A drone particulate matter emission monitoring system

Abstract

The application discloses a kind of unmanned aerial vehicle particulate matter emission monitoring system, including monitoring unit, acquisition transmission unit and check calculation unit;Monitoring unit and acquisition transmission unit are carried on unmanned aerial vehicle, and monitoring unit obtains meteorological and particulate matter concentration data in the flight of unmanned aerial vehicle and uploads to acquisition transmission unit;Acquisition transmission unit receives data and obtains geographic spatial coordinate data, stores and backs up meteorological, particulate matter concentration and geographic spatial data and uploads to check calculation unit;Check calculation unit is integrated in ground station, after receiving data, carries out integrity check and backfill operation, is synthesized by time consistency processing pretreatment data, calculates particulate matter emission amount result in flight area.The application can realize monitoring data real-time acquisition, processing and emission amount result output value, automatically calibrates time to ensure that data is space consistent, is complete by independent module and real-time backup to guarantee data, reduce resource waste, improve efficiency and reliability.

Description

Technical Field

[0001] This invention relates to the field of drone emission monitoring technology, and more specifically, to a drone particulate matter emission monitoring system. Background Technology

[0002] Currently, drone-based particulate matter monitoring technology primarily relies on directly mounting portable particulate matter monitoring devices. This method aims to obtain time series data on particulate matter concentrations at specific spatial locations or to depict the spatial distribution of particulate matter over a given area. To achieve a quantitative assessment of drone emissions, Chinese patent CN115391724B discloses a method for measuring greenhouse gas emissions from drones. However, this method suffers from significant bottlenecks before data processing: the acquisition, local storage, and transmission of monitoring data lack real-time performance. More critically, its data processing workflow (such as crucial time consistency calibration) heavily relies on manual intervention, requiring manual data download and offline processing. This processing mode significantly extends the data processing cycle, making it difficult to meet the needs of rapid on-site calculations, failing to achieve the goal of on-site monitoring and immediate output, and significantly limiting timeliness.

[0003] Secondly, the built-in clocks of different monitoring devices differ, and the system lacks an efficient and automated time calibration mechanism. This directly leads to difficulties in aligning the device monitoring data required for the flux algorithm in the time dimension, affecting the accuracy of the model input data and thus reducing the efficiency of the emission calculation process and the reliability of the final results.

[0004] Furthermore, the drone location information collection and data transmission links are susceptible to environmental interference or obstruction, often leading to the loss of critical location information or unexpected data transmission interruptions. Simultaneously, the entire data collection, storage, and verification process lacks real-time backup and effective data traceability mechanisms. If data is lost or corrupted during flight, critical data is often irretrievable due to the lack of real-time backup and effective recovery methods. Ultimately, the lack of data integrity guarantees renders valuable drone flights ineffective due to invalid data acquisition, resulting in a waste of drone platform, sensor resources, and human resources. Summary of the Invention

[0005] To address the technical problems existing in the background art, the present invention innovatively provides a drone particulate matter emission monitoring system, which realizes real-time acquisition, processing and emission result output of monitoring data, automatically calibrates time to ensure spatiotemporal consistency between data, ensures data integrity through independent modules and real-time backup, reduces resource waste, and improves efficiency and reliability.

[0006] To achieve the aforementioned technical objectives, this invention discloses a drone particulate matter emission monitoring system, comprising a monitoring unit, a data acquisition and transmission unit, and a verification and calculation unit. Both the monitoring unit and the data acquisition and transmission unit are mounted on the drone. The monitoring unit acquires meteorological data and particulate matter concentration data during the drone's flight and uploads it to the data acquisition and transmission unit. The data acquisition and transmission unit receives the meteorological data and particulate matter concentration data monitored by the monitoring unit, acquires geospatial coordinate data during the drone's flight, stores and backs up the meteorological data, particulate matter concentration data, and geospatial coordinate data, and uploads them to the verification and calculation unit. The verification and calculation unit is integrated into a ground station. It receives the meteorological data, particulate matter concentration data, and geospatial coordinate data uploaded by the data acquisition and transmission unit, performs data backfilling operations to ensure the meteorological data, particulate matter concentration data, and geospatial coordinate data pass data integrity checks, performs time consistency processing, synthesizes preprocessed data, and calculates the particulate matter emission result within the drone's flight area based on the preprocessed data.

