the symmetric encryption algorithm due to the higher algorithm complexity. Therefore, when the network transmits important information, two encryption algorithms are often used in a mixed mode. The data storage unit stores collected data information and analysis results through an HDFS data storage mode, the HDFS is a data storage system in Hadoop distributed computation, the data storage system is developed based on the requirement of accessing and processing oversized files through a streaming data mode, in the HDFS, the file reading and writing process is a process of interacting clients, nameNodes and dataNodes together, the HDFS data storage mode can process oversized files and can operate on a relatively cheap commercial machine cluster, the HDFS can well process 'write once and read and write many times' tasks through streaming access data, one data set can be copied into different storage nodes once being generated, and then in response to various data analysis task requests, the analysis tasks can involve most of data in the data set in most cases. Therefore, HDFS requests to read the entire data set more efficiently than reading one record.
Further, the pollution analysis module comprises a source tracing unit and a diffusion analysis unit, wherein the source tracing unit is used for tracing the source of the microplastic pollution according to the collected data, so that related personnel can know the specific situation of the microplastic from the source conveniently, measures are taken, the diffusion analysis unit is used for analyzing the diffusion situation of the microplastic, the related personnel can conveniently clean the pollution, serious pollution problems caused by the large-scale diffusion of the microplastic are avoided, and the cleaning efficiency of the related personnel is improved.
Further, the early warning reminding module comprises a screen display unit and a voice alarm unit, wherein the screen display unit is used for displaying a pollution range and guiding a processing range for related personnel through screen display equipment according to an analysis result, so that the related personnel can conveniently and rapidly clean micro-plastic pollution, the related personnel can be guaranteed to clean the pollution most efficiently, the voice alarm unit is used for broadcasting the related personnel through voice equipment according to the analysis result, the related personnel can be guaranteed to receive warning reminding information in real time, and the problem that pollution is spread in a large range due to untimely measures is avoided.
A water environment pollution analysis management method based on big data comprises the following steps:
s1, basic data information is collected, the content and the diffusion condition of micro plastics in a water environment are monitored in real time through micro plastic monitoring equipment, and encryption storage is carried out;
s2, tracing the microplastic pollution in the water environment according to the acquired basic data information and the microplastic content condition;
s3, predicting the micro plastic pollution diffusion range of each monitoring point according to the collected micro plastic diffusion condition and historical data, and performing prediction analysis on the cleaning area of related personnel;
and S4, according to an analysis result, when microplastic pollution occurs, alarming and reminding related personnel through a display device and a voice device.
Further, in step S2, the following steps are included:
s201, establishing a plane rectangular coordinate system according to the collected water flow direction, the equipment monitoring position information and the content of microplastic in the water environment, wherein the coordinate system can be set by related technicians;
s202, establishing a Gaussian diffusion model through the following formula:
where G (x, y) represents the average microplastic content over a period of time t at the monitoring point (x, y) in the plane, G is represented as the source intensity, which refers to a measure of the intensity of the generated or emitted contaminant, α x and αy Expressed as diffusion parameters on the x-axis and y-axis, v expressed as water flow velocity, (x) 0 ，y 0 ) Expressed as preset pollution source coordinates;
s203, calculating the content value C of the microplastic at the monitoring position according to the content of the microplastic in the water environment monitored at the monitoring position by the following formula:
wherein P is expressed as microplastic content index, Z H High value, Z, expressed as microplastic content limit L Low value, Z, expressed as microplastic content limit H and ZL Is a high-low numerical value which is equal to the content limit value of the microplastic, each level value is a fixed value, P H Pollution index, P, corresponding to the high value expressed as microplastic content limit L A pollution index corresponding to a low-order value expressed as a microplastic content limit value, wherein the pollution index is a dimensionless number, and each level value is a set fixed value;
the source strength G is calculated by the following formula:
wherein T is expressed as time, and S is expressed as monitoring the water environment surface area;
s204, defining a spherical search area beta, wherein the center point (x i ，y i ) Second-order Taylor for Gaussian diffusion model functionValue g after expansion * And (3) performing calculation:
wherein d is expressed as a variation parameter,represented as a vector differential operator;
the correlation index γ is calculated by the following formula:
wherein ,f(xi )-f(x i +d) is expressed as the actual drop-off content value, f (x) i )-g * Expressed as a predicted drop-in content value between adjacent monitoring points of the microplastic, a correlation index threshold is set to be gamma Threshold value When gamma > gamma Threshold value When the two-stage Taylor expansion representing the Gaussian diffusion model function is an approximate objective function, the change parameter d is correct, otherwise, when gamma is less than or equal to gamma Threshold value When the method is used, the searching is needed to be carried out again, the change parameters are updated continuously, and a final convergence solution is obtained after multiple iterations, so that the preset pollution source coordinate position (x) is deduced reversely through data fitting 0 ，y 0 )。
Further, in step S3, the following steps are included:
