Air sampling method for simulating various complex environments

Abstract

The invention discloses an air sampling method for simulating various complex environments, which comprises the following steps of: 1, selecting the position of a simulation acquisition chamber, and acquiring relevant information around the simulation acquisition chamber; 2, analyzing the acquired related information around the simulation acquisition room to obtain simulation acquisition room evaluation information; 3, when the evaluation information of the simulation acquisition chamber is that evaluation is passed, air sampling equipment testing in the simulation acquisition chamber is carried out; 4, performing simulated air sampling after the air sampling equipment passes the test; 5, in the simulation sampling process, simulation content needs to be analyzed, and simulation evaluation information is obtained; and 6, judging whether to export the air sampling information collected after environment simulation according to the specific content of the simulation evaluation information. According to the invention, various complex environments can be better simulated, and the accuracy of air sampling data after data simulation is ensured.

Description

Technical Field

[0001] The present invention relates to the field of sampling methods, and specifically to an air sampling method for simulating diverse and complex environments. Background Art

[0002] With the continuous improvement of people's attention to air quality in different environments, whether it is exploring gas circulation and pollutant migration and transformation in the ecosystem in the scientific research field, accurately controlling the air quality in factory workshops in the industrial scenario, or studying the impact of indoor and outdoor environments on human health in the public health field, there is an urgent need for air sampling technologies that can highly restore the real environmental characteristics. Traditional single-environment and fixed-point sampling can no longer meet the diverse research needs. For example, when studying the air pollution distribution under urban microclimate, different regions are affected by a variety of factors such as traffic flow, building layout, and green coverage, which prompts researchers to seek methods that can simulate complex environments and accurately sample.

[0003] Existing air sampling methods are difficult to simulate diverse and complex environments, lack rationality in the selection and layout of sampling points, resulting in sampling results that cannot accurately reflect the overall environmental conditions, and lack a systematic evaluation of the sampling environment, equipment, and sampling process, which has a certain impact on the use of air sampling methods. Therefore, an air sampling method for simulating diverse and complex environments is proposed. Summary of the Invention

[0004] In view of the deficiencies in the prior art, the present invention provides an air sampling method for simulating diverse and complex environments, including the following steps:

[0005] Step 1: Select the location of the simulated collection room and collect relevant information around the simulated collection room;

[0006] Step 2: Analyze the relevant information collected around the simulated collection room to obtain the evaluation information of the simulated collection room;

[0007] Step 3: When the evaluation information of the simulated collection room passes the evaluation, conduct a test on the air sampling equipment in the simulated collection room;

[0008] Step 4: Conduct simulated air sampling after the air sampling equipment passes the test;

[0009] Step 5: During the simulated sampling process, analyze the simulated content to obtain the simulated evaluation information;

[0010] Step 6: Determine whether to export the air sampling information collected after simulating the environment according to the specific content of the simulated evaluation information.

[0011] Furthermore, the specific process of collecting relevant information around the simulated collection room is as follows:

[0012] Extract the center point of the simulated acquisition chamber as the center point, and draw a circle with a preset length r as the radius;

[0013] The area within the circle is the simulated position monitoring area. By collecting the number of abnormal areas in the simulated position monitoring area, relevant information around the simulated acquisition chamber can be obtained.

[0014] Furthermore, the determination process of the abnormal area is as follows: Taking the center point as the reference point, construct a plane coordinate system. The plane coordinate system divides the simulated position monitoring area into four equal areas, which are marked as area A1, area A2, area A3, and area A4;

[0015] Monitor the air quality in area A1, area A2, area A3, and area A4;

[0016] When the air quality in any one of area A1, area A2, area A3, and area A4 exceeds the preset standard, mark this area as an abnormal area.

[0017] Furthermore, the specific process of the air quality in area A1 is as follows:

[0018] Taking the reference point as the starting point, set three groups of air sampling devices within a preset distance a1 from the starting point, and the intervals between the three groups of air sampling devices need to be greater than the preset value. Mark the three air qualities collected by the three groups of air sampling devices as k1, k2, and k3;

[0019] Set two groups of air sampling devices between a distance a1 and a distance a2 from the starting point. The interval between the two groups of air sampling devices needs to be greater than the preset value. Mark the two air qualities collected by the two groups of air sampling devices as k4 and k5;

[0020] Set a group of air sampling devices outside a distance a2 from the starting point to the preset length r, and mark the air quality collected by the group of air sampling devices as k6;

[0021] Perform calculation processing on k1, k2, and k3, calculate the average value of k1, k2, and k3, and obtain the first air parameter kk1;

[0022] Perform calculation processing on k4 and k5, calculate the average value of k4 and k5, and obtain the second air parameter kk2;

[0023] Assign a correction coefficient b1 to the first air parameter kk1, assign a correction coefficient b2 to k6, and b1 > b2;

[0024] Through the formula (kk1 * b1 + kk2 + k6 * b2) / 3 = K 空, that is, the air quality of monitoring area A1 is obtained;

[0025] The processes of obtaining the air quality of area A2, area A3, and area A4 are the same as the process of obtaining the air quality of area A1.

[0026] Furthermore, the specific process of obtaining the evaluation information of the simulation collection chamber is as follows: extract the number of abnormal areas from the relevant information around the simulation collection chamber. When the number of abnormal areas is greater than or equal to 2, generate the evaluation information of the simulation collection chamber. At this time, the evaluation information of the simulation collection chamber is that the evaluation of the simulation collection chamber fails;

[0027] When the number of abnormal areas is less than 2, generate the evaluation information of the simulation collection chamber. At this time, the evaluation information of the simulation collection chamber is that the evaluation of the simulation collection chamber passes.

