Pollution source detection method and system based on water environment treatment

Abstract

The application discloses a pollution source detection method and system based on water environment treatment, and relates to the technical field of intelligent detection, and comprises the following steps: emitting laser with a first Brillouin linewidth in combination with a distribution range; adjusting the first Brillouin linewidth based on feedback data of the laser; moving the coordinates of the pollution source based on a pollution diffusion model, a three-point positioning method and pollution parameters of a current detection point; and obtaining new coordinates of the pollution source. The application greatly improves positioning accuracy by detecting changes in trace pollution concentration and combining model inversion, does not need to be close to a pollution area, supports a closed-loop mechanism of detection and updating, can realize three-dimensional positioning by only using three detection points, does not need to densely arrange a sensor network, greatly reduces hardware cost and maintenance burden, is suitable for emergency and rapid deployment, and can maintain stable performance under complex conditions such as wind field changes, terrain undulations and water layering.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent detection, and in particular to a pollution source detection method and system based on water environment governance. BACKGROUND

[0002] In recent years, with the development of the integration of new materials, the Internet of Things and artificial intelligence, water pollution monitoring has rapidly developed from traditional laboratory analysis to online, intelligent and ecological direction. Optical, electrochemical and biological sensors have become mainstream. Fluorescence-spectrum organic matter monitors can realize rapid early warning of water source pollution. GIS, remote sensing and model filling data gaps support diffusion simulation and health risk assessment of emerging pollutants such as PFAS, PPCPs and antibiotic resistance genes.

[0003] At present, a river water pollution real-time tracing method is disclosed in Chinese patent CN120233054A. The method obtains the location of the pollution source in the river basin, obtains the type of pollutants discharged by the pollution source, obtains the pollutant particle parameters and the pollutant type, obtains the river connection relationship of the river basin, confirms the input flow and output flow of the pollutant, obtains the theoretical pollutant level based on the output flow of the pollutant, the theoretical water flow velocity of the river basin and the pollutant particle parameters, obtains the measured pollutant level based on the measured pollutant concentration and the measured water flow velocity, and obtains the source of the pollutant based on the measured pollutant level and the theoretical pollutant level. However, the related art does not use a rapid detection method to locate the position of the pollution source, which is not conducive to the rapid response of pollution source detection. No monitoring method can be established to migrate with dynamic scenarios, which is not conducive to the dynamic and adaptive nature of pollution source detection. SUMMARY

[0004] The technical problem solved by the present application is that the related art does not use a rapid detection method to locate the position of the pollution source, which is not conducive to the rapid response of pollution source detection. No monitoring method can be established to migrate with dynamic scenarios, which is not conducive to the dynamic and adaptive nature of pollution source detection.

[0005] To solve the above technical problems, the present application provides the following technical solutions. In a first aspect, a pollution source detection method based on water environment governance includes the following steps: step S100, selecting any three non-collinear positions as detection points, and the detection points meet the first constraint condition. At the detection point, a first Brillouin linewidth laser is emitted in combination with the distribution range. The first Brillouin linewidth is adjusted based on the feedback data of the laser to obtain the self-Brillouin linewidth of the detection point. The initial emission direction is represented as an arbitrary direction. The emission direction of the detection point is determined by selecting the emission direction corresponding to the maximum energy of the reflected wave.

[0006] In step S200, based on the constructed pollutant diffusion model and the three-point positioning method, a polynomial corresponding to the three-dimensional Cartesian coordinates of the detection point is obtained.

[0007] In step S300, based on the polynomial corresponding to the three-dimensional Cartesian coordinates of the detection point and the pollutant parameters of the current detection point, the coordinates of the pollution source are moved, and the coordinates of the new pollution source are obtained.

[0008] As a preferred scheme of the pollution source detection method based on water environment treatment, step S100 includes the following sub-steps: in step S101, any water area to be detected is selected, and the distribution range of the water area to be detected is obtained;

[0009] In step S102, the geometric center point of the distribution range is obtained, any three non-collinear positions are selected as detection points, and the sum of the Euclidean distances between the detection points and the geometric center point is calculated. The sum of the Euclidean distances between the detection points and the geometric center point is greater than or equal to the first distance, which is the first constraint condition;

[0010] In step S103, any monitoring point is jumped to, and a laser with a first Brillouin linewidth is emitted at the detection point, wherein the first Brillouin linewidth is matched based on the distribution range;

[0011] In step S104, feedback data from the water area is received, and the feedback data is represented as the Brillouin linewidth of the laser reflected by the water area;

[0012] In step S105, the saturation coefficient is calculated according to the feedback data and the first Brillouin linewidth, the saturation coefficient is compared with the preset saturation threshold, and the first operation is performed on the first Brillouin linewidth according to the comparison result;

[0013] The first operation includes a regulation operation and a non-regulation operation;

[0014] When the first operation is the regulation operation, step S106 is jumped to, and when the first operation is the non-regulation operation, step S107 is jumped to;

[0015] In step S106, the first Brillouin linewidth is continuously changed until the saturation degree corresponding to the continuously changed first Brillouin linewidth is greater than or equal to the preset saturation threshold, and then step S107 is jumped to;

[0016] In step S107, the feedback data at this time is set as the self-Brillouin linewidth of the detection point;

[0017] In step S108, steps S101 to S107 are cycled to complete the self-Brillouin linewidth of each monitoring point of the water area to be detected.

[0018] As a preferred solution of the pollution source detection method based on water environment treatment, in the step S200, the following sub-steps are included: in the step S201, assuming that the water area is polluted, setting the pollution parameter of the pollution source, setting the three-dimensional coordinates of the pollution source as (0, 0, 0), and converting the ZP coordinates of each grid of the distribution boundary and the coordinates of the detection point from the ZP coordinate system to the three-dimensional Cartesian coordinate system;

[0019] In the step S202, the pollution parameter of the pollution source is longitudinally and laterally decomposed in the three-dimensional Cartesian coordinate system.

