Optimization analysis method and system of air purification system

Abstract

The application provides an optimization analysis method and system of an air purification system, relates to the field of information processing supported automation system optimization technology, and is based on dividing effective grids according to a map of a region to be purified and a single purification coverage area of a purification device, and determining the coordinates of each effective grid to be cleaned; the concentration of pollutants and air flow characteristics of the effective grid are collected, and the danger level is divided by weighted summation; the purification grids to be purified whose pollutant concentration exceeds a preset safety threshold are screened, sorted according to the danger level and initially purified, and then monitored dynamically according to the level setting interval; after the purification operation is repeated until all the purification grids to be purified reach the standard, the residual trend of the pollutants of each purification grid to be purified is analyzed; in the next purification, the danger level of the effective grid is further weighted in combination with the residual trend of the pollutants, the purification priority is optimized, and through dynamic monitoring and residual trend analysis, the accurate allocation and efficient use of purification resources are realized.

Description

Technical Field

[0001] This invention relates to the field of air purification logic technology, specifically to an optimization analysis method and system for air purification systems. Background Technology

[0002] Currently, most air purification devices or systems are based on preset path planning and timed purification strategies. Household air purification devices are widely used in residential settings to monitor and purify pollutant concentrations in different indoor areas.

[0003] The common approach is to first create a two-dimensional map of the area to be purified, divide it into work units according to a certain grid pattern, and then move the purification device grid by grid, detecting pollutant concentration at the center of each grid or a designated location. When the detected value exceeds a set threshold, the purification device will be triggered to purify the air in that area. This method has already achieved automated air purification in indoor environments such as homes, offices, and schools, and has played a positive role in improving air quality and reducing human intervention. However, the above method still has certain shortcomings in risk assessment and purification strategy optimization. First, most existing systems rely only on the pollutant concentration sampled at instant as the basis for judgment, which is difficult to reflect the impact of air flow conditions on the diffusion, dilution, and redistribution of pollutants. Therefore, it is easy to have a problem of mismatch between the purification sequence and the actual risk. Second, even if the concentration in some areas is not prominent in a single measurement, the concentration will quickly rise again after purification due to airflow stagnation or intermittent release of pollutants. Existing technologies do not provide effective means to identify and deal with these areas that are prone to repeated exceedances. As a result, some high-risk areas have not received enough attention, while some low-risk areas may be repeatedly purified, resulting in uneven resource allocation, increased energy consumption, and reduced purification efficiency.

[0004] Therefore, there is an urgent need for a method that can incorporate quantitative analysis of airflow characteristics and pollutant residue trends on the basis of traditional pollutant concentration measurement, and dynamically adjust the hazard level of each grid.

[0005] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0006] The purpose of this invention is to provide an optimization analysis method and system for air purification systems to solve the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] The optimization analysis method for air purification systems includes the following specific steps:

[0009] 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.

[0010] 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.

[0011] 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.

[0012] 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.

[0013] 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.

[0014] Furthermore, 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 parameter of a single grid in the two-dimensional raster map is set so that the area of ​​a single grid matches 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.

[0015] Furthermore, the method for setting the geometric center of each effective grid as the coordinates to be cleaned is as follows:

[0016] 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 obstacles are detected at the initial coordinates to be cleaned, the geometric center point is used as the origin, and the nearest obstacle-free coordinate with Euclidean geometric distance is searched within the effective grid range. Finally, the selected obstacle-free coordinates are determined as the alternative coordinates to be cleaned.

[0017] Furthermore, the airflow characteristic data is the airflow residence time, and the specific method for calculating the airflow residence time is as follows:

[0018] 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.

[0019] Furthermore, 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:

[0020] 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:

[0021] 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.

[0022] 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.

[0023] 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.

[0024] The method for classifying the hazard levels of effective grids is as follows:

[0025] 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.

[0026] 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.

[0027] Furthermore, the method for measuring the pollutant concentration in the grid to be purified after the initial purification, by setting monitoring intervals according to the hazard level of the grid to be purified, is as follows:

[0028] 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.

[0029] 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.

[0030] Furthermore, the method for analyzing the residual trend of pollutants in each grid to be cleaned is as follows:

[0031] Based on the concentration change data of the grid to be purified during the purification process, combined with monitoring interval records, the pollutant residue trend of each grid is analyzed, and the process is divided into two scenarios:

[0032] 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.

[0033] 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.

[0034] Furthermore, 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:

[0035] 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.

[0036] 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.

[0037] 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.

[0038] Additionally, an optimization analysis system for air purification systems is provided, characterized in that: the system is used to execute the aforementioned optimization analysis method for air purification systems, including:

[0039] 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.

