Atmospheric underway mobile monitoring device and dynamic calibration method

Abstract

The atmosphere sailing mobile monitoring device comprises an upper shell and a lower shell, the lower shell is of an inverted circular truncated cone structure, a plurality of sampling through holes are formed in the side face of the lower shell in the circumferential direction, a water collecting groove and a drainage hole are formed in the lower end of the lower shell, a sampling opening and a ventilation opening are formed in the lower shell, and the sampling through holes are communicated with the sampling opening. The sampling port is connected with a gas sensor through a sampling pipe, the gas sensor is connected with a fan, a heating and dehumidifying module is arranged at the lower end of the sampling port, and a power module, a positioning module, a communication module and a main control module are further arranged on the lower shell. The space-time limitation of a traditional calibration mode is broken through, a multi-directional interactive calibration chain network is formed, and the calibration efficiency is improved; the method has the advantages that the calibration reliability is improved, the calibration accuracy is improved, the energy consumption is reduced, the influence of car roof dust accumulation is avoided, and water vapor condensation in the monitoring process is removed.

Description

Technical Field

[0001] The present invention relates to the technical field of urban air environment quality monitoring, and in particular to an atmospheric cruise mobile monitoring device and a dynamic calibration method. Background Art

[0002] Currently, mobile atmospheric monitoring systems involve installing an atmospheric monitoring device atop a moving vehicle (taxis, buses, specialized survey vehicles, etc.) or integrated into a roof light. These devices collect real-time atmospheric data on PM, CO, O₃, VOCs, and other levels, enabling rapid mapping of regional air pollution. Compared to fixed monitoring methods, mobile atmospheric monitoring breaks through traditional application and regulatory models, expanding the monitoring scope and improving data representativeness. They also achieve high temporal and spatial resolution coverage at low cost, facilitating refined urban management.

[0003] The calibration method for traditional cruise monitoring systems uses fixed urban standard stations as the calibration target. This has the following drawbacks: Because fixed standard stations are located off-road and only output one set of monitoring data every hour, the temporal and spatial ranges of data comparison are inconsistent; the uniform coefficient correction method lacks individual corrections for different sensors, making it difficult to ensure data accuracy. Furthermore, to protect against rain and water, the sampling port of the mobile atmospheric monitoring device is located below the device, with the atmospheric sampling airflow entering from the bottom. This presents several issues: it is impossible to sample the atmosphere from all directions, and the monitoring results are easily affected by dust accumulation on the vehicle roof; moisture cannot be effectively removed during the monitoring process, resulting in condensation. Chinese patent application number CN202010075417.X discloses a dynamic calibration method for spatially distributed air quality cruise monitoring sensors. This method utilizes multiple calibration reference points and forms a chain calibration network through a "calibration-marking-recalibration" cycle, eliminating reliance on fixed urban standard stations. However, this method has the following problems: static calibration model: calibration relies on a preset time and space range, and lacks dynamic compensation for environmental dynamic factors and other social factors; low data credibility: for temporarily marked secondary mobile calibration benchmarks, there is a lack of dynamic management throughout the entire life cycle; one-way calibration transfer: the one-way transfer calibration architecture centered on a fixed benchmark does not form a multi-directional interactive calibration network.

[0004] In summary, there is at least one of the following technical problems: Since the fixed standard stations are set away from the road and only one set of monitoring data is output every hour, the temporal and spatial scope of data comparison is inconsistent.

[0005] The uniform coefficient correction method lacks individual correction for different sensors and is difficult to ensure the accuracy of the data.

[0006] Static calibration model, calibration relies on a preset time and space range, and lacks dynamic compensation for environmental dynamic factors and other social factors.

[0007] The data credibility is low, and there is a lack of dynamic management throughout the entire life cycle of temporarily marked secondary mobile calibration benchmarks.

[0008] One-way calibration transfer, a one-way transfer calibration architecture centered on a fixed reference point, does not form a multi-directional interactive calibration network.

[0009] It is impossible to sample the atmosphere in all directions, and the monitoring results are easily affected by dust accumulated on the roof.

