Rapid detection method, system and device for water pollution applied to groundwater remediation

Abstract

The present invention belongs to the technical field of water pollution detection, and discloses a method, system and device for rapid detection of water pollution applied to groundwater remediation, including the following: obtaining a concentration change curve corresponding to the concentration data of target pollutants collected at multiple position detection points according to a sampling frequency within multiple sampling periods; analyzing the position tendency degree of the concentration change of the target pollutant in different sampling periods according to the concentration change curves of the multiple position detection points; calculating the environmental disturbance significance coefficient of the detection points at different positions according to the position tendency degree of the detection points at different positions, in combination with the concentration change curve; dividing the concentration data of the detection points at different positions into a normal data set and an environmental disturbance data set according to the environmental disturbance significance coefficient; completing the construction of a rapid detection and prediction model for groundwater remediation water pollution according to the normal data set and the environmental disturbance data set, and realizing dynamic detection and early warning of groundwater remediation water pollution.

Description

Technical Field

[0001] The present invention relates to the technical field of water pollution detection, and in particular to a method, system and device for rapid detection of water pollution applied to groundwater remediation. Background Art

[0002] Groundwater pollutants are generated and enter the environment through various channels and pollute groundwater. The sources of groundwater pollution can be divided into two categories: point source pollution and non-point source pollution. Point source pollution refers to pollution sources with fixed discharge points, such as sewage discharge outlets, landfills, industrial production facilities, etc. Because its discharge points are relatively concentrated and pollutant discharge is concentrated, it is easy to cause the concentration of groundwater pollutants in local areas to increase, and it is easy to determine the source of pollution, and it is easy to trace and determine the responsibility for pollution. Non-point source pollution refers to pollution sources that have no fixed discharge points and are dispersed, such as the use of agricultural fertilizers and pesticides, urban runoff, etc. Its pollution sources are widely distributed, and it is difficult to accurately determine the specific source of pollution. The concentration of pollutants is low, but due to the wide range, the overall pollution load is large, and the control is difficult, and it is necessary to take a variety of measures to control it.

[0003] One of the most commonly used groundwater remediation technologies at present is extraction treatment, which transports contaminated groundwater to the ground by building pumping wells, and after qualified treatment, the repaired groundwater is injected or discharged into the corresponding pipe network or water body in situ. The advantages of extraction treatment are simple technology, easy operation, and suitable for the treatment of most groundwater pollutants; for groundwater with a large pollution range and a large buried depth of pollutants, early treatment is effective and the treatment effect is obvious. However, it will cause great disturbance to the environment, and there are also problems of tailing and rebound. The hydraulic connection of groundwater is complex, and the source and nature of pollutants are complex. However, in actual projects, the underground structure is complex and different aquifers have different characteristics. Therefore, there is currently no accurate detection method for the detection of water pollution status after groundwater remediation. Summary of the invention

[0004] In order to overcome the problem that the above-mentioned prior art cannot quickly and accurately detect the water pollution status after groundwater restoration, the present invention provides a method, system and device for rapid detection of water pollution applied to groundwater restoration.

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0006] A rapid detection method for water pollution applied to groundwater remediation, the method comprising the following steps:

[0007] After groundwater remediation, the concentration data of target pollutants collected at multiple location detection points in multiple sampling periods according to the sampling frequency are obtained, and the corresponding concentration change curve is formed;

[0008] According to the concentration change curves of multiple detection points, the position tendency of the concentration change of the target pollutants at different detection points in different sampling periods is analyzed;

[0009] According to the positional tendency of the detection points at different locations, combined with the concentration change curves of the detection points at the corresponding locations, the environmental disturbance significance coefficients of the detection points at different locations are calculated;

[0010] According to the significant coefficient of environmental disturbance, the concentration data of detection points at different locations are divided into a normal data set and an environmental disturbance data set;

[0011] Based on the normal data set and the environmental disturbance data set, a rapid detection and prediction model for groundwater remediation water pollution is constructed to achieve dynamic detection and early warning of groundwater remediation water pollution.

[0012] Preferably, the target pollutants include one or more of nitrogen, phosphorus and compounds thereof.

[0013] Preferably, according to the concentration change curves of multiple position detection points, the position tendency of the concentration change of the target pollutant at different position detection points in different sampling periods is analyzed, including:

[0014] Obtain the concentration change curve of any detection point at any location, and use the end time of the groundwater remediation operation as the segmentation point to divide the concentration change curve into the remediation operation section and the post-remediation operation section;

[0015] The derivative of the concentration change curve corresponding to the repair operation section is obtained to obtain the concentration change rate, thereby obtaining the concentration change rate mean value representing the concentration change status of the repair operation section;

[0016] Obtain the coordinates of each position detection point, calculate the relative distance between any two position detection points, and determine the neighboring position detection points and their number based on the relative distance;

[0017] Based on the number of neighboring position detection points, the total number of sampling cycles, the average concentration change rate of the concentration change conditions of the position detection point in the repair operation section, and the average concentration change rate of the concentration change conditions of the neighboring position detection points adjacent to the position detection point in the repair operation section, the position tendency of the concentration changes of the target pollutants at different position detection points in different sampling cycles is calculated.