[0007] Furthermore, the present invention provides a drone particulate matter emission monitoring system, wherein the monitoring unit includes a meteorological monitoring device and a particulate matter monitoring device, the meteorological monitoring device being used to acquire the time t of each spatial point within the meteorological monitoring device during the drone's flight. m The meteorological data M is below; the particulate matter monitoring device is used to acquire the time t of each spatial point within the particulate matter monitoring device during the flight of the UAV. a The particulate matter concentration data C is below.

[0008] Furthermore, the present invention provides a particulate matter emission monitoring system for unmanned aerial vehicles (UAVs), wherein the acquisition and transmission unit includes a satellite positioning module, a data acquisition and storage module, and a first communication module. The satellite positioning module is used to acquire the location of each spatial point during the flight of the UAV at the satellite timing time t. c The data acquisition and storage module is used to collect, store, and back up data obtained by meteorological monitoring equipment, particulate matter monitoring equipment, and satellite positioning module, and to filter the required supplementary data according to the data supplementation request instruction issued by the verification calculation unit; the first communication module is used to transmit the stored data of the data acquisition and storage module to the verification calculation unit in the downlink, and to forward the data supplementation request instruction issued by the verification calculation unit to the data acquisition and storage module.

[0009] Furthermore, the present invention provides a particulate matter emission monitoring system for unmanned aerial vehicles (UAVs), wherein the verification calculation unit includes a second communication module, a verification processing module, and a throughput calculation module. The second communication module is used to transmit the stored data from the data acquisition and storage module transmitted by the first communication module to the verification processing module, and to transmit the data replenishment request command issued by the verification processing module to the first communication module. The verification processing module is used to check the data integrity of the stored data after it is locally stored at the ground station, and to generate a data replenishment request command for the data that fails the data integrity check and perform a replenishment operation until all data passes the data integrity check. The data that passes the data integrity check is then integrated into the preprocessed data required by the throughput calculation module after time consistency processing. The throughput calculation module is used to obtain the particulate matter emission result within the UAV flight area based on the preprocessed data.

[0010] Furthermore, in the unmanned aerial vehicle (UAV) particulate matter emission monitoring system of the present invention, the verification processing module performs a time integrity check on the stored data to check the data integrity. The time integrity check involves the following steps:

[0011] Sort the stored data in ascending order of timestamps;

[0012] Traverse the data sequence of stored data, calculate the time interval Δt = ti+1-ti (i = 1, 2, ..., n-1) between two consecutive data, and compare each Δt with the maximum allowed continuous time interval T. If Δt ≤ T, it is determined that the time is continuous and the next group is checked. If Δt > T, it is determined that the time is discontinuous.

[0013] If the time is not continuous, the breakpoint information is recorded. The breakpoint information includes the breakpoint position between the i-th and i+1-th data, the actual interval ti+1, and the state of the marked breakpoint to be replenished. Based on the breakpoint information, the first data replenishment request instruction is sent to the data acquisition and storage module through the second communication module and the first communication module to request the acquisition of missing data in the time interval (ti, ti+1].

[0014] The data acquisition and storage module selects data within the time interval (ti, ti+1] from the backup data as time-replenished data according to the first data replenishment request instruction, and fills the original stored data of the verification processing module with the time-replenished data through the first communication module and the second communication module.

[0015] Furthermore, in the UAV particulate matter emission monitoring system of the present invention, the verification processing module performs a parameter integrity check on the stored data to check the data integrity. The parameter integrity check involves the following steps:

[0016] Iterate through each piece of data in the stored data and check each parameter in the parameter set of each piece of data for missing values;

[0017] If all parameters are complete, the parameters are considered complete, and the next data item is checked.

[0018] If at least one parameter is missing, it is determined that the parameter is incomplete and the missing value information is recorded. The missing value information includes the timestamp of the missing value data, the name of the missing value parameter, and the status of the missing value to be replenished. Based on the missing value information, a second data replenishment request instruction is sent to the data acquisition and storage module through the second communication module and the first communication module to request the acquisition of the missing value parameter data corresponding to the missing value timestamp.