[0028] Furthermore, the specific process of testing the air sampling equipment in the simulation collection chamber is as follows:

[0029] An air sampling robot is set in the simulation collection chamber, and air sampling equipment at different heights is set on the air sampling robot;

[0030] First, adjust the air state in the simulation chamber to the test state, then send a control command to the air sampling robot to control the operation of the air sampling robot for air sampling, and monitor the operation information of the air sampling robot in real time. After reaching the collection duration, extract the real-time air quality collected by the air sampling equipment on the air sampling robot;

[0031] First, analyze the operation information of the air sampling robot. When the operation information of the air sampling robot is normal, then analyze the real-time air quality. When the deviation of the real-time air quality from the test state is within the preset range, it means that the air sampling equipment passes the test;

[0032] At the same time, an abnormal determination of the air sampling robot is also carried out;

[0033] When any one of the operation information of the air sampling robot is abnormal or the air sampling robot is determined to be abnormal occurs, it is directly determined that the air sampling equipment fails the test.

[0034] Furthermore, the abnormal judgment process of the operation information of the air sampling robot is as follows:

[0035] Extract the operation information of the air sampling robot. The operation information of the air sampling robot includes robot position information, air collection equipment lifting information, and robot operation status information;

[0036] Continuously collect the position information of the robot, process the robot position information, and obtain the real-time collection route. When the similarity deviation between the real-time collection route and the fixed route is greater than the preset value, it indicates that there is an abnormality in the operation information of the air sampling robot;

[0037] After dividing the collection chamber into a grid, the collection chamber grid is obtained, that is, the collection chamber is divided into 1m×1m grids, and then the robot position information is marked in the grid;

[0038] Record the number of times staying in a single grid for more than the preset duration during the air sampling process, marked as Y1;

[0039] Then record the number of times the robot appears in any two adjacent grids during the air sampling process, marked as Y2;

[0040] When Y1 is greater than the preset value or Y2 is greater than the preset value, it indicates that there is an abnormality in the operation information of the air sampling robot;

[0041] For the lifting information of the air collection device, the lifting information of the air collection device includes the time point when the air collection sampling device reaches the preset height and the lifting trajectory;

[0042] Process the time point when the air collection sampling device reaches the preset height, obtain the rising speed, calculate the absolute value of the difference between the rising speed and the standard threshold, and obtain the first parameter;

[0043] Process the lifting trajectory, measure the angle between the lifting trajectory and the vertical line, and obtain the second parameter;

[0044] When the first parameter is greater than the preset value or the second parameter is greater than the preset angle, it indicates that there is an abnormality in the operation information of the air sampling robot.

[0045] Continuously monitor the position of the air sampling robot. The collection chamber grid includes grids with different air qualities, including low-quality grids, medium-quality grids, and high-quality grids;

[0046] When the position of the air sampling robot moves from a low-quality grid to a medium-quality grid, a first determination is made. Extract the air quality d1 collected by the air sampling device on the air sampling robot in the low-quality grid and the air quality d2 collected in the medium-quality grid. When the deviation value between d2 and d1 is less than the deviation value between the air quality of the low-quality grid and the air quality of the medium-quality grid, it is determined that the air sampling robot is abnormal;

[0047] When the position of the air sampling robot moves from a medium-quality grid to a high-quality grid, a second determination is made. The second determination process is the same as the first determination process;

[0048] When the position of the air sampling robot moves from a low-quality grid to a high-quality grid, it is directly determined that the air sampling robot is abnormal;

[0049] When the air sampling robot stays in a high-quality grid without having been in a low-quality grid or a medium-quality grid, and the duration during which the air quality sampled by the air sampling device of the air sampling robot is lower than the air quality corresponding to the high-quality grid exceeds a preset duration, it is determined that the air sampling robot is abnormal;

[0050] At the same time, analyze the driving path of the air sampling robot, extract the number of times of driving from a low-quality grid to a medium-quality grid in the driving path to obtain the abnormal driving times. When the abnormal driving times are greater than a preset value, it is determined that the air sampling robot is abnormal.

[0051] Furthermore, the specific process of simulating air sampling after the air sampling device passes the test is as follows:

[0052] The user fills in the environmental type to be simulated in a preset interface to obtain the environmental type required by the user;

[0053] After that, import the environmental type required by the user into the database, retrieve the environmental content corresponding to the environmental type from the database, feedback the environmental content to the user. After the user selects the corresponding environmental content, the simulation collection room adjusts the indoor air to a standard air environment matching the environmental content.

[0054] Furthermore, the specific process of simulating evaluation information is as follows:

[0055] After adjusting the simulation collection room to a standard air environment matching the environmental content, the air sampling device in the simulation collection room starts to sample the air quality in the simulation collection room to obtain real-time air sampling information, and mark the air sampling information as Ui, where i is the number of air sampling devices;

[0056] After that, select at least m as analysis samples from the air sampling information marked as Ui according to a preset selection rule;

[0057] Compare the m analysis samples with the standard air environment, extract the number of analysis samples with a deviation from the standard air environment greater than a preset range, that is, the number of abnormalities. When the number of abnormalities is greater than m / 3, generate simulation evaluation information, and the simulation evaluation information is simulation evaluation abnormality;

[0058] When the number of abnormalities is less than or equal to m / 3, generate simulation evaluation information, and the simulation evaluation information is simulation evaluation normal;

[0059] Both m and i are positive integers, and m is proportional to i.