[0018] Preferably, according to the position tendency degree of the detection points at different positions, combined with the concentration change curve of the detection points at corresponding positions, the environmental disturbance significance coefficients of the detection points at different positions are calculated, including:

[0019] Sort the positional tendency degrees of all positional detection points within the neighborhood of each positional detection point to obtain a relative sequence of positional tendency degrees;

[0020] For the concentration change curve of any position detection point in the latter part of the repair operation, the revolving door algorithm is used to perform straight line fitting on the concentration change curve in the latter part of the repair operation, and multiple segments of fitting straight lines are used to form a fitting broken line;

[0021] Obtain the dtw score between the fitting polyline of any position detection point in the latter part of the repair operation and the fitting polyline of the remaining position detection points in the neighboring range in the latter part of the repair operation, and calculate the average dtw score of the fitting polyline;

[0022] Arrange the obtained dtw score means of the fitting line in the same order of the position tendency relative sequence to obtain the sequence of the mean dtw score of the fitting line;

[0023] Obtain the relative sequence of the position tendency degree of each position detection point in the later stage of the remediation operation and the target pollutant position change distance on the fitting broken line dtw score sequence;

[0024] Obtain the mean value of the target pollutant position change distance of detection points at different locations;

[0025] The environmental disturbance significance coefficient of different location detection points is calculated by combining the target pollutant position change distance of different location detection points, the mean of the target pollutant position change distance, the sequence number of the position tendency degree of different location detection points in the relative sequence of position tendency degree, and the sequence number of the mean of the fitted broken line dtw score of different location detection points in the sequence of the mean of the fitted broken line dtw score.

[0026] Preferably, the concentration data of detection points at different locations are divided into a normal data set and an environmental disturbance data set according to the environmental disturbance significance coefficient, including:

[0027] Preset abnormal thresholds;

[0028] If the environmental disturbance significance coefficient of the position detection point is greater than or equal to the preset abnormal threshold, the concentration data of the position detection point is divided into environmental disturbance data to form an environmental disturbance data set;

[0029] If the environmental disturbance significance coefficient of the position detection point is less than the preset abnormal threshold, the concentration data of the position detection point is divided into normal data to form a normal data set.

[0030] Preferably, a rapid detection and prediction model for groundwater remediation water pollution is constructed based on a normal data set and an environmental disturbance data set to achieve dynamic detection and early warning of groundwater remediation water pollution, including:

[0031] In the environmental disturbance data set, the data on concentration changes at different detection points in different sampling periods can be obtained;

[0032] According to the parameter acquisition process of the rapid detection and prediction model for groundwater remediation water pollution, the initial parameters of the normal data set and the environmental disturbance data set are respectively obtained;

[0033] The initial parameters of the environmental disturbance data set are weighted by the degree of data reference;

[0034] Finally, the initial parameters of the normal data set are averaged and the processed parameters are used as the parameters of the rapid detection and prediction model for groundwater remediation water pollution, thereby completing the construction of the rapid detection and prediction model for groundwater remediation water pollution.

[0035] Preferably, in the environmental disturbance data set, the data reference degree of concentration changes in different sampling periods at different detection points at different locations is obtained, including:

[0036] In the environmental disturbance data set, the environmental disturbance significance coefficients of different sampling periods detected at different locations are calculated;

[0037] Obtain the maximum value of the environmental disturbance significance coefficient of different sampling periods at different position detection points at the current moment, and the number of sampling periods obtained at the current moment;

[0038] Based on the calculated environmental disturbance significance coefficients of different sampling periods detected at different locations, the maximum value of the environmental disturbance significance coefficients of different sampling periods of detection points at different locations at the current moment, and the number of sampling periods obtained at the current moment, the data reference degree of concentration changes in different sampling periods at detection points at different locations is calculated.

[0039] Preferably, the groundwater remediation water pollution rapid detection prediction model is Predictive models.