[0010] During the monitoring process, moisture cannot be effectively removed and condensation will occur. Summary of the Invention

[0011] The main purpose of the present invention is to provide an atmospheric cruise mobile monitoring device and a dynamic calibration method to solve the problem in the prior art that the fixed standard site is set off the road and only one set of monitoring data is output every hour, resulting in inconsistent time and space ranges for data comparison. The uniform coefficient correction method lacks individual corrections for different sensors, making it difficult to ensure the accuracy of the data. The static calibration model relies on a preset time and space range for calibration and lacks dynamic compensation for environmental dynamic factors and other social factors. The data credibility is low, and there is a lack of dynamic management of the entire life cycle for temporarily marked secondary mobile calibration reference points. One-way calibration transfer, a one-way transfer calibration architecture centered on a fixed reference point, does not form a multi-directional interactive calibration network. It is impossible to sample the atmosphere in all directions, and the monitoring results are easily affected by dust accumulated on the roof. Moisture cannot be effectively removed during the monitoring process, resulting in at least one technical problem of water vapor condensation.

[0012] In order to achieve the above-mentioned purpose, according to one aspect of the present invention, there is provided an atmospheric cruise mobile monitoring device, comprising an upper shell and a lower shell, the lower shell being an inverted frustum structure, a plurality of sampling through holes being provided circumferentially on the side surface of the lower shell, a water collecting trough and a drainage hole being provided at the lower end of the lower shell, a sampling port and a vent being provided on the lower shell, the sampling port being connected to a gas sensor through a sampling tube, the gas sensor being connected to a fan, a heating and dehumidification module being provided at the lower end of the sampling port, and a power supply module, a positioning module, a communication module and a main control module being further provided on the lower shell.

[0013] Preferably, the upper shell cover is arranged on the lower shell, the upper shell is provided with an anti-flocculation net, and the lower shell is also provided with a mounting base, and the mounting base is installed on the mobile body. The main control module, communication module, positioning module, heating and dehumidification module, fan and gas sensor are respectively connected to the power supply module, and the communication module, positioning module, heating and dehumidification module, fan and gas sensor are respectively connected to the main control module.

[0014] According to another aspect of the present invention, a dynamic calibration method for an atmospheric cruise mobile monitoring device is provided, comprising: Step 1: Select a fixed reference point; Step 2: Mark the moving benchmark. The moving benchmark is valid for 24 hours. If the conditions are not met, the qualification will be revoked immediately. Step 3: Dynamically expand the mobile reference points to form a calibration chain network; Step 4: Based on the calibration data uploaded to the cloud platform, a multi-source weighted calibration model is constructed to generate calibration coefficients; Step 5: Group consensus verification: When the calibration residuals of ≥3 devices at the same location are less than 5%, a reliable calibration coefficient is generated and written into the device; Step 6: Repeat steps 2-5 to complete the calibration.

[0015] Preferably, in step 1, key city nodes are selected as fixed reference points, and calibration is performed on the driving route of the mobile vehicle to reduce the calibration cost, wherein the key city nodes include charging stations, parking lots and transportation hubs.

[0016] Preferably, in step 2, when the mobile vehicle enters the fixed reference point and the preset GPS electronic fence and the vehicle speed is ≤5km / h, the calibration process is automatically started. If the calibration residual of the mobile vehicle with the fixed reference point is less than 5% for three consecutive times, the mobile vehicle is marked as a mobile reference point. The calibration residual is calculated as:

[0017] in, is the monitoring value of the mobile vehicle at time t; is the monitoring value of the fixed reference point at time t; t is the time point in the calibration process; Among them, the mobile reference point is valid for 24 hours. If the single calibration residual is greater than 10%, the marking qualification will be revoked immediately. If the calibration residual exceeds the threshold of 5% for three consecutive times, the equipment failure will be automatically marked, and abnormal data will be eliminated and the self-test program will be started.

[0018] Preferably, in step 3, the mobile reference point utilizes vehicle congestion or red light waiting time to interact with adjacent mobile monitoring vehicles or fixed reference points through communication to initiate calibration and form a chain network, wherein the fixed reference point presets the GPS electronic fence range.

