Data management system and method for wastewater monitoring

Abstract

The invention discloses a data management system and method for wastewater monitoring, and relates to the technical field of data management, and the method comprises the steps: shooting a panoramic image of a wastewater discharge pool, obtaining historical sampling data, and obtaining all feature sampling data; determining the total number of the wastewater monitoring devices, dividing a water pool area into a plurality of feature areas according to the water pool area corresponding to the wastewater discharge pool and the water body feature ratio corresponding to each piece of feature sampling data, and setting the number of cycles for circulation to obtain a target area in the water pool area and a corresponding target point; and determining a target sampling number, obtaining a water body characteristic degree of each target point, marking the target points according to the distance between the target points, and sampling at the marked target points. According to the invention, the position of the sampling point is intelligently and reasonably selected according to the actual characteristics of the water body, so that the sampled data is more representative, and powerful data support is provided for subsequent wastewater treatment work.

Description

Technical Field

[0001] The present invention relates to the technical field of data management, and in particular to a data management system and method for wastewater monitoring. Background Art

[0002] During the operation of the factory, various types of wastewater will be continuously generated. These wastewaters must undergo multiple treatment steps before they can meet the discharge standards. Before discharge, sampling is crucial. It is a key link to ensure that the discharged water meets the standards. Wastewater is generally stored in wastewater discharge pools such as regulating tanks, disinfection tanks and sedimentation tanks, and then sampled. However, as far as the current sampling situation is concerned, there are some problems that cannot be ignored: relying on manual sampling is the main sampling method at present, and this method will have problems such as improper selection of sampling points, low efficiency and high subjectivity in sampling, resulting in the lack of representativeness of the sampled data. Therefore, the sampling point location should be selected intelligently and reasonably according to the actual characteristics of the water body to make the sampled data more representative. Not only can we fully understand whether the wastewater treatment process is reasonable, but also accumulate valuable data resources for subsequent wastewater treatment work, and provide strong data support for it. ‌ Summary of the invention

[0003] The object of the present invention is to provide a data management system and method for wastewater monitoring to solve the problems raised in the prior art.

[0004] To achieve the above object, the present invention provides the following technical solutions: A data management method for wastewater monitoring, comprising the following steps: Step S100: taking a panoramic image of the wastewater discharge pool, establishing a plane coordinate system of the wastewater discharge pool, obtaining historical sampling data, obtaining the water body characteristic degree corresponding to each sampling data according to the position of the sampling point corresponding to each sampling data in the plane coordinate system, and the water body state parameters at the time of sampling, and converting it into a water body characteristic ratio, and then obtaining all characteristic sampling data according to the sampling results corresponding to each sampling data; In this scheme, a drone can be deployed directly above the wastewater discharge pool to take a panoramic image. The panoramic image should take a complete picture of the wastewater discharge pool, and a plane coordinate system can be obtained according to the length and width of the wastewater discharge pool. Step S200: determining the total number of wastewater monitoring devices, and dividing the pool area into a number of characteristic areas according to the pool area corresponding to the wastewater discharge pool and the water body characteristic ratio corresponding to each characteristic sampling data; Step S300: according to the water body characteristic ratio corresponding to each characteristic sampling data, the number of cycles is set to cycle, the target area in the pool area and the target point corresponding to each target area are obtained, and each wastewater monitoring device is deployed at the target point position; Step S400: Determine the target sampling quantity, obtain the water body characteristic degree of each target point by analyzing the monitoring data of the wastewater monitoring equipment, mark the target points according to the distance between the target points, and perform sampling at the marked target points.

[0005] Furthermore, step S100 includes: Step S110: randomly select a number of sampling points from the plane coordinate system, and perform sampling at each sampling point as a batch of sampling data, and then randomly select a number of sampling points and perform sampling, and so on, to obtain a number of batches, and classify all sampling data of the same batch into a sampling set to obtain a number of sampling sets; the sampling data includes the sampling point, sampling time, water state parameters, and sampling results during sampling, and the sampling results include water quality parameters; in the plane coordinate system, the boundary area of ​​the wastewater discharge pool and the area of ​​the components whose height is greater than the height threshold are obtained, and are all used as obstacle areas; Step S120: Obtain a sampling point P0 corresponding to a certain sampling data in a certain sampling set, take the sampling point P0 as the center and the range of radius r as the sampling detection range, divide the radius r evenly into N parts, and then divide the sampling detection range into N sub-detection ranges, and sort them in order from small to large in area; obtain the obstacle area S in the nth sub-detection range n , get the weight of the nth sub-detection range: W n =S n *(N+1-n)∑N h=1h; Obtain the water body state parameter V corresponding to a certain sampling data, as well as the weights of all sub-detection ranges, and obtain the water body characteristic degree of a certain sampling data: , where k c is the water body characteristic coefficient; Step S130: Obtain all water body characteristic levels corresponding to a certain sampling set, and obtain the sampling data D corresponding to the maximum water body characteristic level max , except for the sampled data D max The water body characteristic degrees of the remaining sampling data are divided by the maximum water body characteristic degree to obtain several water body characteristic ratios; obtain sampling data D max Corresponding water quality parameter A is obtained, and the water quality parameters corresponding to the remaining sampling data and the variance of water quality parameter A are obtained. The sampling data with variance less than the variance threshold is taken as the feature sampling data; and then all the feature sampling data are obtained according to each sampling set.