[0020] In the step S203, the historical flow parameters of the water area are obtained, and the longitudinal average flow rate and the lateral average flow rate are obtained according to the historical flow parameters of the water area.

[0021] In the step S204, the concentration change equation is obtained according to the longitudinally decomposed pollution parameter of the pollution source, the laterally decomposed pollution parameter of the pollution source, the longitudinal average flow rate and the lateral average flow rate.

[0022] In the step S205, the time-space model of the pollutant concentration is constructed according to the concentration change equation.

[0023] As a preferred solution of the pollution source detection method based on water environment treatment, in the step S205, the following sub-steps are included: in the step S2051, the boundary condition is constructed according to the three-dimensional Cartesian coordinates of each grid of the distribution boundary.

[0024] In the step S2052, the concentration change equation is solved according to the boundary condition, and the influence expression of the pollution source is obtained.

[0025] In the step S2053, the time-space model of the pollutant concentration is constructed according to the influence expression of the pollution source.

[0026] As a preferred solution of the pollution source detection method based on water environment treatment, the three-dimensional Cartesian coordinates of the detection point in any known origin are obtained, the straight line distance of any two coordinates is calculated, the sum of the straight line distances of the two coordinates is set as the second constraint condition, the straight line distance of any two coordinates is set as the third constraint condition, the three-dimensional Cartesian coordinates of the detection point are obtained, the three-dimensional Cartesian coordinates of the detection point are calculated by the three-dimensional distance formula, the equation group is constructed according to the three-dimensional distance formula, the third constraint condition and the second constraint condition, the polynomial corresponding to the three-dimensional Cartesian coordinates of the detection point is obtained, and the polynomial corresponding to the three-dimensional Cartesian coordinates of the detection point includes the polynomial expression corresponding to the x coordinate, the polynomial expression corresponding to the y coordinate and the polynomial expression corresponding to the z coordinate.

[0027] As a preferred scheme of the pollution source detection method based on water environment treatment, the current pollutant concentration of the three detection points is obtained, and the method for obtaining the current pollutant concentration of the three detection points comprises the following steps: matching the bulk viscosity coefficient of the water area and the shear viscosity coefficient of the water area corresponding to the self-emitted Brillouin linewidth, and matching the pollutant concentration corresponding to the bulk viscosity coefficient of the water area and the shear viscosity coefficient of the water area.

[0028] As a preferred scheme of the pollution source detection method based on water environment treatment, the method for obtaining the current pollutant concentration of the three detection points reverses the three-dimensional Cartesian coordinates of the pollution source according to the current pollutant concentration of the detection point and the polynomials corresponding to the three-dimensional Cartesian coordinates of the detection point.

[0029] The method for reversing the three-dimensional Cartesian coordinates of the pollution source comprises the following steps: bringing the current pollutant concentration of the detection point into the space-time model of the pollutant concentration to obtain a corresponding C value, calculating the average value of the C value, and setting the average value of the C value as the pollutant concentration of the pollution source.

[0030] As a preferred scheme of the pollution source detection method based on water environment treatment, the pollution source coordinates are continuously moved from (0, 0, 0), and during the continuous movement, the abscissa and ordinate of the pollution source coordinates are always distributed in the three-dimensional Cartesian coordinates of each grid of the distribution boundary, and the distribution is greater than or equal to the corresponding minimum value and less than or equal to the corresponding maximum value.

[0031] The C value corresponding to the pollution source coordinates after any movement is obtained, and the C value is subtracted from the average value of the C value to obtain a pollution concentration difference.

[0032] As a preferred scheme of the pollution source detection method based on water environment treatment, each pollution concentration difference is traversed, the smallest pollution concentration difference is selected, the three-dimensional Cartesian coordinates corresponding to the smallest pollution concentration difference are set as the coordinates of a new pollution source, and the three-dimensional Cartesian coordinates of the original pollution source are replaced according to the coordinates of the new pollution source.

[0033] The coordinates of the new pollution source are output.

[0034] In a second aspect, a pollution source detection system based on water environment treatment comprises a detection module, a calculation module and a positioning module.

[0035] The detection module selects any three non-collinear positions as detection points, and the detection points satisfy a first constraint condition. At the detection points, a first Brillouin linewidth is emitted in combination with a distribution range, the first Brillouin linewidth is adjusted based on feedback data of the laser to obtain a self-emitted Brillouin linewidth of the detection point.

[0036] The calculation module obtains a polynomial corresponding to the three-dimensional Cartesian coordinates of the detection point based on the constructed pollutant diffusion model and the three-point positioning method;

[0037] The positioning module moves the coordinates of the pollution source based on the polynomial corresponding to the three-dimensional Cartesian coordinates of the detection point and the pollutant parameter of the current detection point, and obtains the coordinates of the new pollution source.

[0038] The present application has the following advantages: the Brillouin linewidth is extremely sensitive to environmental parameter changes, and can detect trace changes in pollutant concentration; combined with model inversion, the positioning accuracy is greatly improved, which is superior to traditional infrared / visible light remote sensing; no need to approach the pollution area, data can be obtained through laser remote sensing, especially suitable for toxic, explosive, high-temperature or difficult-to-access environments, such as chemical plant leaks, nuclear contaminated areas, deep-sea hydrothermal vents, etc.; supports a closed-loop mechanism of detecting and updating in real time, and can track moving pollution sources in real time, such as ship pollution and vehicle leaks; the traditional method is mostly static snapshot, which cannot respond to dynamic changes; only three detection points are needed to realize three-dimensional positioning, without the need for dense sensor network, greatly reducing the hardware cost and maintenance burden, suitable for emergency rapid deployment; Brillouin scattering has a response to synchronous changes in temperature, pressure, flow rate, etc., and through multi-parameter coupling modeling, it can maintain stable performance under complex conditions such as wind field changes, terrain undulations, and water layering. BRIEF DESCRIPTION OF DRAWINGS

[0039] Figure 1 The basic flowchart of the pollution source detection method based on water environment treatment provided by an embodiment of the present application is shown. DETAILED DESCRIPTION

[0040] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0041] It should be understood that the step numbers used herein are only for the convenience of description, and do not limit the execution sequence of the steps. It should be understood that the terms used in the specification of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application.