[0040] A rapid water pollution detection system for groundwater remediation, comprising:

[0041] The data acquisition module is used to obtain the concentration data of target pollutants collected at multiple location detection points in multiple sampling periods according to the sampling frequency after groundwater remediation, and to form a corresponding concentration change curve;

[0042] A position tendency degree calculation module is used to analyze the position tendency degree of the concentration change of the target pollutant at different position detection points in different sampling periods according to the concentration change curves of multiple position detection points;

[0043] The environmental disturbance significant coefficient calculation module is used to calculate the environmental disturbance significant coefficients of different position detection points according to the position tendency of different position detection points and the concentration change curve of the corresponding position detection points;

[0044] A division module is used to divide the concentration data of detection points at different locations into a normal data set and an environmental disturbance data set according to the environmental disturbance significance coefficient;

[0045] The prediction model construction module is used to complete the construction of a rapid detection and prediction model for groundwater remediation water pollution based on normal data sets and environmental disturbance data sets, and to achieve dynamic detection and early warning of groundwater remediation water pollution.

[0046] A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the method for rapid detection of water pollution applied to groundwater remediation is implemented.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] After groundwater restoration, the present invention obtains concentration data of target pollutants collected at multiple position detection points according to sampling frequencies within multiple sampling periods, and composes corresponding concentration change curves; based on the concentration change curves of multiple position detection points, the position tendency degree of concentration changes of target pollutants at different position detection points in different sampling periods is analyzed; based on the position tendency degree of different position detection points, combined with the concentration change curves of corresponding position detection points, the environmental disturbance significance coefficients of different position detection points are calculated; based on the environmental disturbance significance coefficient, the concentration data of different position detection points are divided into a normal data set and an environmental disturbance data set; based on the normal data set and the environmental disturbance data set, the construction of a rapid detection and prediction model for groundwater restoration water body pollution is completed, so as to realize dynamic detection and early warning of groundwater restoration water body pollution.

[0049] The present invention can utilize the constructed rapid detection and prediction model for groundwater remediation water pollution to quickly and accurately detect groundwater remediation water bodies; at the same time, the accurate detection results obtained can be used to complete the subsequent coordination operations of groundwater remediation and realize rapid detection and adjustment of water pollution for groundwater remediation. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 It is a flowchart of the steps of the method for rapid detection of water pollution applied to groundwater remediation of the present invention;

[0051] Figure 2 It is a principle block diagram of the water pollution rapid detection system applied to groundwater remediation according to the present invention;

[0052] Figure 3 is a schematic block diagram of a computer device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0053] 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 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. The present invention is described in detail below in combination with the drawings and specific implementation methods.

[0054] It should be understood that when used in this specification, the terms "include" and "comprising" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or collections thereof.

[0055] It should also be understood that the terms used in this specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification of the present invention, unless the context clearly indicates otherwise, the singular forms of "a", "an" and "the" are intended to include plural forms.

[0056] It should be further understood that the term “and / or” used in the specification of the present invention refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0057] Example 1

[0058] The present invention provides a method for rapid detection of water pollution applied to groundwater remediation. Figure 1 As shown, the method comprises the following steps:

[0059] After groundwater remediation, the concentration data of target pollutants collected at multiple location detection points in multiple sampling periods according to the sampling frequency are obtained, and the corresponding concentration change curve is formed;

[0060] According to the concentration change curves of multiple detection points, the position tendency of the concentration change of the target pollutants at different detection points in different sampling periods is analyzed;

[0061] According to the positional tendency of the detection points at different locations, combined with the concentration change curves of the detection points at the corresponding locations, the environmental disturbance significance coefficients of the detection points at different locations are calculated;

[0062] According to the significant coefficient of environmental disturbance, the concentration data of detection points at different locations are divided into a normal data set and an environmental disturbance data set;

[0063] Based on the normal data set and the environmental disturbance data set, a rapid detection and prediction model for groundwater remediation water pollution is constructed to achieve dynamic detection and early warning of groundwater remediation water pollution.

[0064] In a specific embodiment, after groundwater remediation, the concentration data of target pollutants collected at multiple location detection points in multiple sampling periods according to the sampling frequency are obtained, and a corresponding concentration change curve is formed, which specifically includes the following:

[0065] This embodiment sets up water quality detection devices at multiple groundwater remediation facilities to obtain target pollutants after groundwater remediation, thereby obtaining groundwater quality data. The specific collection method is to extract the concentration data of target pollutants at multiple location detection points within a sampling period of 60 days after the groundwater remediation operation is completed, and the sampling frequency is The target pollutant concentration data collected at multiple detection points in multiple sampling periods according to the sampling frequency are obtained to form the target pollutant concentration data of groundwater. The concentration data in a sampling period at a detection point can form a corresponding concentration change curve. In this embodiment, the target pollutants include one or more of nitrogen, phosphorus and their compounds.