[0019] The data acquisition and storage module selects the missing value parameter data corresponding to the missing value timestamp in the backup data as the missing value data according to the second data replenishment request instruction, and fills the original stored data of the verification processing module with the replenished data through the first communication module and the second communication module.

[0020] Furthermore, in the present invention, a drone particulate matter emission monitoring system is provided, wherein the verification processing module performs the following steps when processing the data that has passed the inspection for time consistency:

[0021] The meteorological data M is calibrated to the satellite timing t of the satellite positioning module using the following formula. c ;

[0022] M(t c )=M(t m +Δt mc -Δt m )

[0023] In the formula, M(t) c ) represents t after time consistency processing c real-time meteorological data, t m Δt represents the internal time of the meteorological monitoring equipment. mc Δt is the difference between the internal time of the meteorological monitoring equipment and the satellite timing time of the satellite positioning module. m The response time of meteorological monitoring equipment to changes in external wind speed and direction;

[0024] The particulate matter concentration data C is calibrated to the satellite timing time t of the satellite positioning module using the following formula. c ;

[0025] C(t c )=C(t a +Δt ac -Δt a -Δt at )

[0026] In the formula, C(t)c ) represents t after time consistency processing c Time-based particulate matter concentration data, t a Δt represents the internal time of the particulate matter monitoring device. ac To monitor the difference between the internal time of the device and the satellite timing time of the satellite positioning module, Δt a To monitor the response time of the device to changes in external particulate matter concentration, Δt at The time it takes for ambient air to pass through the particulate matter sampling tube;

[0027] The geospatial coordinate data G is calibrated to the satellite timing time t of the satellite positioning module using the following formula. c ;

[0028] G f (t c ) = G f (t f +Δt fc )

[0029] In the formula, G f (t c ) represents t after time consistency processing c The geospatial coordinate data of the drone, where tf is the drone's internal time and Δt is the time. fc This is the difference between the internal time of the drone and the satellite time synchronization time of the satellite positioning module.

[0030] Furthermore, the present invention provides a drone particulate matter emission monitoring system, wherein the ground station also integrates a drone control system, and the verification processing module calculates the spatial positioning deviation between the satellite positioning module and the drone control system by reading the temporal and spatial data of the drone control system.

[0031] Furthermore, the present invention provides a particulate matter emission monitoring system for unmanned aerial vehicles (UAVs), wherein the verification processing module integrates data loss, data replenishment, and spatial positioning deviation as the basis for quality control of particulate matter emission results within the UAV flight area.

[0032] Furthermore, the present invention provides a drone particulate matter emission monitoring system, wherein the meteorological data M includes a meridional wind speed component v, a zonal wind speed component u, a vertical wind speed component w, temperature T, and air pressure P, and the particulate matter concentration data C includes PM1, PM2.5 ... 2.5 PM 10 Total suspended particulate matter (TSP), the geospatial coordinate data G includes altitude Z c Longitude X c and latitude Y c

[0033] The beneficial effects of this invention are as follows: This invention achieves real-time acquisition, storage, and transmission of monitoring data through a data acquisition and transmission unit, and completes the data processing flow of time consistency calibration on-site with the help of a verification calculation unit. This eliminates the need for manual intervention, manual data downloading, and offline processing, thereby significantly shortening the data processing cycle, meeting the requirements of the flux model for rapid on-site calculation, achieving the goal of on-site monitoring and on-site value output, and significantly improving timeliness. Simultaneously, the equipped verification calculation unit can automatically perform time consistency calibration between data, effectively solving the problem of differences in the built-in clocks of different monitoring devices, and constructing an efficient and automated time calibration mechanism. This ensures that preprocessed data is accurately aligned in the time dimension, achieving real-time and accurate matching between monitoring data points and the UAV's flight space and time, ensuring the accuracy of preprocessed data, improving the efficiency of the emission calculation process, and enhancing the reliability of the final results. In addition, data storage and backup functions can be implemented on the drone itself, thereby avoiding the risk of data loss during the transmission process from the drone to the ground station. Even if data loss occurs in the data received by the ground station, it can be recovered based on the backup data on the drone, ensuring the integrity of the data acquired by the ground station. Through storage and verification processing, real-time data collection, real-time backup, and real-time data integrity checks are achieved, establishing a sound real-time backup and effective data traceability mechanism. Even if data loss or damage occurs during flight, critical data can be recovered through real-time backup and effective recovery methods, ensuring data integrity. Attached Figure Description

[0034] Figure 1 This is a schematic diagram of the framework structure of a drone particulate matter emission monitoring system according to the present invention;

[0035] Figure 2 This is a schematic diagram of the workflow of the verification processing unit in a drone particulate matter emission monitoring system of the present invention. Detailed Implementation

[0036] The following is a detailed explanation and description of a drone particulate matter emission monitoring system according to the present invention, with reference to the accompanying drawings.

