A deep water sampling system and method

Abstract

The application relates to the technical field of pollutant detection, and discloses a deep water sampling system and a sampling method, the system comprising: a collection module configured to determine a water area to be monitored, collect the area of the water area to be monitored, and determine an initial sampling frequency according to the area of the water area to be monitored; a judgment module configured to compare a heavy metal ion change rate with a heavy metal ion change rate threshold value, and judge whether the initial sampling frequency is adjusted according to a comparison result; an adjustment module configured to judge whether the adjusted sampling frequency is corrected according to real-time characteristic data, and obtain a corrected sampling frequency; and a processing module configured to collect organic matter content data of the water area to be monitored according to the corrected sampling frequency, and determine a pollution level of the water area to be monitored according to the organic matter content data and heavy metal ion concentration data. The application not only improves the accuracy of data collection, but also ensures the efficiency and adaptability of sampling activities through real-time monitoring and dynamic adjustment.

Description

Technical Field

[0001] This invention relates to the field of pollutant detection technology, and more specifically, to a deep-water sampling system and sampling method. Background Technology

[0002] In current deepwater sampling techniques, researchers and engineers typically employ a fixed-frequency sampling method. This method maintains a constant frequency during sampling, regardless of changes in the aquatic environment. However, this method has a significant drawback: it cannot adapt to dynamic changes in the aquatic environment. Because the aquatic environment is influenced by numerous factors, changes in these factors can alter the properties of the water. Therefore, when using fixed-frequency sampling, the accuracy and representativeness of the sampling data are often insufficient, failing to fully reflect the true condition of the water body.

[0003] Therefore, how to improve the sampling efficiency and accuracy of deep-water sampling systems has become a technical problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0004] In view of this, the present invention proposes a deep-water sampling system and sampling method, aiming to solve the problem of improving the sampling efficiency and accuracy of deep-water sampling systems in the current technology.

[0005] In one aspect, the present invention proposes a deep-water sampling system, comprising:

[0006] The data acquisition module is configured to determine the water area to be monitored, acquire the area of ​​the water area to be monitored, and determine the initial sampling frequency based on the area of ​​the water area to be monitored;

[0007] The judgment module is configured to control the acquisition module to collect heavy metal ion concentration data of the water area to be monitored through the initial sampling frequency, establish a heavy metal ion concentration dataset based on the heavy metal ion concentration data, determine the heavy metal ion concentration change rate of the water area to be monitored based on the heavy metal ion concentration dataset, compare the heavy metal ion change rate with a heavy metal ion change rate threshold, and determine whether to adjust the initial sampling frequency based on the comparison result.

[0008] The adjustment module is configured to determine the adjustment coefficient of the initial sampling frequency based on the change rate of heavy metal ions when it is determined that the initial sampling frequency needs to be adjusted, and to obtain the adjusted sampling frequency; it is also configured to control the acquisition module to acquire real-time characteristic data of the water area to be monitored, and to determine whether to correct the adjusted sampling frequency based on the real-time characteristic data, and to obtain the corrected sampling frequency.

[0009] The processing module is configured to collect organic matter content data of the water body to be monitored according to the modified sampling frequency, and determine the pollution level of the water body to be monitored based on the organic matter content data and heavy metal ion concentration data.

[0010] Furthermore, when determining the initial sampling frequency based on the area of ​​the water body to be monitored, the following steps are included:

[0011] The area of ​​the water body to be monitored is compared with the area of ​​the first water body and the area of ​​the second water body, and the initial sampling frequency is determined based on the comparison result; wherein, the area of ​​the first water body is smaller than the area of ​​the second water body.

[0012] When the area of ​​the water body to be monitored is less than or equal to the area of ​​the first water body, the initial sampling frequency is determined to be the first initial sampling frequency;

[0013] When the area of ​​the water body to be monitored is greater than the first water body area and less than or equal to the second water body area, the initial sampling frequency is determined to be the second initial sampling frequency.

[0014] When the area of ​​the water body to be monitored is greater than the area of ​​the second water body, the initial sampling frequency is determined to be the third initial sampling frequency;

[0015] Wherein, the first initial sampling frequency is less than the second initial sampling frequency, and the second initial sampling frequency is less than the third initial sampling frequency.

[0016] Further, when comparing the change rate of heavy metal ions with a threshold for the change rate of heavy metal ions, and determining whether to adjust the initial sampling frequency based on the comparison result, the following steps are included:

[0017] When the rate of change of heavy metal ions is greater than or equal to the threshold of the rate of change of heavy metal ions, it is determined that the initial sampling frequency should be adjusted.