[0066] Since the sources of groundwater pollution can be divided into two categories: point source pollution and non-point source pollution, there will be different data change characteristics with the working time of groundwater remediation. The treatment effect of point source pollution is better, but there are problems of tailing and rebound, and the hydraulic connection of groundwater is complex, and the source and nature of pollutants are complex; in actual projects, the underground structure is complex, and different aquifers have different characteristics. Therefore, the detection of water pollution status after groundwater remediation is not accurate, especially the location of groundwater remediation facilities and the disturbance of the environment by remediation technology, which leads to an increase in the fluctuation characteristics of the concentration data of target pollutants, so that the water pollution status analyzed from the data is inaccurate.

[0067] This embodiment is based on the point source pollution and non-point source pollution of groundwater. With the working time of groundwater remediation, there will be different data change characteristics, as well as the influence of the location distribution structure of multiple location detection points. Among them, point source pollution usually comes from specific and identifiable pollution sources, such as sewage outlets, industrial wastewater pipes, etc., and its pollution range is relatively concentrated and limited. With the progress of groundwater remediation, the concentration data of target pollutants detected near point source pollution may change more obviously and violently, showing the characteristics of gradual improvement or change centered on the pollution source. Non-point source pollution is more scattered and widespread, such as the large-scale use of agricultural fertilizers and pesticides, urban surface runoff, etc. The impact range of this pollution is large, and the concentration data of target pollutants may change relatively slowly, and show similar change trends in a large area. In addition, detection points at different locations may show a wider range of pollution distribution characteristics, and the degree of influence of non-point source pollution may vary due to factors such as distance and water flow path.

[0068] In a specific embodiment, based on the concentration change curves of multiple position detection points, the position tendency of the concentration change of the target pollutant at different position detection points in different sampling periods is analyzed, including:

[0069] Obtain the concentration change curve of any detection point at any location, and use the end time of the groundwater remediation operation as the segmentation point to divide the concentration change curve into the remediation operation section and the post-remediation operation section;

[0070] The derivative of the concentration change curve corresponding to the repair operation section is obtained to obtain the concentration change rate, thereby obtaining the concentration change rate mean value representing the concentration change status of the repair operation section;

[0071] Obtain the coordinates of each position detection point, calculate the relative distance between any two position detection points, and determine the neighboring position detection points and their number based on the relative distance;

[0072] Based on the number of neighboring position detection points, the total number of sampling cycles, the average concentration change rate of the concentration change conditions of the position detection point in the repair operation section, and the average concentration change rate of the concentration change conditions of the neighboring position detection points adjacent to the position detection point in the repair operation section, the position tendency of the concentration changes of the target pollutants at different position detection points in different sampling cycles is calculated.

[0073] In this embodiment, for the positional tendency of the concentration changes at different locations of the acquired groundwater water quality data, the derivative mean of the concentration change curve of the remediation operation section (that is, the mean of the concentration change rate) can represent the groundwater change status at the location detection point. The larger the value, the more sensitive the pollution status at the location is to the remediation technology treatment. For multiple adjacent location detection points that are closer in actual location, the closer the location, the more consistent the treatment effects can be considered; for location detection points with smaller change differences, the more obvious their positional tendency can be considered, and the greater the possibility that the location detection point is a non-point source pollution. This embodiment provides the first The calculation method of the position tendency degree of each position detection point is as follows:

[0074] ;

[0075] in, Indicates The position tendency of each position detection point, represents the total number of sampling periods, Indicates The average concentration change rate of the detection points at each location, It means the The first position detection point The average concentration change rate of the adjacent detection points is represents the negative correlation normalization function.

[0076] in, It represents the concentration change of the target pollutants (such as nitrogen and phosphorus) at the detection point caused by the sewage discharge operation at the sewage discharge port on the concentration change curve, and the degree of position tendency over multiple sampling periods; that is, it indicates the significance of the change under the structural influence caused by the flow of sewage above the groundwater along the groundwater. The greater the position tendency, the greater the possibility that the concentration data of the target pollutants obtained at this detection point are affected by non-point source pollutants.

[0077] In a specific embodiment, the environmental disturbance caused by the movement of groundwater flow will further cause the overall fluctuation of the concentration change curve under the influence of sewage discharge. However, due to the unclear actual disturbance conditions, on the one hand, the disturbance of the extraction and remediation technology may accelerate the spread of pollution to a certain extent. For example, during the disturbance process, the originally fixed or precipitated pollutants may be resuspended and migrated, thereby expanding the scope and degree of pollution within a certain range. On the other hand, if operated properly, the extraction and remediation technology may also slow down the pollution. For example, through reasonable extraction and treatment, some pollutants can be removed in time to reduce the total amount of pollution, which can relatively slow down the development of pollution to a certain extent. Therefore, the analysis of the status of environmental disturbance changes should be based on the difference change characteristics from the original pollution status; therefore, the relative relationship of the position tendency degree of the adjacent position detection point can be used to characterize the influence mode of the target position detection point; the greater the change, the greater the concentration data of the target pollutant at the target position detection point is affected by the environmental disturbance.

