Greenhouse gas concentration monitoring method and system based on multi-source data fusion

Abstract

The present invention discloses a greenhouse gas concentration monitoring method and system based on multi-source data fusion, and relates to the technical field of gas monitoring. The system comprises a satellite remote sensing data module, a monitoring point selection and collection module, a meteorological data fusion module, a concentration change detection module, a multi-source data fusion module and a data analysis and prediction module which are operated in sequence; the technical key points are as follows: triggering corresponding detection strategies according to situations, ensuring both rapid and effective monitoring of high-concentration areas and accurate multi-point coverage of low-concentration areas, mobilizing monitoring resources in a targeted manner, comprehensively considering multi-source data and combining gas concentration correction values, thereby ensuring the accuracy of current gas concentration standard values, improving the accuracy of greenhouse gas concentration detection, and then considering the data obtained by satellite remote sensing and the gas concentration standard values ​​again, through subsequent processing, it is possible to determine whether there is an abnormality in system operation, thereby ensuring the normal operation of the entire monitoring operation.

Description

Technical Field

[0001] The present invention relates to the field of gas monitoring technology, and in particular to a greenhouse gas concentration monitoring method and system based on multi-source data fusion. Background Art

[0002] Gas monitoring refers to the process of detecting and analyzing various gas components in the air. The purpose is to understand the types, concentrations and changes of gases. The main monitored objects are greenhouse gases: such as carbon dioxide, methane, nitrous oxide, etc. These gases have a significant impact on global warming and climate change; existing monitoring methods include: on-site monitoring: using portable or fixed gas detection instruments to directly measure gas concentrations at the monitoring site; remote remote sensing: using satellites, drones or other remote sensing technologies to monitor gas distribution and concentrations in large areas; laboratory analysis: after collecting air samples, take them back to the laboratory and use high-precision analytical instruments for detailed component analysis.

[0003] The technical solution pointed out in the document entitled "A greenhouse gas concentration monitoring system and method" with the existing authorization announcement number CN116953178B includes: adding a refraction period on the basis of the existing technology, and measuring the intensity change of the output spectrum to obtain a second spectrum, taking the first greenhouse gas concentration and the second greenhouse gas concentration as inputs, and passing them into a neural network model, in which the loss of the absorption spectrum due to adding a refraction period can be obtained according to the difference ratio between the first spectrum and the second spectrum, and the accurate greenhouse gas concentration can be further output. However, the above scheme does not take into account the actual impact of changes in the meteorological environment, and does not take into account data from multiple sources;

[0004] In combination with the above documents and existing technologies, traditional concentration monitoring of greenhouse gases, such as carbon dioxide, only relies on a few ground monitoring stations to obtain data, and multiple related sensors are configured and used in different regions. As a result, it is impossible to simultaneously guarantee the detection efficiency and quality according to the actual situation. At the same time, traditional methods often fail to consider the impact of meteorological factors on the concentration when analyzing greenhouse gas concentrations, resulting in the failure to improve the accuracy of subsequent greenhouse gas monitoring values ​​and the inability to affect the monitoring errors caused by meteorological changes. Summary of the invention

[0005] 1. Technical issues to be resolved

[0006] In view of the deficiencies in the prior art, the present invention provides a greenhouse gas concentration monitoring method and system based on multi-source data fusion, which triggers corresponding detection strategies according to the situation, thereby ensuring both rapid and effective monitoring of high-concentration areas and accurate multi-point coverage of low-concentration areas, and mobilizing monitoring resources in a targeted manner. By comprehensively considering multi-source data and combining gas concentration correction values, the accuracy of the current gas concentration standard value is guaranteed, thereby improving the accuracy of greenhouse gas concentration detection. Then, considering the data obtained by satellite remote sensing and the gas concentration standard value again, through subsequent calculations and analysis, it is possible to determine whether there are any abnormalities in the system operation, thereby ensuring the normal operation of the entire monitoring operation, and solving the problems raised in the background technology.

[0007] (II) Technical solution

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0009] Greenhouse gas concentration monitoring system based on multi-source data fusion, including:

[0010] The satellite remote sensing data module obtains the greenhouse gas concentration distribution data of different sub-areas in the selected area, and selects the highest value of greenhouse gas concentration in the corresponding sub-area. It builds a rule engine to compare the highest value of greenhouse gas concentration corresponding to each sub-area with the preset limit value, and calibrates the corresponding sub-area as a high-concentration sub-area or a low-concentration sub-area according to the comparison results;

[0011] The monitoring point selects the collection module and selects any partition as the monitoring site. When the partition is a high-concentration partition, the No. 1 detection strategy is triggered to obtain the monitoring site data. When the partition is a low-concentration partition, the No. 2 detection strategy is triggered to obtain the monitoring site data.