[0018] When the rate of change of heavy metal ions is less than the threshold of the rate of change of heavy metal ions, it is determined that the initial sampling frequency will not be adjusted.

[0019] Further, when it is determined that the initial sampling frequency needs to be adjusted, the adjustment coefficient of the initial sampling frequency is determined based on the change rate of heavy metal ions, and the adjusted sampling frequency is obtained by including:

[0020] The difference in heavy metal ion changes is obtained based on the change rate of heavy metal ions and the threshold value of the change rate of heavy metal ions. The adjustment coefficient is determined based on the difference in heavy metal ion changes. The adjustment coefficient is inversely proportional to the difference in heavy metal ion changes.

[0021] The product of the adjustment coefficient and the initial sampling frequency is the adjusted sampling frequency.

[0022] Further, determining whether to correct the adjusted sampling frequency based on the real-time feature data, and obtaining the corrected sampling frequency, includes:

[0023] Collect historical feature data and calculate the similarity between the real-time feature data and the historical feature data;

[0024] The similarity is compared with the similarity threshold, and the comparison result determines whether the sampling frequency adjustment needs to be corrected.

[0025] When the similarity threshold is less than or equal to the similarity threshold, it is determined that the corrected sampling frequency should be corrected.

[0026] When the similarity is greater than the similarity threshold, it is determined that the corrected sampling frequency will not be corrected.

[0027] Furthermore, the similarity is obtained by the following formula:

[0028]

[0029] Where S represents similarity, A represents real-time feature vector, B represents historical feature vector, ωi represents feature weight, Ai represents the i-th element of real-time feature vector, Bi represents the i-th element of historical feature vector, and n represents vector dimension.

[0030] Furthermore, the real-time feature data includes real-time water temperature, real-time water flow velocity, real-time water flow direction, real-time dissolved oxygen content, and real-time pH value;

[0031] The historical characteristic data includes historical water temperature, historical water flow velocity, historical water flow direction, historical dissolved oxygen content, and historical pH value.

[0032] Further, determining when to correct the modified sampling frequency includes:

[0033] A preset correction coefficient range is defined, wherein the correction coefficient range includes a first correction coefficient, a second correction coefficient, and a third correction coefficient;

[0034] Calculate the similarity ratio between the stated similarity and the stated similarity threshold;

[0035] When the similarity ratio is greater than or equal to 0.5 and less than 0.65, the first correction coefficient is selected as the correction coefficient corresponding to the adjusted sampling frequency, and the product of the first correction coefficient and the adjusted sampling frequency is used as the adjusted sampling frequency.

[0036] When the similarity ratio is greater than or equal to 0.65 and less than 0.85, the second correction coefficient is selected as the correction coefficient corresponding to the adjusted sampling frequency, and the product of the second correction coefficient and the adjusted sampling frequency is used as the adjusted sampling frequency.

[0037] When the similarity ratio is greater than or equal to 0.85, the third correction coefficient is selected as the correction coefficient corresponding to the adjusted sampling frequency, and the product of the third correction coefficient and the adjusted sampling frequency is used as the adjusted sampling frequency.

[0038] Furthermore, when determining the pollution level of the water body to be monitored based on the organic matter content data and heavy metal ion concentration data, the following steps are included:

[0039] Pollution indicators were calculated based on the organic matter content data and heavy metal ion concentration data.

[0040] The pollution index is compared with a first pollution index threshold, a second pollution index threshold, and a third pollution index threshold, and the pollution level of the water body to be monitored is determined based on the comparison results; wherein, the first pollution index threshold is less than the second pollution index threshold, and the second pollution index threshold is less than the third pollution index threshold.

[0041] When the pollution index is less than or equal to the first pollution index threshold, the pollution level of the water body to be monitored is determined to be Level 1.

[0042] When the pollution index is greater than the first pollution index threshold and less than or equal to the second pollution index threshold, the pollution level of the water body to be monitored is determined to be the second level.

[0043] When the pollution index is greater than the second pollution index threshold and less than or equal to the third pollution index threshold, the pollution level of the water body to be monitored is determined to be level three.

[0044] When the pollution index is greater than the third pollution index threshold, the pollution level of the water body to be monitored is determined to be level four.

