Optimization analysis method and system of air purification system

Abstract

The invention provides an optimization analysis method and system of an air purification system, and relates to the technical field of automation system optimization supported by information processing, effective grids are divided based on a map of a to-be-purified area and a single purification coverage area of a purification device, and to-be-cleaned coordinates of each effective grid are determined; pollutant concentration and air flow characteristics of the effective grids are collected, and danger levels are divided through weighted summation; to-be-purified grids with pollutant concentration exceeding a preset safety threshold value are screened, sorting is carried out according to danger levels, primary purification is carried out, and then monitoring intervals are set according to the levels to carry out dynamic monitoring; the purification operation is repeated until all the to-be-purified grids reach the standard, and then the pollutant residue trend of all the to-be-purified grids is analyzed; in the next purification process, the danger level of the effective grid is further weighted by combining the pollutant residual trend, the purification priority is optimized, and accurate distribution and efficient utilization of purification resources are achieved through dynamic monitoring and residual trend analysis.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of air purification logic, in particular to an optimization analysis method and system of an air purification system. BACKGROUND

[0002] At present, air purification devices or air purification systems are mostly based on preset path planning and timing purification strategies. Currently, household air purification devices are widely used in residential scenarios to monitor the pollutant concentration in different areas of the room and perform purification operations.

[0003] A common approach is to first establish a two-dimensional map of the area to be purified, divide the work units according to a certain grid method, and then move the purification device by grid to detect the pollutant concentration at the center of each grid or designated location. When the detection value exceeds the set threshold, the purification device will trigger the purification device to purify the area. This method has been able to achieve automatic air purification in indoor environments such as homes, offices, and schools, and has played a positive role in improving air quality and reducing manual intervention. However, the above method still has some deficiencies in risk assessment and purification strategy optimization. Firstly, most existing systems only rely on instantaneous sampling of pollutant concentration as the basis for judgment, which makes it difficult to reflect the influence of air flow conditions on pollutant diffusion, dilution, and redistribution, thus easily causing the problem of mismatch between purification order and actual risk. Secondly, even if the concentration of some areas is not outstanding in a single measurement, the concentration will quickly rise after purification due to air flow retention or intermittent release of pollution sources. The existing technology does not provide effective means to identify and handle such areas prone to repeated exceedance, resulting in some high-risk areas not being given enough attention, while some low-risk areas may be repeatedly purified, causing uneven resource allocation, increased energy consumption, and reduced purification efficiency. Therefore, it is urgent to introduce quantitative analysis of air flow characteristics and pollutant residual trends based on traditional pollutant concentration measurement to dynamically adjust the risk level of each grid.

[0004] The above information disclosed in the background section is only intended to strengthen the understanding of the background of the present disclosure, and therefore it can include information that does not constitute prior art known to those of ordinary skill in the art. SUMMARY

[0005] The purpose of the present application is to provide an optimization analysis method and system of an air purification system to solve the problems raised in the background.

[0006] To achieve the above purpose, the present application provides the following technical solutions: The optimization analysis method of the air purification system comprises the following specific steps: S1: Based on the completed modeling of the map of the area to be purified, set the grid size to grid the map, judge whether the grid is a valid grid according to the area of the grid and number the valid grid, and set the geometric center of each valid grid as the cleaning coordinate; S2: Based on the cleaning coordinates of all grids, traverse all valid grids, obtain the pollutant concentration and air flow characteristic data of each valid grid, and combine the air flow characteristic data of each valid grid with the pollutant concentration to construct a comprehensive risk assessment model and divide the risk level of the valid grid by using the weighted summation method; S3: Select the valid grid whose pollutant concentration exceeds the preset safety threshold and mark it as a grid to be purified, and sort the grids to be purified according to the risk level, and perform purification at the cleaning coordinate of each purification grid in order to complete the initial purification of the grid to be purified; S4: Set the monitoring interval according to the risk level of the grid to be purified to measure the pollutant concentration of the grid to be purified after the initial purification, repeat step S3 until the measured pollutant concentration of all grids to be purified is less than the preset safety threshold, complete the air purification of the area to be purified once, and extract the measured pollutant concentration of each grid to be purified during the purification, and analyze the pollutant residue trend of each grid to be purified; S5: When air purification is performed on the area to be purified next time, the comprehensive risk assessment model is reconstructed and further weighted according to the pollutant residue trend, and the risk level of the corresponding valid grid is optimized when air purification is performed on the area to be purified next time.

[0007] Further, when setting the grid size for grid division, taking the physical area covered by the purification device in a single purification operation as the basis, the edge length parameter of a single grid in the two-dimensional grid map is set so that the area of a single grid matches the coverage area of the purification device in a single purification operation. Then, the map is divided into grids according to the standard edge length, and the actual area of each grid is calculated. When the area of a single grid is 70% or more of the coverage area of the purification device in a single purification operation, the grid is directly marked as an independent valid grid. When the area of a single grid is less than 70% of the coverage area of the purification device in a single purification operation, the grid needs to be merged with adjacent grids that have common edge lengths. The grid formed after merging needs to meet the requirement that the total area is not less than 70% of the coverage area of the purification device in a single purification operation. Finally, the independent grids and the merged grids that meet the area requirement are uniformly marked as valid grids and numbered in order.

[0008] Further, the method of setting the geometric center of each valid grid as the cleaning coordinate is as follows: The geometric center point coordinate of each effective grid is set as an initial cleaning coordinate. If there is no obstacle at the initial cleaning coordinate, the geometric center point is directly taken as a final cleaning coordinate. If an obstacle is detected at the initial cleaning coordinate, the non-obstacle coordinate with the shortest Euclidean geometric distance in the range of the effective grid with the geometric center point as the origin is searched, and the screened non-obstacle coordinate is finally determined as a replacement cleaning coordinate.