[0019] Preferably, in step 4, a multi-source weighted calibration model is constructed Extract atmospheric monitoring data and environmental parameter data from fixed reference points, mobile reference points, and mobile monitoring equipment in the same space and time, and only select data pairs with environmental differences ≤ 10%; The dynamic weight compensation formula based on environmental factors is:

[0020] in, This is the coefficient calibrated when the sensor leaves the factory; is the weight of environmental factors (temperature, humidity, wind speed, etc.); is the environmental parameter deviation; is the spatial weight. The closer the distance, the greater the weight. When the distance exceeds the preset GPS electronic fence, is 0; is the monitoring value; If the calibration residual exceeds the threshold of 5% for three consecutive times, the device will be automatically marked as faulty, abnormal data will be eliminated, and the self-check program will be started.

[0021] Preferably, in step 5, all monitoring equipment calibration data are uploaded to the cloud platform in real time, and the cloud platform verifies the calibration results through a multi-node consensus mechanism: when the calibration residuals of ≥3 devices at the same location are <5%, a reliable calibration coefficient is generated; when residual abnormalities occur, the system automatically triggers equipment abnormality self-inspection and mobile reference point qualification review.

[0022] Preferably, in step 6, steps 1 to 5 are repeatedly performed to continuously calibrate the cruise mobile monitoring device to achieve a complete calibration process, wherein the calibration can be divided into regular calibration and irregular calibration.

[0023] Preferably, a taxi carrying an atmospheric mobile monitoring device is charged at a charging station with a fixed reference point. When the taxi enters a radius of 200m from the fixed reference point and the speed is ≤5km / h, the calibration process is started. When the vehicle is turned off, the battery in the mobile device starts to supply power. The data upload frequency of the mobile monitoring device is 3s. The entire calibration takes more than 1.5 minutes, that is, 30 sets of data or more are taken for comparison. The first calibration residual is generated after the mobile vehicle is calibrated with the fixed reference point. The mobile vehicle completes two calibrations with other fixed reference points at different time periods or on different dates. The three calibration residuals are all less than 5%. At this time, the mobile vehicle is Marked as a mobile reference point; when the mobile reference point is in a traffic jam or red light, it monitors the moving vehicle, realizes data exchange through the communication network, and starts data calibration. At this time, if there is a fixed reference point within a radius of 200m, the data of the fixed reference point will also be uploaded for calibration; based on the calibration data uploaded simultaneously and spatially by the fixed reference point, mobile reference point and moving vehicle, data pairs with environmental differences ≤10% are selected, and the calibration coefficient is calculated according to the multi-source weighted calibration model. At this time, the calibration coefficient is not directly written to the device; when the calibration residuals of ≥3 devices at the same location are <5%, a reliable calibration coefficient is generated, and the calibration coefficient is written to the device to complete the calibration.

[0024] The application of the technical solution of the present invention has the following technical effects: By establishing a dual calibration mechanism of fixed reference point calibration and mobile reference point calibration, the time and space limitations of traditional calibration methods are broken through, a multi-directional interactive calibration chain network is formed, and calibration efficiency is improved.

[0025] The marked mobile benchmark points are dynamically managed throughout their life cycle. When they do not meet the requirements, the mobile benchmark qualifications are immediately revoked to improve the credibility of calibration.

[0026] The multi-source data fusion dynamic calibration algorithm performs environmental parameter compensation and spatial distance weight distribution, avoiding simple coefficient correction and improving calibration accuracy.

[0027] Utilizing existing facilities such as power stations, parking lots, and transportation hubs reduces deployment costs and achieves high coverage at low cost. Calibration is performed during traffic congestion to reduce energy consumption.

[0028] Unlike traditional devices that sample from the bottom, the design of the lower shell allows for sampling in all directions, avoiding the impact of dust accumulation on the roof.