[0060] Furthermore, the content of the preset selection rule is to extract the positions of the air sampling devices corresponding to all air sampling information, select m air sampling devices from them, and pair up the selected sampling devices two by two. The distance between each pair shall not be less than the preset distance e1, and the distance between the sampling devices in the same pair shall not be greater than the preset distance e2, where e2 < e1.

[0061] The beneficial effects of the present invention are reflected in:

[0062] By determining the location of the simulated collection room and carefully collecting and analyzing the surrounding information, the adverse effects of external interference factors on simulated sampling are excluded to the greatest extent. Based on the comprehensive judgment of air quality at multiple points, the one-sidedness of a single monitoring point is avoided, making the assessment of the surrounding environmental quality more scientific and accurate, ensuring the rationality of the location selection of the simulated collection room, and reducing the impact of external interference factors on the subsequent sampling accuracy from the source.

[0063] Air sampling devices are set at multiple positions and multiple heights in the simulated collection room, and a three-dimensional coordinate system is established to track the position changes of the devices, which can comprehensively monitor the air conditions at different spatial levels, and at the same time ensure the stability of the devices in the simulated environment, preventing sampling deviation caused by device displacement.

[0064] By comparing the information collected by the device with the real air quality, the strict deviation limit requirements prompt the device accuracy to meet the standard, ensuring that the data obtained by the sampling device can truthfully reflect the air conditions in the simulated environment. Allowing users to fill in the simulated environment type as needed and relying on the database to retrieve and match the content meet the diverse scientific research and testing needs. Whether it is to simulate an industrial pollution area, a forest oxygen bar or a specific laboratory environment, etc., accurate simulation can be achieved.

[0065] After the user independently selects the environmental content, the air in the simulated collection room is adjusted to meet the target environmental standards, making the collected air samples highly targeted, providing convenient conditions for studying the air composition, pollutant concentration, etc. in different environments, and expanding the application scenarios of this method.

[0066] In the evaluation link during the simulated sampling process, the analysis samples are determined according to the preset selection rule, fully considering the rationality of the spatial distribution of the samples, avoiding deviation caused by concentrated selection, and ensuring the representativeness of the analysis samples.

[0067] By comparing with the standard air environment and determining the simulated evaluation results based on the number of anomalies, problems in the sampling process can be discovered in a timely manner. Only when the evaluation is normal can the sampling information be exported, effectively filtering out the sampling data that may have errors or do not meet the requirements, improving the quality and credibility of the final collected data, and providing a reliable basis for subsequent research, decision-making, etc. based on these data. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the specific embodiments or the prior art. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0069] Figure 1 is the overall flowchart of the present invention. Specific embodiments

[0070] The following will describe in detail the embodiments of the technical solutions of the present invention in conjunction with the drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention, so they are only examples and cannot be used to limit the protection scope of the present invention.

[0071] It should be noted that unless otherwise specified, the technical terms or scientific terms used in this application should have the ordinary meaning understood by those skilled in the art to which the present invention belongs.

[0072] As Figure 1 shown, an air sampling method for simulating diverse and complex environments includes the following steps:

[0073] Step 1: Select the location of the simulated collection chamber and collect relevant information around the simulated collection chamber;

[0074] Step 2: Analyze the relevant information collected around the simulated collection chamber to obtain the evaluation information of the simulated collection chamber;

[0075] Step 3: When the evaluation information of the simulated collection chamber passes the evaluation, conduct a test on the air sampling equipment in the simulated collection chamber;

[0076] Step 4: Conduct simulated air sampling after the air sampling equipment passes the test;

[0077] Step 5: During the simulated sampling process, it is necessary to analyze the simulated content to obtain the simulated evaluation information;

[0078] Step 6: Determine whether to export the air sampling information collected after the simulated environment according to the specific content of the simulated evaluation information;

[0079] When the simulated evaluation information is normal, the air sampling information will be exported;

[0080] When the simulated evaluation information is abnormal, the environment will be simulated again and air sampling will be conducted.

[0081] The specific process of collecting the relevant information around the simulated collection chamber is as follows:

[0082] Extract the center point of the simulated acquisition room as the center point, and draw a circle with a preset length r as the radius;

[0083] The area within the circle is the simulated position monitoring area. By collecting the number of abnormal areas in the simulated position monitoring area, relevant information around the simulated acquisition room can be obtained;

[0084] Based on the relevant information around the simulated acquisition room, the surrounding environmental state of the simulated acquisition room can be understood. Then, considering the environmental conditions, it can be determined whether to select the simulated acquisition room at this location as the final selected one. A simulated acquisition room with a better surrounding environment is least affected by external environmental factors when diverse and complex environments need to be simulated subsequently.

[0085] The determination process of the abnormal area is as follows: Taking the center point as the reference point, a plane coordinate system is constructed. The plane coordinate system divides the simulated position monitoring area into four equal regions, which are marked as Area A1, Area A2, Area A3, and Area A4;

[0086] Monitor the air quality in Area A1, the air quality in Area A2, the air quality in Area A3, and the air quality in Area A4;

[0087] When the air quality in any one of the air qualities in Area A1, the air quality in Area A2, the air quality in Area A3, and the air quality in Area A4 exceeds the preset standard, mark this area as an abnormal area.