[0009] Further, the air flow characteristic data is air flow residence time, and a specific method for calculating the air flow residence time is as follows: A traceable substance that can be accurately detected is released to each effective grid, and the concentration change of the traceable substance is monitored in real time. When the concentration of the traceable substance decreases from a peak value to 50% of an initial concentration, a time length corresponding to this time is recorded, and the time length is the air flow residence time of the effective grid.

[0010] Further, a method for constructing a comprehensive risk assessment model by using a weighted summation method to combine the air flow characteristic data of each effective grid with the pollutant concentration and dividing the danger levels of the effective grids is as follows: A method for constructing a comprehensive risk assessment model by using a weighted summation method to combine the air flow characteristic data of each effective grid with the pollutant concentration is as follows: The maximum air flow residence time of all effective grids is obtained, the ratio of the air flow residence time of each effective grid to the maximum value is calculated, and the normalized air flow residence time of the effective grid is obtained. The weight coefficient of the pollutant concentration and the weight coefficient of the normalized air flow residence time are set. The weight coefficient of the pollutant concentration is greater than the weight coefficient of the normalized air flow residence time. Both the weight coefficients are greater than 0 and the sum is 1. The pollutant concentration and the normalized air flow residence time of the effective grid are weighted by using the corresponding weight coefficients, and are summed. The summation result is marked as a comprehensive risk assessment value of the effective grid, and a comprehensive risk assessment model for calculating the comprehensive risk assessment value of the effective grid is obtained. A method for dividing the danger levels of the effective grids is as follows: The comprehensive risk assessment value of each effective grid is calculated based on the comprehensive risk assessment model. The preset danger levels are three levels of high, medium and low. A first comprehensive risk assessment value threshold and a second comprehensive risk assessment value threshold are set. The first comprehensive risk assessment value threshold is less than the second comprehensive risk assessment value threshold, and both the thresholds are greater than 0. When the comprehensive risk assessment value is not less than the second comprehensive risk assessment value threshold, the effective grid is marked as a high danger level. When the comprehensive risk assessment value is less than the second comprehensive risk assessment value threshold and not less than the first comprehensive risk assessment value threshold, the effective grid is marked as a medium danger level. When the comprehensive risk assessment value is less than the first comprehensive risk assessment value threshold, the effective grid is marked as a low danger level.

[0011] Further, the method for measuring the concentration of pollutants of the to-be-purified grid after the initial purification according to the monitoring interval set according to the risk level of the to-be-purified grid is: According to the high, medium and low three risk levels of the grid division, corresponding monitoring intervals are set, and the monitoring intervals are a high-risk level monitoring interval, a medium-risk level monitoring interval and a low-risk level monitoring interval, that is, the monitoring interval of the grid of the high-risk level corresponds to the high-risk level monitoring interval, the monitoring interval of the grid of the medium-risk level corresponds to the medium-risk level monitoring interval, and the monitoring interval of the grid of the low-risk level corresponds to the low-risk level monitoring interval. The high-risk level monitoring interval is smaller than the medium-risk level monitoring interval, and the medium-risk level monitoring interval is smaller than the low-risk level monitoring interval, and the time of the three is less than 1 hour. After the initial purification of the purification device is completed, the to-be-purified grid is matched with the corresponding monitoring interval according to the high, medium and low three risk levels, and then the concentration of pollutants of the to-be-purified grid is measured according to the set corresponding monitoring interval.

[0012] Further, the method for analyzing the pollutant residue trend of each to-be-purified grid is: Based on the concentration change data of the to-be-purified grid in the purification process, combined with the monitoring interval record, the pollutant residue trend of each grid is analyzed, and two scenarios are processed: For the to-be-purified grid purified multiple times, the total number of times that a grid is purified by the purification device is extracted, and for each two consecutive purification processes, the pollutant concentration rebound strength between the two purifications is calculated. The specific process is as follows: the interval time between the two purifications is extracted, the difference between the pollutant concentration measured before the later purification and the pollutant concentration after the previous purification is taken as the pollutant concentration change, and the ratio of the pollutant concentration change to the corresponding interval time is taken as the pollutant concentration rebound strength between the two purifications. The arithmetic mean of the concentration rebound strength between all two purifications is taken, and the average value is the pollutant residue trend of the grid. For the to-be-purified grid whose pollutant concentration measured according to the set monitoring interval after the initial purification is less than the preset safety threshold, mark it as a single-purification to-be-purified grid, extract the pollutant concentration after the initial purification of the purification device and the last detected pollutant concentration, and the time interval between the initial purification and the last detected pollutant concentration. The difference between the last detected pollutant concentration and the pollutant concentration after the initial purification is taken as the pollutant concentration change, wherein the pollutant concentration change of this type of grid is non-negative, and the value is 0 when the pollutant concentration change is negative. The ratio of the pollutant concentration change to the corresponding interval time is taken as the pollutant residue trend of the grid.

[0013] Further, the method of re-establishing the comprehensive risk assessment model and further weighting according to the pollutant residual trend is to: For the multiple purification to be purified grid, extract the pollutant residual trend of all such grids, filter out the maximum and minimum values, subtract the minimum value from the residual trend value of each grid, and then divide by the difference between the maximum and minimum values to obtain the normalized residual trend of such grids; For the first purification after detection according to the monitoring interval, the pollutant concentration is less than the preset safety threshold, extract the pollutant residual trend of all such grids, and take the maximum residual trend as the reference, divide the residual trend of each grid by the reference value, and multiply by 0.3 to obtain the normalized residual trend of such grids; According to the pollutant residual trend, the danger level of the corresponding effective grid is further weighted, and the specific method is to combine the air flow characteristic data of each effective grid with the pollutant concentration to construct a comprehensive risk assessment model using a weighted summation method, and the output result is defined as the initial comprehensive risk assessment value. The sum of 1 and the normalized residual trend is used as the residual trend basic adjustment coefficient, and the initial comprehensive risk assessment value is multiplied to obtain the further weighted comprehensive risk assessment value.