[0040] 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, and construct a comprehensive risk assessment model by combining the airflow characteristic data of each effective grid with the pollutant concentration using a weighted summation method, and classify the hazard level of the effective grids.

[0041] 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.

[0042] 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.

[0043] 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.

[0044] Compared with the prior art, the beneficial effects of the present invention are:

[0045] By gridding the area to be purified according to the single coverage area of ​​the purification device and setting the geometric center as the coordinates of the effective grid, a comprehensive risk assessment model is constructed by combining the pollutant concentration and airflow characteristics of each grid to classify the danger level. Grids with pollutant concentrations exceeding the preset safety threshold are prioritized for purification according to their danger level, and differentiated monitoring intervals are matched to improve the resource utilization and purification effect of the purification device. The present invention also analyzes the pollutant residue trend based on the dynamic change data of pollutant concentration before and after purification of each effective grid, and constructs a further weighted comprehensive risk assessment model to classify the danger level of the corresponding effective grid. This allows for further attention to areas where pollutant concentrations are prone to rebound, and the monitoring interval and purification priority are adjusted according to preset rules, solving the problem that the purification order of existing methods does not match the actual risk. Attached Figure Description

[0046] Figure 1 This is a schematic diagram of the overall method flow of the present invention;

[0047] Figure 2This is a normalized airflow characteristic data diagram of the present invention;

[0048] Figure 3 This is a schematic diagram illustrating the comprehensive risk assessment calculation of the present invention;

[0049] Figure 4 This is a comparison chart of the comprehensive risk assessment before and after weighting of this invention;

[0050] Figure 5 This is a schematic diagram of the overall system structure of the present invention. Detailed Implementation

[0051] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0052] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0053] Example:

[0054] Please see Figures 1 to 4 The present invention provides a technical solution:

[0055] The optimization analysis method for air purification systems includes the following specific steps:

[0056] 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.

[0057] Based on the physical area that the air purification device can cover in a single purification operation, the side length of each grid cell in the two-dimensional grid map is set. Since the area covered by the air purification device is circular, the area of ​​the circle needs to be calculated based on the area that the device itself can cover. Then, the area occupied by the grid cells divided by inscribed squares is used as the single purification coverage area. This ensures that the designed area of ​​each grid cell is highly compatible with the area that the purification device itself can cover. This avoids incomplete purification due to grids that are too large, and also prevents unnecessary movement of the purification device due to grids that are too small. After the initial grid division, the actual area of ​​each grid cell is calculated. When the area of ​​a single grid cell reaches 70% or more of the single purification coverage area of ​​the purification device, it indicates that... The area of ​​this grid matches the purification capacity of the air purification device, so there's no need to merge it. This grid is directly marked as an independent, effective grid. If the area of ​​a single grid is less than 70% of the single-cycle purification coverage area of ​​the air purification device, because the grid area is too small, individual purification would reduce operational efficiency and make it difficult to guarantee the integrity of the area's purification. In this case, it is merged with an adjacent grid, selecting grids that share a complete long side. Depending on the actual situation, two, three, or even more grids can be combined until the total area meets the requirement. That is, the merged grid must have a total area not less than 70% of the single-cycle purification coverage area of ​​the air purification device, matching the single-cycle purification coverage area. When the air purification device operates within this merged grid, its purification range can still cover the entire area. The area is then merged, and all independent grids meeting the area requirements, along with the merged grid, are uniformly marked as valid grids and numbered sequentially. This provides a clear coordinate basis for subsequent grid traversal, data collection, and purification operations by the purification device. The geometric coordinates of the boundary vertices of each valid grid are extracted and their average value is calculated. This average value is used as the coordinates of the geometric center point of that grid and set as the initial coordinates to be cleaned. The geometric center point is located at the center of the grid space. When the purification device operates at this location, its purification range can maximally cover all corners of the grid. It also allows the purification device to generate an operation path based on the coordinates, ensuring that the collected pollutant concentration and airflow data reflect the overall pollution status of the grid. If there are no obstacles at the initial coordinates to be cleaned, the geometric center point is directly used. The initial coordinates to be cleaned are determined by the first point. If an obstacle is detected at the initial coordinates to be cleaned, the geometric center point is used as the origin. Within the effective grid range, the nearest unobstructed coordinates with Euclidean geometric distance are searched, and the area where the coordinates are located is within the working range reachable by the purification device. Specifically, an inner circle is constructed with the geometric center of the grid as the origin and half the diagonal of the purification device as the radius. An outer circle is constructed with the purification radius of the purification device. The smallest unobstructed area that is closest to the geometric center and can accommodate the purification device body is found in the annular area between the inner and outer circles. The center of this area is taken as the alternative coordinates to be cleaned. Finally, the selected unobstructed coordinates are determined as the alternative coordinates to be cleaned and associated with the corresponding effective grid number.