[0006] In this scheme, the characteristic degree of the water body is the mixing degree of the water. There are two types of obstacle areas, one is the columns, walls and other components in the pool, and the other is the surrounding walls. The water body state parameter is the water flow rate, and the water quality parameter is the pH value, etc. Due to the viscosity of the wall, the water flow will form a boundary layer around the wall, so the closer the sampling point is to the wall, the more uneven the water flow mixes with the surroundings. Therefore, the closer the distance to the wall and the more walls there are, the smaller the mixing degree should be. Since the flow rate is also closely related to the mixing degree, when the flow rate is high, the mixing of the surrounding substances is more uniform. Therefore, the greater the flow rate V, the greater the mixing degree. When the flow rate is high, the acid and alkaline substances in the pool mix quickly instead of accumulating. Therefore, at locations with high flow rates and fewer obstacle areas, the water quality parameters are closer to the actual equilibrium state of the water body and more representative. However, the data with a large difference from the pH value when the flow rate is high cannot be estimated for its authenticity, so this part of the data is not representative and cannot be used as characteristic sampling data; Further, step S200 includes: Step S210: Mark the position of the sampling point corresponding to each feature sampling data on the plane coordinate system; obtain the sampling point b closest to the sampling point a, and take the distance between the sampling point a and the sampling point b as L ab and the corresponding water body characteristic ratios are respectively used as C a and C b , if C a <C b , starting from sampling point a and pointing to the direction of sampling point b, with a size of K*|C b -C a |*L ab , get the sampling vector of sampling point a, K is the vector coefficient, K>0; if C a >C b , starting from sampling point a and pointing in the opposite direction of sampling point b, with a size of K*|C b -C a |*L ab , get the sampling vector of sampling point a; if C a =C b , then there is no sampling vector for sampling point a; then the sampling vectors corresponding to all sampling points are obtained, and the positioning vector is obtained by adding them; Step S220: Randomly obtain several coordinate points in the pool area, calculate the average value to obtain the central facility point, take the central facility point as the starting point of the positioning vector, and take the end point of the positioning vector as the feature point; take the total number of wastewater monitoring equipment as M, obtain the total area of ​​the pool area, and obtain the average area S ^=area / M; randomly obtain a coordinate point from the edge of the pool area, and connect it with the feature point to obtain the feature line segment L1, and rotate the feature line segment L1 clockwise with the feature point as the center until the area enclosed by the rotated feature line segment L2, the feature line segment L1, and the edge line of the pool area is equal to the average area S ^ When , the rotation stops, and the enclosed area is taken as the feature area, and so on, M areas of S are obtained. ^ characteristic area.

[0007] Furthermore, step S300 includes: Step S310: Set the number of loops T=1, randomly obtain several coordinate points in a certain feature area, calculate the average value to obtain the coordinates of the central area of ​​the certain feature area, and obtain the distance weight corresponding to a certain sampling point q according to the distance between a certain sampling point q in a certain feature area and the coordinates of the central area as W q =e -D , where e is the natural index, D is the distance between a sampling point q and the coordinates of the central area; according to the distance weight and water body characteristic ratio corresponding to each sampling data in a certain characteristic area, the characteristic water body characteristic ratio corresponding to a certain characteristic area is Y=K Y *∑Q q=1W q *C q , K Y is the water body characteristic degree coefficient, Q is the total number of sampling data in a certain characteristic area, C q is the water body characteristic ratio corresponding to a certain sampling data; if there is no corresponding sampling data in a certain characteristic area, the water body characteristic ratio corresponding to the sampling point closest to the central area coordinates is used as the characteristic water body characteristic ratio corresponding to the certain characteristic area; according to the characteristic water body characteristic ratios of all characteristic areas, the average ratio C is obtained ^ , and remove C from the characteristic ratio of each characteristic water body ^ , get the area adjustment ratio corresponding to each feature area; Step S320: multiply each area adjustment ratio by the average area S ^ , obtain the iterative area of ​​each characteristic area, adjust the area of ​​each characteristic area to the iterative area according to steps S200 to S300, reset the coordinates of each central area, calculate the characteristic water body characteristic ratio of each characteristic area after adjustment, obtain the area adjustment ratio again, add 1 to the value of the number of cycles T; set the maximum value of the number of cycles T to T max , when the number of cycles T reaches T max When , the adjustment is stopped, and the final feature areas are obtained as the target areas, and the coordinates of the central areas of the last cycle are used as target points to obtain M target points.