[0045] Compared with existing technologies, the advantages of this invention are as follows: The deep-water sampling system provided by this invention has a flexible sampling strategy, capable of dynamically adjusting the sampling frequency and method according to the real-time conditions of the water area. The initial sampling frequency is determined based on the area of ​​the water area to be monitored, which provides a foundation for subsequent sampling activities. By collecting heavy metal ion concentration data and establishing a dataset, the system can assess the rate of change of heavy metal ion concentration and compare it with a preset threshold to determine whether the sampling frequency needs to be adjusted. If adjustment is required, an adjustment coefficient will be determined based on the rate of change of heavy metal ion concentration, and the sampling frequency will be further corrected. Finally, the system will collect organic matter content data based on the corrected sampling frequency and combine it with heavy metal ion concentration data to determine the pollution level of the water area. This not only improves the accuracy of data collection but also ensures the efficiency and adaptability of sampling activities through real-time monitoring and dynamic adjustment, providing strong technical support for environmental monitoring and pollution control.

[0046] In another aspect, the present invention also proposes a deep-water sampling method, comprising the following steps:

[0047] S100: Determine the water area to be monitored, collect the area of ​​the water area to be monitored, and determine the initial sampling frequency based on the area of ​​the water area to be monitored;

[0048] S200: Using the initial sampling frequency, control the acquisition module to collect heavy metal ion concentration data of the water area to be monitored, establish a heavy metal ion concentration dataset based on the heavy metal ion concentration data, determine the heavy metal ion concentration change rate of the water area to be monitored based on the heavy metal ion concentration dataset, compare the heavy metal ion change rate with a heavy metal ion change rate threshold, and determine whether to adjust the initial sampling frequency based on the comparison result;

[0049] S300: When it is determined that the initial sampling frequency needs to be adjusted, the adjustment coefficient of the initial sampling frequency is determined according to the change rate of heavy metal ions to obtain the adjusted sampling frequency; it is also configured to control the acquisition module to acquire real-time characteristic data of the water area to be monitored, and determine whether to correct the adjusted sampling frequency according to the real-time characteristic data to obtain the corrected sampling frequency;

[0050] S400: Collect organic matter content data of the water area to be monitored according to the corrected sampling frequency, and determine the pollution level of the water area to be monitored based on the organic matter content data and heavy metal ion concentration data.

[0051] It is understandable that the aforementioned deep-water sampling system and sampling method have the same beneficial effects, and will not be elaborated further here. Attached Figure Description

[0052] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0053] Figure 1 This is a structural block diagram of a deep-water sampling system provided in an embodiment of the present invention;

[0054] Figure 2 This is a flowchart of a deep-water sampling method provided in an embodiment of the present invention. Detailed Implementation

[0055] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the disclosure to those skilled in the art. It should be noted that, unless otherwise specified, embodiments and features in the embodiments of the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0056] See Figure 1 As shown in some embodiments of this application, this embodiment provides a deep-water sampling system, including:

[0057] The data acquisition module is configured to determine the water area to be monitored, acquire the area of ​​the water area to be monitored, and determine the initial sampling frequency based on the area of ​​the water area to be monitored;

[0058] The judgment module is configured to control the acquisition module to collect heavy metal ion concentration data of the water area to be monitored through the initial sampling frequency, establish a heavy metal ion concentration dataset based on the heavy metal ion concentration data, determine the heavy metal ion concentration change rate of the water area to be monitored based on the heavy metal ion concentration dataset, compare the heavy metal ion change rate with a heavy metal ion change rate threshold, and determine whether to adjust the initial sampling frequency based on the comparison result.

[0059] The adjustment module is configured to determine the adjustment coefficient of the initial sampling frequency based on the change rate of heavy metal ions when it is determined that the initial sampling frequency needs to be adjusted, and to obtain the adjusted sampling frequency; it is also configured to control the acquisition module to acquire real-time characteristic data of the water area to be monitored, and to determine whether to correct the adjusted sampling frequency based on the real-time characteristic data, and to obtain the corrected sampling frequency.

[0060] The processing module is configured to collect organic matter content data of the water body to be monitored according to the modified sampling frequency, and determine the pollution level of the water body to be monitored based on the organic matter content data and heavy metal ion concentration data.

[0061] Understandably, the deep-water sampling system provided in this embodiment, by identifying the water area to be monitored, can more accurately determine the sampling area, thereby improving the accuracy and reliability of the data. By monitoring the rate of change in heavy metal ion concentration in real time and comparing it with a preset threshold, the system can adjust the sampling frequency to ensure that key information can be captured in a timely manner when pollution conditions change. This not only improves monitoring efficiency but also reduces unnecessary sampling, thus saving resources. After determining the pollution level, the processing module can further guide the implementation of corresponding environmental protection measures, such as adjusting wastewater treatment processes or taking emergency response measures, to mitigate or prevent further spread of pollution. In this way, the deep-water sampling system and sampling method provide strong technical support for the monitoring and management of water pollution.

