A Dynamic Monitoring Method for Agricultural Non-point Source Pollution Based on Multi-Source Heterogeneous Data

Abstract

This invention discloses a dynamic monitoring method for agricultural non-point source pollution based on multi-source heterogeneous data, belonging to the field of pollution dynamic monitoring technology. It addresses the problems of distorted monitoring data and low monitoring accuracy. By selecting multiple sets of different input powers to input into a flue gas capture system and setting a detection time, the method monitors the flue gas flow rate and carbon dioxide concentration under each input power. After screening the input powers, candidate capture powers are obtained. An input range is set based on the candidate powers, and capture powers are randomly set, marked, and input into the system within the range. The corresponding vibration frequency is detected, and the capture powers are sorted and the changes in adjacent powers and vibration frequencies are calculated. A target capture power is then comprehensively selected. Based on the target power, the method monitors whether farmland flue gas emissions meet standards, thereby dynamically optimizing agricultural non-point source pollution monitoring from both energy-saving and efficiency-improving perspectives, and achieving timely early warning of pollution risks.

Description

Technical Field

[0001] This invention relates to the field of pollution dynamic monitoring technology, and more specifically, to a method for dynamic monitoring of agricultural non-point source pollution based on multi-source heterogeneous data. Background Technology

[0002] Agricultural non-point source pollution refers to the non-point source emissions of pollutants generated by activities such as fertilization, irrigation, pesticide use, and burning of crop straw during agricultural production. This type of pollution is characterized by dispersed emission sources, uneven spatial and temporal distribution, and complex pollutants.

[0003] The existing technology has the following shortcomings:

[0004] Currently, some studies have attempted to use flue gas capture systems to monitor farmland straw burning or soil greenhouse gas emissions. However, due to the unstable operating state of flue gas capture systems under different input power, abnormal equipment vibration frequency or excessive power fluctuations are easily caused, resulting in distorted monitoring data. Existing methods usually cannot automatically screen based on equipment power adjustment characteristics and operational stability, making it impossible to select appropriate input power for the flue gas capture system and maintain stable operation, thus reducing monitoring accuracy and reliability. Therefore, a dynamic monitoring method for agricultural non-point source pollution based on multi-source heterogeneous data is proposed.

[0005] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0006] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide a dynamic monitoring method for agricultural non-point source pollution based on multi-source heterogeneous data. This method addresses the problems mentioned in the background art by employing power regulation characteristic analysis, equipment vibration frequency characteristic monitoring, and a multi-source data fusion and screening mechanism.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a method for dynamic monitoring of agricultural non-point source pollution based on multi-source heterogeneous data, comprising the following steps:

[0008] Step S1: In the farmland to be tested, select multiple sets of different input power to input the flue gas capture system in the farmland to be tested, set the detection time, and detect the flue gas flow rate and carbon dioxide concentration absorbed by the flue gas capture system under each set of input power within the detection time.

[0009] Step S2: Calculate the carbon content of flue gas under each group of input power based on carbon dioxide concentration, generate flue gas flow coefficient under each group of input power after standard processing of flue gas flow rate, and screen each group of input power to obtain candidate capture power based on the carbon content of flue gas.

[0010] Step S3: Set the input power range according to the candidate capture power, randomly set the capture power in each input power range, mark it, and input it into the flue gas capture system in the farmland to be tested, and detect the vibration frequency of the capture equipment under each capture power.

[0011] Step S4: After sorting the capture power, calculate the power change of adjacent capture power and the vibration frequency change of the capture equipment. Combine the power change and the vibration frequency change of the capture equipment to select the target capture power. Use the target capture power as the input power of the flue gas capture system at the farmland monitoring point to be tested. Detect the flue gas emission of the capture equipment and determine whether to issue a pollution alarm.

[0012] In a preferred embodiment, in step S1, the input power range of the flue gas capture system in the historical database is called, multiple input powers are randomly set within the input power range and grouped, a period of time is selected as the detection time, and each group of input power is used as the input of the flue gas capture system in each detection time. The flow rate of the flue gas absorbed by the flue gas capture system under each group of input power is detected by the flow meter during the detection time.