[0008] The target point is only determined based on historical sampling data. Its main purpose is to determine where the sampling points should be in the future and to determine the location of each monitoring device. The sampling point location during specific sampling is selected from the target point. The advantage of this is that the placement of the monitoring equipment is fixed by the method of the above steps, and the monitoring equipment does not need to be re-placed every time sampling is performed, which not only saves manpower but is also more convenient. The placement of the monitoring equipment obtained by the above method is more reasonable.

[0009] Furthermore, step S400 includes: Step S410: Obtain the wastewater monitoring equipment at a target point, start from the current moment, record the water state parameters at each moment in the previous S seconds, and obtain the parameter average value, and obtain the current water body characteristic degree of a target point according to step S100; determine the target sampling number as G, 1≤G≤M, M is the total number of target points, obtain the coordinates of each target point, and according to step S200, obtain the target vector of target point a and each of the remaining target points, a total of M-1 target vectors, and then add each target vector to obtain the total target vector VT corresponding to target point a a , and take the feature points as the total target vector VT a The starting point of the total target vector VT a The end point of is taken as the characteristic end point corresponding to the target point a, and then the characteristic end point corresponding to each target point is obtained; Step S420: Set the number of loops B = 1, obtain the minimum radius required to be tangent to the pool area with each characteristic end point as the center, and mark the target point corresponding to the minimum value of each minimum radius. If there are multiple minimum radii with the same minimum value, mark the target point with the smallest water body characteristic degree; then remove the marked target points, reselect each characteristic end point, add 1 to the value of the number of loops B, and end when the value of the number of loops B is G, thereby obtaining G marked target points, and sampling is performed at the marked target points.

[0010] When the number of samples is small, characteristic points with relatively small mixing degrees are needed, because characteristic points with small mixing degrees can more comprehensively reflect the actual situation of the wastewater. Characteristic points with small mixing degrees mean that the point is less affected by external factors and its water quality characteristics are more representative. Therefore, when the number of samples is limited, selecting characteristic points with small mixing degrees for sampling can more accurately reflect the water quality of the wastewater and help formulate more effective governance and management measures.

[0011] A data management system for wastewater monitoring, comprising a module for obtaining characteristic sampling data, a module for dividing characteristic regions, a module for obtaining target regions and a module for sampling target points; Obtaining characteristic sampling data module: used to take a panoramic image of the wastewater discharge pool, establish a plane coordinate system of the wastewater discharge pool, obtain historical sampling data, obtain the water body characteristic degree corresponding to each sampling data according to the position of the sampling point corresponding to each sampling data in the plane coordinate system, and the water body state parameters at the time of sampling, and convert it into a water body characteristic ratio, and then obtain all characteristic sampling data according to the sampling results corresponding to each sampling data; Characteristic area division module: used to determine the total number of wastewater monitoring equipment, and divide the pool area into several characteristic areas according to the pool area corresponding to the wastewater discharge pool and the water body characteristic ratio corresponding to each characteristic sampling data; Obtaining target area module: used to set the number of cycles according to the water body characteristic ratio corresponding to each characteristic sampling data, obtain the target area in the pool area, and the target point corresponding to each target area, and deploy each wastewater monitoring equipment at the target point position; Target point sampling module: used to determine the target sampling quantity, obtain the water body characteristic degree of each target point by analyzing the monitoring data of the wastewater monitoring equipment, mark the target points according to the distance between the target points, and sample at the marked target points.