[0029] The design of the heating and dehumidification module at the air inlet and the design of the groove through-holes at the bottom of the lower shell can effectively eliminate the problem of water vapor condensation during the monitoring process. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The accompanying drawings, which constitute part of this application, are intended to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are intended to explain the present invention and do not constitute an undue limitation of the present invention. In the accompanying drawings: Figure 1 It shows a front view of the atmospheric cruise mobile monitoring device according to the present invention; Figure 2 Shown Figure 1 A cross-sectional view of the atmospheric cruise mobile monitoring device; Figure 3 Shown Figure 1 Structural view of the atmospheric cruise mobile monitoring device; Figure 4 Shown Figure 1 Dynamic calibration flow chart of the atmospheric cruise mobile monitoring device.

[0031] The above drawings include the following reference numerals: 1-Upper shell 2-Lower shell 3-Mounting base 4-Anti-flocculation net 5-Sampling port 6-Gas sensor 7-Fan 8-Ventilation port 9-Power module 10-Main control module 11-Communication module 12-Positioning module 13-Heating and dehumidification module 14-Sampling tube DETAILED DESCRIPTION

[0032] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0033] like Figures 1 to 4 As shown, an embodiment of the present invention provides an atmospheric cruise mobile monitoring device, including an upper shell 1 and a lower shell 2, wherein the lower shell 2 is an inverted frustum structure, and a plurality of sampling through holes are provided on the circumferential side of the lower shell 2, and a water collecting trough and a drainage hole are provided at the lower end of the lower shell 2, and a sampling port 5 and a vent 8 are provided on the lower shell 2, the sampling port 5 is connected to the gas sensor 6 through a sampling tube 14, and the gas sensor 6 is connected to the fan 7, and a heating and dehumidification module 13 is provided at the lower end of the sampling port 5, and a power supply module 9, a positioning module 12, a communication module 11 and a main control module 10 are also provided on the lower shell 2.

[0034] In this embodiment, the upper shell 1 is covered on the lower shell 2, the upper shell 1 is provided with an anti-flocculation net 4, and the lower shell 2 is also provided with a mounting base 3, and the mounting base 3 is installed on the mobile body. The main control module 10, communication module 11, positioning module 12, heating and dehumidification module 13, fan 7 and gas sensor 6 are respectively connected to the power supply module 9, and the communication module 11, positioning module 12, heating and dehumidification module 13, fan 7 and gas sensor 6 are respectively connected to the main control module 10.

[0035] Specifically, an atmospheric cruise mobile monitoring device includes an upper shell 1, a lower shell 2, a mounting base 3, an anti-flocculation net 4 and a core component module. The upper shell 1 is cylindrical, pyramidal, stepped, etc. The embodiment shows a cylindrical shape. The size of the lower surface of the upper shell 1 is larger than the size of the upper surface of the lower shell 2, which can play a role in shielding rainwater. The lower shell 2 is provided with a sampling hole, a water collection tank, and a drainage hole. The lower shell 2 is frustum-shaped, wide at the top and narrow at the bottom, and gradually narrows from the upper surface to the lower surface, which is beneficial to prevent rainwater from entering. The function of the sampling hole is to allow the atmospheric sampling airflow to enter the data monitoring module from all sides of the device, so that sampling can be achieved in all directions, while avoiding the influence of dust accumulation on the roof. The function of the water collection tank is to collect water vapor and rainwater generated during the monitoring process and discharge them in time through the drainage hole. The mounting base 3 is used to connect the roof and the lower shell 2. It has strong magnetism and can be directly adsorbed on the roof. Soft rubber is installed at the bottom of the mounting base 3, which can play a buffering and shock-absorbing role, which is beneficial to protecting the device. The anti-flocculation net 4 is cylindrical, connected to the upper shell 1, and covers the outside of the lower shell 2, which can prevent the flocculent matter from clogging the sampling port 5. The cylindrical design has the effect of self-purification and sewage discharge. As the wind direction changes, the flocculent matter hanging outside the anti-flocculation net 4 can be blown away. The core component module is located inside the upper shell 1 and on the top of the lower shell 2. It includes a sampling port 5, a gas sensor 6, a fan 7, a vent 8, a power module 9, a main control module 10, a communication module 11, a positioning module 12, and a heating and dehumidification module 13. The sampling port 5, the gas sensor 6 and the fan 7 are connected through a sampling tube 14. A heating and dehumidification module 13 is provided at the lower end of the sampling port 5, which can be a heating wire, a heating net, etc. The vent 8 is located at the end of the fan 7 and is connected to the lower shell 2, and the gas can pass through the vent 8.