[0037] like Figure 1As shown in the figure, this invention discloses a drone particulate matter emission monitoring system, specifically including a monitoring unit 10, a data acquisition and transmission unit 20, and a verification and calculation unit 30. Both the monitoring unit 10 and the data acquisition and transmission unit 20 are mounted on the drone. The monitoring unit 10 acquires meteorological data and particulate matter concentration data during the drone's flight and uploads it to the data acquisition and transmission unit 20. The data acquisition and transmission unit 20 receives the meteorological data and particulate matter concentration data monitored by the monitoring unit 10 and acquires the geospatial coordinate data during the drone's flight. It stores and backs up the meteorological data, particulate matter concentration data, and geospatial coordinate data and uploads them to the verification and calculation unit 30. The verification and calculation unit 30 is integrated into a ground station. The verification and calculation unit 30 receives the meteorological data, particulate matter concentration data, and geospatial coordinate data uploaded by the data acquisition and transmission unit 20. It uses data backfilling operations to ensure the meteorological data, particulate matter concentration data, and geospatial coordinate data pass data integrity checks, performs time consistency processing, and synthesizes preprocessed data. Based on the preprocessed data, it calculates the particulate matter emission result within the drone's flight area.

[0038] In this embodiment, the acquisition and transmission unit 20 enables real-time acquisition, storage, and transmission of monitoring data. The verification calculation unit 30 facilitates on-site time consistency calibration, eliminating manual intervention and the need for manual data downloading and offline processing. This significantly shortens the data processing cycle, meets the flux model's requirement for rapid on-site calculation, achieves on-site monitoring and output, and significantly improves timeliness. Simultaneously, the equipped verification calculation unit 30 automatically performs time consistency calibration between data points, effectively resolving the discrepancies in the built-in clocks of different monitoring devices. This establishes an efficient and automated time calibration mechanism, ensuring precise alignment of preprocessed data in the time dimension. This achieves real-time and accurate matching of monitoring data points with the UAV's flight space and time, guaranteeing the accuracy of preprocessed data and improving the efficiency of emission calculation and the reliability of the final results. In addition, data storage and backup functions can be implemented on the drone itself, thereby avoiding the risk of data loss during the transmission process from the drone to the ground station. Even if data loss occurs in the data received by the ground station, it can be recovered based on the backup data on the drone, ensuring the integrity of the data acquired by the ground station. Through storage and verification processing, real-time data collection, real-time backup, and real-time data integrity checks are achieved, establishing a sound real-time backup and effective data traceability mechanism. Even if data loss or damage occurs during flight, critical data can be recovered through real-time backup and effective recovery methods, ensuring data integrity.

[0039] In one embodiment of the present invention, the monitoring unit 10 includes a meteorological monitoring device 11 and a particulate matter monitoring device 12. The meteorological monitoring device 11 is used to acquire the time t of each spatial point within the meteorological monitoring device 11 during the flight of the UAV. mThe meteorological data M is monitored by a three-dimensional ultrasonic meteorological instrument, which can be used for meteorological monitoring equipment 11. The monitored meteorological data M includes the meridional wind speed component v, the zonal wind speed component u, the vertical wind speed component w, temperature T, and air pressure P. The particulate matter monitoring equipment 12 is used to acquire the time t of each spatial point within the particulate matter monitoring equipment 12 during the flight of the UAV. a The particulate matter concentration data C below includes PM1 and PM2.5 concentrations. 2.5 PM 10 Total suspended particulate matter (TSP). These settings enable comprehensive collection of critical meteorological and particulate matter information during UAV flight, providing multi-dimensional and high-precision foundational data support for subsequent data processing, calculations, and related analyses.