[0014] In addition, an optimization analysis system of an air purification system is also provided, characterized in that: the system is used to execute the optimization analysis method of the air purification system described above, comprising: The coordinate construction module is used to set the grid size based on the map of the completed modeling of the to-be-purified area, divide the map into grids, determine whether the grid is an effective grid according to the area of the grid, and number the effective grid. The geometric center of each effective grid is set as the cleaning coordinate; The danger level division module is used to traverse all effective grids based on the cleaning coordinates of all grids, obtain the pollutant concentration and air flow characteristic data of each effective grid, construct a comprehensive risk assessment model using a weighted summation method, and divide the danger level of the effective grid; The pollutant detection module is used to filter out the effective grid with a pollutant concentration exceeding the preset safety threshold, and mark it as a to-be-purified grid, and sort the to-be-purified grids according to the danger level from high to low. Purification is carried out at the cleaning coordinates of each purification grid in order to complete the initial purification of the to-be-purified grid; The pollution purification module is used for measuring the pollution concentration of the primary purified grid according to the monitoring interval of the grid according to the danger level, repeating step S3 until the pollution concentration of all the measured grids is less than the preset safety threshold, completing the air purification of the purification area, and extracting the pollution concentration of each grid measured during the purification, and analyzing the pollution residue trend of each grid; The purification sequence optimization module is used for re-establishing the comprehensive risk assessment model and further weighting according to the pollution residue trend when the next air purification of the purification area is performed, and optimizing the danger level of the corresponding effective grid.

[0015] Compared with the prior art, the present application has the following advantages: By grid processing the purification area according to the single coverage area of the purification device and setting the geometric center as the coordinate of the representative effective grid, the comprehensive risk assessment model is constructed by weighting the pollution concentration of each grid and the air flow characteristics to divide the danger level, the grid with the pollution concentration exceeding the preset safety threshold is sorted according to the danger level for priority purification, and the differentiated monitoring interval is matched, so as to improve the resource utilization rate and purification effect of the purification device; the present application also analyzes the pollution residue trend according to the dynamic change data of the pollution concentration of each effective grid before and after purification, and constructs a further weighted comprehensive risk assessment model to divide the danger level of the corresponding effective grid, so as to further pay attention to the area with easy pollution concentration rebound and adjust the monitoring interval and purification priority according to the preset rule, thereby solving the problem that the purification sequence of the prior method does not match the actual risk. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 The present application is a whole method flowchart; Figure 2 The present application is a normalized air flow characteristic data chart; Figure 3 The present application is a comprehensive risk assessment calculation schematic diagram; Figure 4 The present application is a comparison chart of the comprehensive risk assessment before and after weighting; Figure 5 The present application is a whole system structure schematic diagram. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical scheme and advantages of the present application clearer, the present application is further described in detail below with specific examples.

[0018] Unless otherwise defined, technical terms or scientific terms used in the present application shall have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs. The terms "first", "second", and similar terms are used herein merely to distinguish one element from another, and are not intended to imply any order or sequence. The terms "comprises", "comprising", "includes", "including" and the like are used herein to mean either "consisting of" or "consisting essentially of" unless otherwise defined. The terms "connected", "coupled" and the like are used herein to mean either an indirect or direct connection or coupling, and allow that intervening elements may be present. The terms "upper", "lower", "left", "right" and the like are used herein only to denote relative positions, and can change accordingly when the absolute position of the described object changes.

[0019] Embodiments: Please refer to Figures 1 to 4 The present application provides a technical solution: The optimization analysis method of the air purification system includes the following specific steps: S1: Based on the map of the to-be-purified area that has been modeled, the grid size is set to divide the map into grids, it is judged whether the grid is an effective grid according to the area of the grid, the effective grid is numbered, and the geometric center of each effective grid is set as a to-be-cleaned coordinate; The length of a single grid in a two-dimensional grid map is set based on the physical area covered by a single purification operation of the purification device. Since the range covered by the purification device is circular, the area of the circle covered by the purification device needs to be calculated, and then the area occupied by the grid divided by the inscribed square is used as the single purification coverage area to ensure that the design area of a single grid is highly adaptable to the area covered by the purification device. This avoids incomplete purification due to a grid that is too large, and prevents an increase in the frequency of invalid movements of the purification device due to a grid that is too small. After preliminary division of the grid, the actual area of each grid is calculated. When the area of a single grid is 70% or more of the single purification coverage area of the purification device, it indicates that the size of the grid area matches the purification capacity of the purification device, and there is no need to merge. The grid is directly marked as an independent and effective grid. When the area of a single grid is less than 70% of the single purification coverage area of the purification device, the grid area is too small, and separate purification will reduce the efficiency of the operation and make it difficult to ensure the integrity of the regional purification. Therefore, it is merged with adjacent grids, and the grid sharing a complete long side is selected for merging. Two, three or even multiple grids can be combined according to the actual situation until the total area meets the standard. That is, the total area of the merged grid needs to be at least 70% of the single purification coverage area of the purification device to match the single purification coverage area of the purification device. When the purification device operates in the merged grid, its purification range can still cover the entire merged area. Finally, the independent grid and the merged grid that meet the area requirements are marked as effective grids and numbered in order to provide a clear coordinate basis for subsequent purification device grid traversal, data collection and purification operation. The geometric coordinates of the boundary vertices of each effective grid are extracted and the average value is calculated. The average value is used as the geometric center point coordinate of the grid and is set as the initial cleaning coordinate. The geometric center point is located at the center of the grid space. When the purification device operates at this point, its purification range can radiate to all corners of the grid to the greatest extent. It also enables the purification device to generate a work path based on the coordinates to ensure that the collected pollutant concentration and airflow data can reflect the overall pollution status of the grid. If there are no obstacles at the initial cleaning coordinate, the geometric center point is directly used as the final cleaning coordinate. If obstacles are detected at the initial cleaning coordinate, the closest non-obstacle coordinate within the effective grid range is searched from the geometric center point as the origin. The coordinate is within the reachable working range of the purification device. The specific method is to construct an inner circle with the grid geometric center as the origin and the 1 / 2 of the diagonal of the purification device body as the radius, and then construct an outer circle with the purification radius of the purification device. The smallest obstacle-free area in the annular region between the inner circle and the outer circle is found, and the center of the area is taken as the alternative cleaning coordinate. Finally, the selected non-obstacle coordinate is determined as the alternative cleaning coordinate and is associated with the number of the corresponding effective grid.