[0078] In this embodiment, according to the position tendency degree of the detection points at different positions, combined with the concentration change curve of the detection points at the corresponding positions, the environmental disturbance significance coefficients of the detection points at different positions are calculated, including:

[0079] The position tendency degrees of all position detection points within the neighborhood of each position detection point are sorted to obtain a relative sequence of position tendency degrees; the specific relative sequence of position tendency degrees obtained is ,as follows:

[0080] ;

[0081] in, The order of positions is not fixed.

[0082] For the concentration change curve of any position detection point in the latter part of the repair operation, the revolving door algorithm is used to perform straight line fitting on the concentration change curve in the latter part of the repair operation, and multiple segments of fitting straight lines are used to form a fitting broken line;

[0083] Obtain the dtw score between the fitting polyline of any position detection point in the latter part of the repair operation and the fitting polyline of the remaining position detection points in the neighboring range in the latter part of the repair operation, and calculate the average dtw score of the fitting polyline;

[0084] In this embodiment, the method for calculating the dtw score between two fitting broken lines is a prior art and will not be described in detail here. The dtw score is the similarity calculated for two sequences consisting of the turning point coordinates of the two fitting broken lines.

[0085] Arrange the obtained dtw score means of the fitting line in the same order of the position tendency relative sequence to obtain the sequence of the mean dtw score of the fitting line;

[0086] In this embodiment, for the fitted broken line dtw score mean sequence and the relative sequence of position tendency degree on the concentration change curve in the later stage of the remediation operation, each neighboring position detection point has a corresponding element in the fitted broken line dtw score mean sequence and the relative sequence of position tendency degree, and the change in the position of the element can be considered as a difference from the original pollution condition caused by the change in environmental disturbance.

[0087] Obtain the relative sequence of the position tendency degree of each position detection point in the later stage of the remediation operation and the target pollutant position change distance on the fitting broken line dtw score sequence;

[0088] In this embodiment, the target pollutant position change distance is specifically obtained as follows. For example, if A1 is the first element of the first sequence, it corresponds to the first position detection point of the neighbor corresponding to the B3 element of the second sequence, that is, its node order changes from 1 to 3, so the target pollutant position change distance is =2, and the calculation method for the position change distances of other target pollutants is the same.

[0089] Obtain the mean value of the target pollutant position change distance of detection points at different locations;

[0090] The environmental disturbance significance coefficient of different location detection points is calculated by combining the target pollutant position change distance of different location detection points, the mean of the target pollutant position change distance, the sequence number of the position tendency degree of different location detection points in the relative sequence of position tendency degree, and the sequence number of the mean of the fitted broken line dtw score of different location detection points in the sequence of the mean of the fitted broken line dtw score.

[0091] In this embodiment, the calculation The calculation formula of the significant coefficient of environmental disturbance at each detection point is as follows:

[0092] ;

[0093] ;

[0094] in, Indicates The significant coefficient of environmental disturbance at each detection point; Indicates The distance of change in the position of the target pollutant in the two sequences after the remediation operation of the position detection point; Indicates the target pollutant position change distance of all position detection points The mean of Indicates The degree of change in the position of the target pollutant at each position detection point in the two sequences in the latter part of the remediation operation; Indicates The order number of the position tendency degree of each position detection point in the relative sequence of position tendency, Indicates The order of the mean scores of the fitting polyline dtw of the position detection points in the latter part of the repair operation on the mean score sequence of the fitting polyline dtw; Indicates The environmental disturbance at a location detection point in the later stage of the remediation operation causes the significance of the fluctuation characteristics of the local area composed of the location detection point and its neighboring location detection points. The greater the significance of the fluctuation characteristics, the greater the impact of the environmental disturbance on the concentration data of the target pollutant.

[0095] In a specific embodiment, the concentration data of detection points at different locations are divided into a normal data set and an environmental disturbance data set according to the environmental disturbance significance coefficient, including:

[0096] Preset abnormal thresholds;

[0097] If the environmental disturbance significance coefficient of the position detection point is greater than or equal to the preset abnormal threshold, the concentration data of the position detection point is divided into environmental disturbance data to form an environmental disturbance data set;

[0098] If the environmental disturbance significance coefficient of the position detection point is less than the preset abnormal threshold, the concentration data of the position detection point is divided into normal data to form a normal data set.

[0099] In this embodiment, the environmental disturbance significance coefficient of all position detection points is obtained, which represents the significance of the concentration data of the position detection point under the influence of environmental disturbance. The concentration data at the position detection point is screened. Specifically: if the environmental disturbance significance coefficient of the position detection point is greater than or equal to , then the concentration data of the position detection point is divided into environmental disturbance data to form an environmental disturbance data set; if the environmental disturbance significance coefficient of the position detection point is less than , then the concentration data of the position detection point is divided into normal data to form a normal data set. Thus, the concentration data is divided into two sets, the normal data set and the environmental disturbance data set, which is convenient for the subsequent adjustment of the prediction model.