[0040] In one embodiment of the present invention, the acquisition and transmission unit 20 includes a satellite positioning module 21, a data acquisition and storage module 22, and a first communication module 23. The satellite positioning module 21 is used to acquire the location of each spatial point during the flight of the UAV at the satellite timing time t. c The geospatial coordinate data G below includes the elevation Z. c Longitude X c The data acquisition and storage module 22 is used to collect, store, and back up data acquired by the meteorological monitoring equipment 11, particulate matter monitoring equipment 12, and satellite positioning module 21. It also filters the required supplementary data according to the data supplementation request command issued by the verification calculation unit 30. The first communication module 23 is used to transmit the stored data of the data acquisition and storage module 22 to the verification calculation unit 30 and forward the data supplementation request command issued by the verification calculation unit 30 to the data acquisition and storage module 22. Through the above settings, accurate spatiotemporal marking, secure storage backup, and efficient transmission interaction of multi-source data can be realized. When the data of the verification calculation unit 30 is incomplete, the data acquisition and storage module 22 can filter the required supplementary data according to the data supplementation request command, providing reliable support for data integrity assurance and subsequent processing.

[0041] In one embodiment of the present invention, the verification calculation unit 30 includes a second communication module 31, a verification processing module 32, and a throughput calculation module 33. The second communication module 31 is used to transmit the stored data of the data acquisition and storage module 22 transmitted by the first communication module 23 to the verification processing module 32, and to transmit the data replenishment request command issued by the verification processing module 32 to the first communication module 23 via uplink. The verification processing module 32 is used to check the data integrity of the stored data after it is stored locally at the ground station, and to generate a data replenishment request command for the data that fails the data integrity check and perform a replenishment operation until all data passes the data integrity check. The data that passes the data integrity check is then integrated into the preprocessed data required by the flux calculation module 33 after time consistency processing. Integration means putting all the data into a single dataset according to the format required by the flux calculation module 33. The flux calculation module 33 is used to obtain the particulate matter emission results within the UAV flight area based on the preprocessed data. The flux calculation module 33 maps the particulate matter concentration to a two-dimensional plane based on the spatial location information of each point and performs interpolation to establish a vertical particulate matter transport cross section. Combining turbulent fluctuations, the flux model is used to calculate the wind vector and particulate matter flux at each point on the transport cross section. Finally, the net particulate matter flux on each transport cross section is integrated to obtain the particulate matter emission results within the flight area. More specifically, the flux calculation module 33 can adopt the method disclosed in patent CN115391724B. In the calculation process, all variables involving greenhouse gases are replaced with the corresponding particulate matter parameters in this application. The detailed calculation process will not be elaborated here. Through the above settings, efficient, reliable, and time-consistent data transmission can be ensured, providing high-quality preprocessed data for accurate calculation of particulate matter emissions in the flight area and ensuring the accuracy and effectiveness of the calculation results.

[0042] like Figure 2 As shown, in one embodiment of the present invention, the verification processing module 32 needs to perform a time integrity check on the stored data to check the data integrity. The following steps are performed during the time integrity check:

[0043] Sort the stored data in ascending order of timestamp;

[0044] Traverse the data sequence of stored data, calculate the time interval Δt = ti+1-ti (i = 1, 2, ..., n-1) between two consecutive data, and compare each Δt with the maximum allowed continuous time interval T. If Δt ≤ T, it is determined that the time is continuous and the next group is checked. If Δt > T, it is determined that the time is discontinuous.

[0045] If the time is not continuous, the breakpoint information is recorded. The breakpoint information includes the breakpoint position between the i-th and i+1-th data, the actual interval ti+1, and the status of the marked breakpoint to be replenished. Based on the breakpoint information, the first data replenishment request instruction is sent to the data acquisition and storage module 22 through the second communication module 31 and the first communication module 23 to request the acquisition of missing data in the time interval (ti, ti+1].

[0046] The data acquisition and storage module 22 selects data within the time interval (ti, ti+1] from the backup data as time-replenished data according to the first data replenishment request instruction, and fills the original stored data of the verification processing module 32 with the time-replenished data through the first communication module 23 and the second communication module 31.