[0062] Specifically, determining the initial sampling frequency based on the area of ​​the water body to be monitored includes:

[0063] The area of ​​the water body to be monitored is compared with the area of ​​the first water body and the area of ​​the second water body, and the initial sampling frequency is determined based on the comparison result; wherein, the area of ​​the first water body is smaller than the area of ​​the second water body.

[0064] When the area of ​​the water body to be monitored is less than or equal to the area of ​​the first water body, the initial sampling frequency is determined to be the first initial sampling frequency;

[0065] When the area of ​​the water body to be monitored is greater than the first water body area and less than or equal to the second water body area, the initial sampling frequency is determined to be the second initial sampling frequency.

[0066] When the area of ​​the water body to be monitored is greater than the area of ​​the second water body, the initial sampling frequency is determined to be the third initial sampling frequency;

[0067] Wherein, the first initial sampling frequency is less than the second initial sampling frequency, and the second initial sampling frequency is less than the third initial sampling frequency.

[0068] Understandably, this approach allows the system to flexibly adjust sampling frequencies based on the area of ​​the water body, adapting to monitoring needs at different scales. Furthermore, by monitoring the rate of change in heavy metal ion concentration in real time and comparing it with preset thresholds, the system can dynamically adjust the sampling frequency, ensuring timely capture of critical information when pollution conditions change. This not only improves monitoring efficiency but also reduces unnecessary sampling, thereby conserving resources.

[0069] Specifically, when comparing the change rate of heavy metal ions with a threshold for the change rate of heavy metal ions, and determining whether to adjust the initial sampling frequency based on the comparison result, the following steps are included:

[0070] When the rate of change of heavy metal ions is greater than or equal to the threshold of the rate of change of heavy metal ions, it is determined that the initial sampling frequency should be adjusted.

[0071] When the rate of change of heavy metal ions is less than the threshold of the rate of change of heavy metal ions, it is determined that the initial sampling frequency will not be adjusted.

[0072] Understandably, in practical applications, the system compares the real-time monitored rate of change in heavy metal ion concentration with a preset threshold. If the rate of change exceeds the threshold, the system adjusts the sampling frequency to ensure timely capture of key information regarding pollution changes. This dynamic adjustment mechanism allows the sampling frequency to change according to actual pollution conditions, thereby improving monitoring flexibility and efficiency. Conversely, if the rate of change in heavy metal ion concentration is below the threshold, the system maintains the current sampling frequency, avoiding unnecessary frequent sampling and further conserving resources. In this way, deep-water sampling systems can more accurately reflect the pollution status of water bodies, providing a scientific basis for environmental protection and pollution control.

[0073] Specifically, when it is determined that the initial sampling frequency needs to be adjusted, the adjustment coefficient of the initial sampling frequency is determined based on the change rate of heavy metal ions, and the adjusted sampling frequency is obtained by including:

[0074] The difference in heavy metal ion changes is obtained based on the change rate of heavy metal ions and the threshold value of the change rate of heavy metal ions. The adjustment coefficient is determined based on the difference in heavy metal ion changes. The adjustment coefficient is inversely proportional to the difference in heavy metal ion changes.

[0075] The product of the adjustment coefficient and the initial sampling frequency is the adjusted sampling frequency.

[0076] Understandably, the adjustment coefficient is determined based on the actual changes in heavy metal ion concentration, ensuring that the sampling frequency adjustment is both timely and reasonable. Through an inverse relationship, the system can adjust the sampling frequency according to the severity of changes in heavy metal ion concentration, thereby increasing the sampling frequency when pollution intensifies and decreasing it when pollution is stable. This intelligent adjustment mechanism not only improves the accuracy of monitoring but also effectively avoids waste of resources.

[0077] Specifically, determining whether to correct the adjusted sampling frequency based on the real-time feature data, and obtaining the corrected sampling frequency, includes:

[0078] Collect historical feature data and calculate the similarity between the real-time feature data and the historical feature data;

[0079] The similarity is compared with the similarity threshold, and the comparison result determines whether the sampling frequency adjustment needs to be corrected.

[0080] When the similarity threshold is less than or equal to the similarity threshold, it is determined that the corrected sampling frequency should be corrected.

[0081] When the similarity is greater than the similarity threshold, it is determined that the corrected sampling frequency will not be corrected.