[0020] S2: Based on the cleaning coordinates of all grids, traverse all valid grids to obtain the pollutant concentration and air flow characteristic data of each valid grid, and combine the air flow characteristic data of each valid grid with the pollutant concentration to construct a comprehensive risk assessment model by using the weighted summation method and divide the risk level of the valid grid; The air flow characteristic data is the air flow residence time, wherein the specific method for calculating the air flow residence time is: releasing a detectable tracer substance to the valid grid, when the tracer concentration decreases from the peak value to 50% of the initial concentration, the corresponding time is the air flow residence time, which is the most commonly used in the tracer method, and can directly reflect the effective residence ability of the pollutant, and is a general index for measuring the air flow residence characteristics of the local area, the longer the residence time, the higher the pollution accumulation risk, and the larger the value, then, obtaining the maximum air flow residence time of all valid grids, calculating the ratio of the air flow residence time of each grid to the maximum value, obtaining the normalized air flow residence time, and keeping the value between [0, 1]; As shown in Figure 2 With the increase of the distance from the grid to the ventilation, the normalized air flow residence time of different valid grids increases, that is, with the gradual increase of the distance from the valid grid to the ventilation, the normalized air flow residence time shows a continuous upward trend, reflecting that the lower the efficiency of the pollutant being carried away, diffused and diluted by the air flow, the easier the concentration rebound.

[0021] The pollutant concentration is the most direct and core index for measuring the pollution accumulation risk, which is essentially the harm of the pollutant to the human body, and the concentration itself is a quantitative embodiment of the harm degree, which is the most decisive for risk assessment and is given the highest weight, that is, the pollutant concentration weight coefficient needs to be greater than the air flow residence time weight coefficient, the wind speed influence is the key adjusting factor for indirectly affecting the risk by changing the diffusion efficiency of the pollutant, the air flow residence time reflects the length of the time that the pollutant itself stays in the grid, which is easily affected by the wind speed, so the weight size is second; Based on the cleaning coordinates of all grids, the purification device traverses all valid grids to obtain the pollutant concentration of each valid grid, and uses the weighted summation method to combine the air flow characteristic data of each valid grid with the pollutant concentration to construct a comprehensive risk assessment model. Extract the normalized air flow residence time of all valid grids, set the weight coefficient of the pollutant concentration and the weight coefficient of the normalized air flow residence time, and set the weight coefficient of the pollutant concentration to be greater than the weight coefficient of the normalized air flow residence time, both of which are greater than 0 and the sum is 1; The pollutant concentration and the normalized air flow residence time of the valid grid are weighted by using the corresponding weight coefficients, and are summed, and the summation result is calibrated as the comprehensive risk assessment value of the valid grid, and a comprehensive risk assessment model for calculating the comprehensive risk assessment value of the valid grid is obtained:

[0022] In the formula, This represents the overall risk assessment value. Indicates pollutant concentration. This represents the normalized residence time of the airflow. This represents the pollutant concentration weighting coefficient. The value represents the weighting coefficient of airflow residence time. The comprehensive risk assessment value reflects the overall risk level of pollutant accumulation. The larger the value, the more difficult it is for pollutants in the grid to diffuse and dilute, and the easier it is to form high concentrations of pollution. The overall pollution risk is higher. It quantifies the impact of pollutant concentration and airflow residence time on the risk of pollution accumulation. From the perspective of the nature of pollution accumulation, the concentration of pollutants in a certain area is ultimately determined by the amount of pollutant released from the pollution source and the diffusion capacity of the airflow. The longer the residence time, the longer the pollutants stay in the area, and the more likely the concentration will increase due to continuous release or secondary accumulation. This allows for both reflecting the current level of pollution and quantifying the future trend of pollution changes. Therefore, a weighted approach is used to quantify the comprehensive risk based on both pollutant concentration and airflow residence time. Both values ​​are positively correlated with the comprehensive risk assessment value. The specific method for dividing the hazard levels of the effective grid is as follows: The comprehensive risk assessment value for each effective grid is calculated based on the comprehensive risk assessment model. The preset hazard levels are high, medium, and low. A first comprehensive risk assessment value threshold and a second comprehensive risk assessment value threshold are set. The first comprehensive risk assessment value threshold is set as follows: The second comprehensive risk assessment threshold is ; The threshold for the first comprehensive risk assessment value is less than the threshold for the second comprehensive risk assessment value, and both are greater than 0; When the comprehensive risk assessment value is not less than the second comprehensive risk assessment value threshold, the effective grid is marked as high-risk. When the comprehensive risk assessment value is less than the second comprehensive risk assessment value threshold but not less than the first comprehensive risk assessment value threshold, the effective grid is marked as medium-risk. When the comprehensive risk assessment value is less than the first comprehensive risk assessment value threshold, the effective grid is marked as low-risk.