[0012] Further, the module for obtaining characteristic sampling data includes obtaining an obstacle area unit, calculating a water body characteristic degree unit and obtaining characteristic sampling data unit; Obtaining an obstacle area unit: for randomly selecting a number of sampling points from a plane coordinate system, and performing sampling at each sampling point to obtain a number of sampling sets; drawing an obstacle area in the plane coordinate system; The unit for calculating the degree of water body characteristics is used to obtain the sampling point corresponding to a certain sampling data in a certain sampling set, obtain the sampling detection range, and divide it into several sub-detection ranges to obtain the weight of each sub-detection range; and obtain the degree of water body characteristics of a certain sampling data according to the water body state parameters corresponding to the certain sampling data; Obtain characteristic sampling data unit: used to obtain all water body characteristic levels in a certain sampling set, and then obtain the water body characteristic ratio of each sampling data; and then obtain all characteristic sampling data according to each sampling set.

[0013] Further, obtaining the target area module includes obtaining an area adjustment ratio unit and obtaining a target area unit; The area adjustment ratio obtaining unit is used to randomly obtain a number of coordinate points in a certain feature area, obtain the coordinates of the central area of ​​a certain feature area, and obtain the feature mixing ratio corresponding to the certain feature area; according to the feature mixing ratios of all feature areas, obtain the area adjustment ratio corresponding to each feature area; Obtaining the target area unit: used to obtain the iterative area of ​​each feature area, and loop to obtain the final feature areas as the target areas, and use the coordinates of each central area of ​​the last loop as the target point.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention provides a data management system and method for wastewater monitoring, including: taking a panoramic image of a wastewater discharge pool, obtaining historical sampling data, and obtaining all characteristic sampling data; determining the total number of wastewater monitoring equipment, dividing the pool area into several characteristic areas according to the pool area corresponding to the wastewater discharge pool and the water body characteristic ratio corresponding to each characteristic sampling data, setting the number of cycles to cycle, and obtaining the target area in the pool area, and the corresponding target point; determining the target sampling number, obtaining the degree of water body characteristics of each target point, and marking the target point according to the distance between the target points, and sampling at the marked target point. The present invention makes the sampled data more representative by intelligently and reasonably selecting the sampling point location according to the actual characteristics of the water body, and provides strong data support for subsequent wastewater treatment work. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A schematic diagram of a flow chart of a data management method for wastewater monitoring according to the present invention; Figure 2 This is a structural diagram of a data management system for wastewater monitoring according to the present invention. DETAILED DESCRIPTION

[0016] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0017] Example: Figure 1 As shown, the present invention provides a data management method and technical solution for wastewater monitoring, comprising the following steps: Step S100: Take a panoramic image of the wastewater discharge pool, establish a plane coordinate system of the wastewater discharge pool, obtain historical sampling data, and obtain the water body characteristic degree corresponding to each sampling data according to the position of the sampling point corresponding to each sampling data in the plane coordinate system and the water body state parameters at the time of sampling, and convert it into a water body characteristic ratio, and then obtain all characteristic sampling data according to the sampling results corresponding to each sampling data.

[0018] In this scheme, a drone can be deployed directly above the wastewater discharge pool to take a panoramic image. The panoramic image should capture the entire wastewater discharge pool and obtain a plane coordinate system based on the length and width of the wastewater discharge pool.

[0019] Step S110: randomly select a number of sampling points from the plane coordinate system, and perform sampling at each sampling point as a batch of sampling data, and then randomly select a number of sampling points and perform sampling, and so on, to obtain several batches, and group all the sampling data of the same batch into a sampling set to obtain several sampling sets; the sampling data includes the sampling point, sampling time, water state parameters, and sampling results at the time of sampling, and the sampling results include water quality parameters; in the plane coordinate system, the boundary area of ​​the wastewater discharge pool and the area of ​​the components whose height is greater than the height threshold are obtained, and they are all used as obstacle areas.

[0020] Step S120: Obtain a sampling point P0 corresponding to a certain sampling data in a certain sampling set, take the sampling point P0 as the center and the range of radius r as the sampling detection range, divide the radius r evenly into N parts, and then divide the sampling detection range into N sub-detection ranges, and sort them in order from small to large in area; obtain the obstacle area S in the nth sub-detection range n , get the weight of the nth sub-detection range: W n =S n *(N+1-n)∑N h=1h; Obtain the water body state parameter V corresponding to a certain sampling data, as well as the weights of all sub-detection ranges, and obtain the water body characteristic degree of a certain sampling data: , where k c is the water body characteristic coefficient.

[0021] Step S130: Obtain all water body characteristic levels corresponding to a certain sampling set, and obtain the sampling data D corresponding to the maximum water body characteristic level max , except for the sampled data D max The water body characteristic degrees of the remaining sampling data are divided by the maximum water body characteristic degree to obtain several water body characteristic ratios; obtain sampling data D max Corresponding water quality parameter A is obtained, and the water quality parameters corresponding to the remaining sampling data and the variance of water quality parameter A are obtained. The sampling data with variance less than the variance threshold is taken as the feature sampling data; and then all the feature sampling data are obtained according to each sampling set.