[0013] A carbon dioxide sensor is used to detect the concentration of carbon dioxide absorbed by the flue gas capture system under each input power group. For each flue gas capture system under each input power group, the carbon dioxide concentration in the test environment where the flue gas capture system is located is detected before the detection time, and the carbon dioxide concentration in the test environment where the flue gas capture system is located is detected a second time after the detection time. The difference between the two detection results is taken as the concentration of carbon dioxide absorbed by the flue gas capture system under the corresponding input power group.

[0014] In a preferred embodiment, in step S2, in the test environment, the total concentration of gas in the test environment is detected by a gas composition analyzer, and the ratio of carbon dioxide concentration to total gas concentration is calculated to obtain the carbon content of flue gas under each group of input power.

[0015] By calling the historical flue gas flow database, the maximum and minimum historical flue gas flow values ​​are determined to construct a standardized reference range. The flue gas flow is then standardized to obtain the flue gas flow coefficient.

[0016] In a preferred embodiment, in step S2, the flue gas flow coefficient and the carbon content of the flue gas are substituted into the logistic regression calculation to obtain the input power screening score.

[0017] The input power screening score is compared with the preset screening threshold. If the input power screening score exceeds the screening threshold, the current input power group is marked as a candidate capture power.

[0018] If the input power screening score is lower than the screening threshold, the current input power group will be screened out.

[0019] In a preferred embodiment, in step S3, the candidate capture power values ​​are sorted in ascending order from smallest to largest to obtain the candidate capture power in ascending order. An interval between adjacent power values ​​is constructed based on the ascending order to form the input power interval corresponding to the candidate capture power.

[0020] In each input power range, the capture power is randomly set according to the segmented uniform random sampling rule, and the capture power is marked.

[0021] The capture power is input to the flue gas capture system as the capture power of the corresponding input power range.

[0022] In a preferred embodiment, in step S3, after the capture power is input to the flue gas capture system, the vibration frequency of the capture equipment under each capture power is detected.

[0023] The vibration frequency of the collection device is obtained by calculating the ratio of the number of mechanical vibrations collected by vibration sensors installed on the main body of the collection device within a set unit time to the unit time length.

[0024] In a preferred embodiment, in step S4, the capture power is sorted in ascending order of numerical value, and the difference between adjacent capture power values ​​is calculated and the absolute value is processed to obtain the power change of adjacent capture power.

[0025] The difference between the vibration frequencies of the capture equipment corresponding to adjacent capture powers is calculated and the absolute value is processed to obtain the change in the vibration frequency of the capture equipment for adjacent capture powers.

[0026] The power change and the vibration frequency change of the capture equipment are standardized.

[0027] The target power score is obtained by calculating the ratio between the standardized power change and the vibration frequency change of the capture equipment.

[0028] In a preferred embodiment, in step S4, the target power score is compared with a preset target threshold.

[0029] If the target power score exceeds the target threshold, the current capture power is marked and the average power is calculated from the marked power as the target marked power;

[0030] If the target power score is lower than the target threshold, the current capture power will be filtered out.

[0031] In a preferred embodiment, in step S4, the target marker power is used as the input power of the flue gas capture system at the monitoring point of the farmland to be tested, and the flue gas emission of the capture device is obtained by monitoring the flue gas emission of the capture device through a flow sensor and a gas concentration sensor.

[0032] In a preferred embodiment, in step S4, the flue gas emission amount is compared and analyzed with a preset pollution alarm threshold.

[0033] If the flue gas emissions exceed the pollution alarm threshold, it is determined that there is a potential pollution risk at the current farmland monitoring point, triggering a pollution alarm.

[0034] If the flue gas emission is below the pollution alarm threshold, the current farmland monitoring point is determined to be in an acceptable emission state, and routine monitoring is maintained.