[0023] Based on the hazard levels, grids with high pollutant concentrations and long airflow residence times are prioritized for purification, for example, by setting... Table 1 shows the results for 30 effective grids, numbered 1-30, ordered from closest to furthest from the ventilation opening. Pollutant concentrations were collected using sensors from the purification device. The airflow residence time of each grid was measured using the tracer method and normalized. The comprehensive risk assessment value is calculated using the above formula, and a comprehensive risk summary table is generated after summarizing the results. Table 1: Summary Table of Comprehensive Risks

[0024] As Figure 3 shown, the formula is used to calculate the comprehensive risk assessment value of the two dimensions of pollutant concentration and air flow retention time, and then a curve graph is generated. The farther away from the ventilation opening, the larger the normalized air flow retention time. However, due to the different pollutant concentrations in each area, the comprehensive risk assessment values of different effective grids fluctuate greatly, which conforms to the real situation.

[0025] S3: Screen out the effective grid whose pollutant concentration exceeds the preset safety threshold, and mark it as a to-be-cleaned grid. Sort the to-be-cleaned grids according to the level of danger, and clean the to-be-cleaned grid at the to-be-cleaned coordinates of each cleaning grid in order to complete the initial cleaning of the to-be-cleaned grid; According to the pollutant type, indoor air quality standard or scene requirement setting, the safety threshold of the pollutant concentration is preset, such as formaldehyde is lower than , etc. The effective grid whose pollutant concentration exceeds the preset safety threshold is marked as a to-be-cleaned grid. According to the high, medium and low three danger levels, the monitoring intervals are set as high danger level monitoring interval , medium danger level monitoring interval and low danger level monitoring interval , and , the cleaning device is sorted in descending order according to the danger level of the to-be-cleaned grid. The principle of high risk first, medium risk second and low risk last is followed to clean the air of each to-be-cleaned grid. During a single air cleaning period, the air cleaning device will continuously monitor the pollutant concentration until the concentration is reduced to the preset cleaning termination threshold to stop working, ensuring that the indoor air reaches a more reliable safety level. When the danger levels are the same, the cleaning device preferentially cleans nearby to avoid moving back and forth due to the comprehensive risk assessment value, which reduces the operation efficiency, so that the monitoring resources focus on the grid with a higher possibility of exceeding the safety threshold of the pollutant concentration, and avoid high-frequency monitoring of the grid with a higher possibility of insufficient pollutant concentration.

[0026] S4: Set monitoring intervals according to the hazard level of the grid to be purified and measure the pollutant concentration of the grid after the initial purification. Repeat step S3 until the pollutant concentration of all grids is less than the preset safety threshold, thus completing one purification of the area to be purified. After completing one purification of the area to be purified, extract the pollutant concentration measured in each grid during the purification period and analyze the pollutant residual trend of each grid. After the initial purification by the purification device is completed, measure the pollutant concentration of the grid to be purified at the set monitoring intervals, provided that none exceed 1 hour. If the monitoring interval is too long, it may be impossible to deal with the rapid rebound of the pollution concentration in time. It is a balance between capturing effective changes and avoiding over-monitoring. Record the number of times the purification device in each grid to be purified is recorded. Repeat step S3 until the pollutant concentration measured in all the grids to be purified is less than the preset safety threshold, thus completing one air purification cycle for the area to be purified. For grids to be purified multiple times, extract the total number of times a grid in this type of grid has been purified by the purification device. For every two consecutive purification processes, calculate the pollutant concentration rebound intensity between the two purification cycles. Specifically, extract the interval time between two purification cycles, use the difference between the pollutant concentration measured before the next purification cycle and the pollutant concentration measured after the previous purification cycle as the pollutant concentration change, and use the ratio of the pollutant concentration change to the corresponding interval time as the pollutant concentration rebound intensity between the two purification cycles. Take the arithmetic mean of the concentration rebound intensity between all two purification cycles. This average value is the pollutant residual trend of the grid to be purified after multiple purification cycles. The formula used to calculate the intensity of the rebound in pollutant concentration after each two purification cycles is as follows: ; In the formula, This indicates the intensity of the pollutant concentration rebound between two consecutive purification cycles. Indicates the first The concentration of pollutants after secondary purification This indicates the concentration of pollutants after the previous purification cycle. This concentration can be considered a constant value. The air purifier has a preset purification termination threshold; purification ends when this threshold is reached. This indicates the time interval between two purification processes, where, The value is an integer greater than 1. The arithmetic mean of the rebound intensity of pollutant concentration between each two purifications is taken as the pollutant residual trend of the grid to be purified after multiple purifications. The grid to be purified after multiple purifications is essentially the grid where pollutants repeatedly exceed the safety threshold after the initial and subsequent purifications. This indicates that there may be a continuous and high-intensity pollution source in the grid, and it should be prioritized in the next air purification. For the to-be-purified grid after the initial purification, the to-be-purified grid whose pollutant concentration is less than the preset safety threshold at the set monitoring interval is marked as a single purification to-be-purified grid. The pollutant concentration after the initial purification and the last detection of a certain grid purification device, and the time interval between the initial purification and the last detection of the pollutant concentration are extracted. The difference between the last detection and the initial purification of the pollutant concentration is taken as the pollutant concentration change, wherein the pollutant concentration change of this type of grid is non-negative, and the pollutant concentration change is taken as 0 when it is negative. The ratio of the pollutant concentration change to the corresponding interval time is taken as the pollutant residue trend of the grid; wherein the formula for calculating the pollutant residue trend of a certain grid is: ; wherein, represents the pollutant residue trend of the single purification to-be-purified grid, represents the last detection of the pollutant concentration, represents the time interval between the initial purification and the last detection of the pollutant concentration, represents the initial purification of the pollutant concentration. Since the air purification device will preset the purification termination threshold, the purification will be terminated when the purification termination threshold is reached, so the value of the initial purification of the pollutant concentration can be regarded as the same as , and since the continuous reduction of the pollutant concentration has no actual negative impact, only the non-negative change is retained as the pollutant residue trend for subsequent analysis through ; For the multiple purification to-be-purified grids, the pollutant residue trends of all such grids are extracted, and the maximum and minimum values are selected. The residue trend value of each grid is subtracted from the minimum value, and then divided by the difference between the maximum value and the minimum value to obtain the normalized residue trend of such grids. For the to-be-purified grid whose pollutant concentration is less than the preset safety threshold after the initial purification and detection at the monitoring interval, the pollutant residue trends of all such grids are extracted, and the maximum residue trend is taken as the reference. The residue trend of each grid is divided by the reference value, and then multiplied by 0.3 to obtain the normalized residue trend of such grids, so as to limit the normalized residue trend of such grids to [0, 0.3], avoiding that the purification priority of such grids is higher than that of the grid whose pollutant concentration repeatedly exceeds the safety threshold, and ensuring that the multiple purification to-be-purified grids always obtain higher priority.