[0036] Another embodiment of the present invention provides a method for using an atmospheric cruise mobile monitoring device, comprising: Step 1: Select a fixed reference point; Step 2: Mark the moving benchmark. The moving benchmark is valid for 24 hours. If the conditions are not met, the qualification will be revoked immediately. Step 3: Dynamically expand the mobile reference points to form a calibration chain network; Step 4: Based on the calibration data uploaded to the cloud platform, a multi-source weighted calibration model is constructed to generate calibration coefficients; Step 5: Group consensus verification: When the calibration residuals of ≥3 devices at the same location are less than 5%, a reliable calibration coefficient is generated and written into the device; Step 6: Repeat steps 2-5 to complete the calibration.

[0037] Specifically, S1: Select fixed reference points. Select key nodes in the city (such as charging stations, parking lots, and transportation hubs) as fixed reference points, and implement calibration on the driving route of the mobile vehicle to reduce calibration costs. S2: Mobile reference point marking. When the mobile vehicle enters the fixed reference point and the preset GPS electronic fence and the vehicle speed is ≤5km / h, the calibration process is automatically started. If the calibration residual of the mobile vehicle with the fixed reference point is less than 5% for three consecutive times, the mobile vehicle is marked as a mobile reference point. The calculation formula for the calibration residual is:

[0038] in, is the monitoring value of the mobile vehicle at time t; is the monitoring value of the fixed reference point at time t; t is the time point in the calibration process The moving reference point is valid for 24 hours. If the residual error of a single calibration exceeds 10%, the marking qualification is immediately revoked. If the residual error of the calibration exceeds the threshold (5%) for three consecutive times, the device is automatically marked as faulty, abnormal data is eliminated, and the self-test program is initiated.

[0039] S3: Dynamic calibration expansion: Mobile reference points utilize vehicle congestion or red light waiting time to communicate with nearby mobile monitoring vehicles or fixed reference points (within the preset GPS electronic fence) to exchange real-time data and initiate calibration, forming a chain network. S4: Construct a multi-source weighted calibration model to extract atmospheric monitoring data and environmental parameter data from fixed reference points, mobile reference points, and mobile monitoring equipment in the same space and time, and only select data pairs with environmental differences ≤10%. The dynamic weight compensation formula based on environmental factors is:

[0040] in, This is the coefficient calibrated when the sensor leaves the factory; is the weight of environmental factors (temperature, humidity, wind speed, etc.); is the environmental parameter deviation; is the spatial weight. The closer the distance, the greater the weight. When the distance exceeds the preset GPS electronic fence, is 0; C is the corresponding monitoring value under fixed calibration, mobile calibration, calibration and original state.

[0041] If the calibration residual exceeds the threshold (5%) for three consecutive times, the device will be automatically marked as faulty, abnormal data will be eliminated, and the self-check program will be started.

[0042] S5: Group consensus verification: All monitoring equipment calibration data is uploaded to the cloud platform in real time. The cloud platform verifies the calibration results through a multi-node consensus mechanism: when the calibration residuals of ≥3 devices at the same location are less than 5%, a reliable calibration coefficient is generated. If a residual anomaly occurs, the system automatically triggers a device anomaly self-check and mobile reference point qualification review.

[0043] S6: Repeat steps S1-S5 to continuously calibrate the mobile monitoring device, completing a complete calibration process. Calibration can be divided into regular calibration and irregular calibration.

[0044] In this embodiment, the equipment within the fixed reference point is regularly calibrated against national standard stations, with comparative monitoring performed as close to the national monitoring station as possible. The fixed reference point equipment is aligned with the vehicle roof height, contains the same sensors as the onboard equipment, and integrates environmental parameter compensation modules (temperature, humidity, and air pressure) to ensure data reliability.