[0035] The technical effects and advantages of this invention are as follows:

[0036] This invention selects multiple sets of different input power to input into a flue gas capture system, sets a detection time, and detects the flue gas flow rate and carbon dioxide concentration absorbed by the system under each set of input power within the detection time. After screening each set of input power, candidate capture power is obtained. Input power ranges are set according to the candidate capture power, and capture power is randomly set and marked within each input power range and input into the flue gas capture system. The vibration frequency of the capture equipment under each capture power is detected. After sorting the capture power, the power change of adjacent capture power and the vibration frequency change of the capture equipment are calculated. The target capture power is selected by combining the power change and the vibration frequency change of the capture equipment. Based on the target capture power as input, the flue gas emission of the capture equipment at the monitoring point of the farmland under test is monitored to see if it meets the standard. Thus, the monitoring of agricultural non-point source pollution is dynamically optimized from the aspects of energy saving and efficiency improvement, effectively improving the monitoring accuracy and system stability, and realizing timely early warning of pollution risks. Attached Figure Description

[0037] Figure 1 This is a flowchart illustrating the implementation of the dynamic monitoring method for agricultural non-point source pollution based on multi-source heterogeneous data according to the present invention.

[0038] Figure 2 This is a schematic diagram illustrating the steps of the dynamic monitoring method for agricultural non-point source pollution based on multi-source heterogeneous data according to the present invention. Detailed Implementation

[0039] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0040] This invention selects multiple sets of different input power to input into a flue gas capture system, sets a detection time, and detects the flue gas flow rate and carbon dioxide concentration absorbed by the system under each set of input power within the detection time. After screening each set of input power, candidate capture power is obtained. Input power ranges are set according to the candidate capture power, and capture power is randomly set and marked within each input power range and input into the flue gas capture system. The vibration frequency of the capture equipment under each capture power is detected. After sorting the capture power, the power change of adjacent capture power and the vibration frequency change of the capture equipment are calculated. The target capture power is selected by combining the power change and the vibration frequency change of the capture equipment. Based on the target capture power as input, the flue gas emission of the capture equipment at the monitoring point of the farmland under test is monitored to see if it meets the standard. Thus, the monitoring of agricultural non-point source pollution is dynamically optimized from the aspects of energy saving and efficiency improvement.

[0041] Please see Figures 1 to 2 The specific operation procedure for the dynamic monitoring method of agricultural non-point source pollution based on multi-source heterogeneous data is as follows:

[0042] Step S1: In the farmland to be tested, select multiple sets of different input power to input the flue gas capture system in the farmland to be tested, set the detection time, and detect the flue gas flow rate and carbon dioxide concentration absorbed by the flue gas capture system under each set of input power within the detection time.

[0043] Step S2: Calculate the carbon content of flue gas under each group of input power based on carbon dioxide concentration, generate flue gas flow coefficient under each group of input power after standard processing of flue gas flow rate, and screen each group of input power to obtain candidate capture power based on the carbon content of flue gas.

[0044] Step S3: Set the input power range according to the candidate capture power, randomly set the capture power in each input power range, mark it, and input it into the flue gas capture system in the farmland to be tested, and detect the vibration frequency of the capture equipment under each capture power.

[0045] Step S4: After sorting the capture power, calculate the power change of adjacent capture power and the vibration frequency change of the capture equipment. Combine the power change and the vibration frequency change of the capture equipment to select the target capture power. Use the target capture power as the input power of the flue gas capture system at the farmland monitoring point to be tested. Detect the flue gas emission of the capture equipment and determine whether to issue a pollution alarm.

[0046] The specific implementation is as follows:

[0047] In step S1, the flue gas capture system is a system used to capture carbon dioxide from industrial emissions or combustion processes and prevent it from being released into the atmosphere around farmland. It operates after being powered on by a set input power to achieve the capture effect of carbon dioxide and flue gas.

[0048] In the farmland under test, flue gas emissions cause great pollution to the agricultural environment. Different input power will affect the flue gas carbon capture efficiency and energy consumption of the flue gas capture system. By optimizing the input power, the flue gas carbon capture efficiency and energy consumption can be balanced.