[0042] As used in the specification and the appended claims of the present application, unless otherwise clearly indicated by the context, the singular forms "a", "an" and "the" are intended to include the plural forms as well.

[0043] The terms "comprise" and "include" indicate the presence of the described features, integers, steps, operations, elements, and / or components but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0044] The term "and / or" means any combination of one or more of the associated listed items and all possible combinations thereof, and includes these combinations.

[0045] With the development of the integration of new materials, Internet of Things, and artificial intelligence, water pollution monitoring has rapidly developed from traditional laboratory analysis to online, intelligent, and ecological direction. Optical, electrochemical, and biological sensors have become mainstream. Fluorescence-spectrum organic matter monitoring instruments can realize rapid early warning of water source pollution. GIS, remote sensing, and models fill in data gaps to support diffusion simulation and health risk assessment of emerging pollutants such as PFAS, PPCPs, and antibiotic resistance genes.

[0046] Based on this, the embodiment of the present application provides a pollution source detection method based on water environment governance.

[0047] The pollution source detection method based on water environment governance provided by the embodiment of the present application relates to the field of intelligent detection. The pollution source detection method based on water environment governance provided by the embodiment of the present application can be applied to a terminal, can be applied to a server side, and can also be software running in a terminal or a server side. In some embodiments, the terminal can be a smart phone, a tablet computer, a notebook computer, a desktop computer, etc. The server side can be configured as an independent physical server, can be configured as a server cluster or a distributed system composed of multiple physical servers, can also be configured as a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and basic cloud computing services such as big data and artificial intelligence platforms, etc. The software can be an application that implements the pollution source detection method based on water environment governance, etc., but is not limited to the above forms.

[0048] The application can also be implemented in a variety of computing system environments or configurations, including a personal computer, a server computer, a handheld or portable device, a tablet, a multiprocessor system, a microprocessor-based system, a set top box, programmable consumer electronics, a network PC, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like. The application can be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, and the like, that perform particular tasks or implement particular abstract data types. The application can also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules can be located in both local and remote computer storage media including memory storage devices.

[0049] Embodiments, with reference to Figure 1 For an embodiment of the application, a pollution source detection method based on water environment treatment is provided, including the following steps: step S100, selecting any three non-collinear positions as detection points, and the detection points meet the first constraint condition; at the detection point, a laser with a first Brillouin linewidth is emitted in combination with the distribution range, the first Brillouin linewidth is adjusted based on the feedback data of the laser, and the self-Brillouin linewidth of the detection point is obtained, wherein the initial emission direction is represented as an arbitrary direction, and the emission direction of the detection point is determined by selecting the emission direction corresponding to the maximum energy of the reflected wave;

[0050] Step S200, based on the constructed pollutant diffusion model and the three-point positioning method, a polynomial corresponding to the three-dimensional Cartesian coordinates of the detection point is obtained.

[0051] Step S300, based on the polynomial corresponding to the three-dimensional Cartesian coordinates of the detection point and the pollutant parameters of the current detection point, the coordinates of the pollution source are moved, and the coordinates of the new pollution source are obtained.

[0052] Further preferably, the self-lasing Brillouin linewidth is extremely sensitive to changes in environmental parameters, can detect changes in trace pollutant concentrations, and combined with model inversion, greatly improves positioning accuracy, is superior to traditional infrared / visible light remote sensing, does not need to approach the pollution area, and can obtain data through laser remote sensing, is particularly suitable for toxic, explosive, high-temperature or difficult-to-access environments, such as chemical plant leaks, nuclear contaminated areas, deep-sea hydrothermal vents, etc., supports a closed-loop mechanism that detects and updates in real time, can track moving pollution sources such as ship emissions and vehicle leaks, and traditional methods are mostly static snapshots that cannot respond to dynamic changes. Only three detection points are needed to achieve three-dimensional positioning, there is no need for a dense sensor network, which greatly reduces hardware costs and maintenance burdens, and is suitable for emergency rapid deployment. Brillouin scattering responds to simultaneous changes in temperature, pressure, flow rate, etc., and through multi-parameter coupling modeling, it can maintain stable performance under complex conditions such as changes in wind fields, terrain undulations, and water layering.

[0053] Further preferably, the water area, such as a river, ocean, etc., has a water surface with different elevations, i.e., the water surface can be considered as a three-dimensional space, so three non-collinear position points are selected as detection points, which is conducive to the back calculation of the corresponding self-lasing Brillouin linewidth of the pollution source.

[0054] Further preferably, the present application is based on the assumption that the water area has been polluted by industrial wastewater, domestic wastewater, etc., so the Brillouin linewidth of the pollution source can be bound with the bulk viscosity coefficient of the water area and the shear viscosity coefficient of the water area, and the bulk viscosity coefficient of the water area and the shear viscosity coefficient of the water area are not constant values of pure water, i.e., the detection process of the present application is meaningful. When the pollution of any water area to be detected is not serious, i.e., the calculated Brillouin linewidth of the pollution source is less than or equal to the first linewidth, then jump to the next water area to be detected. Since only three detection points are selected for reasoning, the rapid response of the detection is improved, and compared with the prior art, there is a significant progress.