[0082] Understandably, by comparing the similarity between real-time monitoring data and historical data, the system can determine whether the pollution status of the water body has changed significantly. If the similarity is below a set threshold, it indicates that the pollution status may have changed, and the system will automatically adjust the sampling frequency to adapt to the new monitoring needs. Conversely, if the similarity is above the threshold, it indicates that the pollution status is relatively stable, and the system will maintain the current sampling frequency, avoiding unnecessary sampling operations. In this way, the deep-water sampling system can respond more intelligently to the dynamic changes in water pollution, ensuring the timeliness and accuracy of monitoring data, and providing strong support for timely and effective environmental protection measures.

[0083] Specifically, the similarity is obtained by the following formula:

[0084]

[0085] Where S represents similarity, A represents real-time feature vector, B represents historical feature vector, ωi represents feature weight, Ai represents the i-th element of real-time feature vector, Bi represents the i-th element of historical feature vector, and n represents vector dimension.

[0086] Understandably, the above formula allows the system to quantitatively assess the degree of difference between real-time and historical data. The introduction of feature weights ωi enables the system to consider the importance of different features when calculating similarity, thus more accurately reflecting changes in water pollution levels. For example, some features may be more sensitive to changes in pollution levels, and therefore are given higher weights to ensure these features play a greater role in similarity calculations. In this way, the deep-water sampling system not only provides timely monitoring data but also intelligently adjusts the sampling frequency based on the importance and trends of the data, thereby providing more accurate and efficient decision support for environmental protection efforts. A concrete example will illustrate how to calculate the similarity between real-time and historical feature data.

[0087] In this embodiment, the real-time feature vectors include real-time water temperature vector, real-time water flow velocity vector, real-time water flow direction vector, real-time dissolved oxygen content vector, and real-time pH value vector; the historical feature vectors include historical water temperature vector, historical water flow velocity vector, historical water flow direction vector, historical dissolved oxygen content vector, and historical pH value vector. By comparing corresponding elements of these vectors, the system can calculate the similarity between real-time and historical data. For example, if the difference between the real-time and historical water temperature vectors is large, it may indicate a significant change in water temperature, and the system will adjust the sampling frequency based on this change. The similarity calculation result will directly affect the sampling frequency adjustment decision, ensuring that the dynamic adjustment of the sampling frequency is both scientific and reasonable. In this way, the deep-water sampling system can more accurately monitor changes in the aquatic environment, providing more timely and accurate data support for environmental protection and pollution control.

[0088] Specifically, the real-time feature data includes real-time water temperature, real-time water flow velocity, real-time water flow direction, real-time dissolved oxygen content, and real-time pH value.

[0089] The historical characteristic data includes historical water temperature, historical water flow velocity, historical water flow direction, historical dissolved oxygen content, and historical pH value.

[0090] Understandably, the acquisition of real-time and historical characteristic data is accomplished through multiple sensors within the deep-water sampling system. These sensors are designed to withstand the high pressure and corrosive conditions of deep-water environments, ensuring the accuracy and reliability of the data. The system's data processing unit periodically collects sensor readings and compares them with stored historical data. Through this comparison, the system can identify early signs of pollution events, thereby adjusting the sampling frequency in a timely manner to ensure that the entire process of a pollution event is captured.

[0091] Specifically, determining to correct the modified sampling frequency includes:

[0092] A preset correction coefficient range is defined, wherein the correction coefficient range includes a first correction coefficient, a second correction coefficient, and a third correction coefficient;

[0093] Calculate the similarity ratio between the stated similarity and the stated similarity threshold;

[0094] When the similarity ratio is greater than or equal to 0.5 and less than 0.65, the first correction coefficient is selected as the correction coefficient corresponding to the adjusted sampling frequency, and the product of the first correction coefficient and the adjusted sampling frequency is used as the adjusted sampling frequency.

[0095] When the similarity ratio is greater than or equal to 0.65 and less than 0.85, the second correction coefficient is selected as the correction coefficient corresponding to the adjusted sampling frequency, and the product of the second correction coefficient and the adjusted sampling frequency is used as the adjusted sampling frequency.

[0096] When the similarity ratio is greater than or equal to 0.85, the third correction coefficient is selected as the correction coefficient corresponding to the adjusted sampling frequency, and the product of the third correction coefficient and the adjusted sampling frequency is used as the adjusted sampling frequency.