[0049] The input power range of the flue gas capture system is called from the historical database. Multiple input powers are randomly set within the input power range and grouped. A period of time is selected as the detection time. Each group of input power is used as the input of the flue gas capture system in each detection time. The flow rate of the flue gas absorbed by the flue gas capture system under each group of input power is detected by the flow meter during the detection time.

[0050] The flue gas flow rate is the amount of flue gas absorbed by the flue gas capture system within the detection time after it is started. The larger the amount of flue gas absorbed by the flue gas capture system within the detection time, the better its capture effect and the higher its capture efficiency.

[0051] A carbon dioxide sensor is used to detect the concentration of carbon dioxide absorbed by the flue gas capture system under each input power group. For each group of input power flue gas capture system, the carbon dioxide concentration in the test environment where the flue gas capture system is located is detected before the detection time, and the carbon dioxide concentration in the test environment where the flue gas capture system is located is detected a second time after the detection time. The difference between the two detection results is taken as the concentration of carbon dioxide absorbed by the flue gas capture system under the corresponding group of input power.

[0052] It should be explained that when using the above method to detect the carbon dioxide concentration in the test environment, the gas absorbed and treated by the flue gas capture system needs to be discharged from the test environment. This can be done by connecting a pipe to discharge the gas from the test environment, thus preventing the treated gas from still containing a small amount of carbon dioxide from returning to the test environment, thereby improving the accuracy of carbon dioxide concentration detection in the test environment.

[0053] The higher the concentration of carbon dioxide absorbed by the flue gas capture system within the detection time, the better its flue gas carbon capture effect and the higher its flue gas carbon capture efficiency.

[0054] It should be noted that a historical database refers to a database that stores and manages historical data. In this example, the historical database is the historical database of the flue gas capture system. The input power used by the flue gas capture system during a historical period is retrieved through the historical database, and the range between the maximum and minimum input power used during that period is used as the input power range. A flow meter is an instrument for measuring fluid flow rate and is used to detect the flue gas flow rate in the test environment. A carbon dioxide sensor is a device used to detect and measure the carbon dioxide concentration in the environment. In this example, it is used to detect the carbon dioxide concentration in the test environment before and after the detection time.

[0055] In step S2, in the test environment, the total concentration of gas in the test environment is detected by a gas composition analyzer, and the ratio of carbon dioxide concentration to total gas concentration is calculated to obtain the carbon content of flue gas under each input power.

[0056] Among them, the gas composition analyzer is a device used to detect the concentration of multiple gas components in a specific environment. It can collect and analyze the volume fraction of gases including but not limited to carbon dioxide, oxygen, nitrogen, carbon monoxide, sulfur dioxide, and methane in the test environment in real time. It uses devices such as infrared gas analyzers, mass spectrometers, or multi-channel gas detection modules. The specific equipment selection is determined by the experimenters based on the test environment of the farmland to be tested, and will not be elaborated here.

[0057] Furthermore, by calling the historical flue gas flow database, the maximum and minimum historical flue gas flow values ​​are determined to construct a standardized reference range and standardize the flue gas flow.

[0058] Specifically, the standardization process is based on a linear normalization method, which converts the flue gas flow rate into a dimensionless flue gas flow coefficient. The linear normalization method is as follows, and the specific formula is expressed below:

[0059] ;

[0060] In the formula, The flue gas flow rate is the input power. The flue gas flow coefficient is the value corresponding to the input power. This is the highest historical flue gas flow rate. This represents the historical minimum flue gas flow rate.

[0061] It should be noted that the flue gas flow history database refers to the database used to record, store, and retrieve flue gas flow data collected by the flue gas capture system under different operating cycles or different operating conditions, which will not be elaborated here;

[0062] Substituting the flue gas flow coefficient and the carbon content of the flue gas into the logistic regression calculation, the input power screening score is obtained. The specific formula is expressed as follows:

[0063] ;

[0064] In the formula, L is the result of logistic regression calculation, i.e., the input power screening score, e is the natural base, and y is the linear combination term of the logistic regression model, specifically set as follows:

[0065] ;

[0066] In the formula, For bias terms, The flue gas flow coefficient is the value corresponding to the input power. The percentage of carbon in flue gas. as well as These are the regression coefficients for the flue gas flow rate coefficient and the carbon content of the flue gas, respectively.