[0055] Step S100 includes the following sub-steps, step S101, selecting any water area to be detected, obtaining the distribution range of the water area to be detected;

[0056] Step S102, obtaining the geometric center point of the distribution range, selecting any three non-collinear positions as detection points, calculating the sum of the Euclidean distances between the detection points and the geometric center point, and setting the sum of the Euclidean distances between the detection points and the geometric center point to be greater than or equal to the first distance as the first constraint condition;

[0057] Step S103, jumping to any monitoring point, emitting a first Brillouin linewidth laser at the detection point, wherein the first Brillouin linewidth is matched based on the distribution range;

[0058] Step S104, receiving feedback data from the water area, the feedback data representing the Brillouin linewidth of the laser reflected back by the water area;

[0059] S105, according to the feedback data and the first Brillouin line width calculation saturation coefficient, the saturation coefficient and the preset saturation threshold comparison, according to the comparison result, the first operation of the first Brillouin line width is executed;

[0060] The first operation includes regulation operation and non-regulation operation;

[0061] When the first operation is the regulation operation, jump to step S106, when the first operation is the non-regulation operation, jump to step S107;

[0062] Step S106, the first Brillouin line width is continuously changed, until the saturation degree corresponding to the first Brillouin line width after continuous change is greater than or equal to the preset saturation threshold, jump to step S107;

[0063] Step S107, the feedback data at this time is set as the self-publishing Brillouin line width of the detection point;

[0064] Step S108, the steps S101~S107 are cycled, and the self-publishing Brillouin line width of each monitoring point of the water area to be detected is completed.

[0065] Further preferably, the distribution range is represented as a spatial curved surface constituted by a water area plane, and the distribution range contains a distribution boundary, and the distribution boundary is automatically obtained by a boundary layer extraction code.

[0066] Further preferably, the distribution range is automatically cut into each two-dimensional grid based on a finite element segmentation algorithm.

[0067] Further preferably, the first Brillouin line width is configured with a matching method, and the matching method comprises: obtaining the distribution boundary, obtaining the straight line distance of the pixel coordinates of any two grid points in the distribution boundary, sorting the straight line distance in descending order, selecting the two grid points corresponding to the largest numerical value of the straight line distance as the boundary points, obtaining the pixel coordinates of the boundary points, and converting the pixel coordinates of the boundary points from the pixel coordinate system to the ZP coordinate system (spatial rectangular coordinate system);

[0068] Obtaining the straight line distance of the boundary points in the ZP coordinate system, recording the straight line distance of the boundary points in the ZP coordinate system as the effective medium length, obtaining the ZP coordinates of the geometric center point of any detection point, obtaining the scattering light intensity corresponding to the ZP coordinates of the geometric center point of the detection point according to the effective medium length and the calculation expression of the scattering light intensity, calling the emission database, inputting the scattering light intensity corresponding to the ZP coordinates of the geometric center point of the detection point into the emission database, matching the corresponding Brillouin line width, and recording the corresponding Brillouin line width as the first Brillouin line width.

[0069] Further preferably, the calculation expression of the scattering light intensity is ;

[0070] wherein, is the effective medium length, is the ZP coordinate of the geometric center point of the detection point corresponding to the scattered light intensity, and g are both constants, and e is a constant.

[0071] Further preferably, the first value is set as a saturation threshold, a saturation coefficient is calculated according to the feedback data and the first Brillouin linewidth, and the saturation coefficient is configured to have a calculation method, the calculation method comprising: calculating a first difference value of the feedback data and the first Brillouin linewidth, calculating a first ratio of the first difference value and the first Brillouin linewidth, and setting the first saturation degree as the saturation coefficient, wherein the greater the value of the saturation coefficient, the greater the matching degree of the emission parameter and the detection point.

[0072] Further preferably, when the comparison result is that the saturation coefficient is less than the preset saturation threshold, the first operation is set as a regulation operation, and when the comparison result is that the saturation coefficient is greater than or equal to the preset saturation threshold, the first operation is set as a regulation operation.

[0073] Further preferably, continuously changing the first Brillouin linewidth is achieved by changing the incident light wavelength and the incident angle, and the continuous change means continuously increasing or continuously decreasing the first Brillouin linewidth;

[0074] The first wavelength is set as a wavelength change amount, the first angle is set as an angle change amount, the incident light wavelength is continuously increased or continuously decreased according to the first wavelength, and the incident angle is continuously increased or continuously decreased according to the first angle;

[0075] wherein, the change frequency of the incident light wavelength and the incident angle is the same, that is, a single regulation process includes regulating the incident light wavelength once and regulating the incident angle once.

[0076] Step S200 includes the following sub-steps: step S201, assuming that the water area is contaminated, setting a pollution parameter of a pollution source, setting the three-dimensional coordinates of the pollution source as (0, 0, 0), and converting the ZP coordinates of each grid of the distribution boundary and the coordinates of the detection point from the ZP coordinate system to the three-dimensional Cartesian coordinate system;

[0077] Step S202, longitudinally decomposing and transversely decomposing the pollution parameter of the pollution source in the three-dimensional Cartesian coordinate system;

[0078] Step S203, obtaining a historical flow parameter of the water area, and obtaining a longitudinal average flow velocity and a transverse average flow velocity according to the historical flow parameter of the water area;

[0079] Step S204, obtaining a concentration variation equation according to the pollution parameters of the pollution source after longitudinal decomposition, the pollution parameters of the pollution source after transverse decomposition, the longitudinal average flow velocity and the transverse average flow velocity;

[0080] Step S205, constructing a time-space model of the pollutant concentration according to the concentration variation equation.

[0081] Further preferably, the pollution parameters are represented as the pollutant concentration and the pollutant emission amount.