[0100] In a specific embodiment, a rapid detection and prediction model for groundwater remediation water pollution is constructed based on a normal data set and an environmental disturbance data set, and a dynamic detection and early warning of groundwater remediation water pollution is realized, including:

[0101] In the environmental disturbance data set, the data on concentration changes at different detection points in different sampling periods can be obtained;

[0102] According to the parameter acquisition process of the rapid detection and prediction model for groundwater remediation water pollution, the initial parameters of the normal data set and the environmental disturbance data set are respectively obtained; the rapid detection and prediction model for groundwater remediation water pollution is Predictive models.

[0103] The initial parameters of the environmental disturbance data set are weighted by the degree of data reference;

[0104] Finally, the initial parameters of the normal data set are averaged and the processed parameters are used as the parameters of the rapid detection and prediction model for groundwater remediation water pollution, thereby completing the construction of the rapid detection and prediction model for groundwater remediation water pollution.

[0105] In this embodiment, in the environmental disturbance data set, the data reference degree of concentration changes in different sampling periods at different detection points at different locations is obtained, including:

[0106] In the environmental disturbance data set, the environmental disturbance significance coefficients of different sampling periods detected at different locations are calculated;

[0107] Obtain the maximum value of the environmental disturbance significance coefficient of different sampling periods at different position detection points at the current moment, and the number of sampling periods obtained at the current moment;

[0108] Based on the calculated environmental disturbance significance coefficients of different sampling periods detected at different locations, the maximum value of the environmental disturbance significance coefficients of different sampling periods of detection points at different locations at the current moment, and the number of sampling periods obtained at the current moment, the data reference degree of concentration changes in different sampling periods at detection points at different locations is calculated.

[0109] This embodiment lists and calculates the data reference degree of concentration changes in different sampling periods at different detection points, and the calculation formula is as follows:

[0110] ;

[0111] in, Indicates The first position detection point The environmental disturbance significance coefficient of the concentration data of the sampling period is, Indicates the current moment The maximum value of the significant coefficient of environmental disturbance of the concentration data of the sampling period of the detection point at each location, It indicates the number of sampling cycles obtained at the current moment. It is worth noting that the maximum value of the significant coefficient of environmental disturbance is unlikely to be zero under normal circumstances, so the case where the maximum value of the significant coefficient of environmental disturbance is zero is not considered here.

[0112] This embodiment obtains the final rapid detection and prediction model for groundwater remediation water pollution. When the concentration data of target pollutants (such as nitrogen and phosphorus) at a location detection point are obtained, the nitrogen and phosphorus concentration data of multiple subsequent location detection points are predicted. Combined with the local nitrogen and phosphorus content requirement standard values, dynamic detection and early warning of water pollution in groundwater remediation can be achieved.

[0113] Example 2

[0114] Based on the method for rapid detection of water pollution applied to groundwater remediation described in Example 1, this embodiment also provides a system for rapid detection of water pollution applied to groundwater remediation, such as Figure 2 As shown, including:

[0115] The data acquisition module is used to obtain the concentration data of target pollutants collected at multiple location detection points in multiple sampling periods according to the sampling frequency after groundwater remediation, and to form a corresponding concentration change curve;

[0116] A position tendency degree calculation module is used to analyze the position tendency degree of the concentration change of the target pollutant at different position detection points in different sampling periods according to the concentration change curves of multiple position detection points;

[0117] The environmental disturbance significant coefficient calculation module is used to calculate the environmental disturbance significant coefficients of different position detection points according to the position tendency of different position detection points and the concentration change curve of the corresponding position detection points;

[0118] A division module is used to divide the concentration data of detection points at different locations into a normal data set and an environmental disturbance data set according to the environmental disturbance significance coefficient;

[0119] The prediction model construction module is used to complete the construction of a rapid detection and prediction model for groundwater remediation water pollution based on normal data sets and environmental disturbance data sets, and to achieve dynamic detection and early warning of groundwater remediation water pollution.

[0120] See also Figure 3 , Figure 3 5 is a schematic block diagram of a computer device provided by an embodiment of the present invention. The computer device 500 is a server, which may be an independent server or a server cluster composed of multiple servers.

[0121] See also Figure 3The computer device 500 includes a processor 502 , a memory and a network interface 505 connected via a system bus 501 , wherein the memory may include a non-volatile storage medium 503 and an internal memory 504 .

[0122] The non-volatile storage medium 503 can store an operating system 5031 and a computer program 5032. When the computer program 5032 is executed, the processor 502 can execute a rapid water pollution detection method for groundwater remediation.