[0088] The specific process of the air quality in Area A1 is as follows:

[0089] Taking the reference point as the starting point, set three groups of air sampling devices within a preset distance a1 from the starting point. The intervals between the three groups of air sampling devices need to be greater than the preset value. Mark the three air qualities collected by the three groups of air sampling devices as k1, k2, and k3;

[0090] Set two groups of air sampling devices between a distance a1 and a distance a2 from the starting point. The interval between the two groups of air sampling devices needs to be greater than the preset value. Mark the two air qualities collected by the two groups of air sampling devices as k4 and k5;

[0091] Set a group of air sampling devices outside a distance a2 from the starting point to the preset length r. Mark the air quality collected by the group of air sampling devices as k6;

[0092] Perform calculation processing on k1, k2, and k3, calculate the average value of k1, k2, and k3, and obtain the first air parameter kk1;

[0093] Perform calculation processing on k4 and k5, calculate the average value of k4 and k5, and obtain the second air parameter kk2;

[0094] Assign a correction factor b1 to the first air parameter kk1 and a correction factor b2 to k6, where b1 > b2;

[0095] Since the area corresponding to the first air parameter is closest to the position of the simulation collection chamber and has a greater impact on it, b1 > b2. Generally, b1 is taken as 1.1 and b2 is taken as 0.9;

[0096] Through the formula (kk1 * b1 + kk2 + k6 * b2) / 3 = K 空 , that is, the air quality of monitoring area A1 is obtained;

[0097] The process of obtaining the air quality of area A2, area A3, and area A4 is the same as the process of obtaining the air quality of area A1;

[0098] The simulated position monitoring area is equally divided into four areas (A1, A2, A3, A4) for separate monitoring, ensuring full coverage of the entire simulated position monitoring area, avoiding omission of some areas due to unreasonable division of the monitoring area, thus comprehensively grasping the air quality status around the simulation collection chamber, and further being able to more accurately determine whether the simulation collection chamber at this position is suitable for selection.

[0099] The specific process of obtaining the simulated collection chamber evaluation information is as follows: Extract the number of abnormal areas from the relevant information around the simulation collection chamber. When the number of abnormal areas is greater than or equal to 2, generate the simulated collection chamber evaluation information. At this time, the simulated collection chamber evaluation information is that the simulation collection chamber evaluation fails;

[0100] When the number of abnormal areas is less than 2, generate the simulated collection chamber evaluation information. At this time, the simulated collection chamber evaluation information is that the simulation collection chamber evaluation passes;

[0101] When the number of abnormal areas is too large, it means that the air environment state of the entire simulated position monitoring area is poor, that is, this position is not suitable for selection.

[0102] The specific process of testing the air sampling equipment in the simulated collection chamber is as follows:

[0103] An air sampling robot is set in the simulated collection chamber, and air sampling equipment at different heights is set on the air sampling robot;

[0104] First, adjust the air state in the simulation chamber to the test state, then send a control command to the air sampling robot to control the operation of the air sampling robot for air sampling, and monitor the operation information of the air sampling robot in real time. After reaching the collection duration, extract the real-time air quality collected by the air sampling equipment on the air sampling robot;

[0105] First, analyze the operation information of the air sampling robot. When the operation information of the air sampling robot is normal, then analyze the real-time air quality. When the deviation between the real-time air quality and the test state is within the preset range, it means that the air sampling device passes the test;

[0106] At the same time, the abnormality determination of the air sampling robot is also carried out;

[0107] When any one of the following occurs: the operation information of the air sampling robot is abnormal or the air sampling robot is determined to be abnormal, it is directly determined that the air sampling device fails the test.

[0108] By setting an air sampling robot in the simulated collection room and setting air sampling devices at different heights on the robot, air samples can be obtained from multiple height levels, so as to more comprehensively reflect the air quality status in the simulated collection room, avoid the one-sidedness of the sampling results caused by a single sampling height, and make the sampling results more accurately represent the air situation in the entire simulated collection room.

[0109] First, adjust the air state in the simulation room to the test state, and then control the air sampling robot to run for air sampling. By real-time monitoring the operation information of the air sampling robot and analyzing the deviation between the real-time air quality it collects and the test state, the performance of the air sampling device can be comprehensively and effectively tested to ensure that it can operate reliably in the subsequent formal sampling process, thereby ensuring the quality and credibility of the collected air sampling information.

[0110] By detailed monitoring and analysis of the operation information of the air sampling robot, abnormal situations that may occur during the operation of the device before sampling can be detected in time, such as the deviation of the robot's position, the abnormal lifting of the air collection device, etc., so as to make adjustments and repairs in advance, avoid sampling failure or inaccurate sampling data caused by equipment failures, and improve the efficiency and success rate of the sampling work;

[0111] By the air sampling robot carrying air sampling devices at multiple heights, synchronous testing of different height layers is realized. Combining the analysis of operation information and the verification of real-time air data, a dual testing standard is formed, and the test state is consistent with the actual sampling state, ensuring the effectiveness of the test results.