[0097] Understandably, by setting different correction coefficient ranges, the system can flexibly adjust the sampling frequency based on the specific similarity values ​​between real-time and historical data. For example, when the similarity ratio falls between 0.5 and 0.65, the first correction coefficient is selected to increase the sampling frequency by a small margin. When the similarity ratio is between 0.65 and 0.85, the second correction coefficient is used to adjust the sampling frequency by a moderate margin. And when the similarity ratio is greater than or equal to 0.85, the third correction coefficient is used to adjust the sampling frequency by a larger margin. This tiered adjustment mechanism ensures that the adjustment of the sampling frequency neither overreacts to minor changes nor ignores important pollution events, thereby optimizing resource utilization efficiency while ensuring the quality of monitoring data. In this way, the deep-water sampling system can more intelligently adapt to the dynamic changes in the aquatic environment, providing scientific and reasonable data support for environmental protection and pollution control.

[0098] In this embodiment, the first, second, and third correction coefficients are in the order of first correction coefficient < second correction coefficient < third correction coefficient. This setting ensures that the adjustment range of the sampling frequency increases with the increase of the similarity ratio. For example, if the similarity ratio is low, it indicates that the current water condition has not changed much compared to historical data. In this case, the system will use a smaller first correction coefficient to avoid frequent sampling operations and save resources. Conversely, if the similarity ratio is high, it indicates that the water condition has changed significantly. The system will use a larger third correction coefficient to ensure that these changes can be captured in a timely manner, providing accurate data support for the formulation of environmental protection measures. In this way, the deep-water sampling system can not only intelligently respond to the dynamic changes in water pollution, but also rationally allocate sampling resources according to the actual changes in water conditions, thereby improving monitoring efficiency.

[0099] Specifically, when determining the pollution level of the water body to be monitored based on the organic matter content data and heavy metal ion concentration data, the following steps are included:

[0100] Pollution indicators were calculated based on the organic matter content data and heavy metal ion concentration data.

[0101] In this embodiment, the pollution index is obtained by the following formula:

[0102] W = k1 × C + k2 × D;

[0103] Where W represents the pollution index, k1 and k2 represent the influence coefficients, C represents the organic matter content, and D represents the heavy metal ion concentration.

[0104] The pollution index is compared with a first pollution index threshold, a second pollution index threshold, and a third pollution index threshold, and the pollution level of the water body to be monitored is determined based on the comparison results; wherein, the first pollution index threshold is less than the second pollution index threshold, and the second pollution index threshold is less than the third pollution index threshold.

[0105] When the pollution index is less than or equal to the first pollution index threshold, the pollution level of the water body to be monitored is determined to be Level 1.

[0106] When the pollution index is greater than the first pollution index threshold and less than or equal to the second pollution index threshold, the pollution level of the water body to be monitored is determined to be the second level.

[0107] When the pollution index is greater than the second pollution index threshold and less than or equal to the third pollution index threshold, the pollution level of the water body to be monitored is determined to be level three.

[0108] When the pollution index is greater than the third pollution index threshold, the pollution level of the water body to be monitored is determined to be level four.

[0109] Understandably, the system compares calculated pollution indicators with preset pollution thresholds to classify the pollution status of water bodies. This classification mechanism helps to quickly identify the severity of pollution, providing a basis for taking appropriate environmental protection measures. For example, when the pollution indicator is below the first pollution threshold, the system classifies the water body as Level 1, meaning the pollution level is relatively low and may only require routine monitoring and management. However, if the pollution indicator exceeds the third pollution threshold, the system classifies the water body as Level 4, indicating a severe pollution situation requiring immediate emergency measures, such as increasing monitoring frequency and initiating pollution control procedures. Through this classification process, the deep-water sampling system not only provides accurate pollution data but also assists decision-makers in developing more targeted environmental management strategies to effectively respond to various pollution incidents.

[0110] See Figure 2 As shown in some embodiments of this application, this embodiment provides a deep-water sampling method, including the following steps:

[0111] S100: Determine the water area to be monitored, collect the area of ​​the water area to be monitored, and determine the initial sampling frequency based on the area of ​​the water area to be monitored;

[0112] S200: Using the initial sampling frequency, control the acquisition module to collect heavy metal ion concentration data of the water area to be monitored, establish a heavy metal ion concentration dataset based on the heavy metal ion concentration data, determine the heavy metal ion concentration change rate of the water area to be monitored based on the heavy metal ion concentration dataset, compare the heavy metal ion change rate with a heavy metal ion change rate threshold, and determine whether to adjust the initial sampling frequency based on the comparison result;

[0113] S300: When it is determined that the initial sampling frequency needs to be adjusted, the adjustment coefficient of the initial sampling frequency is determined according to the change rate of heavy metal ions to obtain the adjusted sampling frequency; it is also configured to control the acquisition module to acquire real-time characteristic data of the water area to be monitored, and determine whether to correct the adjusted sampling frequency according to the real-time characteristic data to obtain the corrected sampling frequency;

[0114] S400: Collect organic matter content data of the water area to be monitored according to the corrected sampling frequency, and determine the pollution level of the water area to be monitored based on the organic matter content data and heavy metal ion concentration data.