s301, according to real-time monitoring of the content and the diffusion of the micro plastics in the water environment by the micro plastic monitoring equipment, obtaining micro plastic data of the same monitoring point at different moments, and establishing a plane rectangular coordinate system; according to the distribution conditions of the microplastic in the water environment obtained by monitoring at different moments, a distribution image is obtained, information of the spatial geographic position is added to the microplastic distribution boundary, and an edge detection algorithm is utilized to extract the profile of the microplastic distribution boundary so as to obtain a microplastic distribution region E;
s302, distributing boundary wheels to microplastic simultaneously when microplastic existsIn the case of normal and tangential diffusion of the profile, however, the diffusion in the tangential direction does not affect the profile position, so that only the diffusion of the profile line in the normal direction is calculated. The normal velocity field for microplastic diffusion is calculated by the following formulaAnd (3) performing calculation:
wherein ,(nx ，n y ) The normal unit vector expressed as the profile line of the microplastic distribution boundary, the velocity field refers to a flow field formed by velocity at discrete points in a space;
the distance function r (t, x, y) is calculated by the following formula:
wherein t is represented as a monitoring moment, (x, y) is represented as a position coordinate of a point in the water environment, and D is represented as a nearest distance from the point (x, y) to a microplastic distribution boundary;
the gradient of the distance functionThe method comprises the following steps:
wherein , and />Expressed as tangential and normal,/->Expressed as gradient operators;
thenAcquiring normal velocity field distribution of micro-plastic diffusion through real-time monitoring data, and carrying out solution on the position of micro-plastic diffusion at the subsequent moment after the continuation of a non-polluted area so as to acquire a micro-plastic diffusion prediction position profile;
s303, obtaining the predicted contour circumference of the t' moment as S according to the micro plastic diffusion predicted position contour t′ According to the collected basic data, the running speed v of the related personnel for installing the micro plastic cleaning material is obtained Dress(s) The processing position is calculated by the following formula:
wherein, deltat 'is expressed as the total time for installing cleaning materials, and the time t' and the corresponding micro plastic diffusion position are obtained by solving and expressed as the optimal cleaning position;
s304, displaying a predicted pollution range to related personnel through display equipment according to the analysis result, and displaying a predicted optimal cleaning position.
Further, in step S4, when micro plastic pollution occurs, the predicted micro plastic pollution source, pollution range and treatment range guidance are displayed to related personnel through the display device, and the related personnel are alerted through the voice device, so that the water environment pollution cleaning efficiency of the related personnel is improved, the micro plastic pollution is prevented from spreading in a large area, the water environment is guaranteed to be tidy, and the health of people is guaranteed.
Compared with the prior art, the invention has the following beneficial effects:
the invention collects basic data information, monitors the content and the diffusion condition of micro plastic in the water environment in real time through micro plastic monitoring equipment, and monitors the water flow speed of the water environment through a water flow sensor; according to the collected data information, the content of the microplastic in the water environment of different monitoring points is analyzed, the microplastic pollution condition is traced, so that related personnel can conveniently and rapidly clean the microplastic pollution source, and more microplastic pollution is avoided; according to the collected data information, the pollution diffusion conditions of the monitoring position at different moments are analyzed, the pollution diffusion range of the monitoring position is predicted, so that the optimal cleaning position is predicted, waste caused by large-scale installation of cleaning materials in advance is avoided, pollution leakage caused by small installation of the cleaning materials is avoided, the cleaning efficiency of related personnel on micro plastic pollution is improved, and the treatment of water environment pollution is promoted.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a schematic diagram of the module composition of a water environment pollution analysis management system based on big data;
fig. 2 is a flow chart of steps of a water environment pollution analysis and management method based on big data.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1-2, the present invention provides the following technical solutions: a water environment pollution analysis management system based on big data, the pollution analysis management system includes: the system comprises a data acquisition module, a database, a pollution analysis module and an early warning and reminding module;
the output end of the data acquisition module is connected with the input end of the database, the output end of the database is connected with the input end of the pollution analysis module, the output end of the pollution analysis module is connected with the input end of the early warning reminding module, and the output end of the pollution analysis module is connected with the input end of the database;
the data acquisition module is used for acquiring basic data information and monitoring microplastic in a water environment in real time, the data acquisition module comprises a basic data acquisition unit and a pollution monitoring unit, the basic data acquisition unit is used for acquiring basic data information such as water flow direction, equipment monitoring position, spectrum information and basic physical characteristics of the microplastic, and the pollution monitoring unit monitors the coverage condition and content of the microplastic through microplastic monitoring equipment such as Raman spectrometer, energy spectrometer, microorganism mass spectrometer and the like, monitors the content and diffusion condition of the microplastic in the water environment in real time and monitors the water flow speed of the water environment through a water flow sensor.