[0022] In this scheme, the characteristic degree of the water body is the mixing degree of the water. There are two types of obstacle areas, one is the columns, walls and other components in the pool, and the other is the surrounding walls. The water body state parameter is the water flow rate, and the water quality parameter is the pH value, etc. Due to the viscosity of the wall, the water flow will form a boundary layer around the wall, so the closer the sampling point is to the wall, the more uneven the water flow mixes with the surroundings. Therefore, the closer the distance to the wall and the more walls there are, the smaller the mixing degree here should be. Since the flow rate is also closely related to the mixing degree, when the flow rate is high, the mixing of the surrounding substances is more uniform, so the greater the flow rate V, the greater the mixing degree. When the flow rate is high, the acid and alkaline substances in the pool mix quickly instead of accumulating. Therefore, at locations with high flow rates and fewer obstacle areas, the water quality parameters are closer to the actual equilibrium state of the water body and more representative. However, the data with a large difference from the pH value when the flow rate is high cannot be estimated for its authenticity, so this part of the data is not representative and cannot be used as characteristic sampling data.

[0023] Step S200: Determine the total number of wastewater monitoring devices, and divide the pool area into several characteristic areas according to the pool area corresponding to the wastewater discharge pool and the water body characteristic ratio corresponding to each characteristic sampling data.

[0024] Step S210: Mark the position of the sampling point corresponding to each feature sampling data on the plane coordinate system; obtain the sampling point b closest to the sampling point a, and take the distance between the sampling point a and the sampling point b as L ab and the corresponding water body characteristic ratios are respectively used as C a and C b , if C a <C b , starting from sampling point a and pointing to the direction of sampling point b, with a size of K*|C b -C a |*L ab , get the sampling vector of sampling point a, K is the vector coefficient, K>0; if C a >C b , starting from sampling point a and pointing in the opposite direction of sampling point b, with a size of K*|C b -C a |*L ab , get the sampling vector of sampling point a; if C a =C b , then there is no sampling vector for sampling point a; then the sampling vectors corresponding to all sampling points are obtained, and the positioning vector is obtained by adding them.

[0025] Step S220: Randomly obtain several coordinate points in the pool area, calculate the average value to obtain the central facility point, take the central facility point as the starting point of the positioning vector, and take the end point of the positioning vector as the feature point; take the total number of wastewater monitoring equipment as M, obtain the total area of ​​the pool area, and obtain the average area S ^ =area / M; randomly obtain a coordinate point from the edge of the pool area, and connect it with the feature point to obtain the feature line segment L1, and rotate the feature line segment L1 clockwise with the feature point as the center until the area enclosed by the rotated feature line segment L2, the feature line segment L1, and the edge line of the pool area is equal to the average area S ^ When , the rotation stops, and the enclosed area is taken as the feature area, and so on, M areas of S are obtained. ^ characteristic area.

[0026] Step S300: according to the water body characteristic ratio corresponding to each characteristic sampling data, the number of cycles is set to cycle, the target area in the pool area and the target point corresponding to each target area are obtained, and each wastewater monitoring device is deployed at the target point position.

[0027] Step S310: Set the number of loops T=1, randomly obtain several coordinate points in a certain feature area, calculate the average value to obtain the coordinates of the central area of ​​the certain feature area, and obtain the distance weight corresponding to a certain sampling point q according to the distance between a certain sampling point q in a certain feature area and the coordinates of the central area as W q =e -D , where e is the natural index, D is the distance between a sampling point q and the coordinates of the central area; according to the distance weight and water body characteristic ratio corresponding to each sampling data in a certain characteristic area, the characteristic water body characteristic ratio corresponding to a certain characteristic area is Y=K Y *∑Q q=1W q *C q , K Y is the water body characteristic degree coefficient, Q is the total number of sampling data in a certain characteristic area, C q is the water body characteristic ratio corresponding to a certain sampling data; if there is no corresponding sampling data in a certain characteristic area, the water body characteristic ratio corresponding to the sampling point closest to the central area coordinates is used as the characteristic water body characteristic ratio corresponding to the certain characteristic area; according to the characteristic water body characteristic ratios of all characteristic areas, the average ratio C is obtained ^ , and remove C from the characteristic ratio of each characteristic water body ^ , and obtain the area adjustment ratio corresponding to each feature area.