[0067] It should be noted that when the flue gas flow rate coefficient and the proportion of carbon in the flue gas are larger, it indicates that the flue gas capture system absorbs a higher total amount of flue gas and a higher proportion of carbon dioxide concentration within the detection time at the corresponding input power. In other words, the carbon capture effect corresponding to the input power is better. Therefore, the flue gas flow rate coefficient and the proportion of carbon in the flue gas can be used as positive weighted indicators for fusion calculation. The larger the input power screening score, the stronger the comprehensive capture capability of the input power, and the more likely it is to be selected as a candidate capture power.

[0068] The input power screening score is compared with the preset screening threshold. If the input power screening score exceeds the screening threshold, the current input power group is marked as a candidate capture power.

[0069] If the input power screening score is lower than the screening threshold, the current input power group will be screened out.

[0070] It should be noted that the preset screening threshold was set by the researchers based on the statistical analysis results of historical capture efficiency distribution and the energy consumption control of the actual carbon capture system, and will not be elaborated here.

[0071] In step S3, the candidate capture power values ​​are sorted in ascending order from smallest to largest to obtain the candidate capture power in ascending order. Based on the ascending order, the interval between adjacent power values ​​is constructed to form the input power interval corresponding to the candidate capture power.

[0072] Specifically, the ascending sort format is denoted as:

[0073] ;

[0074] In the formula, Sort in ascending order, where n is the total number of candidate capture powers. The power of the nth candidate capture;

[0075] Furthermore, the input power range corresponding to the candidate capture power is denoted as follows:

[0076] ;

[0077] In the formula, For the k-th input power interval, For the k-th candidate capture power, The power of the (k+1)th candidate capture power.

[0078] In each input power range, the capture power is randomly set according to the segmented uniform random sampling rule, and the capture power is marked.

[0079] Within each input power range, the capture power is generated according to a piecewise uniform random sampling rule. The specific calculation formula is as follows:

[0080] ;

[0081] In the formula, For capture power, The random coefficients are located in the input power range and are uniformly distributed in the interval 0-1.

[0082] The capture power is input to the flue gas capture system as the capture power of the corresponding input power range;

[0083] It should be noted that the piecewise uniform random sampling rule is a sampling method that randomly selects a representative value from a numerical interval based on a uniform probability distribution function. For the input power interval, the randomly selected sampling point is used as the capture power.

[0084] Furthermore, the capture power refers to the system operating power determined based on the input power and system load characteristics. It is the electrical power actually input into the flue gas capture system to drive the carbon capture reaction process. As can be understood by those skilled in the art, although power is a basic physical quantity, the capture power described in this embodiment needs to be clarified in conjunction with the characteristics of the electric drive system to avoid ambiguity in the terminology.

[0085] Furthermore, the input power range refers to the closed or half-open range constructed based on the power values ​​of adjacent candidate collections, which is used to limit the random sampling range. The specific selection of the closed or half-open range is determined by those in the field based on the number of sets and their corresponding power ranges. The researchers in this experiment need to understand that it is a real continuous range, not a discrete set, to avoid misunderstanding.

[0086] It should be noted that, in order to avoid confusion in power units and ambiguity in technical understanding, all power-related parameters (including input power, capture power, rated power, etc.) involved in this article are measured in a unified unit set by the researchers. This unit can be set to kilowatt or watt. The uniformity of the unit of measurement ensures that the power comparison, grouping, sorting and control operations in each step are carried out under a consistent measurement system.

[0087] After the capture power is input to the flue gas capture system, the vibration frequency of the capture equipment under each capture power is detected;

[0088] The vibration frequency of the capture equipment refers to the number of mechanical vibrations that occur in the structural components of the capture equipment within a set unit time under the condition of capture power drive. The acquisition logic is to calculate the vibration frequency of the capture equipment by comparing the number of mechanical vibrations collected by the vibration sensors installed on the capture equipment body within a set unit time with the unit time length.