[0058] 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.

[0059] The airflow characteristic data is the airflow residence time. The specific method for calculating the airflow residence time is as follows: a detectable tracer substance is released into the effective grid. When the tracer concentration drops from the peak to 50% of the initial concentration, the corresponding time is the airflow residence time. This is the most commonly used tracer method and can directly reflect the effective residence capacity of pollutants. It is a general indicator for measuring the airflow residence characteristics of a local area. The longer the residence time, the higher the risk of pollution accumulation and the larger the value. Then, the maximum airflow residence time of all effective grids is obtained, and the ratio of the airflow residence time of each grid to the maximum value is calculated to obtain the normalized airflow residence time, so that the value is maintained between [0, 1].

[0060] like Figure 2 As shown, as the distance from the grid to the ventilation point increases, the normalized airflow residence time of different effective grids also increases. That is, as the distance from the effective grid to the ventilation point gradually increases, the normalized airflow residence time shows a continuous upward trend, reflecting that the efficiency of pollutants being carried away and diffused by the airflow is lower, and concentration rebound is more likely to occur.

[0061] Pollutant concentration is the most direct and core indicator for measuring the risk of pollution accumulation. Its essence is the harm of pollutants to the human body, and concentration itself is a quantitative manifestation of the degree of harm. It has the strongest decisive influence on risk assessment and is given the highest weight. That is, the pollutant concentration weight coefficient must be greater than the airflow residence time weight coefficient. Wind speed influence is a key regulatory factor that indirectly affects risk by changing the diffusion efficiency of pollutants. Airflow residence time reflects the ability of pollutants to stay in the grid for a long time and is easily affected by wind speed. Therefore, its weight is secondary.

[0062] Based on the clean coordinates of all grids, the purification device traverses all effective grids to obtain the pollutant concentration of each effective grid. The method for constructing a comprehensive risk assessment model by combining the airflow characteristic data of each effective grid with the pollutant concentration using a weighted summation method is as follows:

[0063] Extract the normalized airflow residence time of all valid grids, set the weight coefficients for pollutant concentration and normalized airflow residence time, and set the weight coefficient for pollutant concentration to be greater than the weight coefficient for normalized airflow residence time. Both weight coefficients are greater than 0 and their sum is 1.

[0064] The pollutant concentration and normalized airflow residence time of the effective grid are weighted using corresponding weighting coefficients and summed. The summation result is then calibrated as the comprehensive risk assessment value of the effective grid, resulting in a comprehensive risk assessment model for calculating the comprehensive risk assessment value of this effective grid.

[0065]

[0066] 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.

[0067] 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:

[0068] 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 ;

[0069] 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;

[0070] 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.

[0071] 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.

[0072] Table 1: Summary Table of Comprehensive Risks

[0073]

[0074] like Figure 3 As shown, after calculating the comprehensive risk assessment value for pollutant concentration and airflow residence time using the above formula, a curve is generated. The farther away from the ventilation opening, the greater the normalized airflow residence time. However, due to the different pollutant concentrations in different areas, the comprehensive risk assessment value of different effective grids also fluctuates greatly, which is consistent with the actual situation.

[0075] 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.

[0076] Based on the type of pollutant, indoor air quality standards, or scenario requirements, preset safety thresholds for pollutant concentrations are established, such as... Formaldehyde levels are below For grids where pollutant concentrations exceed preset safety thresholds, the effective grids are designated as grids to be cleaned. Monitoring intervals are set according to three hazard levels: high, medium, and low, with the high-hazard level monitoring interval being the specific interval. Monitoring interval for medium-risk levels and low-risk level monitoring interval ,and The air purification devices sort the grids to be purified in descending order of their hazard level, following the principle of prioritizing high-risk, followed by medium-risk, and lastly low-risk. During a single air purification cycle, the air purification devices continuously monitor the pollutant concentration until it drops to the preset purification termination threshold before stopping operation. This ensures that the indoor air reaches a more reliable and safe level. When the hazard levels are the same, the purification devices prioritize purifying the nearest grid to avoid moving the purification devices back and forth due to the comprehensive risk assessment value, which would reduce operational efficiency. This allows monitoring resources to focus on grids where the pollutant concentration is more likely to exceed the safety threshold, avoiding high-frequency monitoring of grids where the pollutant concentration is more likely to be insufficient.

[0077] 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.

[0078] 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.

[0079] The formula used to calculate the intensity of the rebound in pollutant concentration after each two purification cycles is as follows:

[0080] ;

[0081] 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.