[0028] Step S320: multiply each area adjustment ratio by the average area S ^, obtain the iterative area of ​​each characteristic area, adjust the area of ​​each characteristic area to the iterative area according to steps S200 to S300, reset the coordinates of each central area, calculate the characteristic water body characteristic ratio of each characteristic area after adjustment, obtain the area adjustment ratio again, add 1 to the value of the number of cycles T; set the maximum value of the number of cycles T to T max , when the number of cycles T reaches T max When , the adjustment is stopped, and the final feature areas are obtained as the target areas, and the coordinates of the central areas of the last cycle are used as target points to obtain M target points.

[0029] The target point is only determined based on historical sampling data. Its main purpose is to determine where the sampling points should be in the future and to determine the location of each monitoring device. The sampling point location during specific sampling is selected from the target point. The advantage of this is that the placement of the monitoring equipment is fixed by the method of the above steps, and the monitoring equipment does not need to be re-placed every time sampling is performed, which not only saves manpower but is also more convenient. The placement of the monitoring equipment obtained by the above method is more reasonable.

[0030] Step S400: Determine the target sampling quantity, obtain the water body characteristic degree of each target point by analyzing the monitoring data of the wastewater monitoring equipment, mark the target points according to the distance between the target points, and perform sampling at the marked target points.

[0031] Step S410: Obtain the wastewater monitoring equipment at a target point, start from the current moment, record the water state parameters at each moment in the previous S seconds, and obtain the parameter average value, and obtain the current water body characteristic degree of a target point according to step S100; determine the target sampling number as G, 1≤G≤M, M is the total number of target points, obtain the coordinates of each target point, and according to step S200, obtain the target vector of target point a and each of the remaining target points, a total of M-1 target vectors, and then add each target vector to obtain the total target vector VT corresponding to target point a a , and take the feature points as the total target vector VT a The starting point of the total target vector VT a The end point of is taken as the characteristic end point corresponding to the target point a, and then the characteristic end point corresponding to each target point is obtained; Step S420: Set the number of loops B = 1, obtain the minimum radius required to be tangent to the pool area with each characteristic end point as the center, and mark the target point corresponding to the minimum value of each minimum radius. If there are multiple minimum radii with the same minimum value, mark the target point with the smallest water body characteristic degree; then remove the marked target points, reselect each characteristic end point, add 1 to the value of the number of loops B, and end when the value of the number of loops B is G, thereby obtaining G marked target points, and sampling is performed at the marked target points.

[0032] When the number of samples is small, the priority is to select characteristic points with a relatively small degree of mixing, because characteristic points with a small degree of mixing can more comprehensively reflect the actual situation of the wastewater. Characteristic points with a small degree of mixing mean that the point is less affected by external factors and its water quality characteristics are more representative. Therefore, when the number of samples is limited, selecting characteristic points with a small degree of mixing for sampling can more accurately reflect the water quality of the wastewater and help formulate more effective governance and management measures.

[0033] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. A data management method for wastewater monitoring, characterized in that: The following steps are involved: Step S100: taking a panoramic image of the wastewater discharge pool, establishing a plane coordinate system of the wastewater discharge pool, obtaining historical sampling data, obtaining the water body characteristic degree corresponding to each sampling data according to the position of the sampling point corresponding to each sampling data in the plane coordinate system, and the water body state parameters at the time of sampling, and converting it into a water body characteristic ratio, and then obtaining all characteristic sampling data according to the sampling results corresponding to each sampling data; Step S200: determining the total number of wastewater monitoring devices, and dividing the pool area into a number of characteristic areas according to the pool area corresponding to the wastewater discharge pool and the water body characteristic ratio corresponding to each characteristic sampling data; Step S300: according to the water body characteristic ratio corresponding to each characteristic sampling data, the number of cycles is set to cycle, the target area in the pool area and the target point corresponding to each target area are obtained, and each wastewater monitoring device is deployed at the target point position; Step S400: Determine the target sampling quantity, obtain the water body characteristic degree of each target point by analyzing the monitoring data of the wastewater monitoring equipment, mark the target points according to the distance between the target points, and perform sampling at the marked target points.