[0027] S5: When air purification is performed on the to-be-purified area next time, the comprehensive risk assessment model is reconstructed and further weighted according to the pollutant residue trend, and the danger level of the corresponding effective grid is optimized when air purification is performed on the to-be-purified area next time. When air purification is performed on the next occasion, the pollutant concentration and air flow characteristic data of each effective grid are obtained after purification is completed, that is, the danger level of the corresponding effective grid is further weighted according to the pollutant residual trend, and the specific method is that the result output by the comprehensive risk assessment model constructed by using the weighted summation method of the air flow characteristic data of each effective grid combined with the pollutant concentration is defined as an initial comprehensive risk assessment value, 1 and the sum of the normalized residual trends are used as a residual trend basic adjustment coefficient, and the initial comprehensive risk assessment value is multiplied to obtain a further weighted comprehensive risk assessment value, and according to the calculation result of the comprehensive risk assessment model, the danger level of the corresponding effective grid is further weighted according to the pollutant residual trend: In the formula, the further weighted comprehensive risk assessment value is represented, the normalized residual trend is represented, the residual trend basic adjustment coefficient is represented, and further, the grid with a pollutant easy to rise will have a higher comprehensive risk assessment value in the next comprehensive risk assessment; Table 2 shows the comprehensive risk assessment value calculated by combining the residual trend weighting according to the above formula, and the effective grid number, comprehensive risk assessment value, and normalized pollutant residual trend danger level data collection table; Table 2: Danger level data collection table

[0028] As shown in Figure 4 , when the is adopted, the grid numbers 15 and 16 are still low-risk after further weighting, and such grids have weak pollutant residual trends, low real-time pollutant concentrations, and short air flow retention times, so they are suitable for post-processing in the purification priority sequence, which is consistent with the engineering logic. The grid numbers 1, 2, 5, 7, 8, 10, 11, 12, 14, 17, and 18, although their basic comprehensive risk assessment values do not exceed the high-risk threshold, do not significantly reach a very high level, but they also have high pollutant concentrations, long air flow retention times, and high pollutant residual trends, which imply the possibility of continuous pollution source release, so it is considered that the danger level needs to be raised from low to medium and from medium to high. The effective grid with a high danger level is given priority to purification operation, so that the purification operation is more targeted.

[0029] Please refer to Figure 5 , the application further provides an optimization analysis system of an air purification system for executing the optimization analysis method of the air purification system, which comprises: ​A coordinate construction module is configured to set a grid size based on a map of the to-be-cleaned area which has been modeled, divide the map into grids, determine whether a grid is a valid grid according to the area of the grid and number the valid grids, and set the geometric center of each valid grid as a to-be-cleaned coordinate; A danger level division module is configured to traverse all the valid grids based on the to-be-cleaned coordinates of all the grids, obtain the pollutant concentration and air flow characteristic data of each valid grid, and construct a comprehensive risk assessment model by using a weighted summation method to combine the air flow characteristic data and the pollutant concentration of each valid grid and divide the danger levels of the valid grids; A pollutant detection module is configured to screen out valid grids whose pollutant concentration exceeds a preset safety threshold, label the valid grids as to-be-cleaned grids, sort the to-be-cleaned grids according to the danger levels of the to-be-cleaned grids, and perform purification at the to-be-cleaned coordinates of each to-be-cleaned grid in order to complete the initial purification of the to-be-cleaned grids; A pollutant purification module is configured to set a monitoring interval according to the danger levels of the to-be-cleaned grids, measure the pollutant concentration of the to-be-cleaned grids after the initial purification, repeat step S3 until the measured pollutant concentration of all the to-be-cleaned grids is less than the preset safety threshold, complete the air purification of the to-be-cleaned area, extract the measured pollutant concentration of each to-be-cleaned grid during the air purification, and analyze the pollutant residue trend of each to-be-cleaned grid; A purification sequence optimization module is configured to re-construct the comprehensive risk assessment model and further weight according to the pollutant residue trend when air purification is performed on the to-be-cleaned area next time, and optimize the danger levels of the corresponding valid grids when air purification is performed on the to-be-cleaned area next time.

[0030] The above formulas are all dimensionless values, and the formulas are obtained by collecting a large amount of data to simulate a formula of the nearest real situation, and the preset parameters in the formula are set by a person skilled in the art according to the actual situation.