[0082] After the initial purification of a grid, grids whose pollutant concentrations are all below a preset safety threshold at the set monitoring intervals are marked as grids that have undergone single-stage purification. The pollutant concentrations after the initial purification and the last detected pollutant concentration of a grid are extracted, along with the time interval between the initial purification and the last detected pollutant concentration. The difference between the last detected pollutant concentration and the initial purification concentration is taken as the pollutant concentration change. When the pollutant concentration change of this type of grid is non-negative, it is retained; when the pollutant concentration change is negative, it is set to 0. The ratio of the pollutant concentration change to the corresponding time interval is taken as the pollutant residual trend of the grid.

[0083] The formula used to calculate the pollutant residue trend for a certain grid is as follows:

[0084] ;

[0085] In the formula, This indicates the residual contaminant trend in the grid to be cleaned after a single cleaning cycle. This indicates the concentration of pollutants detected in the last test. This indicates the time interval between the initial purification by the purification device and the last detection of pollutant concentration. This indicates the pollutant concentration after the initial purification. Since air purifiers have a preset purification termination threshold, purification ends when this threshold is reached. Therefore, the value of the pollutant concentration after the initial purification can be considered as... Similarly, since the continuous decrease in pollutant concentration has no actual negative impact, therefore... This item only retains non-negative changes as pollutant residue trends for subsequent analysis;

[0086] 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.

[0087] For grids to be purified after the initial purification, where the pollutant concentration is consistently below the preset safety threshold according to monitoring intervals, the pollutant residual trend of all such grids is extracted. Using the largest residual trend as a benchmark, the residual trend of each grid is divided by this benchmark value and then multiplied by 0.3 to obtain the normalized residual trend of this type of grid. This limits the normalized residual trend of this type of grid to the range of [0, 0.3], preventing the purification priority of this type of grid from being higher than that of grids where pollutants repeatedly exceed the safety threshold, and ensuring that grids to be purified after multiple purifications always receive a higher priority.

[0088] S5: When the air is purified in the next area, 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 optimized when the air is purified in the next area.

[0089] In the next air purification of the area to be purified, after purification, the pollutant concentration and airflow characteristic data of each effective grid are obtained. This involves further weighting the hazard level of the corresponding effective grid based on the pollutant residue trend. Specifically, the output of a comprehensive risk assessment model constructed by combining the airflow 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 residue trend is used as the residue trend adjustment coefficient, which is multiplied by the initial comprehensive risk assessment value. The result is the further weighted comprehensive risk assessment value. Based on the calculation results of the comprehensive risk assessment model, and combined with the pollutant residue trend, the hazard level of the corresponding effective grid is further weighted.

[0090] ;

[0091] In the formula, This represents a further weighted overall risk assessment value. This indicates the residual trend after normalization. This is the residual trend adjustment coefficient, which means that in grids where pollutants are prone to rebound, the comprehensive risk assessment value will increase in the next comprehensive risk assessment.

[0092] Table 2 shows the comprehensive risk assessment values ​​calculated by combining the above formula with residual trend weighting, covering the effective grid number, comprehensive risk assessment values, and the hazard level data collection table of the normalized pollutant residual trend.

[0093] Table 2: Hazard Level Data Collection Table

[0094]

[0095] like Figure 4 As shown, when using At that time, grids 15 and 16, after further weighting, were still classified as low-risk. These grids exhibited weak pollutant residual trends, low real-time pollutant concentrations, and short airflow residence times. Therefore, they were suitable for post-treatment in the purification priority sequence, which aligns with the engineering logic. Although grids 1, 2, 5, 7, 8, 10, 11, 12, 14, 17, and 18 did not exceed the high-risk threshold in their basic comprehensive risk assessment values, and although they did not reach a significantly high level, they also exhibited relatively high pollutant concentrations and long airflow residence times. Furthermore, due to the high value of pollutant residual trends, they implied the possibility of continuous pollution source release. Therefore, it was considered that the hazard level needed to be raised from low to medium and from medium to high. Purification operations should be prioritized for effective grids with high-risk levels to make the purification operations more targeted.

[0096] Please see Figure 5 The present invention also provides an optimization analysis system for an air purification system, used to perform the above-described optimization analysis method for an air purification system, comprising:

[0097] 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.

[0098] 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, and construct a comprehensive risk assessment model by combining the airflow characteristic data of each effective grid with the pollutant concentration using a weighted summation method, and classify the hazard level of the effective grids.

[0099] 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.

[0100] 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.

[0101] 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.

[0102] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0103] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution.

[0104] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0105] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this 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, and the hazard level of the corresponding effective grid is 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 pollutant residue trend of 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, and construct a comprehensive risk assessment model by combining the airflow characteristic data of each effective grid with the pollutant concentration using a weighted summation method, and 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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