The database is used for encrypting and storing acquired data and analysis results, the database comprises a data encryption unit and a data storage unit, the data encryption unit encrypts the acquired data information and the analysis results through an RSA encryption algorithm, the data security of the system is guaranteed, the condition of data leakage or data tampering is avoided, the RSA encryption is a public key cryptosystem, the so-called public key cryptosystem is a cryptosystem which uses different encryption keys and decryption keys, the decryption keys are not feasible in calculation by the known encryption keys, and the RSA algorithm security is based on the difficulty of large number decomposition. The difficulty of recovering plaintext from a public key and ciphertext is equivalent to decomposing the product of two large primes; in order to improve the confidentiality strength, the RSA key is at least 500 bits long, 1024 bits are generally recommended, and the key length of the current commercial RSA algorithm is 2048 bits; the RSA algorithm has better security than the symmetric encryption algorithm, but the encryption processing efficiency is not as high as that of the symmetric encryption algorithm due to the higher algorithm complexity. Therefore, when the network transmits important information, two encryption algorithms are often used in a mixed mode. The data storage unit stores collected data information and analysis results through an HDFS data storage mode, the HDFS is a data storage system in Hadoop distributed computation, the data storage system is developed based on the requirement of accessing and processing oversized files through a streaming data mode, in the HDFS, the file reading and writing process is a process of interacting clients, nameNodes and dataNodes together, the HDFS data storage mode can process oversized files and can operate on a relatively cheap commercial machine cluster, the HDFS can well process 'write once and read and write many times' tasks through streaming access data, one data set can be copied into different storage nodes once being generated, and then in response to various data analysis task requests, the analysis tasks can involve most of data in the data set in most cases. Therefore, HDFS requests to read the entire data set more efficiently than reading one record.
The pollution analysis module is used for analyzing and processing collected data, the pollution analysis module comprises a source tracing unit and a diffusion analysis unit, the source tracing unit is used for tracing the source of microplastic pollution according to the collected data, relevant personnel are convenient to know the specific situation of the microplastic from the source, measures are taken, the diffusion analysis unit is used for analyzing the diffusion situation of the microplastic, the relevant personnel are convenient to carry out pollution cleaning, serious pollution problems caused by large-scale diffusion of the microplastic are avoided, and the cleaning efficiency of the relevant personnel is improved.
The early warning and reminding module is used for carrying out early warning and reminding on related personnel according to the analysis result. The early warning reminding module comprises a screen display unit and a voice alarm unit, wherein the screen display unit is used for displaying and guiding a treatment range of pollution ranges of related personnel through screen display equipment such as mobile phones or computers according to analysis results, so that the related personnel can conveniently and rapidly clean micro-plastic pollution, the pollution can be cleaned most efficiently, the voice alarm unit is used for broadcasting the related personnel through voice equipment such as broadcasting or sounding and the like according to the analysis results, the related personnel can receive warning reminding information in real time, and the pollution large-scale diffusion caused by untimely measures is avoided.