[0112] The process of abnormal judgment of the operation information of the air sampling robot is as follows:

[0113] Extract the operation information of the air sampling robot. The operation information of the air sampling robot includes the robot position information, the air collection device lifting information, and the robot operation state information;

[0114] Continuously collect the position information of the robot, process the robot position information, and obtain the real-time collection route. When the similarity deviation between the real-time collection route and the fixed route is greater than the preset value, it indicates that there is an abnormality in the operation information of the air sampling robot;

[0115] After dividing the collection chamber into a grid, the collection chamber grid is obtained, that is, the collection chamber is divided into 1m×1m grids, and then the robot position information is marked in the grid;

[0116] Record the number of times staying in a single grid for more than the preset duration during the air sampling process, and mark it as Y1;

[0117] Then record the number of times the robot appears in any two adjacent grids during the air sampling process, and mark it as Y2;

[0118] When Y1 is greater than the preset value or Y2 is greater than the preset value, it indicates that there is an abnormality in the operation information of the air sampling robot;

[0119] For the lifting information of the air collection device, the lifting information of the air collection device includes the time point when the air collection sampling device reaches the preset height and the lifting trajectory;

[0120] Process the time point when the air collection sampling device reaches the preset height, obtain the rising speed, calculate the absolute value of the difference between the rising speed and the standard threshold, and obtain the first parameter;

[0121] Process the lifting trajectory, measure the angle between the lifting trajectory and the vertical line, and obtain the second parameter;

[0122] When the first parameter is greater than the preset value or the second parameter is greater than the preset angle, it indicates that there is an abnormality in the operation information of the air sampling robot.

[0123] Continuously monitor the position of the air sampling robot. The collection chamber grid includes grids with different air qualities, including low-quality grids, medium-quality grids, and high-quality grids;

[0124] When the position of the air sampling robot moves from a low-quality grid to a medium-quality grid, perform the first determination. Extract the air quality d1 collected by the air sampling device on the air sampling robot in the low-quality grid and the air quality d2 collected in the medium-quality grid. When the deviation value between d2 and d1 is less than the deviation value between the air quality of the low-quality grid and the air quality of the medium-quality grid, it is determined that the air sampling robot is abnormal;

[0125] When the position of the air sampling robot moves from a medium-quality grid to a high-quality grid, perform the second determination. The second determination process is the same as the first determination process;

[0126] When the position of the air sampling robot moves from a low-quality grid to a high-quality grid, it is directly determined that the air sampling robot is abnormal;

[0127] When the air sampling robot stays in a high-quality grid without having been in a low-quality grid or a medium-quality grid, and the duration during which the air quality sampled by the air sampling device of the air sampling robot is lower than the air quality corresponding to the high-quality grid exceeds the preset duration, it is determined that the air sampling robot is abnormal;

[0128] At the same time, analyze the driving path of the air sampling robot, extract the number of times of driving from a low-quality grid to a medium-quality grid in the driving path, obtain the abnormal driving times, and when the abnormal driving times are greater than the preset value, it is determined that the air sampling robot is abnormal;

[0129] By conducting multi-dimensional analysis on the operation information of the air sampling robot, including robot position information, air collection device lifting information, and robot operation status information, etc., it is possible to accurately locate the abnormal situations and their specific positions that occur during the operation of the robot. For example, by monitoring the robot position information to obtain the real-time collection route and comparing it with the fixed route for similarity, it can be clearly determined whether the robot is operating according to the predetermined trajectory; after gridifying the collection room to obtain the collection room grid, recording the residence time of the robot in the grid and the number of times it appears in adjacent grids can further refine the positioning of abnormal situations and provide a more accurate basis for subsequent fault troubleshooting and repair.

[0130] Conduct a detailed analysis on the lifting information of the air collection device, including the time point of reaching the preset height, the lifting speed, and the lifting trajectory, etc. By setting strict parameter thresholds, accurately evaluate the lifting performance of the device to ensure that the air sampling device can sample at the accurate height and time, thereby ensuring the accuracy and consistency of the sampling data and providing a high-quality data basis for subsequent air quality analysis.

[0131] Through the comprehensive monitoring and abnormal judgment of the operation information, it is possible to timely discover and solve the problems that may occur during the sampling process, reduce the sampling interruption or repeated sampling caused by equipment failures or abnormal operations, etc., thereby improving the work efficiency of the entire air sampling and ensuring that the sampling work can be carried out smoothly and efficiently;

[0132] The fixed route similarity analysis ensures the standardization of the sampling path, the grid residence time control avoids repeated sampling, the double constraints of the speed threshold and the angle deviation ensure the vertical lifting of the sampling device, the vertical line angle monitoring prevents sampling errors caused by the tilting of the device, and the analysis of the frequency of appearance in adjacent grids detects abnormal movements of the robot. The multi-dimensional abnormal judgment (position, movement, state) improves the accuracy of fault identification;

[0133] It ensures the comprehensiveness, accuracy, and efficiency of the air sampling equipment test. Through an automated test process and intelligent anomaly detection, it ensures the reliability of subsequent simulated sampling data, providing a solid technical foundation for air sampling in complex environments;

[0134] When the air sampling robot moves from a low-quality grid to a high-quality grid, it may adsorb air impurities in the low-quality grid, which will affect the air quality of the subsequent high-quality grid collected. Therefore, it is necessary to promptly determine that the robot is abnormal, clean the robot, and then drive it into the high-quality grid, thereby ensuring the accuracy of air sampling;

[0135] The settings in the first determination process and the second determination process are also to find out whether the robot will affect the final sampling result.

[0136] The specific process of simulated air sampling after the air sampling equipment test passes is as follows:

[0137] The user fills in the environmental type to be simulated in the preset interface to obtain the environmental type required by the user;

[0138] After that, the environmental type required by the user is imported into the database, the environmental content corresponding to the environmental type is retrieved from the database, and the environmental content is fed back to the user. After the user selects the corresponding environmental content, the simulated collection room adjusts the indoor air to a standard air environment matching the environmental content.