[0031] The above embodiments can be realized by software, hardware, firmware or any combination thereof. When realized by software, the above embodiments can be realized in the form of a computer program product. Those skilled in the art can realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized by hardware or software depends on the specific application and design constraints of the technical solutions.

[0032] The units described as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, and may be located in one place, or distributed on multiple network units. Part or all of the units can be selected to achieve the purpose of the embodiment of the present application according to actual needs.

[0033] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto, and any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered within the protection scope of the present application.

Claims

1. An optimization analysis method for an air purification system, characterized in that, The specific steps include: S1: Based on the completed modeling of the area to be cleaned, the map is divided into grids by setting the grid size. The area of ​​the grid determines whether the grid is a valid grid and the valid grids are numbered. The geometric center of each valid grid is set as the coordinate to be cleaned. S2: Based on the clean coordinates of all grids, traverse all effective grids, obtain the pollutant concentration and airflow characteristic data of each effective grid, combine the airflow characteristic data of each effective grid with the pollutant concentration, use a weighted summation method to construct a comprehensive risk assessment model, and classify the hazard level of the effective grids. S3: Select effective grids with pollutant concentrations exceeding the preset safety threshold, mark them as grids to be cleaned, sort them according to their hazard level, and perform initial cleaning at the cleaning coordinates of each grid in order. S4: Set monitoring intervals according to the hazard level of the grid to be purified and measure the pollutant concentration of the grid after the first purification. Repeat step S3 until the pollutant concentration of all grids to be purified is less than the preset safety threshold, and complete one purification of the air in the area to be purified. After completing one purification of the air in the area to be purified, extract the pollutant concentration measured in each grid to be purified during the purification period and analyze the pollutant residual trend of each grid to be purified. S5: When the air in the area to be purified is purified for the next time, the comprehensive risk assessment model is reconstructed and further weighted according to the pollutant residue trend. The hazard level of the corresponding effective grid is then optimized when the air in the area to be purified is purified for the next time.

2. The optimization analysis method for the air purification system according to claim 1, characterized in that: When setting the grid size for grid division, the physical area that the purification device can cover in a single purification operation is used as the benchmark. The side length parameters of individual grids in the two-dimensional raster map are set to match the area of ​​a single grid with the area covered by the purification device in a single purification operation. The map is then divided into grids according to this standard side length. The actual area of ​​each grid is calculated. When the area of ​​a single grid reaches 70% or more of the area covered by the purification device in a single purification operation, the grid is directly marked as an independent and valid grid. When the area of ​​a single grid is less than 70% of the area covered by the purification device in a single purification operation, it needs to be merged with adjacent grids that share a common side length. The grid formed after merging must meet the requirement that the total area is not less than 70% of the area covered by the purification device in a single purification operation. Finally, the independent grids that meet the area requirements and the merged grids are uniformly marked as valid grids and numbered sequentially.

3. The optimization analysis method for the air purification system according to claim 1, characterized in that: The method for setting the geometric center of each effective grid as the coordinates to be cleaned is as follows: The coordinates of the geometric center point of each effective grid are set as the initial coordinates to be cleaned. If there are no obstacles at the initial coordinates to be cleaned, the geometric center point is directly used as the final coordinates to be cleaned. If an obstacle is detected at the initial coordinates to be cleaned, the coordinates with the geometric center point as the origin are searched for the nearest obstacle-free coordinates in terms of Euclidean geometric distance within the effective grid range. Finally, the selected obstacle-free coordinates are determined as the alternative coordinates to be cleaned.

4. The optimization analysis method for the air purification system according to claim 1, characterized in that: The airflow characteristic data is the airflow residence time, and the specific method for calculating the airflow residence time is as follows: A tracer substance that can be accurately detected is released into each effective grid, and the change in tracer concentration is monitored in real time. When the tracer concentration drops from the peak to 50% of the initial concentration, the corresponding duration is recorded. This duration is the airflow residence time of that effective grid.

5. The optimization analysis method for the air purification system according to claim 4, characterized in that: The method for constructing a comprehensive risk assessment model and classifying the hazard levels of effective grids by combining the airflow characteristic data of each effective grid with pollutant concentrations using a weighted summation method is as follows: The method for constructing a comprehensive risk assessment model by combining the airflow characteristic data of each effective grid with pollutant concentration using a weighted summation method is as follows: Obtain the maximum airflow residence time for all valid grids, calculate the ratio of the airflow residence time of each valid grid to this maximum value, and obtain the normalized airflow residence time of that valid grid. Set a weighting coefficient for pollutant concentration and a weighting coefficient for normalized airflow residence time. The set weighting coefficient for pollutant concentration is greater than the weighting coefficient for normalized airflow residence time. Both weighting coefficients are greater than 0 and their sum is 1. The pollutant concentration and normalized airflow residence time of the effective grid are weighted by corresponding weighting coefficients and summed. The summation result is calibrated as the comprehensive risk assessment value of the effective grid, thus obtaining a comprehensive risk assessment model for calculating the comprehensive risk assessment value of the effective grid. The method for classifying the hazard levels of effective grids is as follows: The comprehensive risk assessment value of each effective grid is calculated based on the comprehensive risk assessment model. The preset hazard levels are high, medium and low. A first comprehensive risk assessment value threshold and a second comprehensive risk assessment value threshold are set. The first comprehensive risk assessment value threshold is less than the second comprehensive risk assessment value threshold, and both are greater than 0. When the comprehensive risk assessment value is not less than the second comprehensive risk assessment value threshold, the effective grid is marked as high-risk. When the comprehensive risk assessment value is less than the second comprehensive risk assessment value threshold but not less than the first comprehensive risk assessment value threshold, the effective grid is marked as medium-risk. When the comprehensive risk assessment value is less than the first comprehensive risk assessment value threshold, the effective grid is marked as low-risk.