[0045] In this embodiment, the GPS electronic fence can intelligently shrink the calibration radius according to the pollution situation (data comes from the city's fixed standard station data). The worse the air quality, the smaller the calibration radius.

[0046] In this embodiment, the calibration residual of the mobile vehicle with the fixed reference point is less than 5% for three consecutive times, which means that the mobile vehicle completes three calibrations at different times or on different days, and the calibration residual of each time is less than 5%. In this embodiment, the mobile vehicle calibration process collects at least 30 sets of data to eliminate instantaneous fluctuations.

[0047] In this embodiment, the mobile device is connected to the vehicle battery via the cigarette lighter to achieve power supply. When the vehicle stops and turns off during calibration, the monitoring device can be temporarily powered by the charge and discharge management module of the backup battery in the mobile device.

[0048] Specifically, a taxi carrying a mobile atmospheric monitoring device charges at a charging station equipped with a fixed reference point. When the taxi enters a 200m radius of the fixed reference point and the vehicle speed is ≤5km / h, the calibration process begins. When the vehicle is turned off, the battery in the mobile device starts to supply power. The data upload frequency of the mobile monitoring device is 3s, and the entire calibration takes more than 1.5 minutes, that is, 30 sets of data or more are taken for comparison. The calibration of the mobile vehicle and the fixed reference point is completed to generate the first calibration residual. The mobile vehicle completes two calibrations with other fixed reference points at different time periods or on different dates. The calibration residuals of the three calibrations are all less than 5%. At this time, the mobile vehicle is marked as a mobile reference point.

[0049] When a mobile reference point detects a moving vehicle in a traffic jam or at a red light, it communicates with the mobile reference point through the communication network and initiates data calibration. At this time, if there is a fixed reference point within a 200m radius, the data from the fixed reference point will also be uploaded for calibration.

[0050] Based on the calibration data uploaded simultaneously from fixed reference points, mobile reference points, and a moving vehicle, data pairs with environmental differences ≤ 10% are selected and calibration coefficients are calculated using a multi-source weighted calibration model. The calibration coefficients are not directly written to the device at this time.

[0051] When the calibration residuals of ≥3 devices at the same location are less than 5%, a reliable calibration coefficient is generated and written into the device to complete the calibration.

[0052] In another embodiment, when a city fixed standard station indicates that there is local heavy pollution, the GPS electronic fence in the heavily polluted area is set to 50m to reduce the impact of local pollution on calibration.

[0053] Monitoring devices are installed on top of mobile vehicles (taxis, buses, etc.), while calibration stations are deployed at key urban nodes (such as charging stations, parking lots, and transportation hubs). Equipment at the calibration stations is regularly calibrated against national standard stations, with comparative monitoring conducted as close to national control stations as possible. The calibration station equipment is located at the same height as the vehicle roof and contains the same sensors as the onboard equipment. It also integrates environmental parameter compensation modules (temperature, humidity, and air pressure) to ensure data baseline reliability. A dual-mode trigger calibration mechanism is employed. Active trigger mode: When a vehicle enters the calibration station's preset range (GPS fence) and its speed is ≤5 km / h, the calibration process automatically initiates. The entire calibration process takes ≥n minutes. When the vehicle is stopped and the engine is turned off, the backup battery's charge and discharge management module provides a temporary power supply to the monitoring equipment. If the vehicle exits the standard station within n minutes, the calibration is invalidated. Passive trigger mode: To address the issue of localized contamination at a single calibration station, which can cause significant data deviation, this invention proposes an alternative calibration method. This method utilizes vehicle congestion or red light wait times (≥n minutes) to communicate with other monitoring vehicles or nearby calibration stations (within the GPS fence) for real-time data exchange. A multi-source data fusion algorithm extracts atmospheric monitoring data and environmental parameter data from calibration stations and onboard devices simultaneously and spatially. Only data pairs with environmental differences of ≤10% are selected. A dynamic weight compensation formula, based on environmental factors, automatically flags a device as faulty if the calibration residual exceeds a threshold (e.g., ±15%) for three consecutive times. Abnormal data is removed, and a self-check process is initiated. Data cross-validation ensures that all calibration data is uploaded to the blockchain in real time for verification. Calibration results are verified through a multi-node consensus mechanism. A trusted calibration coefficient is generated when the deviation between the calibration station data and the data of five or more devices at the same location is less than 5%. If a single device consistently deviates from the group data, a real-time alarm is triggered and data upload is suspended.