[0012] The meteorological data fusion module obtains the meteorological data of the monitoring site and generates the gas concentration correction value based on the pre-processed meteorological data;

[0013] The concentration change detection module detects the change value of the maximum value of the greenhouse gas concentration in the monitoring area at two moments before and after, synchronously obtains the adjustment value of the gas concentration correction value at two moments before and after, and obtains the ratio of at least three consecutive change values ​​to the adjustment value. If the difference between the maximum value and the minimum value in the ratio does not exceed the preset first standard threshold, then continue to the next step of operation, otherwise, execute the adjustment strategy;

[0014] The multi-source data fusion module generates the current gas concentration standard value of the monitoring site based on the pre-processed monitoring site data and gas concentration correction value, combined with the maximum value of greenhouse gas concentration;

[0015] The data analysis and prediction module counts the standard value of gas concentration and the maximum value of greenhouse gas concentration at each historical moment within the preset historical time period T, generates the gas standard stability index and the remote sensing accuracy stability index, and executes the troubleshooting strategy when the difference between the two exceeds the preset second standard threshold.

[0016] Furthermore, the process of calibrating the corresponding partition as a high-concentration partition or a low-concentration partition according to the comparison results is: when the maximum greenhouse gas concentration exceeds the limit value, the corresponding partition is calibrated as a high-concentration partition; when the maximum greenhouse gas concentration does not exceed the limit value, the corresponding partition is calibrated as a low-concentration partition.

[0017] Furthermore, the triggered detection strategy No. 1 is:

[0018] A monitoring point located at the center of the monitoring site is started, and multiple types of sensors are configured in the monitoring point to collect greenhouse gas concentration data in real time. The data of each greenhouse gas concentration is processed using a data fusion algorithm to obtain the monitoring site data. The multiple types of sensors configured in the monitoring point include infrared gas analyzers, laser gas analyzers, and electrochemical sensors.

[0019] Furthermore, the second detection strategy triggered is:

[0020] The monitoring points located at the center of the monitoring site and two other locations are started to divide the monitoring site into three parts. Each monitoring point is located at the center of each part, and each monitoring point is equipped with multiple types of sensors to collect greenhouse gas concentration data in real time. After the greenhouse gas concentration data of each monitoring point is processed by data fusion algorithm, buffer data is obtained, and then each buffer data is averaged to obtain the monitoring site data.

[0021] Furthermore, the meteorological data is wind speed;

[0022] The process of preprocessing meteorological data is: data cleaning and dimensionless processing;

[0023] Then, the formula based on the correction value of the generated gas concentration is as follows:

[0024]

[0025] In the formula, Indicates the gas concentration correction value, represents the calibration coefficient, Indicates the current wind speed. Indicates the base wind speed.

[0026] Furthermore, the change value represents: the absolute value of the difference between the maximum greenhouse gas concentration in the monitoring area at the previous moment and the maximum greenhouse gas concentration in the monitoring area at the next moment; the adjustment value represents: the absolute value of the difference between the gas concentration correction value at the previous moment and the gas concentration correction value at the next moment;

[0027] After obtaining the ratio of three consecutive change values ​​to the adjustment value, the formula on which the ratio is based is as follows:

[0028]

[0029] The difference between the maximum and minimum values ​​in the ratio represents: .

[0030] Furthermore, the adjustment strategy implemented is:

[0031] In the process of generating gas concentration correction values, the calibration factor Adjust so that the calibration factor in the formula based on the generated gas concentration correction value is The value of is obtained by adjusting the original k by 0.1 each time to obtain a calibration coefficient k±0.1 until the difference between the maximum and minimum values ​​in the ratio does not exceed the preset first standard threshold.

[0032] Furthermore, the current gas concentration standard value of the monitoring site is generated based on the following formula:

[0033]

[0034] In the formula, Indicates the standard value of gas concentration. Indicates monitoring data. Indicates the highest value of greenhouse gas concentration, represent the preset proportional coefficients, and represents the error correction factor, and The value range is 0~2.

[0035] Furthermore, the calculation formula of the standard stability index of generated gas is as follows:

[0036]

[0037] In the formula, represents the gas standard stability index, represents the standard value of gas concentration at historical time t, where t=1, 2, ..., n, n is a positive integer, and n=T, It represents the average value of the standard value of gas concentration at each historical time t within the historical time period T;

[0038] The calculation formula for generating the remote sensing accuracy stability index is as follows:

[0039]

[0040] In the formula, Represents the remote sensing accuracy stability index, represents the maximum value of greenhouse gas concentration at historical time t, It represents the average value of the maximum value of greenhouse gas concentration at each historical moment t within the historical time period T;

[0041] The implemented inspection strategy is: arrange personnel to inspect and repair the various types of sensors configured in satellites and monitoring points in turn.