[0089] It should be noted that structural components in the collection equipment refer to components that directly participate in the gas or liquid flow path during the collection process and generate a mechanical response due to the collection power. The specific components are selected by the researchers based on the physical properties of the collection medium, and will not be elaborated here.

[0090] The flue gas capture system is connected to multiple capture devices via electrical signals. The capture power is input into the flue gas capture system and transmitted to the capture devices. The data is collected by vibration sensors and then transmitted back to the flue gas capture system to complete operations such as data calculation and logical judgment.

[0091] Specifically, the unit time was determined by the researchers based on the data sampling rate and the system response characteristics, and will not be elaborated here.

[0092] Among them, the vibration sensor is a high-sensitivity miniature piezoelectric accelerometer that can accurately sense and record minute vibration changes of structural components. Its sensing signal is processed by the analog-to-digital conversion module and then input to the host computer for frequency calculation and state analysis.

[0093] In step S4, the capture power is sorted in ascending order of numerical value, and the difference between adjacent capture power values ​​is calculated and the absolute value is processed to obtain the power change of adjacent capture power.

[0094] Similarly, the difference between the vibration frequencies of the capture equipment corresponding to adjacent capture powers is calculated and the absolute value is processed to obtain the change in the vibration frequency of the capture equipment for adjacent capture powers.

[0095] The power change and the vibration frequency change of the capture equipment are standardized to keep them under the same dimension.

[0096] It should be noted that the standardization methods include, but are not limited to, standard linear transformation based on interval scaling, statistical Z-Score standardization method, or normalization method based on nonlinear mapping function. The application methods of standardization will not be elaborated here.

[0097] The target power score is obtained by calculating the ratio of the standardized power change to the vibration frequency change of the capture equipment.

[0098] The target power score is compared with the preset target threshold.

[0099] If the target power score exceeds the target threshold, the current capture power is marked and the average power is calculated from the marked power as the target marked power;

[0100] If the target power score is lower than the target threshold, the current capture power will be filtered out.

[0101] It should be noted that the target threshold was set by the researchers based on the structural characteristics of the collection equipment and the stability requirements of the vibration frequency, and will not be elaborated here.

[0102] Among them, when the power change is larger, it indicates that the input power adjustment range is larger in the adjacent power range, while the vibration response is relatively smooth. The larger the target power score, the higher the power adjustment efficiency and the more stable the operation under the unit vibration cost of that power range. It should be marked first. Conversely, when the vibration frequency change of the capture equipment is larger, it indicates that the equipment is more sensitive to small power changes and has resonance or instability. The smaller the target power score, the less suitable it is to be selected and screened out.

[0103] For example, set five capture powers and sort them in ascending order, i.e., A capture power < B capture power < C capture power < D capture power < E capture power;

[0104] Then the power change of adjacent capture power is |B capture power - A capture power|, |C capture power - B capture power|, |D capture power - C capture power|, |E capture power - D capture power|. Similarly, the vibration frequency change of the capture equipment for adjacent capture power can be obtained.

[0105] The target power score is obtained by the power change of adjacent capture power and the vibration frequency change of the capture equipment of adjacent capture power. If the target power score corresponding to the capture power of A and B exceeds the target threshold, then the capture power of A and B are marked. Similarly, if the target power score corresponding to the capture power of B and C exceeds the target threshold, then the capture power of C is added and marked. The average power is calculated from the marked power as the target marked power.

[0106] The target marked power is used as the input power of the flue gas capture system at the monitoring point of the farmland to be tested. The flue gas emission of the capture equipment is monitored by a flow sensor and a gas concentration sensor to obtain the flue gas emission of the capture equipment.