[0115] It is understood that the deep-water sampling method provided in this embodiment has a flexible sampling strategy, capable of dynamically adjusting the sampling frequency and method according to the real-time conditions of the water area. In step S100, the initial sampling frequency is determined based on the area of ​​the water area to be monitored, which provides a basis for subsequent sampling activities. In step S200, by collecting heavy metal ion concentration data and establishing a dataset, the system can assess the rate of change of heavy metal ion concentration and compare it with a preset threshold to determine whether the sampling frequency needs to be adjusted. If adjustment is required, step S300 will determine an adjustment coefficient based on the rate of change of heavy metal ion concentration and further correct the sampling frequency. Finally, in step S400, the system will collect organic matter content data based on the corrected sampling frequency and combine it with heavy metal ion concentration data to determine the pollution level of the water area. This sampling method not only improves the accuracy of data collection but also ensures the efficiency and adaptability of sampling activities through real-time monitoring and dynamic adjustment, providing strong technical support for environmental monitoring and pollution control.

[0116] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program goods. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program goods embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0117] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program goods according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0118] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0119] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0120] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A deep-water sampling system, characterized in that, include: The data acquisition module is configured to determine the water area to be monitored, acquire the area of ​​the water area to be monitored, and determine the initial sampling frequency based on the area of ​​the water area to be monitored; The judgment module is configured to control the acquisition module to collect heavy metal ion concentration data of the water area to be monitored through the initial sampling frequency, establish a heavy metal ion concentration dataset based on the heavy metal ion concentration data, determine the heavy metal ion concentration change rate of the water area to be monitored based on the heavy metal ion concentration dataset, compare the heavy metal ion change rate with a heavy metal ion change rate threshold, and determine whether to adjust the initial sampling frequency based on the comparison result. The adjustment module is configured to determine the adjustment coefficient of the initial sampling frequency based on the change rate of heavy metal ions when it is determined that the initial sampling frequency needs to be adjusted, and to obtain the adjusted sampling frequency; it is also configured to control the acquisition module to acquire real-time characteristic data of the water area to be monitored, and to determine whether to correct the adjusted sampling frequency based on the real-time characteristic data, and to obtain the corrected sampling frequency. The processing module is configured to collect organic matter content data of the water area to be monitored according to the corrected sampling frequency, and determine the pollution level of the water area to be monitored based on the organic matter content data and heavy metal ion concentration data. Determining whether to correct the adjusted sampling frequency based on the real-time feature data, and obtaining the corrected sampling frequency, includes: Collect historical feature data and calculate the similarity between the real-time feature data and the historical feature data; The similarity is compared with the similarity threshold, and the comparison result determines whether the sampling frequency adjustment needs to be corrected. When the similarity is less than or equal to the similarity threshold, it is determined that the corrected sampling frequency should be corrected. When the similarity is greater than the similarity threshold, it is determined that the corrected sampling frequency will not be corrected. The similarity is obtained by the following formula: Where S represents similarity, A represents real-time feature vector, B represents historical feature vector, ωi represents feature weight, Ai represents the i-th element of real-time feature vector, Bi represents the i-th element of historical feature vector, and n represents vector dimension. The real-time feature data includes real-time water temperature, real-time water flow velocity, real-time water flow direction, real-time dissolved oxygen content, and real-time pH value. The historical characteristic data includes historical water temperature, historical water flow velocity, historical water flow direction, historical dissolved oxygen content, and historical pH value; Determining whether to correct the modified sampling frequency includes: A preset correction coefficient range is defined, wherein the correction coefficient range includes a first correction coefficient, a second correction coefficient, and a third correction coefficient; Calculate the similarity ratio between the stated similarity and the stated similarity threshold; When the similarity ratio is greater than or equal to 0.5 and less than 0.65, the first correction coefficient is selected as the correction coefficient corresponding to the adjusted sampling frequency, and the product of the first correction coefficient and the adjusted sampling frequency is used as the adjusted sampling frequency. When the similarity ratio is greater than or equal to 0.65 and less than 0.85, the second correction coefficient is selected as the correction coefficient corresponding to the adjusted sampling frequency, and the product of the second correction coefficient and the adjusted sampling frequency is used as the adjusted sampling frequency. When the similarity ratio is greater than or equal to 0.85, the third correction coefficient is selected as the correction coefficient corresponding to the adjusted sampling frequency, and the product of the third correction coefficient and the adjusted sampling frequency is used as the adjusted sampling frequency.