2. A data management method for wastewater monitoring according to claim 1, characterized in that: Step S100 includes: Step S110: randomly select a number of sampling points from the plane coordinate system, and perform sampling at each sampling point as a batch of sampling data, and then randomly select a number of sampling points and perform sampling, and so on, to obtain a number of batches, and classify all sampling data of the same batch into a sampling set to obtain a number of sampling sets; the sampling data includes the sampling point, sampling time, water state parameters, and sampling results during sampling, and the sampling results include water quality parameters; in the plane coordinate system, the boundary area of ​​the wastewater discharge pool and the area of ​​the components whose height is greater than the height threshold are obtained, and are all used as obstacle areas; Step S120: Obtain a sampling point P0 corresponding to a certain sampling data in a certain sampling set, take the sampling point P0 as the center and the range of radius r as the sampling detection range, divide the radius r evenly into N parts, and then divide the sampling detection range into N sub-detection ranges, and sort them in order from small to large in area; obtain the obstacle area S in the nth sub-detection range n , get the weight of the nth sub-detection range: W n =S n *(N+1-n)∑N h=1h; obtain the water body state parameter V corresponding to a certain sampling data, and the weights of all sub-detection ranges, and obtain the water body characteristic degree of the certain sampling data: , where k c is the water body characteristic coefficient; Step S130: Obtain all water body characteristic levels corresponding to the sampling set, and obtain the sampling data D corresponding to the maximum water body characteristic level max , except for the sampled data D max The water body characteristic degrees of the remaining sampling data are divided by the maximum water body characteristic degree to obtain several water body characteristic ratios; obtain sampling data D max The corresponding water quality parameter A is obtained, and the water quality parameters corresponding to the remaining sampling data are obtained, and the variance of the water quality parameter A is obtained, and the sampling data with variance less than the variance threshold is used as the feature sampling data; and then all the feature sampling data are obtained according to each sampling set.

3. A data management method for wastewater monitoring according to claim 1, characterized in that: Step S200 includes: Step S210: Mark the position of the sampling point corresponding to each feature sampling data on the plane coordinate system; obtain the sampling point b closest to the sampling point a, and use the distance between the sampling point a and the sampling point b as L ab and the corresponding water body characteristic ratios are respectively used as C a and C b , if C a <C b , starting from sampling point a and pointing to the direction of sampling point b, with a size of K*|C b -C a |*L ab , get the sampling vector of sampling point a, K is the vector coefficient, K>0; if C a >C b , starting from sampling point a and pointing in the opposite direction of sampling point b, with a size of K*|C b -C a |*L ab , get the sampling vector of sampling point a; if C a =C b , then there is no sampling vector for sampling point a; then the sampling vectors corresponding to all sampling points are obtained, and the positioning vector is obtained by adding them; Step S220: randomly obtain several coordinate points in the pool area, calculate the average value to obtain the central facility point, take the central facility point as the starting point of the positioning vector, and take the end point of the positioning vector as the feature point; take the total number of wastewater monitoring equipment as M, obtain the total area of ​​the pool area, and obtain the average area S ^ =area / M; randomly obtain a coordinate point from the edge of the pool area, and connect it with the feature point to obtain the feature line segment L1, and rotate the feature line segment L1 clockwise with the feature point as the center until the area enclosed by the rotated feature line segment L2, the feature line segment L1, and the edge line of the pool area is equal to the average area S ^ When , the rotation stops, and the enclosed area is taken as the feature area, and so on, M areas of S are obtained. ^ characteristic area.

4. A data management method for wastewater monitoring according to claim 3, characterized in that: Step S300 includes: Step S310: Set the number of loops T=1, randomly obtain several coordinate points in a certain feature area, calculate the average value to obtain the coordinates of the central area of ​​the certain feature area, and obtain the distance weight corresponding to a certain sampling point q according to the distance between a certain sampling point q in a certain feature area and the coordinates of the central area as W q =e -D , where e is the natural index, D is the distance between a sampling point q and the coordinates of the central area; according to the distance weight and water body characteristic ratio corresponding to each sampling data in a certain characteristic area, the characteristic water body characteristic ratio corresponding to a certain characteristic area is Y=K Y *∑Q q=1W q *C q , K Y is the water body characteristic degree coefficient, Q is the total number of sampling data in a certain characteristic area, C q is the water body characteristic ratio corresponding to a certain sampling data; if there is no corresponding sampling data in a certain characteristic area, the water body characteristic ratio corresponding to the sampling point closest to the coordinates of the central area is used as the characteristic water body characteristic ratio corresponding to the certain characteristic area; according to the characteristic water body characteristic ratios of all characteristic areas, the average ratio C is obtained ^ , and remove C from the characteristic ratio of each characteristic water body ^ , get the area adjustment ratio corresponding to each feature area; Step S320: multiply each area adjustment ratio by the average area S ^ , obtain the iterative area of ​​each characteristic area, adjust the area of ​​each characteristic area to the iterative area according to steps S200 to S300, reset the coordinates of each central area, calculate the characteristic water body characteristic ratio of each characteristic area after adjustment, obtain the area adjustment ratio again, add 1 to the value of the number of cycles T; set the maximum value of the number of cycles T to T max , when the number of cycles T reaches T max When , the adjustment is stopped, and the final feature areas are obtained as the target areas, and the coordinates of the central areas of the last cycle are used as target points to obtain M target points.