[0107] It should be noted that the flue gas emission is the raw monitoring value (i.e., the flue gas emission of the capture device) directly collected by the sensor and output in real time by the data processing module. No additional calculation or indirect calculation is required. Specifically, the flow sensor is used to collect the flow characteristics of the flue gas emitted by the capture device in real time, and the gas concentration sensor is used to collect the flue gas composition information simultaneously. The detection data of the two are fused and analyzed by the data processing module to directly generate the flue gas emission of the capture device, and output it to the monitoring terminal in a continuous real-time manner. The specific real-time monitoring sensors selected are not limited and will not be elaborated here.

[0108] The flue gas emissions are compared and analyzed with the preset pollution alarm thresholds;

[0109] If the flue gas emissions exceed the pollution alarm threshold, it is determined that there is a potential pollution risk at the current farmland monitoring point, triggering a pollution alarm.

[0110] If the flue gas emission is below the pollution alarm threshold, the current farmland monitoring point is determined to be in an acceptable emission state, and routine monitoring is maintained.

[0111] It should be noted that the preset pollution alarm threshold was set by the researchers based on the farmland environmental capacity and equipment emission control requirements, and will not be elaborated here.

[0112] It should be noted that after a pollution alarm is triggered, the warning text, graphics, or a combination thereof will be displayed on the visual terminal interface in the form of an alarm word, highlighting, color change, or icon flashing. The content includes words such as "pollution exceeds the standard" and "immediate action" to prompt on-site management personnel or monitoring personnel to take timely intervention measures.

[0113] Finally, it should be noted that in this paper, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0114] Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0115] In this document, the singular forms “a,” “an,” and “the” may also include the plural forms unless the context clearly indicates otherwise. It should also be understood that terms such as “comprising / including” or “having” specify the presence of the stated features, integrals, steps, operations, components, parts, or combinations thereof, but do not preclude the possibility of the presence or addition of one or more other features, integrals, steps, operations, components, parts, or combinations thereof. Meanwhile, the term “and / or” as used in this specification includes any and all combinations of the associated listed items.

[0116] The various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. The various embodiments can be combined as needed, and the same or similar parts can be referred to each other.

[0117] The above description of the disclosed embodiments will enable those skilled in the art to make or use various modifications to these embodiments. It will be readily apparent to those skilled in the art that the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for dynamic monitoring of agricultural non-point source pollution based on multi-source heterogeneous data, characterized in that: Includes the following steps: Step S1: In the farmland to be tested, select multiple sets of different input power to input the flue gas capture system in the farmland to be tested, set the detection time, and detect the flue gas flow rate and carbon dioxide concentration absorbed by the flue gas capture system under each set of input power within the detection time. Step S2: Calculate the carbon content of flue gas under each group of input power based on carbon dioxide concentration, generate flue gas flow coefficient under each group of input power after standard processing of flue gas flow rate, and screen each group of input power to obtain candidate capture power based on the carbon content of flue gas. Step S3: Set the input power range according to the candidate capture power, randomly set the capture power in each input power range, mark it, and input it into the flue gas capture system in the farmland to be tested, and detect the vibration frequency of the capture equipment under each capture power. Step S4: After sorting the capture power, calculate the power change of adjacent capture power and the vibration frequency change of the capture equipment. Combine the power change and the vibration frequency change of the capture equipment to select the target capture power. Use the target capture power as the input power of the flue gas capture system at the farmland monitoring point to be tested. Detect the flue gas emission of the capture equipment and determine whether to issue a pollution alarm.

2. The method for dynamic monitoring of agricultural non-point source pollution based on multi-source heterogeneous data according to claim 1, characterized in that: In step S1, the input power range of the flue gas capture system in the historical database is called, multiple input powers are randomly set within the input power range and grouped, a period of time is selected as the detection time, and each group of input power is used as the input of the flue gas capture system in each detection time. The flow meter detects the flue gas flow rate absorbed by the flue gas capture system under each group of input power in the detection time. A carbon dioxide sensor is used to detect the concentration of carbon dioxide absorbed by the flue gas capture system under each input power group. For each flue gas capture system under each input power group, the carbon dioxide concentration in the test environment where the flue gas capture system is located is detected before the detection time, and the carbon dioxide concentration in the test environment where the flue gas capture system is located is detected a second time after the detection time. The difference between the two detection results is taken as the concentration of carbon dioxide absorbed by the flue gas capture system under the corresponding input power group.