A water environment pollution analysis management method based on big data comprises the following steps:
s1, basic data information is collected, the content and the diffusion condition of micro plastics in a water environment are monitored in real time through micro plastic monitoring equipment, and encryption storage is carried out;
s2, tracing the microplastic pollution in the water environment according to the acquired basic data information and the microplastic content condition;
in step S2, the following steps are included:
s201, establishing a plane rectangular coordinate system according to the collected water flow direction, the equipment monitoring position information and the content of microplastic in the water environment, wherein the coordinate system can be set by related technicians, for example, a connecting line of a starting point and an ending point of the monitoring water flow is used as a coordinate axis;
s202, establishing a Gaussian diffusion model through the following formula:
wherein G (x, y) represents the average microplastic content in the time period t at the monitoring point (x, y) in the plane, G represents the source intensity, which refers to the measurement of the intensity of generated or discharged pollutants, including the source intensity of waste gas, waste water, noise, vibration, solid waste and the like, alpha x and αy Expressed as diffusion parameters on the x-axis and y-axis, v expressed as water flow velocity, (x) 0 ，y 0 ) Expressed as preset pollution source coordinates;
s203, calculating the content value C of the microplastic at the monitoring position according to the content of the microplastic in the water environment monitored at the monitoring position by the following formula:
wherein P is expressed as microplastic content index, Z H High value, Z, expressed as microplastic content limit L Low value, Z, expressed as microplastic content limit H and ZL Is the content limit of the microplasticThe high and low numerical values of the values, each level value is a set fixed value, P H Pollution index, P, corresponding to the high value expressed as microplastic content limit L A pollution index corresponding to a low-order value expressed as a microplastic content limit value, wherein the pollution index is a dimensionless number, and each level value is a set fixed value;
the source strength G is calculated by the following formula:
wherein T is expressed as time, and S is expressed as monitoring the water environment surface area;
s204, defining a spherical search area beta, wherein the center point (x i ，y i ) Value g after two-stage Taylor expansion of Gaussian diffusion model function * And (3) performing calculation:
wherein d is expressed as a variation parameter,represented as a vector differential operator;
the correlation index γ is calculated by the following formula:
wherein ,f(xi )-f(x i +d) is expressed as the actual drop-off content value, f (x) i )-g * Expressed as a predicted drop-in content value between adjacent monitoring points of the microplastic, a correlation index threshold is set to be gamma Threshold value When gamma > gamma Threshold value When the two-stage Taylor expansion representing the Gaussian diffusion model function is an approximate objective function, the variable d is correct, and vice versaWhen gamma is less than or equal to gamma Threshold value When the method is used, the searching is needed to be carried out again, the change parameters are updated continuously, and a final convergence solution is obtained after multiple iterations, so that the preset pollution source coordinate position (x) is deduced reversely through data fitting 0 ，y 0 )。
S3, predicting the micro plastic pollution diffusion range of each monitoring point according to the collected micro plastic diffusion condition and historical data, and performing prediction analysis on the cleaning area of related personnel;
in step S3, the following steps are included:
s301, according to real-time monitoring of the content and the diffusion of the micro plastics in the water environment by the micro plastic monitoring equipment, obtaining micro plastic data of the same monitoring point at different moments, and establishing a plane rectangular coordinate system; according to the distribution conditions of the microplastic in the water environment obtained by monitoring at different moments, a distribution image is obtained, information of the spatial geographic position is added to the microplastic distribution boundary, and an edge detection algorithm is utilized to extract the profile of the microplastic distribution boundary so as to obtain a microplastic distribution region E;
s302, the micro plastic is diffused in the normal direction and the tangential direction of the micro plastic distribution boundary outline, but the diffusion in the tangential direction does not influence the outline position, so that the diffusion of the outline in the normal direction is only calculated. The normal velocity field for microplastic diffusion is calculated by the following formulaAnd (3) performing calculation:
wherein ,(nx ，n y ) The normal unit vector expressed as the profile line of the microplastic distribution boundary, the velocity field refers to a flow field formed by velocity at discrete points in a space;
the distance function r (t, x, y) is calculated by the following formula:
wherein t is represented as a monitoring moment, (x, y) is represented as a position coordinate of a point in the water environment, and D is represented as a nearest distance from the point (x, y) to a microplastic distribution boundary;
the gradient of the distance functionThe method comprises the following steps:
wherein , and />Expressed as tangential and normal,/->Expressed as gradient operators;
thenAcquiring normal velocity field distribution of micro-plastic diffusion through real-time monitoring data, and carrying out solution on the position of micro-plastic diffusion at the subsequent moment after the continuation of a non-polluted area so as to acquire a micro-plastic diffusion prediction position profile;
s303, obtaining the predicted contour circumference of the t' moment as S according to the micro plastic diffusion predicted position contour t′ According to the collected basic data, the running speed v of the related personnel for installing the micro plastic cleaning material is obtained Dress(s) The processing position is calculated by the following formula:
wherein, deltat 'is expressed as the total time for installing cleaning materials, and the time t' and the corresponding micro plastic diffusion position are obtained by solving and expressed as the optimal cleaning position;
s304, displaying a predicted pollution range to related personnel through display equipment according to the analysis result, and displaying a predicted optimal cleaning position.