[0042] The greenhouse gas concentration monitoring method based on multi-source data fusion includes the following steps:

[0043] S1. Obtain the greenhouse gas concentration distribution data of different zones in the selected area, and filter out the highest value of the greenhouse gas concentration in the corresponding zone, build a rule engine, compare the highest value of the greenhouse gas concentration corresponding to each zone with the preset limit value, and calibrate the corresponding zone as a high-concentration zone or a low-concentration zone according to the comparison result;

[0044] S2. Select any partition as the monitoring site. When the partition is a high-concentration partition, the first detection strategy is triggered to obtain the monitoring site data. When the partition is a low-concentration partition, the second detection strategy is triggered to obtain the monitoring site data.

[0045] S3. Obtaining meteorological data of the monitoring site, and generating a gas concentration correction value based on the preprocessed meteorological data;

[0046] S4, detecting the change value of the maximum value of the greenhouse gas concentration in the monitoring area at two moments before and after, synchronously obtaining the adjustment value of the gas concentration correction value at two moments before and after, obtaining the ratio of at least three consecutive change values ​​to the adjustment value, if the difference between the maximum value and the minimum value in the ratio does not exceed the preset first standard threshold, then continue to the next step of operation, otherwise, execute the adjustment strategy;

[0047] S5. Generate the current standard value of the gas concentration at the monitoring site based on the pre-processed monitoring site data and the gas concentration correction value, combined with the maximum value of the greenhouse gas concentration;

[0048] S6. Within the preset historical time period T, the standard value of gas concentration and the maximum value of greenhouse gas concentration at each historical moment are counted to generate a gas standard stability index and a remote sensing accuracy stability index. When the difference between the two exceeds the preset second standard threshold, the troubleshooting strategy is executed.

[0049] (III) Beneficial effects

[0050] The present invention provides a greenhouse gas concentration monitoring method and system based on multi-source data fusion, which has the following beneficial effects:

[0051] 1. By detecting greenhouse gas data of each zone through satellite remote sensing technology and comparing the greenhouse gas data with the defined value, it is possible to distinguish whether the corresponding zone is a high or low concentration zone, so as to trigger the corresponding detection strategy according to the situation in the future, and effectively handle the gas concentration monitoring needs of different regions, ensuring both rapid and effective monitoring of high-concentration areas and accurate coverage of multiple points in low-concentration areas, and mobilizing monitoring resources in a targeted manner, saving costs and manpower;

[0052] 2. The wind speed data is introduced as the correction value, so that the monitoring data reflects the actual situation more accurately, and the change trend of greenhouse gas concentration and correction value in the monitoring area is detected in time. By adjusting the calibration coefficient, the accuracy of the monitoring data is further optimized, and the influence of meteorological factors is effectively dealt with, thus ensuring the real-time and reliability of the monitoring results;

[0053] 3. By comprehensively considering multi-source data and combining it with gas concentration correction values, the accuracy of the current gas concentration standard value is guaranteed, which improves the accuracy of greenhouse gas concentration detection to a certain extent. Then, considering the data obtained by satellite remote sensing and the gas concentration standard value again, through subsequent calculations and analysis, it can be determined whether there are any abnormalities in the system operation, thereby ensuring the normal operation of the entire monitoring operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 It is a schematic diagram of the module structure of the greenhouse gas concentration monitoring system based on multi-source data fusion;

[0055] Figure 2 The figure is a flowchart of the overall steps of the greenhouse gas concentration monitoring method based on multi-source data fusion. DETAILED DESCRIPTION

[0056] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0057] Example 1: Please refer to Figure 1 This embodiment provides a greenhouse gas concentration monitoring system based on multi-source data fusion, and the application scenarios of the system are:

[0058] Greenhouse gas concentration monitoring is performed for the entire area with different partitions. In the entire area, different partitions are divided according to needs, for example, according to area or terrain. Usually, gas monitoring work needs to be performed on different farmlands;

[0059] The design concept of the system is as follows:

[0060] Through satellite remote sensing detection technology, preliminary detection is carried out on different sub-areas of the entire area, and high-concentration and low-concentration areas of greenhouse gases are divided and marked, and high-resolution gas concentration dynamic data of the current sub-area is obtained simultaneously. Then, the corresponding monitoring points are triggered according to the marked high or low concentration areas, and the required greenhouse gas concentration data are obtained and calculated using sensors. Correction values ​​are generated through the acquired meteorological data. After ensuring the accuracy of the correction value through transformation detection technology, multi-source data are fused, that is, high-resolution gas concentration dynamic data, greenhouse gas concentration data and correction value, to generate gas concentration standard values, thereby completing accurate and detailed monitoring of greenhouse gas concentrations in the current sub-area. It is not used for the acquisition of traditional single-source data. This design further ensures the accuracy of the data through multi-source data fusion, meets dynamic needs and takes into account the impact of the meteorological environment.