[0139] The specific process of simulated evaluation information is as follows:

[0140] After the simulated collection room is adjusted to a standard air environment matching the environmental content, the air sampling equipment in the simulated collection room starts to sample the air quality in the simulated collection room, obtains real-time air sampling information, and marks the air sampling information as Ui, where i is the number of air sampling equipment;

[0141] After that, at least m are selected as analysis samples from the air sampling information marked as Ui according to the preset selection rules;

[0142] The m analysis samples are compared with the standard air environment, and the number of analysis samples with a deviation from the standard air environment greater than the preset range is extracted, that is, the number of anomalies. When the number of anomalies is greater than m / 3, simulated evaluation information is generated, and the simulated evaluation information is a simulated evaluation anomaly;

[0143] When the number of anomalies is less than or equal to m / 3, simulated evaluation information is generated, and the simulated evaluation information is a simulated evaluation normal;

[0144] Both m and i are positive integers, and m is proportional to i;

[0145] At least m analysis samples are selected from a large number of air sampling information (Ui) according to the preset selection rules. The rules take into account the representativeness of the samples and avoid the one-sidedness that may be caused by random sampling. For example, when simulating the air environment in a large industrial plant, the air quality in different areas of the plant may vary greatly due to equipment layout and ventilation conditions. Through reasonable selection rules, it is ensured that the selected samples cover sampling information at key locations such as pollution sources, ventilation outlets, and personnel operation areas, so that subsequent analysis can truly reflect the overall situation.

[0146] It is stipulated that m is proportional to i, that is, as the number of sampling devices increases, the number of selected analytical samples also increases accordingly, which ensures that the analytical samples can still maintain sufficient representativeness in large-scale sampling scenarios. For example, in a simulated environment of an ultra-large indoor gymnasium, a large number of air sampling devices are arranged. At this time, the increased analytical samples can more accurately capture the complex and changing air conditions in the gymnasium, preventing the missing of some potential air quality problems due to insufficient sample size.

[0147] The selected m analysis samples are carefully compared with the standard air environment. This comparison method can directly find the degree of difference between the simulated environment and the target environment. Taking the simulated sterile environment of the hospital operating room as an example, the standard air environment requires extremely low microbial content, specific temperature and humidity, and airflow stability. By comparing and analyzing the deviations of key indicators such as the number of microorganisms, temperature and humidity values ​​in the samples with the standard values, it can be accurately judged whether the simulated operating room environment meets the standards.

[0148] The simulation evaluation results are determined based on the number of deviations greater than the preset range (abnormal number), and the abnormal number threshold (m / 3) is set scientifically and reasonably. If the threshold is exceeded, it is judged as a simulation evaluation abnormality, which provides a quantitative standard for quickly identifying simulation failures and avoids the arbitrariness of human subjective judgment. For example, when simulating the clean environment of a food processing workshop, once the number of abnormalities exceeds m / 3, it means that there may be many local areas in the workshop where the air quality does not meet the food processing safety standards, and it is necessary to promptly check the problem and adjust the simulation parameters.

[0149] Through the simulation evaluation information, the quality of the simulation environment is promptly fed back. When the simulation evaluation is abnormal, the air samples collected based on the wrong simulation environment can be avoided from being misused, ensuring that the air data used for subsequent research, testing, and other work is authentic and reliable. For example, in the ultra-clean environment of a simulated electronic chip manufacturing workshop, if the simulation evaluation is abnormal and the collected data is used directly for chip yield analysis without being noticed, it is likely to draw an erroneous conclusion. This evaluation process can effectively avoid such risks.

[0150] The content of the preset selection rule is to extract the positions of the air sampling devices corresponding to all air sampling information, select m air sampling devices from them, pair the selected sampling devices in pairs, and the distance between each pair shall not be less than the preset distance e1, and the distance between the sampling devices in the same pair shall not be greater than the preset value distance e2, where e2 < e1;

[0151] By selecting the information of air sampling devices at different positions as analysis samples, and requiring a certain distance limit between each group of sampling devices, it avoids selecting overly concentrated samples, can cover the air quality in different areas of the simulated collection room, and thus can more comprehensively and accurately reflect the overall air condition in the simulated collection room, making the analysis samples more representative.

[0152] Since the selected samples come from different positions, it reduces the influence of deviations caused by local environmental factors on the evaluation results. For example, if only samples from a local area are selected, the evaluation results may be inaccurate due to special circumstances in that area, such as being close to a ventilation opening or a pollution source. Selecting samples according to this rule can effectively avoid this situation, thereby improving the accuracy and reliability of the simulated evaluation information.

[0153] The regulation of the distance between sampling devices in the rule makes the selected samples more reasonably distributed in space and reduces the correlation between samples. In this way, when comparing the analysis samples with the standard air environment, each sample can relatively independently reflect the air condition. Even if individual samples are abnormal, it will not have too much interference on the overall evaluation results due to overly concentrated or correlated samples, thus enhancing the reliability of the simulated evaluation results.

[0154] This method solves the following existing technical problems:

[0155] Existing sampling methods may be difficult to simulate diverse and complex environments. This technical solution can better adapt to various complex environments and achieve simulated sampling of different target environments by first collecting and analyzing the information around the simulated collection room, retrieving environmental content from the database according to user needs, and regulating the air in the simulated collection room to the corresponding standard air environment.