And S4, according to an analysis result, when microplastic pollution occurs, alarming and reminding related personnel through a display device and a voice device.
In step S4, when the microplastic pollution occurs, the predicted microplastic pollution source, pollution range and treatment range guidance are displayed to the relevant personnel through the display device, such as a mobile phone or a computer, for example, the relevant personnel are guided to install the microplastic adsorption film at the predicted position, and the relevant personnel are warned and reminded through the voice device, such as warning sound or voice prompt, for example, so that the water environment pollution cleaning efficiency of the relevant personnel is improved, the microplastic pollution is prevented from being spread in a large area, the water environment is guaranteed to be clean, and the physical health of the people is guaranteed.
Example 1:
if the actual drop content value between adjacent monitoring points of the micro plastic is 2, the predicted drop content value between adjacent monitoring points of the micro plastic is 2.5, and the related index isIf the related index threshold is set as gamma Threshold value =0.5, then γ>γ Threshold value The second-order taylor expansion representing the gaussian diffusion model function is an approximate objective function; if the related index threshold is set as gamma Threshold value =1, then γ<γ Threshold value The searching is needed again, the change parameters are updated continuously, and a final convergence solution is obtained after multiple iterations, so that the preset pollution source coordinate position (x) is deduced reversely through data fitting 0 ，y 0 )；
If related personnel install the running speed v of the micro plastic cleaning material Dress(s) =5, at time t' pastPredicted contour perimeter S t' =100, remind relevant personnel that this contour position is the clearance position through display device, clear up little plastics pollution, when little plastics pollution spreads to this place, relevant personnel just install the clearance material.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (7)

1. A water environment pollution analysis and management method based on big data is characterized in that: comprises the following steps:
s1, basic data information is collected, the content and the diffusion condition of micro plastics in a water environment are monitored in real time through micro plastic monitoring equipment, and encryption storage is carried out;
s2, tracing the microplastic pollution in the water environment according to the acquired basic data information and the microplastic content condition;
s3, predicting the micro plastic pollution diffusion range of each monitoring point according to the collected micro plastic diffusion condition and historical data, and performing prediction analysis on the cleaning area of related personnel;
s4, according to analysis results, when microplastic pollution occurs, alarming and reminding related personnel through display equipment and voice equipment;
in step S2, the following steps are included:
s201, establishing a plane rectangular coordinate system according to the collected water flow direction, the equipment monitoring position information and the content of microplastic in the water environment;
s202, establishing a Gaussian diffusion model through the following formula:
wherein G (x, y) represents the average microplastic content in the time period t at the monitoring point (x, y) in the plane, G represents the source intensity, alpha x and αy Expressed as diffusion parameters on the x-axis and y-axis, v expressed as water flow velocity, (x) 0 ，y 0 ) Expressed as preset pollution source coordinates;
s203, calculating the content value C of the microplastic at the monitoring position according to the content of the microplastic in the water environment monitored at the monitoring position by the following formula:
wherein P is expressed as microplastic content index, Z H High value, Z, expressed as microplastic content limit L Low value, P, expressed as microplastic content limit H Pollution index, P, corresponding to the high value expressed as microplastic content limit L A pollution index corresponding to a low value expressed as a microplastic content limit;
the source strength G is calculated by the following formula:
wherein T is expressed as time, and S is expressed as monitoring the water environment surface area;
s204, defining a spherical search area beta, wherein the center point (x i ，y i ) Value g after two-stage Taylor expansion of Gaussian diffusion model function * And (3) performing calculation:
wherein d is expressed as a variation parameter,represented as a vector differential operator;
the correlation index γ is calculated by the following formula:
wherein ,f(xi )-f(x i +d) is expressed as the actual drop-off content value, f (x) i )-g * Expressed as a predicted drop-in content value between adjacent monitoring points of the microplastic, a correlation index threshold is set to be gamma Threshold value When gamma is>γ Threshold value When the two-stage Taylor expansion representing the Gaussian diffusion model function is an approximate objective function, the change parameter d is correct, otherwise, when gamma is less than or equal to gamma Threshold value When the method is used, the searching is needed to be carried out again, the change parameters are updated continuously, and a final convergence solution is obtained after multiple iterations, so that the preset pollution source coordinate position (x) is deduced reversely through data fitting 0 ，y 0 )；
In step S3, the following steps are included:
s301, according to real-time monitoring of the content and the diffusion of the micro plastics in the water environment by the micro plastic monitoring equipment, obtaining micro plastic data of the same monitoring point at different moments, and establishing a plane rectangular coordinate system; according to the distribution conditions of the microplastic in the water environment obtained by monitoring at different moments, a distribution image is obtained, information of the spatial geographic position is added to the microplastic distribution boundary, and an edge detection algorithm is utilized to extract the profile of the microplastic distribution boundary so as to obtain a microplastic distribution region E;
s302, a normal velocity field for diffusing the micro plastic through the following formulaAnd (3) performing calculation:
wherein ,(nx ，n y ) A normal unit vector expressed as a microplastic distribution boundary contour;
the distance function r (t, x, y) is calculated by the following formula:
wherein t is represented as a monitoring moment, (x, y) is represented as a position coordinate of a point in the water environment, and D is represented as a nearest distance from the point (x, y) to a microplastic distribution boundary;
the gradient of the distance functionThe method comprises the following steps:
wherein , and />Expressed as tangential and normal,/->Expressed as gradient operators;
thenAcquiring normal velocity field distribution of micro-plastic diffusion through real-time monitoring data, and carrying out solution on the position of micro-plastic diffusion at the subsequent moment after the continuation of a non-polluted area so as to acquire a micro-plastic diffusion prediction position profile;
s303, obtaining the predicted contour circumference of the t' moment as S according to the micro plastic diffusion predicted position contour t' According to the collected basic data, the running speed v of the related personnel for installing the micro plastic cleaning material is obtained Dress(s) The processing position is calculated by the following formula:
the delta t 'is expressed as the total time for installing cleaning materials, and the time t' and the corresponding micro plastic diffusion position are obtained through solving and expressed as the optimal cleaning position;
s304, displaying a predicted pollution range to related personnel through display equipment according to the analysis result, and displaying a predicted optimal cleaning position.
2. The water environment pollution analysis and management method based on big data as claimed in claim 1, wherein the method is characterized in that: in step S4, according to the analysis result, when the microplastic pollution occurs, the predicted microplastic pollution source, pollution range and processing range guidance are displayed to the related personnel through the display device, and the related personnel are warned and reminded through the voice device.
3. A big data based water environmental pollution analysis management system for implementing the big data based water environmental pollution analysis management method of any one of claims 1-2, characterized in that: the pollution analysis management system includes: the system comprises a data acquisition module, a database, a pollution analysis module and an early warning and reminding module;
the output end of the data acquisition module is connected with the input end of the database, the output end of the database is connected with the input end of the pollution analysis module, the output end of the pollution analysis module is connected with the input end of the early warning reminding module, and the output end of the pollution analysis module is connected with the input end of the database; the system comprises a data acquisition module, a database, a pollution analysis module and an early warning reminding module, wherein the data acquisition module is used for acquiring basic data information and monitoring microplastic in a water environment in real time, the database is used for carrying out encryption storage on acquired data and analysis results, the pollution analysis module is used for carrying out analysis processing on the acquired data, and the early warning reminding module is used for carrying out early warning reminding on related personnel according to the analysis results.
4. The water environment pollution analysis management system based on big data according to claim 3, wherein: the data acquisition module comprises a basic data acquisition unit and a pollution monitoring unit, wherein the basic data acquisition unit is used for acquiring basic data information, the pollution monitoring unit monitors the content and the diffusion condition of microplastic in the water environment in real time through microplastic monitoring equipment, and monitors the water flow speed of the water environment through a water flow sensor.
5. The big data-based water environment pollution analysis management system according to claim 4, wherein: the database comprises a data encryption unit and a data storage unit, wherein the data encryption unit encrypts collected data information and analysis results through an RSA encryption algorithm, and the data storage unit stores the collected data information and analysis results through an HDFS data storage mode.
6. The big data-based water environment pollution analysis management system according to claim 5, wherein: the pollution analysis module comprises a source tracing unit and a diffusion analysis unit, wherein the source tracing unit is used for tracing the source of the microplastic pollution according to the collected data, and the diffusion analysis unit is used for analyzing the diffusion condition of the microplastic.
7. The big data-based water environment pollution analysis management system of claim 6, wherein: the early warning reminding module comprises a screen display unit and a voice alarm unit, wherein the screen display unit is used for displaying a pollution range and guiding a processing range of related personnel through screen display equipment according to an analysis result, and the voice alarm unit is used for broadcasting the related personnel through voice equipment according to the analysis result.
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