[0061] Software Design:

[0062] The system includes a satellite remote sensing data module, a monitoring point selection and collection module, a meteorological data fusion module, a concentration change detection module, a multi-source data fusion module, and a data analysis and prediction module, which operate in sequence. The entire system is composed of multiple core modules, thereby achieving accurate monitoring of greenhouse gas concentrations;

[0063] The satellite remote sensing data module uses satellite remote sensing technology to obtain the greenhouse gas concentration distribution data of different sub-areas in the selected area, and screens out the highest value of greenhouse gas concentration in the corresponding sub-area. It builds a rule engine to compare the highest value of greenhouse gas concentration corresponding to each sub-area with the preset limit value. When the highest value of greenhouse gas concentration exceeds the limit value, the corresponding sub-area is calibrated as a high-concentration sub-area. Otherwise, the corresponding sub-area is calibrated as a low-concentration sub-area.

[0064] Among them, using satellite remote sensing technology to obtain greenhouse gas concentration distribution data in different sub-areas of the selected area is to measure the greenhouse gas concentration in the atmosphere of the corresponding sub-area through the TROPOMI sensor carried by the satellite. The greenhouse gas mentioned in this application is carbon dioxide;

[0065] Screening out the highest value of greenhouse gas concentration in the corresponding partition means finding the location or value with the highest concentration in each partition. This analysis can help determine the high-concentration area of ​​greenhouse gas emissions or other important spatial features, such as urban areas, industrial areas or natural geographical features. In this embodiment, it is only for determining the greenhouse gas concentration of the corresponding partition;

[0066] The threshold values ​​for greenhouse gas concentrations are usually determined based on environmental protection standards, health impacts, and the needs of scientific research. These values ​​are usually set by countries or international organizations and may vary according to different geographical regions and climatic conditions;

[0067] The monitoring point selects the acquisition module and selects any partition as the monitoring site. When the partition is displayed as a high-concentration partition, the No. 1 detection strategy is triggered to obtain the monitoring site data. When the partition is displayed as a low-concentration partition, the No. 2 detection strategy is triggered to obtain the monitoring site data.

[0068] The detection strategy designed above can improve monitoring efficiency and coverage: by first identifying high-concentration areas through satellite remote sensing, the system can give priority to mobilizing monitoring points located in the core of the area, so that detailed monitoring data of high-concentration areas can be obtained more quickly. For low-concentration areas, by triggering multiple monitoring points for measurement and averaging, the comprehensiveness and accuracy of monitoring data can be increased;

[0069] Among them, the triggered detection strategy No. 1 is:

[0070] Start the monitoring point at the center of the monitoring site, and configure multiple types of sensors in the monitoring point to collect greenhouse gas concentration data in real time, and use data fusion algorithm to process each greenhouse gas concentration data to obtain the monitoring site data;

[0071] The multiple types of sensors configured in the monitoring point include infrared gas analyzers, laser gas analyzers, and electrochemical sensors; the greenhouse gas concentration data collected in real time are all detected and obtained by infrared gas analyzers, laser gas analyzers, and electrochemical sensors. Before obtaining the monitoring data, it is necessary to ensure that each sensor is in a fault-free state; the data fusion algorithm used includes any one of weighted average and Kalman filtering. In this embodiment, weighted average can be used. After the greenhouse gas concentration data is processed by weighted average calculation, the required monitoring data can be obtained;

[0072] It should be noted that the infrared gas analyzer has the following working principles: it measures the gas concentration by detecting the degree to which infrared light of a specific wavelength is absorbed by the target gas; the laser gas analyzer has the following working principles: it uses the spectral interaction between the laser beam and the gas molecules to measure the gas concentration by analyzing the scattered light, absorbed light, etc.; the electrochemical sensor has the following working principles: it detects the gas concentration by generating a change in current through the chemical reaction between the electrode and the measured gas;

[0073] The second detection strategy triggered is:

[0074] Start the monitoring points located at the center of the monitoring site and at least two other locations, usually three monitoring points, to divide the monitoring site into three parts. Each monitoring point is located at the center of each part, and each monitoring point is equipped with multiple types of sensors to collect greenhouse gas concentration data in real time. After the greenhouse gas concentration data of each monitoring point is processed by data fusion algorithm, buffer data is obtained, and then each buffer data is averaged to obtain the monitoring site data.