[0082] Further preferably, the historical flow parameters include a historical flow direction and a historical flow velocity, the historical flow velocity is obtained by an image method flow measurement method, and the historical flow direction is represented as a direction of a vector corresponding to the pollutant at the assumed pollution source being tangent to the water surface, and the flow velocity being from large to small and along a direction of a central axis of the water area.

[0083] Further preferably, the central axis of the water area is represented as a connecting line of midpoints of the water surface of the water source except for a boundary of the bank, the connecting line being a curve and parallel to any bank of the water area.

[0084] Further preferably, the concentration variation equation is, ;

[0085] wherein C is the pollutant concentration at the pollution source, t is a number of a monitoring time point, that is, data is collected for the tth time according to a detection period, the detection period being able to be changed, is a transverse diffusion coefficient, is a longitudinal diffusion coefficient, is a transverse average flow velocity, is a longitudinal average flow velocity, and S is a compensation coefficient, is a sum value of the compensation coefficients of each iteration, the longitudinal diffusion coefficient, the transverse diffusion coefficient and the compensation coefficient are all constants, is a partial derivative symbol.

[0086] Further preferably, for C, an equation of C is represented as C=f(t)=ax+by, which is represented as, at the t time, the pollutant concentration at the position of the pollution source, and also represented as, a sum value of decomposition amounts of a vector corresponding to the pollutant in x and y axes, wherein a modulus of the vector corresponding to the pollutant is the pollutant concentration, a direction of the vector corresponding to the pollutant is tangent to the water surface, and the flow velocity is from large to small and along a direction of a central axis of the water area.

[0087] Step S205 further includes the following sub-steps, step S2051, constructing a boundary condition according to three-dimensional Cartesian coordinates of each grid of the distribution boundary;

[0088] Step S2052, solving the concentration variation equation according to the boundary condition to obtain an influence expression of the pollution source;

[0089] Step S2053, constructing the time-space model of the pollutant concentration according to the influence expression of the pollution source.

[0090] Further preferably, the influence expression of the pollution source comprises the mass concentration increment of the pollution source at other coordinate points, the mass concentration increment of the near-shore reflection at other points, and the mass concentration increment of the far-shore reflection at other points.

[0091] Further preferably, the boundary condition is expressed as that the value of C is C0 when x is 0 and t is 0, and C is 0 when t tends to infinity;

[0092] Further preferably, the influence expression of the pollution source is

[0093]

[0094]

[0095]

[0096] wherein M is the pollutant emission amount, b is the straight-line distance of the pollution source from the nearest shore of the expected distance, B and h are the maximum width of the water area and the average depth of the water area respectively, n is the reflection number of the shore, x is the difference between the other coordinate point and the horizontal coordinate of the pollution source, y is the difference between the other coordinate point and the vertical coordinate of the pollution source, is the mass concentration increment of the pollution source at other coordinate points, is the mass concentration increment of the near-shore reflection at other points, is the mass concentration increment of the far-shore reflection at other points.

[0097] Further preferably, the time-space model of the pollutant concentration is

[0098] obtaining the coordinate points of the detection point in a three-dimensional Cartesian coordinate system with any known origin, calculating the straight-line distance of any two coordinates, calculating the sum of the straight-line distances of the two coordinates, setting the sum of the straight-line distances of the two coordinates as the second constraint condition, setting the straight-line distance of any two coordinates as the third constraint condition, obtaining the three-dimensional Cartesian coordinates of the detection point, wherein the three-dimensional Cartesian coordinates of the detection point are calculated through a three-dimensional distance formula, constructing an equation group according to the three-dimensional distance formula, the third constraint condition and the second constraint condition, obtaining the polynomial corresponding to the three-dimensional Cartesian coordinates of the detection point, and the polynomial corresponding to the three-dimensional Cartesian coordinates of the detection point comprises a polynomial expression corresponding to the x coordinate, a polynomial expression corresponding to the y coordinate and a polynomial expression corresponding to the z coordinate respectively;

[0099] ​​​​​The current pollutant concentration of the three detection points is obtained, and the method for obtaining the current pollutant concentration of the three detection points comprises the following steps: matching the bulk viscosity coefficient of the water area and the shear viscosity coefficient of the water area corresponding to the self-published Brillouin line width, and matching the pollutant concentration corresponding to the bulk viscosity coefficient of the water area and the shear viscosity coefficient of the water area according to the bulk viscosity coefficient of the water area and the shear viscosity coefficient of the water area.

[0100] Further preferably, the current pollutant concentration represents the pollutant concentration at the current time point adjusted according to the detection period, that is, the current pollutant concentration corresponding to different detection periods is different.

[0101] Further preferably, the matching method of the bulk viscosity coefficient of the water area and the shear viscosity coefficient of the water area comprises the following steps: calling a water quality parameter lookup table, inputting the self-published Brillouin line width into the water quality parameter lookup table, and matching the bulk viscosity coefficient of the water area and the shear viscosity coefficient of the water area corresponding to the self-published Brillouin line width.

[0102] Further preferably, the matching method of the pollutant concentration comprises the following steps: calling a pollution parameter lookup table, inputting the bulk viscosity coefficient of the water area and the shear viscosity coefficient of the water area into the pollution parameter lookup table, obtaining the pollutant concentration corresponding to the bulk viscosity coefficient of the water area and the shear viscosity coefficient of the water area, and recording the pollutant concentration as the current pollutant concentration.

[0103] The method for obtaining the current pollutant concentration of the three detection points reverses the three-dimensional Cartesian coordinates of the pollution source according to the current pollutant concentration of the detection point and the polynomial corresponding to the three-dimensional Cartesian coordinates of the detection point.

[0104] The reverse method of the three-dimensional Cartesian coordinates of the pollution source comprises the following steps: inputting the current pollutant concentration of the detection point into a space-time model of the pollutant concentration to obtain a corresponding C value, calculating the average value of the C value, and setting the average value of the C value as the pollutant concentration of the pollution source.