[0047] In this embodiment, time breakpoints can be accurately identified, and backup data can be used to ensure the integrity of the data time dimension, thereby guaranteeing the continuity and accuracy of subsequent data processing and calculation and improving data reliability.

[0048] like Figure 2 As shown, in one embodiment of the present invention, the verification processing module 32 needs to perform parameter integrity checks on the stored data to perform data integrity checks on the stored data. The following steps are performed during the parameter integrity check:

[0049] Iterate through each piece of data in the stored data and check each parameter in the parameter set of each piece of data for missing values;

[0050] If all parameters are complete, the parameters are considered complete, and the next data item is checked.

[0051] If at least one parameter is missing, it is determined that the parameter is incomplete and the missing value information is recorded. The missing value information includes the timestamp of the missing value data, the name of the missing parameter, and the status of the missing value to be replenished. Based on the missing value information, a second data replenishment request instruction is sent to the data acquisition and storage module 22 through the second communication module 31 and the first communication module 23 to request the acquisition of the missing value parameter data corresponding to the missing value timestamp.

[0052] The data acquisition and storage module 22 selects the missing value parameter data corresponding to the missing value timestamp in the backup data as the missing value data according to the second data replenishment request instruction, and fills the original stored data of the verification processing module 32 with the replenished data through the first communication module 23 and the second communication module 31.

[0053] In this embodiment, missing parameters and their corresponding times can be accurately located. By selectively filling in missing parameters, the completeness of parameters at each time point can be ensured, providing comprehensive and accurate parameter data for subsequent processing and calculation, thereby improving data quality and reliability.

[0054] like Figure 2As shown, in one embodiment of the present invention, the verification processing module 32 performs the following steps when processing the data that has passed the inspection for time consistency:

[0055] The meteorological data M is calibrated to the satellite timing t of the satellite positioning module 21 using the following formula. c ;

[0056] M(t c )=M(t m +Δt mc -Δt m )

[0057] In the formula, M(t) c ) represents t after time consistency processing c real-time meteorological data, t m For the internal time of meteorological monitoring equipment 11, Δt mc Δt is the difference between the internal time of the meteorological monitoring equipment 11 and the satellite timing time of the satellite positioning module 21. m The response time of meteorological monitoring equipment 11 to changes in external wind speed and direction;

[0058] The particulate matter concentration data C is calibrated to the satellite timing time tc of the satellite positioning module 21 using the following formula;

[0059] C(t c )=C(t a +Δt ac -Δt a -Δt at )

[0060] In the formula, C(t) c ) represents t after time consistency processing c Time-based particulate matter concentration data, t a For the internal time of the particulate matter monitoring device 12, Δt ac To monitor the difference between the internal time of the device and the satellite timing time of the satellite positioning module 21, Δt a To monitor the response time of the device to changes in external particulate matter concentration, Δt at The time it takes for ambient air to pass through the particulate matter sampling tube;

[0061] The geospatial coordinate data G is calibrated to the satellite timing time t of the satellite positioning module 21 using the following formula. c ;

[0062] G f (t c ) = G f (t f +Δt fc )

[0063] In the formula, G f(t c ) represents t after time consistency processing c The geospatial coordinate data of the drone, where tf is the drone's internal time and Δt is the time. fc The difference between the internal time of the UAV and the satellite timing time of the satellite positioning module 21.

[0064] In this embodiment, the verification processing module 32 calibrates meteorological data, particulate matter concentration data, and geospatial coordinate data to satellite time using a specific formula. The formula incorporates the difference between the internal time of each device and the satellite time, as well as unique time factors such as device response and sampling. This can accurately eliminate time deviations between different devices, ensuring that all types of data are aligned on the same time reference. This provides high-quality data with unified time for subsequent data integration and throughput calculation, improving the accuracy and reliability of the calculation results.

[0065] In one embodiment of the present invention, the ground station also integrates an unmanned aerial vehicle (UAV) control system 40. The verification processing module 32 reads the time and space data of the UAV control system 40 and calculates the spatial positioning deviation between the satellite positioning module 21 and the UAV control system 40. The verification processing module 32 takes the data missing situation, data replenishment situation and spatial positioning deviation as the basis for quality control of particulate matter emission results in the UAV flight area.