5. A data management method for wastewater monitoring according to claim 4, characterized in that: Step S400 includes: Step S410: Obtain the wastewater monitoring equipment at a target point, start from the current moment, record the water state parameters at each moment in the previous S seconds, and obtain the parameter average value, and obtain the current water body characteristic degree of a target point according to step S100; determine the target sampling number as G, 1≤G≤M, M is the total number of target points, obtain the coordinates of each target point, and according to step S200, obtain the target vector of target point a and each of the remaining target points, a total of M-1 target vectors, and then add each target vector to obtain the total target vector VT corresponding to target point a a , and take the feature points as the total target vector VT a The starting point of the total target vector VT a The end point of is taken as the characteristic end point corresponding to the target point a, and then the characteristic end point corresponding to each target point is obtained; Step S420: Set the number of loops B = 1, obtain the minimum radius required to be tangent to the pool area with each characteristic end point as the center, and mark the target point corresponding to the minimum value of each minimum radius. If there are multiple minimum radii with the same minimum value, mark the target point with the smallest water body characteristic degree; then remove the marked target points, reselect each characteristic end point, add 1 to the value of the number of loops B, and end when the value of the number of loops B is G, thereby obtaining G marked target points, and sampling is performed at the marked target points.

6. A data management system for executing a data management method for wastewater monitoring according to any one of claims 1 to 5, characterized in that: The system includes a module for obtaining feature sampling data, a module for dividing feature regions, a module for obtaining target regions and a module for sampling target points; Obtaining characteristic sampling data module: used to take a panoramic image of the wastewater discharge pool, establish a plane coordinate system of the wastewater discharge pool, obtain historical sampling data, obtain the water body characteristic degree corresponding to each sampling data according to the position of the sampling point corresponding to each sampling data in the plane coordinate system, and the water body state parameters at the time of sampling, and convert it into a water body characteristic ratio, and then obtain all characteristic sampling data according to the sampling results corresponding to each sampling data; Characteristic area division module: used to determine the total number of wastewater monitoring equipment, and divide the pool area into several characteristic areas according to the pool area corresponding to the wastewater discharge pool and the water body characteristic ratio corresponding to each characteristic sampling data; Obtaining target area module: used to set the number of cycles according to the water body characteristic ratio corresponding to each characteristic sampling data, obtain the target area in the pool area, and the target point corresponding to each target area, and deploy each wastewater monitoring equipment at the target point position; Target point sampling module: used to determine the target sampling quantity, obtain the water body characteristic degree of each target point by analyzing the monitoring data of the wastewater monitoring equipment, mark the target points according to the distance between the target points, and sample at the marked target points.

7. A data management system according to claim 6, characterized in that: The module for obtaining characteristic sampling data includes an obstacle area obtaining unit, a water body characteristic degree calculating unit and a characteristic sampling data obtaining unit; Obtaining an obstacle area unit: for randomly selecting a number of sampling points from a plane coordinate system, and performing sampling at each sampling point to obtain a number of sampling sets; drawing an obstacle area in the plane coordinate system; The unit for calculating the degree of water body characteristics is used to obtain the sampling point corresponding to a certain sampling data in a certain sampling set, obtain the sampling detection range, and divide it into several sub-detection ranges to obtain the weight of each sub-detection range; and obtain the degree of water body characteristics of a certain sampling data according to the water body state parameters corresponding to the certain sampling data; Obtain characteristic sampling data unit: used to obtain all water body characteristic levels in a certain sampling set, and then obtain the water body characteristic ratio of each sampling data; and then obtain all characteristic sampling data according to each sampling set.

8. A data management system according to claim 6, characterized in that: The target area obtaining module includes an area adjustment ratio obtaining unit and a target area obtaining unit; The area adjustment ratio obtaining unit is used to randomly obtain a number of coordinate points in a certain feature area, obtain the coordinates of the central area of ​​a certain feature area, and obtain the feature mixing ratio corresponding to the certain feature area; according to the feature mixing ratios of all feature areas, obtain the area adjustment ratio corresponding to each feature area; Obtaining the target area unit: used to obtain the iterative area of ​​each feature area, and loop to obtain the final feature areas as the target areas, and use the coordinates of each central area of ​​the last loop as the target point.

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