[0075] Specifically, the greenhouse gas data of each zone is detected through satellite remote sensing technology. By comparing the greenhouse gas data with the definition value, it is possible to distinguish whether the corresponding zone is a high or low concentration zone, which is convenient for triggering the corresponding detection strategy according to the situation. It effectively handles the gas concentration monitoring needs of different areas, ensures both rapid and effective monitoring of high-concentration areas, and accurate coverage of multiple points in low-concentration areas, mobilizes monitoring resources in a targeted manner, and saves costs and manpower.

[0076] The meteorological data fusion module obtains the meteorological data of the monitoring site and generates the gas concentration correction value based on the pre-processed meteorological data;

[0077] Among them, the meteorological data is wind speed;

[0078] Real-time meteorological data of the monitoring area can be obtained through the data released by the meteorological station;

[0079] The process of preprocessing meteorological data is: data cleaning and dimensionless processing;

[0080] The formula on which the generated gas concentration correction value is based is as follows:

[0081]

[0082] In the formula, Indicates the gas concentration correction value, Represents the calibration coefficient, which is used to adjust the correction intensity. The initial value is set to 0.1. Indicates the current wind speed. Indicates the base wind speed, which is usually set to a fixed value, i.e. 1m / s. When the wind speed is high, it will reduce the greenhouse gas concentration at the monitoring site to a certain extent. When the wind speed is low, the reduced concentration will be less than when the wind speed is high.

[0083] Example: If the current wind speed: wind speed = 2m / s;

[0084] Reference wind speed: Reference wind speed = 1m / s;

[0085] Calibration coefficient: The initial value of the calibration coefficient = 0.1;

[0086] The gas concentration correction value calculated according to the above formula = 0.8.

[0087] Traditional methods often fail to consider the impact of meteorological factors on greenhouse gas concentrations when analyzing concentrations, resulting in low accuracy of the correction value. The solution is to introduce a meteorological data fusion module to calculate the correction value of gas concentration by acquiring and preprocessing wind speed data in real time. This step effectively considers the impact of wind speed on greenhouse gas diffusion and improves the accuracy and reliability of the correction value.

[0088] The concentration change detection module uses satellite remote sensing technology to detect the change value of the maximum value of greenhouse gas concentration in the monitoring area at two moments before and after, and synchronously obtains the adjustment value of the gas concentration correction value at two moments before and after, and obtains the ratio of at least three consecutive change values ​​to the adjustment value. If the difference between the maximum value and the minimum value in the ratio does not exceed the preset first standard threshold, it means that the meteorological correction value is accurate, and the next step of operation is continued. If the difference between the maximum value and the minimum value in the ratio exceeds the preset first standard threshold, the adjustment strategy is executed until the difference between the maximum value and the minimum value in the ratio does not exceed the preset first standard threshold;

[0089] The change value represents:

[0090] The absolute value of the difference between the maximum greenhouse gas concentration in the monitoring area at the previous moment and the maximum greenhouse gas concentration in the monitoring area at the next moment;

[0091] Adjustment value means:

[0092] The absolute value of the difference between the gas concentration correction value at the previous moment and the gas concentration correction value at the next moment;

[0093] After obtaining the ratio of three consecutive change values ​​to the adjustment value, the formula on which the ratio is based is as follows:

[0094]

[0095] The difference between the maximum and minimum values ​​in the ratio represents:

[0096] The preset first standard threshold is set based on historical data acquisition, and can also be adjusted accordingly according to actual needs, which will not be elaborated here;

[0097] The adjustment strategies implemented are:

[0098] In the process of generating gas concentration correction values, the calibration factor Adjust the calibration coefficient k to ±0.1 so that the calibration coefficient k in the formula based on the generated gas concentration correction value is The value of is taken from the original k, and is adjusted by 0.1 each time to obtain a calibration coefficient k±0.1, until the difference between the maximum and minimum values ​​in the ratio does not exceed the preset first standard threshold.

[0099] Specifically, wind speed data was introduced as a correction value to make the monitoring data more accurately reflect the actual situation, and to timely detect changes in greenhouse gas concentrations in the monitoring area and changing trends in correction values. By adjusting the calibration coefficient, the accuracy of the monitoring data was further optimized, effectively responding to the impact of meteorological factors and ensuring the real-time and reliability of the monitoring results.

[0100] The multi-source data fusion module generates the current gas concentration standard value of the monitoring site based on the pre-processed monitoring site data and gas concentration correction value, combined with the maximum value of greenhouse gas concentration;

[0101] The monitoring site data, gas concentration correction values ​​and maximum greenhouse gas concentration values ​​are cleaned and then normalized to remove the units of each data to facilitate subsequent calculations and processing;

[0102] The formula for generating the current gas concentration standard value at the monitoring site is as follows:

[0103]

[0104] In the formula, Indicates the standard value of gas concentration. Indicates monitoring data. Indicates the highest value of greenhouse gas concentration, represent the preset proportional coefficients, and ; represents the error correction factor, whose specific value can be adjusted by the user or generated by analytical function fitting, and The value range is 0~2.