[0156] The sampling point setting is not scientific: Traditional sampling methods may lack rationality in the selection and layout of sampling points, resulting in the sampling results not being able to accurately reflect the overall environmental conditions. In this solution, when air sampling devices are set in the simulated position monitoring area and the simulated collection room, there are clear rules and calculation methods. For example, sampling devices are set at specific distances and quantities in different areas, and the regional air quality is obtained by calculating the mean value and assigning a correction coefficient. In addition, sampling devices are set in the simulated collection room according to a three-dimensional coordinate system, and strict consideration is given to the position deviation of the sampling devices, making the sampling point setting more scientific and able to collect air quality more comprehensively and accurately.

[0157] Lack of systematic evaluation mechanism: Existing sampling methods may lack a systematic evaluation of the sampling environment, equipment, and sampling process. This technical solution covers multiple evaluation links such as the evaluation of the simulated collection room, the testing of air sampling equipment, and the simulated evaluation, which can timely detect whether the sampling environment is suitable, whether the equipment is working properly, and whether there are abnormalities in the simulated sampling process, thus ensuring the reliability and accuracy of the sampling results.

[0158] Simple processing of sampling information: For the collected air sampling information, traditional methods may only perform simple processing and cannot deeply explore the value of the information. This solution performs relatively complex and delicate processing on the air sampling information. For example, analysis samples are selected through preset selection rules, compared with the standard air environment, and simulated evaluation information is generated according to the deviation situation to determine whether to export the air sampling information, improving the processing and utilization level of the sampling information.

[0159] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered by the scope of the claims and the specification of the present invention.

Claims

1. An air sampling method for simulating a diverse and complex environment, characterized in that: The following steps are involved: Step 1: Select the location of the simulated collection room and collect relevant information around the simulated collection room; Step 2: Analyze the collected relevant information around the simulated collection room to obtain the simulated collection room evaluation information; Step 3: When the simulated collection room assessment information is passed, the air sampling equipment in the simulated collection room is tested; Step 4: After the air sampling equipment is tested, simulated air sampling is performed; Step 5: During the simulation sampling process, it is necessary to analyze the simulation content and obtain simulation evaluation information; Step 6: Determine whether to export the air sampling information collected after the simulation environment based on the specific content of the simulation evaluation information.

2. The air sampling method for simulating a diverse and complex environment according to claim 1, characterized in that: The specific process of collecting relevant information around the simulation collection room is as follows: The center point of the simulated collection room is extracted as the center point of the circle, and a circle is drawn with a preset length r as the radius; The area within the circle is the simulated position monitoring area. The number of abnormal areas in the simulated position monitoring area is collected, that is, the relevant information around the simulated collection room is obtained.

3. The air sampling method for simulating a diverse and complex environment according to claim 2, characterized in that: The determination process of the abnormal area is as follows: taking the center point of the circle as the reference point, constructing a plane coordinate system, the plane coordinate system divides the simulated position monitoring area into four areas, which are marked as area A1, area A2, area A3 and area A4; Monitor the air quality in area A1, area A2, area A3 and area A4; When the air quality of any one of the air quality in area A1, area A2, area A3 and area A4 exceeds the preset standard, the area is marked as an abnormal area.

4. The air sampling method for simulating a diverse and complex environment according to claim 3, characterized in that: The specific process of air quality in the A1 area is as follows: Taking the reference point as the starting point, three sets of air sampling devices are set within a preset distance a1 from the starting point, and the intervals between the three sets of air sampling devices must be greater than a preset value. The three air masses collected by the three sets of air sampling devices are marked as k1, k2 and k3; Two sets of air sampling devices are set between the distance a1 and the distance a2 from the starting point. The interval between the two sets of air sampling devices must be greater than the preset value. The two air masses collected by the two sets of air sampling devices are marked as k4 and k5. A group of air sampling devices is set outside the distance a2 from the starting point and within the preset length r, and the air quality collected by the group of air sampling devices is marked as k6; Calculate k1, k2 and k3 to obtain the average of k1, k2 and k3, and obtain the first air parameter kk1; Calculate k4 and k5 to obtain the average of k4 and k5, and obtain the second air parameter kk2; Assign a correction coefficient b1 to the first air parameter kk1, and a correction coefficient b2 to k6, where b1>b2; By the formula (kk1*b1+kk2+k6*b2) / 3=K 空 , that is, the air quality of monitoring area A1 is obtained; The process of obtaining the air quality in area A2, area A3 and area A4 is the same as the process of obtaining the air quality in area A1.

5. The air sampling method for simulating a diverse and complex environment according to claim 4, characterized in that: The specific process of obtaining the simulated collection room evaluation information is as follows: extracting the number of abnormal areas from the relevant information around the simulated collection room, and when the number of abnormal areas is greater than or equal to 2, generating simulated collection room evaluation information, at which time the simulated collection room evaluation information indicates that the simulated collection room evaluation fails; When the number of abnormal areas is less than 2, the simulated collection room evaluation information is generated. At this time, the simulated collection room evaluation information is that the simulated collection room evaluation is passed.