[0105] The pollution source coordinates are continuously moved from (0, 0, 0), and during the continuous movement, the horizontal coordinate and the vertical coordinate of the pollution source coordinates are always distributed in the three-dimensional Cartesian coordinates of each grid of the distribution boundary, and the distribution is represented as greater than or equal to the corresponding minimum value and less than or equal to the corresponding maximum value.

[0106] The C value corresponding to the pollution source coordinates after any movement is obtained, and the C value is subtracted from the average value of the C value to obtain a pollution concentration difference.

[0107] Each pollution concentration difference is traversed, and the smallest pollution concentration difference is selected. The three-dimensional Cartesian coordinates corresponding to the smallest pollution concentration difference are set as the coordinates of the new pollution source, and the original three-dimensional Cartesian coordinates of the pollution source are replaced according to the coordinates of the new pollution source.

[0108] The coordinates of the new pollution source are output.

[0109] Further preferably, the Brillouin linewidth is extremely sensitive to changes in environmental parameters and can detect changes in trace pollutant concentrations. Combined with model inversion, the positioning accuracy is significantly improved, outperforming traditional infrared / visible light remote sensing. It does not require proximity to the contaminated area; data can be acquired through laser remote sensing. It is particularly suitable for toxic, explosive, high-temperature, or inaccessible environments, such as chemical plant leaks, nuclear contaminated areas, and deep-sea hydrothermal vents. It supports a closed-loop mechanism of simultaneous detection and updating, enabling real-time tracking of mobile pollution sources, such as ship discharges and vehicle leaks. In contrast, traditional methods are mostly static snapshots and cannot respond to dynamic changes. Three-dimensional positioning can be achieved with only three detection points, eliminating the need for dense sensor networks, significantly reducing hardware costs and maintenance burdens, and making it suitable for rapid emergency deployment. Brillouin scattering responds to synchronous changes in temperature, pressure, and flow velocity. Through multi-parameter coupled modeling, it can maintain stable performance under complex conditions such as wind field changes, terrain undulations, and water stratification.

[0110] Example 2: Three non-collinear detection points;

[0111]

[0112] The laser emission parameters include a pulse energy of 120 mJ, a pulse width of 8 ns, an initial Brillouin linewidth of 650 MHz, and a saturation coefficient of 0.92 after four adjustments of the feedback data. Since 0.92 is greater than or equal to 0.85 (threshold), the Brillouin linewidth is locked.

[0113] The relationship between the width of the Liyuan Line and the current pollutant concentration is as follows:

[0114]

[0115] It is 0.047ms -1 , It is 0.183ms -1 , It is 0.11m 2 s -1 , It is 0.38m 2 s -1 k is 0.012, h is 1.7m, and... , , , Substituting k and h into the expression for the impact of the pollution source, we get , , The expression;

[0116] The relationship between the self-published Brillouin linewidth and the current pollutant concentration is substituted into the space-time model to obtain the coordinates at which the residual error between the calculated concentration and the measured concentration is minimized, the search step is 1 m, the grid is traversed in 4.8 km*46 km, and the minimum pollutant concentration difference ΔCmin is 0.18 mg / L -1 Corresponding to the new pollution source coordinates (4438492, 4521945, 1.0 m), the point is 12 m away from the nearest shore slope;

[0117] The first Brillouin linewidth acquisition step and experimental data include: using the Canny algorithm to extract the edge of the distribution range binary image obtained in step S101 to obtain a set of boundary pixel points;

[0118] In the pixel coordinate system, traverse the distance between any two points, take the maximum value, and convert it to the ZP coordinate system according to the first proportion to obtain L. L is brought into the calculation expression of the scattering light intensity to calculate the scattering light intensity corresponding to the geometric center of the detection point.

[0119] In the laboratory temperature-controlled pool (20±0.2℃), a standard Brillouin scatterometer is used to establish the corresponding relationship between the Brillouin linewidth and the scattering light intensity from 0 to 1200 MHz, and the corresponding relationship is stored in the emission database.

[0120] The first Brillouin linewidth acquisition experimental data are as follows:

[0121]

[0122] The method for converting the ZP coordinate system to the three-dimensional Cartesian coordinate system in Example 3 includes: the origin is the geometric center of the distribution range of the water area to be measured; the Z axis is along the normal direction of the water surface, and the direction along the normal direction of the water surface upward is the positive direction of the Z axis; the P axis is the projection of the main flow direction of the water area in the horizontal plane, i.e. the projection of the central axis of the water area in the horizontal plane, and the direction of the projection of the main flow direction of the water area in the horizontal plane pointing to the downstream is the positive direction of the P axis; the third axis is orthogonal to the P axis in the horizontal plane, forming a right-hand system.

[0123] The three-dimensional Cartesian coordinate system adopts the local NEU (North, East, Sky) system of the national 2000 geodetic coordinate system (CGCS2000), the positive direction of the X axis is north; the positive direction of the Y axis is east; and the positive direction of the Z axis is skyward.

[0124] The conversion of the ZP coordinate system to the three-dimensional Cartesian coordinate system adopts a seven-parameter Bursa model, and the conversion parameters are obtained by field measurement. A GNSS receiver is erected at the geometric center, and continuous observation is performed for 5 minutes to obtain the origin coordinates. The main flow direction azimuth is measured by a digital compass to obtain the unit vectors of the P axis, the Z axis and the Q axis in the north-east plane.