2. The deep-water sampling system according to claim 1, characterized in that, When determining the initial sampling frequency based on the area of ​​the water body to be monitored, the following are included: The area of ​​the water body to be monitored is compared with the area of ​​the first water body and the area of ​​the second water body, and the initial sampling frequency is determined based on the comparison result; wherein, the area of ​​the first water body is smaller than the area of ​​the second water body. When the area of ​​the water body to be monitored is less than or equal to the area of ​​the first water body, the initial sampling frequency is determined to be the first initial sampling frequency; When the area of ​​the water body to be monitored is greater than the first water body area and less than or equal to the second water body area, the initial sampling frequency is determined to be the second initial sampling frequency. When the area of ​​the water body to be monitored is greater than the area of ​​the second water body, the initial sampling frequency is determined to be the third initial sampling frequency; Wherein, the first initial sampling frequency is less than the second initial sampling frequency, and the second initial sampling frequency is less than the third initial sampling frequency.

3. The deep-water sampling system according to claim 2, characterized in that, When comparing the change rate of heavy metal ions with a threshold for the change rate of heavy metal ions, and determining whether to adjust the initial sampling frequency based on the comparison result, the following steps are included: When the rate of change of heavy metal ions is greater than or equal to the threshold of the rate of change of heavy metal ions, it is determined that the initial sampling frequency should be adjusted. When the rate of change of heavy metal ions is less than the threshold of the rate of change of heavy metal ions, it is determined that the initial sampling frequency will not be adjusted.

4. The deep-water sampling system according to claim 3, characterized in that, When it is determined that the initial sampling frequency needs to be adjusted, the adjustment coefficient of the initial sampling frequency is determined based on the change rate of heavy metal ions. Obtaining the adjusted sampling frequency includes: The difference in heavy metal ion changes is obtained based on the change rate of heavy metal ions and the threshold value of the change rate of heavy metal ions. The adjustment coefficient is determined based on the difference in heavy metal ion changes. The adjustment coefficient is inversely proportional to the difference in heavy metal ion changes. The product of the adjustment coefficient and the initial sampling frequency is the adjusted sampling frequency.

5. The deep-water sampling system according to claim 1, characterized in that, When determining the pollution level of the water body to be monitored based on the organic matter content data and heavy metal ion concentration data, the following methods are included: Pollution indicators were calculated based on the organic matter content data and heavy metal ion concentration data. The pollution index is compared with a first pollution index threshold, a second pollution index threshold, and a third pollution index threshold, and the pollution level of the water body to be monitored is determined based on the comparison results; wherein, the first pollution index threshold is less than the second pollution index threshold, and the second pollution index threshold is less than the third pollution index threshold. When the pollution index is less than or equal to the first pollution index threshold, the pollution level of the water body to be monitored is determined to be Level 1. When the pollution index is greater than the first pollution index threshold and less than or equal to the second pollution index threshold, the pollution level of the water body to be monitored is determined to be the second level. When the pollution index is greater than the second pollution index threshold and less than or equal to the third pollution index threshold, the pollution level of the water body to be monitored is determined to be level three. When the pollution index is greater than the third pollution index threshold, the pollution level of the water body to be monitored is determined to be level four.

6. A deep-water sampling method, applied to the deep-water sampling system as described in any one of claims 1-5, characterized in that, include: Identify the water area to be monitored, collect the area of ​​the water area to be monitored, and determine the initial sampling frequency based on the area of ​​the water area to be monitored; The initial sampling frequency is used to control the acquisition module to collect heavy metal ion concentration data of the water area to be monitored. A heavy metal ion concentration dataset is established based on the heavy metal ion concentration data. The heavy metal ion concentration change rate of the water area to be monitored is determined based on the heavy metal ion concentration dataset. The heavy metal ion change rate is compared with a heavy metal ion change rate threshold. Based on the comparison result, it is determined whether to adjust the initial sampling frequency. When it is determined that the initial sampling frequency needs to be adjusted, the adjustment coefficient of the initial sampling frequency is determined based on the change rate of heavy metal ions to obtain the adjusted sampling frequency; it is also configured to control the acquisition module to acquire real-time characteristic data of the water area to be monitored, and determine whether to correct the adjusted sampling frequency based on the real-time characteristic data to obtain the corrected sampling frequency; Organic matter content data of the water body to be monitored are collected according to the corrected sampling frequency, and the pollution level of the water body to be monitored is determined based on the organic matter content data and the heavy metal ion concentration data.

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