[0054] From the above description, it can be seen that the above embodiments of the present invention achieve the following technical effects: By establishing a dual calibration mechanism of fixed reference point calibration and mobile reference point calibration, the time and space limitations of traditional calibration methods are broken through, a multi-directional interactive calibration chain network is formed, and calibration efficiency is improved.

[0055] Dynamic management of the marked mobile benchmarks throughout their life cycle. Immediately revoke the mobile benchmark qualification when it does not meet the requirements, thus improving calibration credibility. The multi-source data fusion dynamic calibration algorithm performs environmental parameter compensation and spatial distance weight distribution, avoiding simple coefficient correction and improving calibration accuracy.

[0056] Utilizing existing facilities such as power stations, parking lots, and transportation hubs reduces deployment costs and achieves high coverage at low cost. Calibration is performed during traffic congestion to reduce energy consumption.

[0057] Different from the bottom sampling of traditional devices, the design of the lower shell 2 can realize sampling in all directions, avoiding the influence of dust accumulation on the roof.

[0058] The design of the heating and dehumidification module 13 at the air inlet and the design of the groove through-hole at the bottom of the lower shell 2 can effectively eliminate the problem of water vapor condensation during the monitoring process.

[0059] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. An atmospheric cruise mobile monitoring device, characterized in that: It includes an upper shell and a lower shell. The lower shell is an inverted frustum structure. Several sampling holes are provided on the circumferential side of the lower shell. A water collecting trough and a drainage hole are provided at the lower end of the lower shell. A sampling port and a vent are provided on the lower shell. The sampling port is connected to the gas sensor through a sampling tube. The gas sensor is connected to the fan. A heating and dehumidification module is provided at the lower end of the sampling port. The lower shell is also provided with a power supply module, a positioning module, a communication module and a main control module.

2. The atmospheric cruise mobile monitoring device according to claim 1, characterized in that: The upper shell cover is arranged on the lower shell, the upper shell is provided with an anti-flocculation net, and the lower shell is also provided with a mounting base, and the mounting base is installed on the mobile body. The main control module, communication module, positioning module, heating and dehumidification module, fan and gas sensor are respectively connected to the power supply module, and the communication module, positioning module, heating and dehumidification module, fan and gas sensor are respectively connected to the main control module.

3. A dynamic calibration method for an atmospheric navigation mobile monitoring device, based on the atmospheric navigation mobile monitoring device according to any one of claims 1-2, characterized in that: include: Step 1: Select a fixed reference point; Step 2: Mark the moving benchmark. The moving benchmark is valid for 24 hours. If the conditions are not met, the qualification will be revoked immediately. Step 3: Dynamically expand the mobile reference points to form a calibration chain network; Step 4: Based on the calibration data uploaded to the cloud platform, a multi-source weighted calibration model is constructed to generate calibration coefficients; Step 5: Group consensus verification: When the calibration residuals of ≥3 devices at the same location are less than 5%, a reliable calibration coefficient is generated and written into the device; Step 6: Repeat steps 2-5 to complete the calibration.

4. The dynamic calibration method of the atmospheric cruise mobile monitoring device according to claim 3, characterized in that: In step 1, key city nodes are selected as fixed reference points, and calibration is performed on the driving route of the mobile vehicle to reduce the calibration cost. The key city nodes include charging stations, parking lots and transportation hubs.