6. The air sampling method for simulating a diverse and complex environment according to claim 1, characterized in that: The specific process of testing the air sampling equipment in the simulated collection room is as follows: An air sampling robot is set up in the simulated collection room, and air sampling devices set at different heights are set up on the air sampling robot; First, adjust the air state in the simulation room to the test state, then send a control instruction to the air sampling robot to control the air sampling robot to run and perform air sampling, monitor the operation information of the air sampling robot in real time, and extract the real-time air quality collected by the air sampling device on the air sampling robot after the collection time is reached; First, analyze the operation information of the air sampling robot. When the operation information of the air sampling robot is normal, analyze the real-time air quality. When the deviation between the real-time air quality and the test status is within the preset range, it means that the air sampling equipment test has passed. At the same time, abnormality determination of the air sampling robot was also carried out; When any of the following occurs: when there is an abnormality in the operation information of the air sampling robot or when the air sampling robot is judged to be abnormal, it is directly judged that the air sampling device test has failed.

7. The air sampling method for simulating a diverse and complex environment according to claim 6, characterized in that: The abnormality judgment process of the operation information of the air sampling robot is as follows: Extracting the operation information of the air sampling robot, the operation information of the air sampling robot includes the robot position information, the lifting information of the air collection device and the robot operation status information; Continuously collect the robot's position information, process the robot's position information, and obtain the real-time collection route. When the similarity deviation between the real-time collection route and the fixed route is greater than the preset value, it means that there is an abnormality in the operation information of the air sampling robot; The collection room is gridded to obtain the collection room grid, that is, the collection room is divided into 1m×1m grids, and the robot position information is marked in the grids; Record the number of times the air stays in a single grid for more than the preset time during the air sampling process, marked as Y1; Then record the number of times the robot appears simultaneously in any adjacent grids during the air sampling process, marked as Y2; When Y1 is greater than the preset value or Y2 is greater than the preset value, it means that the operation information of the air sampling robot is abnormal; The lifting information of the air collection equipment includes the time point and lifting trajectory of the air collection sampling equipment reaching the preset height; The time point at which the air collection and sampling device reaches a preset height is processed to obtain the rising speed, and the absolute value of the difference between the rising speed and the standard threshold is calculated to obtain the first parameter; The lifting trajectory is processed, and the angle between the lifting trajectory and the vertical line is measured, so as to obtain the second parameter; When the first parameter is greater than the preset value or the second parameter is greater than the preset value angle, it means that the operation information of the air sampling robot is abnormal; The abnormality determination process of the air sampling robot also includes the following processes: The position of the air sampling robot is continuously monitored, and the collection room grid includes grids of different air qualities, including low-quality grids, medium-quality grids, and high-quality grids; When the low-quality grid moves toward the medium-quality grid at the position of the air sampling robot, a first judgment is performed to extract the air quality d1 collected by the air sampling device on the air sampling robot on the low-quality grid and the air quality d2 collected on the medium-quality grid. When the deviation value between d2 and d1 is less than the deviation value between the air quality of the low-quality grid and the air quality of the medium-quality grid, the air sampling robot is judged to be abnormal. When the position of the air sampling robot shows that the medium-quality grid moves toward the high-quality grid, a second determination is performed, and the second determination process is the same as the first determination process; When the low-quality grid at the position of the air sampling robot moves to the high-quality grid, it is directly determined that the air sampling robot is abnormal; When the position of the air sampling robot does not appear in the low-quality grid or the medium-quality grid but stays in the high-quality grid, and the air quality sampled by the air sampling device of the air sampling robot is lower than the air quality corresponding to the high-quality grid for a period of time exceeding the preset time, it is determined that the air sampling robot is abnormal; At the same time, the driving path of the air sampling robot is analyzed, the number of times the robot travels from low-quality grids to medium-quality grids in the driving path is extracted, and the number of abnormal driving times is obtained. When the number of abnormal driving times is greater than the preset value, it is determined that the air sampling robot is abnormal.

8. The air sampling method for simulating a diverse and complex environment according to claim 1, characterized in that: The specific process of performing simulated air sampling after the air sampling equipment passes the test is as follows: The user fills in the environment type to be simulated in the preset interface, and obtains the simulation environment type required by the user; The simulated environment type required by the user is then imported into the database, the environmental content of the corresponding environment type is retrieved from the database, and the environmental content is fed back to the user. After the user selects the corresponding environmental content, the simulation collection room will regulate the indoor air and adjust it to a standard air environment that matches the environmental content.

9. The air sampling method for simulating a diverse and complex environment according to claim 8, characterized in that: The specific process of simulating evaluation information is as follows: After the simulated collection room is adjusted to a standard air environment that matches the environmental content, the air sampling device in the simulated collection room begins to simulate the air quality in the collection room, obtains real-time air sampling information, and marks the air sampling information as Ui, where i is the number of air sampling devices; Then, at least m samples are selected as analysis samples from the air sampling information marked as Ui according to the preset selection rules; Compare m analysis samples with the standard air environment, extract the number of analysis samples with deviations from the standard air environment greater than a preset range, i.e., the number of anomalies. When the number of anomalies is greater than m / 3, generate simulation evaluation information, which is the simulation evaluation anomaly. When the number of abnormalities is less than or equal to m / 3, simulated evaluation information is generated, and the simulated evaluation information means that the simulated evaluation is normal; Both m and i are positive integers, and m is proportional to i.

10. The air sampling method for simulating a diverse and complex environment according to claim 9, characterized in that: The content of the preset selection rule is to extract the positions of the air sampling devices corresponding to all air sampling information, select m air sampling devices therefrom, and group the selected sampling devices in pairs. The spacing between each group shall not be less than the preset distance e1, and the spacing between the sampling devices in the same group shall not be greater than the preset value distance e2, e2<e1.

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