3. The method for dynamic monitoring of agricultural non-point source pollution based on multi-source heterogeneous data according to claim 1, characterized in that: In step S2, in the test environment, the total concentration of gas in the test environment is detected by a gas composition analyzer, and the ratio of carbon dioxide concentration to total gas concentration is calculated to obtain the carbon content of flue gas under each input power. By calling the historical flue gas flow database, the maximum and minimum historical flue gas flow values ​​are determined to construct a standardized reference range. The flue gas flow is then standardized to obtain the flue gas flow coefficient.

4. The method for dynamic monitoring of agricultural non-point source pollution based on multi-source heterogeneous data according to claim 1, characterized in that: In step S2, the flue gas flow coefficient and the carbon content of the flue gas are substituted into the logistic regression calculation to obtain the input power screening score; The input power screening score is compared with the preset screening threshold. If the input power screening score exceeds the screening threshold, the current input power group is marked as a candidate capture power. If the input power screening score is lower than the screening threshold, the current input power group will be screened out.

5. The method for dynamic monitoring of agricultural non-point source pollution based on multi-source heterogeneous data according to claim 1, characterized in that: In step S3, the candidate capture power values ​​are sorted in ascending order from smallest to largest to obtain the candidate capture power in ascending order. Based on the ascending order, the interval between adjacent power values ​​is constructed to form the input power interval corresponding to the candidate capture power. In each input power range, the capture power is randomly set according to the segmented uniform random sampling rule, and the capture power is marked. The capture power is input to the flue gas capture system as the capture power of the corresponding input power range.

6. The method for dynamic monitoring of agricultural non-point source pollution based on multi-source heterogeneous data according to claim 5, characterized in that: In step S3, after the capture power is input to the flue gas capture system, the vibration frequency of the capture equipment under each capture power is detected. The vibration frequency of the collection device is obtained by calculating the ratio of the number of mechanical vibrations collected by vibration sensors installed on the main body of the collection device within a set unit time to the unit time length.

7. The method for dynamic monitoring of agricultural non-point source pollution based on multi-source heterogeneous data according to claim 1, characterized in that: In step S4, the capture power is sorted in ascending order of numerical value, and the difference between adjacent capture power values ​​is calculated and the absolute value is processed to obtain the power change of adjacent capture power. The difference between the vibration frequencies of the capture equipment corresponding to adjacent capture powers is calculated and the absolute value is processed to obtain the change in the vibration frequency of the capture equipment for adjacent capture powers. The power change and the vibration frequency change of the capture equipment are standardized. The target power score is obtained by calculating the ratio between the standardized power change and the vibration frequency change of the capture equipment.

8. The method for dynamic monitoring of agricultural non-point source pollution based on multi-source heterogeneous data according to claim 7, characterized in that: In step S4, the target power score is compared with a preset target threshold. If the target power score exceeds the target threshold, the current capture power is marked and the average power is calculated from the marked power as the target marked power; If the target power score is lower than the target threshold, the current capture power will be filtered out.

9. The method for dynamic monitoring of agricultural non-point source pollution based on multi-source heterogeneous data according to claim 1, characterized in that: In step S4, the target marked power is used as the input power of the flue gas capture system at the monitoring point of the farmland to be tested. The flue gas emission of the capture equipment is monitored by a flow sensor and a gas concentration sensor to obtain the flue gas emission of the capture equipment.

10. The method for dynamic monitoring of agricultural non-point source pollution based on multi-source heterogeneous data according to claim 9, characterized in that: In step S4, the flue gas emission amount is compared and analyzed with the preset pollution alarm threshold. If the flue gas emissions exceed the pollution alarm threshold, it is determined that there is a potential pollution risk at the current farmland monitoring point, triggering a pollution alarm. If the flue gas emission is below the pollution alarm threshold, the current farmland monitoring point is determined to be in an acceptable emission state, and routine monitoring is maintained.

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