[0123] The processor 502 is used to provide computing and control capabilities to support the operation of the entire computer device 500 .

[0124] The internal memory 504 provides an environment for the operation of the computer program 5032 in the non-volatile storage medium 503. When the computer program 5032 is executed by the processor 502, the processor 502 can execute a rapid detection method for water pollution applied to groundwater remediation.

[0125] The network interface 505 is used for network communication, such as providing data information transmission, etc. Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present invention, and does not constitute a limitation on the computer device 500 to which the solution of the present invention is applied. The specific computer device 500 may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0126] The processor 502 is used to run a computer program 5032 stored in the memory to implement the method for rapid detection of water pollution for groundwater remediation disclosed in an embodiment of the present invention.

[0127] Those skilled in the art will understand that Figure 3 The embodiment of the computer device shown in the figure does not constitute a limitation on the specific composition of the computer device. In other embodiments, the computer device may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently. For example, in some embodiments, the computer device may only include a memory and a processor. In such an embodiment, the structure and function of the memory and the processor are the same as those of the embodiment of the computer device. Figure 3 The embodiments shown are consistent and will not be described again here.

[0128] It should be understood that in the embodiment of the present invention, the processor 502 may be a central processing unit (CPU), and the processor 502 may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0129] In another embodiment of the present invention, a computer-readable storage medium is provided. The computer-readable storage medium may be a non-volatile computer-readable storage medium. The computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, the method for rapid detection of water pollution applied to groundwater remediation disclosed in an embodiment of the present invention is implemented.

[0130] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, the specific working process of the above-described equipment, devices and units can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here. Those of ordinary skill in the art can appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented with electronic hardware, computer software or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to the function. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0131] In the several embodiments provided by the present invention, it should be understood that the disclosed equipment, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. Units with the same function may also be combined into one unit. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interfaces, devices or units, or may be an electrical, mechanical or other form of connection.

[0132] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiments of the present invention.

[0133] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0134] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), magnetic disks or optical disks.

[0135] Obviously, the above embodiments of the present invention are only examples for clearly explaining the present invention, and are not intended to limit the implementation methods of the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention shall be included in the protection scope of the present invention.

Claims

1. A rapid detection method for water pollution applied to groundwater remediation, characterized by: The method comprises the following steps: After groundwater remediation, the concentration data of target pollutants collected at multiple location detection points in multiple sampling periods according to the sampling frequency are obtained, and the corresponding concentration change curve is formed; According to the concentration change curves of multiple detection points, the position tendency of the concentration change of the target pollutants at different detection points in different sampling periods is analyzed; According to the positional tendency of the detection points at different locations, combined with the concentration change curves of the detection points at the corresponding locations, the environmental disturbance significance coefficients of the detection points at different locations are calculated; According to the significant coefficient of environmental disturbance, the concentration data of detection points at different locations are divided into a normal data set and an environmental disturbance data set; Based on the normal data set and the environmental disturbance data set, a rapid detection and prediction model for groundwater remediation water pollution is constructed to achieve dynamic detection and early warning of groundwater remediation water pollution; Based on the concentration change curves of multiple detection points, the concentration change of target pollutants at different detection points in different sampling periods is analyzed, including: Obtain the concentration change curve of any detection point at any location, and use the end time of the groundwater remediation operation as the segmentation point to divide the concentration change curve into the remediation operation section and the post-remediation operation section; The derivative of the concentration change curve corresponding to the repair operation section is obtained to obtain the concentration change rate, thereby obtaining the concentration change rate mean value representing the concentration change status of the repair operation section; Obtain the coordinates of each position detection point, calculate the relative distance between any two position detection points, and determine the neighboring position detection points and their number based on the relative distance; According to the number of neighboring position detection points, the total number of sampling cycles, the average concentration change rate of the concentration change condition of the position detection point in the repair operation section, and the average concentration change rate of the concentration change condition of the neighboring position detection points adjacent to the position detection point in the repair operation section, the position tendency degree of the concentration change of the target pollutant at different position detection points in different sampling cycles is calculated; According to the positional tendency of the detection points at different locations, combined with the concentration change curves of the detection points at the corresponding locations, the environmental disturbance significance coefficients of the detection points at different locations are calculated, including: Sort the positional tendency degrees of all positional detection points within the neighborhood of each positional detection point to obtain a relative sequence of positional tendency degrees; For the concentration change curve of any position detection point in the latter part of the repair operation, the revolving door algorithm is used to perform straight line fitting on the concentration change curve in the latter part of the repair operation, and multiple segments of fitting straight lines are used to form a fitting broken line; Obtain the dtw score between the fitting polyline of any position detection point in the latter part of the repair operation and the fitting polyline of the remaining position detection points in the neighboring range in the latter part of the repair operation, and calculate the average of the dtw scores of the fitting polyline; wherein the dtw score is the similarity obtained between the two sequences consisting of the turning point coordinates of the two fitting polylines; Arrange the obtained dtw score means of the fitting line in the same order of the position tendency relative sequence to obtain the sequence of the mean dtw score of the fitting line; Obtain the relative sequence of the position tendency degree of each position detection point in the later stage of the remediation operation and the target pollutant position change distance on the fitting broken line dtw score sequence; Obtain the mean value of the target pollutant position change distance of detection points at different locations; The environmental disturbance significance coefficient of different location detection points is calculated by combining the target pollutant position change distance of different location detection points, the mean of the target pollutant position change distance, the sequence number of the position tendency degree of different location detection points in the relative sequence of position tendency degree, and the sequence number of the mean of the fitted broken line dtw score of different location detection points in the sequence of the mean of the fitted broken line dtw score.