[0105] The data analysis and prediction module counts the standard value of gas concentration and the highest value of greenhouse gas concentration at each historical moment within the preset historical time period T, and generates the gas standard stability index and remote sensing accuracy stability index in turn. If the difference between the two exceeds the preset second standard threshold, the troubleshooting strategy is executed; if the difference between the two does not exceed the preset second standard threshold, the system does not respond, indicating that there is no abnormality in the system and it can continue to be used normally;

[0106] The calculation formula of the standard stability index of generated gas is as follows:

[0107]

[0108] In the formula, represents the gas standard stability index, represents the standard value of gas concentration at historical time t, where t=1, 2, ..., n, n is a positive integer, and n=T, It represents the average value of the standard value of gas concentration at each historical moment t within the historical time period T; the gas standard stability index reflects the stability of greenhouse gas changes;

[0109] The calculation formula for generating the remote sensing accuracy stability index is as follows:

[0110]

[0111] In the formula, Represents the remote sensing accuracy stability index, represents the maximum value of greenhouse gas concentration at historical time t, It represents the average value of the maximum value of greenhouse gas concentration at each historical moment t within the historical time period T;

[0112] The difference between the two means: Difference = ;

[0113] The preset second standard threshold is set based on historical data acquisition, and can also be adjusted accordingly according to actual needs, which will not be elaborated here;

[0114] The troubleshooting strategy implemented is:

[0115] Arrange staff to check and repair the various types of sensors installed in satellites and monitoring points in turn; by comparing the difference between the gas standard stability index and the remote sensing accuracy stability index with the second standard threshold, it can be determined whether there are any abnormalities in the operation of the entire system based on the comparison results. When there are abnormalities, the troubleshooting strategy can be implemented to ensure that the entire system continues to operate.

[0116] Specifically, by comprehensively considering multi-source data and combining it with the gas concentration correction value, the accuracy of the current gas concentration standard value is guaranteed, which improves the accuracy of greenhouse gas concentration detection to a certain extent. Then, considering the data obtained by satellite remote sensing and the gas concentration standard value again, through subsequent calculations and analysis, it is possible to determine whether there are any abnormalities in the system operation, thereby ensuring the normal operation of the entire monitoring operation.

[0117] Example 2: Please refer to Figure 2 Based on Example 1, this embodiment also provides a greenhouse gas concentration monitoring method based on multi-source data fusion, including the following specific steps:

[0118] S1. Obtain the greenhouse gas concentration distribution data of different zones in the selected area, and filter out the highest value of the greenhouse gas concentration in the corresponding zone, build a rule engine, compare the highest value of the greenhouse gas concentration corresponding to each zone with the preset limit value, and calibrate the corresponding zone as a high-concentration zone or a low-concentration zone according to the comparison result;

[0119] S2. Select any partition as the monitoring site. When the partition is a high-concentration partition, the first detection strategy is triggered to obtain the monitoring site data. When the partition is a low-concentration partition, the second detection strategy is triggered to obtain the monitoring site data.

[0120] S3. Obtaining meteorological data of the monitoring site, and generating a gas concentration correction value based on the preprocessed meteorological data;

[0121] S4, detecting the change value of the maximum value of the greenhouse gas concentration in the monitoring area at two moments before and after, synchronously obtaining the adjustment value of the gas concentration correction value at two moments before and after, obtaining the ratio of at least three consecutive change values ​​to the adjustment value, if the difference between the maximum value and the minimum value in the ratio does not exceed the preset first standard threshold, then continue to the next step of operation, otherwise, execute the adjustment strategy;

[0122] S5. Generate the current standard value of the gas concentration at the monitoring site based on the pre-processed monitoring site data and the gas concentration correction value, combined with the maximum value of the greenhouse gas concentration;

[0123] S6. Within the preset historical time period T, the standard value of gas concentration and the maximum value of greenhouse gas concentration at each historical moment are counted to generate a gas standard stability index and a remote sensing accuracy stability index. When the difference between the two exceeds the preset second standard threshold, the troubleshooting strategy is executed.

[0124] In the application, the several formulas involved are all calculated by removing the dimensions and taking their numerical values. The formula is a formula obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The formula is set by technical personnel in this field according to actual conditions.

[0125] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product. A person of ordinary skill in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented in electronic hardware, or in a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution.