5. The dynamic calibration method of the atmospheric cruise mobile monitoring device according to claim 3, characterized in that: In step 2, when the mobile vehicle enters the fixed reference point and the preset GPS electronic fence and the vehicle speed is ≤5km / h, the calibration process is automatically started. If the calibration residual of the mobile vehicle with the fixed reference point is less than 5% for three consecutive times, the mobile vehicle is marked as the mobile reference point. The calibration residual is calculated as: in, is the monitoring value of the mobile vehicle at time t; is the monitoring value of the fixed reference point at time t; t is the time point in the calibration process; Among them, the mobile reference point is valid for 24 hours. If the single calibration residual is greater than 10%, the marking qualification will be revoked immediately. If the calibration residual exceeds the threshold of 5% for three consecutive times, the equipment failure will be automatically marked, and abnormal data will be eliminated and the self-test program will be started.

6. The dynamic calibration method of the atmospheric cruise mobile monitoring device according to claim 3, characterized in that: In step 3, the mobile reference point utilizes vehicle congestion or red light waiting time to communicate with adjacent mobile monitoring vehicles or fixed reference points to exchange real-time data and initiate calibration to form a chain network, wherein the fixed reference point presets the GPS electronic fence range.

7. The dynamic calibration method of the atmospheric cruise mobile monitoring device according to claim 3, characterized in that: In step 4, a multi-source weighted calibration model is constructed. Extract atmospheric monitoring data and environmental parameter data from fixed reference points, mobile reference points, and mobile monitoring equipment in the same space and time, and only select data pairs with environmental differences ≤ 10%; The dynamic weight compensation formula based on environmental factors is: in, This is the coefficient calibrated when the sensor leaves the factory; is the weight of environmental factors, such as temperature, humidity, wind speed, etc.; is the deviation of environmental parameters; is the spatial weight. The closer the distance, the greater the weight. When the distance exceeds the preset GPS electronic fence, is 0; is the monitoring value; If the calibration residual exceeds the threshold of 5% for three consecutive times, the device will be automatically marked as faulty, abnormal data will be eliminated, and the self-check program will be started.

8. The dynamic calibration method of the atmospheric cruise mobile monitoring device according to claim 3, characterized in that: In step 5, all monitoring equipment calibration data is uploaded to the cloud platform in real time, and the cloud platform verifies the calibration results through a multi-node consensus mechanism: when the calibration residuals of ≥3 devices at the same location are less than 5%, a reliable calibration coefficient is generated; when residual abnormalities occur, the system automatically triggers equipment abnormality self-inspection and mobile reference point qualification review.

9. The dynamic calibration method of the atmospheric cruise mobile monitoring device according to claim 3, characterized in that: In step 6, steps 1 to 5 are repeatedly performed to continuously calibrate the cruise mobile monitoring device, thereby completing a complete calibration process, wherein calibration can be divided into regular calibration and irregular calibration.

10. The dynamic calibration method of the atmospheric cruise mobile monitoring device according to claim 3, characterized in that: The vehicle body carrying the atmospheric mobile monitoring equipment is charged at a charging station with a fixed reference point. When the taxi enters the 200m radius of the fixed reference point and the speed is ≤5km / h, the calibration process starts. When the vehicle is turned off, the battery in the mobile device starts to supply power. The data upload frequency of the mobile monitoring device is 3s. The entire calibration takes more than 1.5 minutes, that is, 30 sets of data or more are taken for comparison. The first calibration residual is generated after the calibration of the mobile vehicle and the fixed reference point is completed. The mobile vehicle completes two calibrations with other fixed reference points at different time periods or different dates. The three calibration residuals are all less than 5%. At this time, the mobile vehicle is marked as Mobile reference point; when the mobile reference point is in a traffic jam or red light, it monitors the moving vehicle, realizes data exchange through the communication network, and starts data calibration. At this time, if there is a fixed reference point within a radius of 200m, the data of the fixed reference point will also be uploaded for calibration; based on the calibration data uploaded simultaneously by the fixed reference point, mobile reference point and moving vehicle, data pairs with environmental differences ≤10% are selected, and the calibration coefficient is calculated according to the multi-source weighted calibration model. At this time, the calibration coefficient is not directly written to the device; when the calibration residuals of ≥3 devices at the same location are <5%, a reliable calibration coefficient is generated and written to the device to complete the calibration.

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