[0125] The calculation method of the second constraint condition comprises a minimum value of a sum of straight line distances between any two of the three detection points, for ensuring geometric strength of spatial distribution of the three points, and the coordinates of the three detection points in a three-dimensional Cartesian system are known, and the distance between any two of the detection points is calculated by using a Euclidean distance formula;

[0126] The sum of the distances between the two detection points in each group, i.e., the sum of the straight line distances of the two coordinates, is calculated, and the second distance is set as a threshold value of the sum of the straight line distances of the two coordinates;

[0127] The sum of the straight line distances of the two coordinates greater than or equal to the second distance is set as the second constraint condition.

[0128] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system or a computer program product. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media having computer-usable program code embodied in the medium. The storage media can be realized by any type of volatile or non-volatile storage devices or a combination thereof, such as a static random access memory (SRAM), an electrically erasable programmable read-only memory (EEPROM), an erasable programmable read-only memory (EPROM), a programmable read-only memory (PROM), a read-only memory (ROM), a magnetic storage, a flash memory, a magnetic disk or an optical disk. The computer program instructions can also be stored in a computer readable storage medium which can guide a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable storage medium produce a manufactured product including instruction devices which realize the functions specified in the flowcharts Figure 1 one or more flows and / or blocks Figure 1 one or more blocks.

[0129] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present application but not limit the present application. Although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or replaced by equivalents without departing from the spirit and scope of the present application, and all of them should be covered in the protection scope of the present application.

Claims

1. A pollution source detection method based on water environment management, characterized in that, The process includes the following steps: Step S100, select any three non-collinear locations as detection points, and the detection points satisfy the first constraint condition. At the detection points, based on the distribution range, emit a laser with a first Brillouin linewidth. Based on the feedback data of the laser, adjust the first Brillouin linewidth to obtain the spontaneous Brillouin linewidth of the detection point. The initial emission direction is represented as an arbitrary direction. The emission direction of the detection point is determined by selecting the emission direction corresponding to the energy of the largest reflected wave. The first constraint condition is expressed as follows: the sum of the Euclidean distances between the detection location and the geometric center point is greater than or equal to the first distance. Step S200: Based on the constructed pollutant diffusion model and the three-point positioning method, obtain the polynomial corresponding to the three-dimensional Cartesian coordinates of the detection point, and construct a spatiotemporal model of pollutant concentration according to the polynomial corresponding to the three-dimensional Cartesian coordinates of the detection point. Step S300: Calculate the coordinates of the new pollution source based on the spatiotemporal model of pollutant concentration; Step S200 includes the following sub-steps: Step S201, set the pollution parameters of the pollution source, set the three-dimensional coordinates of the pollution source to (0, 0, 0), and transform the ZP coordinates of each grid of the distribution boundary and the coordinates of the detection points from the ZP coordinate system to the three-dimensional Cartesian coordinate system. Step S202: Decompose the pollution parameters of the pollution source vertically and horizontally in a three-dimensional Cartesian coordinate system. Step S203: Obtain the historical flow parameters of the water body, and based on the historical flow parameters of the water body, obtain the longitudinal average flow velocity and the transverse average flow velocity; Step S204: Based on the pollution parameters of the pollution sources after vertical decomposition, the pollution parameters of the pollution sources after horizontal decomposition, the longitudinal average flow velocity, and the horizontal average flow velocity, obtain the concentration change equation. Step S205: Construct a spatiotemporal model of pollutant concentration based on the concentration change equation; Pollution parameters are expressed as pollutant concentration and pollutant emission. Historical flow parameters include historical flow direction and historical flow velocity. Historical flow velocity is obtained through image-based flow measurement methods. Historical flow direction is represented by the direction of the vector corresponding to the pollutants at the assumed pollution source, which is tangent to the water surface, with the flow velocity decreasing from large to small, and along the central axis of the water body. The central axis of a body of water is represented by a line connecting the midpoints of the water surface of the water source, excluding the boundaries of the shore. The line is a curve and is parallel to any shore of the body of water. The equation for concentration change is: ; Where C represents the pollutant concentration at the pollution source, and t is the monitoring time point number, i.e., the data collected in the t-th instance according to the monitoring cycle. The monitoring cycle can be changed. The lateral diffusion coefficient is... The longitudinal diffusion coefficient is... The lateral average flow velocity, Where S is the longitudinal average flow velocity, and S is the compensation coefficient. Let be the sum of the compensation coefficients from each iteration. The longitudinal diffusion coefficient, transverse diffusion coefficient, and compensation coefficient are all constants. The sign for partial derivatives; For C, the equation of C is C=f(t)=ax+by, which represents the pollutant concentration at the pollution source location at time t. It also represents the sum of the decomposition values ​​of the pollutant vector on the x-axis and y-axis. The magnitude of the pollutant vector is the pollutant concentration, and the direction of the pollutant vector is tangent to the water surface, with the flow velocity decreasing from large to small, and along the central axis of the water area. Step S205 also includes the following sub-steps: Step S2051, construct boundary conditions based on the three-dimensional Cartesian coordinates of each grid of the distribution boundary. Step S2052: Solve the concentration change equation according to the boundary conditions to obtain the influence expression of the pollution source; Step S2053: Based on the influence expression of the pollution source, construct a spatiotemporal model of pollutant concentration; The expression for the impact of the pollution source includes the increase in mass concentration at other coordinate points of the pollution source, the increase in mass concentration at other points due to nearshore reflection, and the increase in mass concentration at other points due to offshore reflection. The boundary conditions are expressed as follows: when x is 0 and t is 0, the value of C is C0; when t approaches infinity, C is 0. The expression for the impact of the pollution source is: ; = ； ； ； Where M represents the pollutant emission amount, b is the straight-line distance from the pollution source to the nearest shore, B and h are the maximum width and average depth of the water area, respectively, n is the number of reflections from the shore, x is the difference between the x-coordinate of other coordinate points and the pollution source, and y is the difference between the y-coordinate of other coordinate points and the pollution source. This represents the increase in mass concentration of the pollution source at other coordinate points. This represents the increase in mass concentration at other points due to near-shore reflection. The increase in mass concentration at other points due to reflection from the far shore; The spatiotemporal model for pollutant concentration is C= ; Obtain the coordinates of the detection point in a three-dimensional Cartesian coordinate system with any known origin. Calculate the straight-line distance between any two coordinates. Calculate the sum of the straight-line distances between the two coordinates. Set the sum of the straight-line distances between the two coordinates as the second constraint condition. Set the straight-line distance between any two coordinates as the third constraint condition. Obtain the three-dimensional Cartesian coordinates of the detection point. The three-dimensional Cartesian coordinates of the detection point are calculated using the three-dimensional distance formula. Construct a system of equations based on the three-dimensional distance formula, the third constraint condition, and the second constraint condition to obtain the polynomial corresponding to the three-dimensional Cartesian coordinates of the detection point. The polynomial corresponding to the three-dimensional Cartesian coordinates of the detection point includes polynomial expressions for the x-coordinate, y-coordinate, and z-coordinate, respectively. The current pollutant concentrations at three monitoring points are obtained. The method for obtaining the current pollutant concentrations at three monitoring points includes matching the volume viscosity coefficient and shear viscosity coefficient of the corresponding water body with the corresponding self-published water body line width, and matching the corresponding pollutant concentrations based on the volume viscosity coefficient and shear viscosity coefficient of the water body. The current pollutant concentration is expressed as the pollutant concentration at the current point in time, adjusted according to the detection cycle; that is, the current pollutant concentration is different for different detection cycles. The matching method for the volume viscosity coefficient and the shear viscosity coefficient of a water body includes retrieving a water quality parameter lookup table, inputting the self-published nadir line width into the water quality parameter lookup table, and matching the volume viscosity coefficient and the shear viscosity coefficient of the water body corresponding to the self-published nadir line width. The method for matching pollutant concentrations includes retrieving a pollution parameter lookup table, inputting the volume viscosity coefficient and shear viscosity coefficient of the water body into the pollution parameter lookup table, obtaining the pollutant concentration corresponding to the volume viscosity coefficient and shear viscosity coefficient of the water body, and recording it as the current pollutant concentration. The method for obtaining the current pollutant concentration at the three monitoring points is to inversely deduce the three-dimensional Cartesian coordinates of the pollution source based on the current pollutant concentration at the monitoring point and the polynomial corresponding to the three-dimensional Cartesian coordinates of the monitoring point. The three-dimensional Cartesian coordinate inverse method for pollution sources includes: inputting the current pollutant concentration at the detection point into the spatiotemporal model of pollutant concentration to obtain the corresponding C value; calculating the average value of the C value; and setting the average value of the C value as the pollutant concentration of the pollution source. The pollution source coordinates are continuously moved from (0, 0, 0), and during the continuous movement, the x-coordinate and y-coordinate of the pollution source coordinates are always distributed in the three-dimensional Cartesian coordinates of each grid on the distribution boundary, which is represented as greater than or equal to the corresponding minimum value and less than or equal to the corresponding maximum value. Obtain the C value corresponding to the coordinates of the pollution source after any movement, and calculate the difference between the C value and the average of the C values ​​to obtain the pollution concentration difference. Iterate through all pollution concentration differences, select the pollution concentration difference with the smallest value, set the three-dimensional Cartesian coordinates corresponding to the pollution concentration difference with the smallest value as the coordinates of the new pollution source, and replace the three-dimensional Cartesian coordinates of the original pollution source with the coordinates of the new pollution source. Output the coordinates of the new pollution source.