[0066] In this embodiment, the UAV control system 40 integrated in the ground station allows the verification processing module 32 to read its temporal and spatial data to calculate the spatial positioning deviation between the satellite positioning module 21 and the UAV control system 40. This deviation is then combined with data loss and recovery status as the basis for quality control of particulate matter emission results. This comprehensively considers key factors such as data integrity and positioning accuracy, providing a multi-dimensional evaluation basis for the reliability of emission results, effectively ensuring result quality and improving the credibility of data application.

[0067] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components, unless otherwise explicitly limited. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0068] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0069] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and simple improvements made on the substantive content of the present invention should be included within the protection scope of the present invention.

Claims

1. A particulate matter emission monitoring system for unmanned aerial vehicles (UAVs), characterized in that, The system comprises a monitoring unit, a data acquisition and transmission unit, and a verification and calculation unit. Both the monitoring unit and the data acquisition and transmission unit are mounted on the UAV. The monitoring unit acquires meteorological data and particulate matter concentration data during the UAV's flight and uploads it to the data acquisition and transmission unit. The data acquisition and transmission unit receives the meteorological data and particulate matter concentration data monitored by the monitoring unit, acquires geospatial coordinate data during the UAV's flight, stores and backs up the meteorological data, particulate matter concentration data, and geospatial coordinate data, and uploads them to the verification and calculation unit. The verification and calculation unit is integrated into a ground station. It receives the meteorological data, particulate matter concentration data, and geospatial coordinate data uploaded by the data acquisition and transmission unit, uses data backfilling operations to ensure the meteorological data, particulate matter concentration data, and geospatial coordinate data pass data integrity checks, performs time consistency processing, synthesizes preprocessed data, and calculates the particulate matter emission result within the UAV's flight area based on the preprocessed data. The monitoring unit includes meteorological monitoring equipment and particulate matter monitoring equipment. The meteorological monitoring equipment acquires the time t of each spatial point within the meteorological monitoring equipment during the UAV's flight. m The meteorological data M is below; the particulate matter monitoring device is used to acquire the time t of each spatial point within the particulate matter monitoring device during the flight of the UAV. a The particulate matter concentration data C is obtained from the data acquisition and transmission unit, which includes a satellite positioning module, a data acquisition and storage module, and a first communication module. The satellite positioning module is used to obtain the satellite timing time t of each spatial point during the flight of the UAV. c The geospatial coordinate data G below; The verification calculation unit includes a second communication module, a verification processing module, and a throughput calculation module. The verification processing module is used to check the data integrity of the stored data after the data acquisition and storage module is stored locally at the ground station, generate a data replenishment request command for the data that fails the data integrity check, and perform the replenishment operation until all data passes the data integrity check. The data that passes the data integrity check is then integrated into the preprocessed data required by the throughput calculation module after time consistency processing. The verification processing module performs the following steps when processing the time consistency of the data that has passed the check: The meteorological data M is calibrated to the satellite timing t of the satellite positioning module using the following formula. c ; M(t c )=M(t m +Δt mc -Δt m ) In the formula, M(t) c ) represents t after time consistency processing c real-time meteorological data, t m Δt represents the internal time of the meteorological monitoring equipment. mc Δt is the difference between the internal time of the meteorological monitoring equipment and the satellite timing time of the satellite positioning module. m The response time of meteorological monitoring equipment to changes in external wind speed and direction; The particulate matter concentration data C is calibrated to the satellite timing time t of the satellite positioning module using the following formula. c ; C(t c )=C(t a +Δt ac -Δt a -Δt at ) In the formula, C(t) c ) represents t after time consistency processing c Time-based particulate matter concentration data, t a Δt represents the internal time of the particulate matter monitoring device. ac To monitor the difference between the internal time of the device and the satellite timing time of the satellite positioning module, Δt a To monitor the response time of the device to changes in external particulate matter concentration, Δt at The time it takes for ambient air to pass through the particulate matter sampling tube; The geospatial coordinate data G is calibrated to the satellite timing time t of the satellite positioning module using the following formula. c ; G f (t c )=G f (t f +Δt fc ) In the formula, G f (t c ) represents t after time consistency processing c Geospatial coordinate data of the drone at any time, t f Let Δt be the internal time of the drone. fc This is the difference between the internal time of the drone and the satellite time synchronization time of the satellite positioning module.