[0126] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0127] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. The greenhouse gas concentration monitoring system based on multi-source data fusion is characterized by: include: The satellite remote sensing data module obtains the greenhouse gas concentration distribution data of different partitions in the selected area, and selects the highest value of greenhouse gas concentration in the corresponding partition, builds a rule engine, compares the highest value of greenhouse gas concentration corresponding to each partition with the preset limit value, and calibrates the corresponding partition as a high-concentration partition or a low-concentration partition according to the comparison result. The process is: when the highest value of greenhouse gas concentration exceeds the limit value, the corresponding partition is calibrated as a high-concentration partition; when the highest value of greenhouse gas concentration does not exceed the limit value, the corresponding partition is calibrated as a low-concentration partition; The monitoring point selects the acquisition module and selects any partition as the monitoring site. When the partition is a high-concentration partition, the No. 1 detection strategy is triggered to obtain the monitoring site data. When the partition is a low-concentration partition, the No. 2 detection strategy is triggered to obtain the monitoring site data. The triggered No. 1 detection strategy is: Start a monitoring point at the center of the monitoring site, and configure multiple types of sensors in the monitoring point to collect greenhouse gas concentration data in real time, and use data fusion algorithm to process each greenhouse gas concentration data to obtain monitoring site data; the multiple types of sensors configured in the monitoring point include infrared gas analyzers, laser gas analyzers and electrochemical sensors; The second detection strategy triggered is: Start the monitoring points located at the center of the monitoring site and two other locations, divide the monitoring site into three parts, and each monitoring point is located at the center of each part. Each monitoring point is equipped with multiple types of sensors to collect greenhouse gas concentration data in real time. After the greenhouse gas concentration data of each monitoring point is processed by data fusion algorithm, buffer data is obtained, and then each buffer data is averaged to obtain the monitoring site data; The meteorological data fusion module obtains the meteorological data of the monitoring site and generates a gas concentration correction value based on the pre-processed meteorological data; the meteorological data is wind speed; The process of preprocessing meteorological data is: data cleaning and dimensionless processing; Then, the formula based on the correction value of the generated gas concentration is as follows: In the formula, Indicates the gas concentration correction value, represents the calibration coefficient, Indicates the current wind speed. Indicates the reference wind speed; The concentration change detection module detects the change value of the maximum greenhouse gas concentration in the monitoring area at two moments before and after, synchronously obtains the adjustment value of the gas concentration correction value at two moments before and after, and obtains the ratio of at least three consecutive change values ​​to the adjustment value. If the difference between the maximum value and the minimum value in the ratio does not exceed the preset first standard threshold, then continue to the next step of operation, otherwise, execute the adjustment strategy; the change value represents: the absolute value of the difference between the maximum greenhouse gas concentration in the monitoring area at the previous moment and the maximum greenhouse gas concentration in the monitoring area at the next moment; the adjustment value represents: the absolute value of the difference between the gas concentration correction value at the previous moment and the gas concentration correction value at the next moment; After obtaining the ratio of three consecutive change values ​​to the adjustment value, the formula on which the ratio is based is as follows: The difference between the maximum and minimum values ​​in the ratio represents: ; The adjustment strategies implemented are: In the process of generating gas concentration correction values, the calibration factor Adjust so that the calibration factor in the formula based on the generated gas concentration correction value is The value of is adjusted by 0.1 from the original k to obtain a calibration coefficient k±0.1, until the difference between the maximum value and the minimum value in the ratio does not exceed the preset first standard threshold; The multi-source data fusion module generates the current gas concentration standard value of the monitoring site based on the pre-processed monitoring site data and gas concentration correction value, combined with the maximum value of greenhouse gas concentration. The formula is as follows: In the formula, Indicates the standard value of gas concentration. Indicates monitoring data. Indicates the highest value of greenhouse gas concentration, represent the preset proportional coefficients, and represents the error correction factor, and The value range is 0~2; The data analysis and prediction module counts the standard value of gas concentration and the maximum value of greenhouse gas concentration at each historical moment within the preset historical time period T, generates the gas standard stability index and the remote sensing accuracy stability index, and executes the troubleshooting strategy when the difference between the two exceeds the preset second standard threshold; the calculation formula for generating the gas standard stability index is as follows: In the formula, represents the gas standard stability index, represents the standard value of gas concentration at historical time t, where t=1, 2, ..., n, n is a positive integer, and n=T, It represents the average value of the standard value of gas concentration at each historical time t within the historical time period T; The calculation formula for generating the remote sensing accuracy stability index is as follows: In the formula, Represents the remote sensing accuracy stability index, represents the maximum value of greenhouse gas concentration at historical time t, It represents the average value of the maximum value of greenhouse gas concentration at each historical moment t within the historical time period T; The implemented inspection strategy is: arrange personnel to inspect and repair the various types of sensors configured in satellites and monitoring points in turn.