2. The rapid detection method for water pollution applied to groundwater remediation according to claim 1 is characterized by: The target pollutants include one or more of nitrogen, phosphorus and their compounds.

3. The rapid detection method for water pollution applied to groundwater remediation according to claim 1 is characterized in that: According to the significant coefficient of environmental disturbance, the concentration data of detection points at different locations are divided into a normal data set and an environmental disturbance data set, including: Preset abnormal thresholds; If the environmental disturbance significance coefficient of the position detection point is greater than or equal to the preset abnormal threshold, the concentration data of the position detection point is divided into environmental disturbance data to form an environmental disturbance data set; If the environmental disturbance significance coefficient of the position detection point is less than the preset abnormal threshold, the concentration data of the position detection point is divided into normal data to form a normal data set.

4. The rapid detection method for water pollution applied to groundwater remediation according to claim 1 is characterized in that: Based on the normal data set and the environmental disturbance data set, the rapid detection and prediction model of groundwater remediation water pollution is constructed to achieve dynamic detection and early warning of groundwater remediation water pollution, including: In the environmental disturbance data set, the data on concentration changes at different detection points in different sampling periods can be obtained; According to the parameter acquisition process of the rapid detection and prediction model for groundwater remediation water pollution, the initial parameters of the normal data set and the environmental disturbance data set are respectively obtained; The initial parameters of the environmental disturbance data set are weighted by the degree of data reference; Finally, the initial parameters of the normal data set are averaged and the processed parameters are used as the parameters of the rapid detection and prediction model for groundwater remediation water pollution, thereby completing the construction of the rapid detection and prediction model for groundwater remediation water pollution.

5. The rapid detection method for water pollution applied to groundwater remediation according to claim 4 is characterized in that: In the environmental disturbance data set, the data on concentration changes at different detection points in different sampling periods can be obtained, including: In the environmental disturbance data set, the environmental disturbance significance coefficients of different sampling periods detected at different locations are calculated; Obtain the maximum value of the environmental disturbance significance coefficient of different sampling periods at different position detection points at the current moment, and the number of sampling periods obtained at the current moment; Based on the calculated environmental disturbance significance coefficients of different sampling periods detected at different locations, the maximum value of the environmental disturbance significance coefficients of different sampling periods of detection points at different locations at the current moment, and the number of sampling periods obtained at the current moment, the data reference degree of concentration changes in different sampling periods at detection points at different locations is calculated.

6. The method for rapid detection of water pollution for groundwater remediation according to claim 4, characterized in that: The groundwater remediation water pollution rapid detection prediction model is: Predictive models.

7. A rapid detection system for water pollution applied to groundwater remediation, the system being used to implement the rapid detection method for water pollution applied to groundwater remediation as claimed in claim 1, characterized in that: include: The data acquisition module is used to obtain the concentration data of target pollutants collected at multiple location detection points in multiple sampling periods according to the sampling frequency after groundwater remediation, and to form a corresponding concentration change curve; A position tendency degree calculation module is used to analyze the position tendency degree of the concentration change of the target pollutant at different position detection points in different sampling periods according to the concentration change curves of multiple position detection points; The environmental disturbance significant coefficient calculation module is used to calculate the environmental disturbance significant coefficients of different position detection points according to the position tendency of different position detection points and the concentration change curve of the corresponding position detection points; A division module is used to divide the concentration data of detection points at different locations into a normal data set and an environmental disturbance data set according to the environmental disturbance significance coefficient; The prediction model construction module is used to complete the construction of a rapid detection and prediction model for groundwater remediation water pollution based on normal data sets and environmental disturbance data sets, and to achieve dynamic detection and early warning of groundwater remediation water pollution.

8. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method for rapid detection of water pollution applied to groundwater remediation according to any one of claims 1 to 6 is implemented.

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