2. The pollution source detection method based on water environment management as described in claim 1, characterized in that, Step S100 includes the following sub-steps: Step S101, select any water area to be detected and obtain the distribution range of the water area to be detected; Step S102: Obtain the geometric center point of the distribution range, select any three non-collinear positions as detection locations, and calculate the sum of the Euclidean distances between the detection locations and the geometric center point; Step S103: Jump to any monitoring point, and at that monitoring point, emit a laser with a first Brillouin linewidth, wherein the first Brillouin linewidth is matched based on the distribution range; Step S104: Receive feedback data from the water area, where the feedback data is represented as the Brillouin linewidth of the laser reflected back from the water area; Step S105: Calculate the saturation coefficient based on the feedback data and the first Brillouin linewidth, compare the saturation coefficient with the preset saturation threshold, and perform the first operation on the first Brillouin linewidth based on the comparison result. The first operation includes both control and non-control operations; When the first operation is a control operation, proceed to step S106; when the first operation is a non-control operation, proceed to step S107. Step S106: Continuously change the first Brillouin linewidth until the saturation corresponding to the continuously changed first Brillouin linewidth is greater than or equal to the preset saturation threshold, then jump to step S107. Step S107: Set the feedback data at this time to the self-published line width of the detection point; Step S108, repeat steps S101 to S107, to complete the self-released abyssal line width of each monitoring point in the water area to be tested.

3. A pollution source detection system based on water environment management, the system being used to execute the pollution source detection method based on water environment management as described in claim 1, characterized in that, It includes a detection module, a calculation module, and a positioning module; The detection module selects any three non-collinear positions as detection locations, and the detection locations satisfy the first constraint condition. At the detection points, combined with the distribution range, a laser with a first Brillouin linewidth is emitted. Based on the feedback data of the laser, the first Brillouin linewidth is adjusted to obtain the spontaneous Brillouin linewidth of the detection point. The calculation module obtains the polynomial corresponding to the three-dimensional Cartesian coordinates of the detection point based on the constructed pollutant diffusion model and the three-point positioning method. The positioning module moves the coordinates of the pollution source based on the polynomial corresponding to the three-dimensional Cartesian coordinates of the detection point and the pollutant parameters of the current detection point, and obtains the new coordinates of the pollution source.

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