6. The optimization analysis method for the air purification system according to claim 5, characterized in that: The method for measuring pollutant concentrations in the grids to be cleaned after the initial cleanup, by setting monitoring intervals according to the hazard level of the grids to be cleaned, is as follows: Based on the high, medium and low hazard levels of the grid division, corresponding monitoring intervals are set respectively. The monitoring intervals are high hazard level monitoring intervals, medium hazard level monitoring intervals and low hazard level monitoring intervals. That is, the monitoring interval of the high hazard level grid corresponds to the high hazard level monitoring interval, the monitoring interval of the medium hazard level grid corresponds to the medium hazard level monitoring interval, and the monitoring interval of the low hazard level grid corresponds to the low hazard level monitoring interval. The monitoring interval for high-risk levels is shorter than that for medium-risk levels, which is shorter than that for low-risk levels. All three intervals are less than 1 hour. After the initial purification by the purification device, the monitoring intervals for the grid to be purified are matched according to the three risk levels of high, medium, and low. Then, the pollutant concentration of the grid to be purified is measured according to the set monitoring intervals.

7. The optimization analysis method for the air purification system according to claim 6, characterized in that: The method for analyzing the residual trend of pollutants in each grid to be cleaned is as follows: Based on the concentration change data of the grid to be purified during the purification process, combined with monitoring interval records, the residual trend of pollutants in each grid is analyzed, and the process is divided into two scenarios: For a grid to be purified multiple times, the total number of times a grid has been purified by the purification device is extracted. For every two consecutive purification processes, the pollutant concentration rebound intensity between the two purification processes is calculated. Specifically, the interval time between two purification processes is extracted, and the difference between the pollutant concentration measured before the next purification process and the pollutant concentration measured after the previous purification process is taken as the pollutant concentration change. The ratio of the pollutant concentration change to the corresponding interval time is taken as the pollutant concentration rebound intensity between the two purification processes. The arithmetic mean of the concentration rebound intensity between all two purification processes is taken, and this average value is the pollutant residual trend of the grid. For grids to be purified where the pollutant concentration measured at the set monitoring intervals is less than the preset safety threshold after the initial purification, they are marked as grids to be purified after a single purification. The pollutant concentration after the initial purification of a certain grid and the pollutant concentration at the last detection, as well as the time interval between the initial purification and the last detection of the pollutant concentration, are extracted. The difference between the last detection of the pollutant concentration and the pollutant concentration after the initial purification is taken as the pollutant concentration change. Among them, the pollutant concentration change of this type of grid is retained when it is non-negative, and the value is set to 0 when it is negative. The ratio of the pollutant concentration change to the corresponding interval time is taken as the pollutant residual trend of the grid.

8. The optimization analysis method for the air purification system according to claim 7, characterized in that: The method for reconstructing the comprehensive risk assessment model and further weighting it according to the pollutant residue trend, and then reclassifying the hazard levels of the corresponding effective grids, is as follows: For the grid to be cleaned multiple times, extract the pollutant residual trend of all grids of this type, select the maximum and minimum values, subtract the minimum value from the residual trend value of each grid, and then divide by the difference between the maximum and minimum values ​​to obtain the normalized residual trend of this type of grid. For the grids to be purified after the initial purification, the pollutant concentration is less than the preset safety threshold when monitored at the interval. The pollutant residual trend of all such grids is extracted. The residual trend of each grid is divided by the maximum residual trend as the benchmark, and then multiplied by 0.3 to obtain the normalized residual trend of such grids. The risk level of the corresponding effective grid is further weighted according to the pollutant residual trend. Specifically, the result of the comprehensive risk assessment model constructed by combining the air flow characteristic data of each effective grid with the pollutant concentration using a weighted summation method is defined as the initial comprehensive risk assessment value. The sum of 1 and the normalized residual trend is used as the residual trend basic adjustment coefficient, which is multiplied by the initial comprehensive risk assessment value to obtain the further weighted comprehensive risk assessment value.

9. An optimization analysis system for air purification systems, characterized in that: The system is used to perform the optimization analysis method of the air purification system according to any one of claims 1-8: The coordinate construction module is used to divide the map into grids based on the completed modeled map of the area to be cleaned, set the grid size, determine whether the grid is a valid grid based on the area of ​​the grid and number the valid grids, and set the geometric center of each valid grid as the coordinate to be cleaned. The hazard level classification module is used to traverse all effective grids based on the clean coordinates of all grids, obtain the pollutant concentration and airflow characteristic data of each effective grid, combine the airflow characteristic data of each effective grid with the pollutant concentration, and construct a comprehensive risk assessment model by weighted summation to classify the hazard level of the effective grids. The pollutant detection module is used to screen out effective grids with pollutant concentrations exceeding a preset safety threshold, mark them as grids to be cleaned, and sort them according to their hazard level. The initial cleaning of each grid is completed by cleaning the cleaning coordinates of each grid in sequence. The pollutant purification module is used to set monitoring intervals according to the hazard level of the grid to be purified and measure the pollutant concentration of the grid after the initial purification. Step S3 is repeated until the pollutant concentration of all grids to be purified is less than the preset safety threshold, thus completing one purification of the air in the area to be purified. After completing one purification of the air in the area to be purified, the pollutant concentration measured in each grid to be purified during the purification period is extracted, and the pollutant residual trend of each grid to be purified is analyzed. The purification sequence optimization module is used to rebuild the comprehensive risk assessment model and further weight it according to the pollutant residue trend when the air purification of the area to be purified is carried out again, and optimize the hazard level of the corresponding effective grid when the air purification of the area to be purified is carried out again.

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