2. The particulate matter emission monitoring system for unmanned aerial vehicles according to claim 1, characterized in that, The data acquisition and storage module is used to collect, store and back up data obtained by meteorological monitoring equipment, particulate matter monitoring equipment and satellite positioning module, and filter the required supplementary data according to the data supplementation request instruction issued by the verification calculation unit. The first communication module is used to transmit the stored data of the data acquisition and storage module to the verification calculation unit in the downlink, and to forward the data replenishment request instruction issued by the verification calculation unit to the data acquisition and storage module.

3. The particulate matter emission monitoring system for unmanned aerial vehicles according to claim 2, characterized in that, The second communication module is used to transmit the stored data from the data acquisition and storage module transmitted by the first communication module to the verification and processing module, and to transmit the data replenishment request command issued by the verification and processing module to the first communication module; the flux calculation module is used to obtain the particulate matter emission result within the UAV flight area based on the preprocessed data.

4. The particulate matter emission monitoring system for unmanned aerial vehicles according to claim 3, characterized in that, The verification processing module performs a time integrity check on the stored data to check its data integrity. The time integrity check involves the following steps: Sort the stored data in ascending order of timestamp; Traverse the data sequence of stored data, calculate the time interval Δt = ti+1 - ti (i = 1, 2, ..., n-1) between two consecutive data, and compare each Δt with the maximum allowed consecutive time interval T. If Δt ≤ T, it is determined that the time is continuous and the next group is checked. If Δt > T, it is determined that the time is discontinuous. If the time is not continuous, the breakpoint information is recorded. The breakpoint information includes the breakpoint position between the i-th and i+1-th data, the actual interval ti+1, and the state of the marked breakpoint to be replenished. Based on the breakpoint information, the first data replenishment request instruction is sent to the data acquisition and storage module through the second communication module and the first communication module to request the acquisition of missing data in the time interval (ti, ti+1]. The data acquisition and storage module selects data within the time interval (ti, ti+1] from the backup data as time-replenished data according to the first data replenishment request instruction, and fills the original stored data of the verification processing module with the time-replenished data through the first communication module and the second communication module.

5. The particulate matter emission monitoring system for unmanned aerial vehicles according to claim 3, characterized in that, The verification processing module performs data integrity checks on the stored data, which requires parameter integrity checks. The parameter integrity checks involve the following steps: Iterate through each piece of data in the stored data and check each parameter in the parameter set of each piece of data for missing values; If all parameters are complete, the parameters are considered complete, and the next data item is checked. If at least one parameter is missing, it is determined that the parameter is incomplete and the missing value information is recorded. The missing value information includes the timestamp of the missing value data, the name of the missing value parameter, and the status of the missing value to be replenished. Based on the missing value information, a second data replenishment request instruction is sent to the data acquisition and storage module through the second communication module and the first communication module to request the acquisition of the missing value parameter data corresponding to the missing value timestamp. The data acquisition and storage module selects the missing value parameter data corresponding to the missing value timestamp in the backup data as the missing value data according to the second data replenishment request instruction, and fills the original stored data of the verification processing module with the replenished data through the first communication module and the second communication module.

6. The particulate matter emission monitoring system for unmanned aerial vehicles according to claim 1, characterized in that, The ground station also integrates an unmanned aerial vehicle (UAV) control system. The verification processing module reads the time and space data of the UAV control system and calculates the spatial positioning deviation between the satellite positioning module and the UAV control system.

7. The particulate matter emission monitoring system for unmanned aerial vehicles according to claim 6, characterized in that, The verification module integrates data loss, data replenishment, and spatial positioning deviation as the basis for quality control of particulate matter emission results within the UAV flight area.

8. The particulate matter emission monitoring system for unmanned aerial vehicles according to claim 3, characterized in that, The meteorological data M includes meridional wind speed component v, zonal wind speed component u, vertical wind speed component w, temperature T, and air pressure P. The particulate matter concentration data C includes PM1 and PM2.

5. 2.5 PM 10 Total suspended particulate matter (TSP), the geospatial coordinate data G includes altitude Z c Longitude X c and latitude Y c .

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