2. A greenhouse gas concentration monitoring method based on multi-source data fusion, using the system described in claim 1, characterized in that: The steps include: S1. Obtain the greenhouse gas concentration distribution data of different partitions in the selected area, and filter out the highest value of the greenhouse gas concentration in the corresponding partition, build a rule engine, compare the highest value of the greenhouse gas concentration corresponding to each partition with the preset limit value, and calibrate the corresponding partition as a high-concentration partition or a low-concentration partition according to the comparison result. The process is: when the highest value of the greenhouse gas concentration exceeds the limit value, calibrate the corresponding partition as a high-concentration partition; when the highest value of the greenhouse gas concentration does not exceed the limit value, calibrate the corresponding partition as a low-concentration partition; S2. Select any partition as the monitoring site. When the partition is a high-concentration partition, the first detection strategy is triggered to obtain the monitoring site data. When the partition is a low-concentration partition, the second detection strategy is triggered to obtain the monitoring site data. The triggered first detection strategy is: Start a monitoring point at the center of the monitoring site, and configure multiple types of sensors in the monitoring point to collect greenhouse gas concentration data in real time, and use data fusion algorithm to process each greenhouse gas concentration data to obtain monitoring site data; the multiple types of sensors configured in the monitoring point include infrared gas analyzers, laser gas analyzers and electrochemical sensors; The second detection strategy triggered is: Start the monitoring points located at the center of the monitoring site and two other locations, divide the monitoring site into three parts, and each monitoring point is located at the center of each part. Each monitoring point is equipped with multiple types of sensors to collect greenhouse gas concentration data in real time. After the greenhouse gas concentration data of each monitoring point is processed by data fusion algorithm, buffer data is obtained, and then each buffer data is averaged to obtain the monitoring site data; S3, obtaining meteorological data of the monitoring site, and generating a gas concentration correction value based on the pre-processed meteorological data; the meteorological data is wind speed; The process of preprocessing meteorological data is: data cleaning and dimensionless processing; Then, the formula based on the correction value of the generated gas concentration is as follows: In the formula, Indicates the gas concentration correction value, represents the calibration coefficient, Indicates the current wind speed. Indicates the reference wind speed; S4. Detect the change value of the maximum value of greenhouse gas concentration in the monitoring area at two moments before and after, synchronously obtain the adjustment value of the gas concentration correction value at two moments before and after, and obtain the ratio of at least three consecutive change values ​​to the adjustment value. If the difference between the maximum value and the minimum value in the ratio does not exceed the preset first standard threshold, then continue to the next step of operation, otherwise, execute the adjustment strategy; the change value represents: the absolute value of the difference between the maximum value of greenhouse gas concentration in the monitoring area at the previous moment and the maximum value of greenhouse gas concentration in the monitoring area at the next moment; the adjustment value represents: the absolute value of the difference between the gas concentration correction value at the previous moment and the gas concentration correction value at the next moment; After obtaining the ratio of three consecutive change values ​​to the adjustment value, the formula on which the ratio is based is as follows: The difference between the maximum and minimum values ​​in the ratio represents: ; The adjustment strategies implemented are: In the process of generating gas concentration correction values, the calibration factor Adjust so that the calibration factor in the formula based on the generated gas concentration correction value is The value of is adjusted by 0.1 from the original k to obtain a calibration coefficient k±0.1, until the difference between the maximum value and the minimum value in the ratio does not exceed the preset first standard threshold; S5. Based on the pre-processed monitoring site data and gas concentration correction value, combined with the maximum value of greenhouse gas concentration, generate the current gas concentration standard value of the monitoring site, based on the following formula: In the formula, Indicates the standard value of gas concentration. Indicates monitoring data. Indicates the highest value of greenhouse gas concentration, represent the preset proportional coefficients, and represents the error correction factor, and The value range is 0~2; S6. Within the preset historical time period T, the standard value of gas concentration and the maximum value of greenhouse gas concentration at each historical moment are counted to generate a gas standard stability index and a remote sensing accuracy stability index. When the difference between the two exceeds the preset second standard threshold, the troubleshooting strategy is executed; the calculation formula for generating the gas standard stability index is as follows: In the formula, represents the gas standard stability index, represents the standard value of gas concentration at historical time t, where t=1, 2, ..., n, n is a positive integer, and n=T, It represents the average value of the standard value of gas concentration at each historical time t within the historical time period T; The calculation formula for generating the remote sensing accuracy stability index is as follows: In the formula, Represents the remote sensing accuracy stability index, represents the maximum value of greenhouse gas concentration at historical time t, It represents the average value of the maximum value of greenhouse gas concentration at each historical moment t within the historical time period T; The implemented inspection strategy is: arrange personnel to inspect and repair the various types of sensors configured in satellites and monitoring points in turn.

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