Air purification method and device for ventilation system

Abstract

The present application relates to the field of green building ventilation and regulation technology, and specifically to an air purification method and device applied to a ventilation system, the method comprising: obtaining the content of each pollutant in the air in the workplace, the pressure difference between indoors and outdoors, and the wind speed data near the purification device and the power consumption data of each device; forming the indoor and outdoor pressure difference and the device power consumption data into two-dimensional data, clustering all the two-dimensional data in each time period, determining the influence coefficient of air quality by the local density and relative distance of the two-dimensional data at each moment, and determining the random change amount of the pollutant trend in each time period in combination with the change trend and random change degree of each pollutant content; determining the airflow disturbance coefficient according to the fluctuation degree and average level of the wind speed data, analyzing the similarity between the airflow disturbance coefficient and the random change amount of the pollutant trend, determining the air purification influence factor, and purifying and regulating. The present application can improve the air ventilation purification efficiency to prevent occupational diseases caused by air pollution.

Description

Technical Field

[0001] The present application relates to the technical field of green building ventilation and regulation, and in particular to an air purification method and device applied to a ventilation system. Background Art

[0002] Indoor air pollution not only has a negative impact on people's quality of life, but also may have long-term potential impacts on health. Occupational diseases are mainly caused by chemical factors, such as air pollution, coal dust, etc. Long-term exposure to air pollution in the working environment can cause pneumoconiosis, dermatitis and allergic rhinitis. These diseases are usually caused by long-term inhalation of pollutants such as dust and harmful gases. Therefore, in order to prevent occupational diseases caused by air pollution, it is necessary to solve the problem of air pollution. At present, air purification devices are widely used in various places such as residential areas, office areas, and large buildings.

[0003] Under the concept of green building, it is necessary to explore more efficient and intelligent air purification strategies based on the unique properties of large buildings, so as to achieve a comprehensive improvement in the air quality inside the building, reduce energy consumption, and promote the construction industry to develop in a green and sustainable direction. For large buildings, they are different from ordinary residential and office areas. They have significant characteristics such as large space scale, high energy consumption, and diverse building structures. Therefore, the requirements for local ventilation are more stringent. Centralized air treatment systems are usually used inside large buildings to uniformly purify indoor air. However, due to environmental changes and the influence of airflow interference on the rotation state of the purification device fan, the stability and efficiency of air purification are insufficient. Summary of the invention

[0004] In order to solve the above technical problems, the purpose of this application is to provide an air purification method and device for a ventilation system. The technical solutions adopted are as follows:

[0005] The present application provides an air purification method for a ventilation system, comprising the following steps:

[0006] Obtain the content of each pollutant in the indoor air, the pressure difference between indoor and outdoor, and the wind speed data near the purification device and the power consumption data of each nearby device at each time period within the preset collection time;

[0007] The indoor and outdoor pressure difference and equipment power consumption data at each time in each time period are combined into two-dimensional data, and all the two-dimensional data in each time period are clustered. The influence coefficient of air quality at each time in each time period is determined through the local density and relative distance of the two-dimensional data at each time after clustering, as well as the average value of the indoor and outdoor pressure difference and equipment power consumption at each time;

[0008] According to the air quality impact coefficient at each time in each time period, the characteristic sequence of each pollutant content is constructed in combination with the content of each pollutant in each time period; by analyzing the change trend and random change degree of the characteristic sequence of each pollutant content, the abnormal fluctuation coefficient of each pollutant content in each time period is obtained, and the random change amount of the pollutant trend in each time period is obtained by combining the abnormal fluctuation coefficient of all pollutant contents in each time period;

[0009] According to the fluctuation degree and average level of wind speed data in each time period, the airflow disturbance coefficient of each time period is determined. According to the similarity between the airflow disturbance coefficient and the random change of pollutant trend, combined with the average level of all pollutant content in all time periods, the air purification influencing factor is determined and the air purification is regulated.

[0010] Preferably, the contents of various pollutants further include particulate matter content, formaldehyde, and nitrogen dioxide content.

[0011] Preferably, the calculation formula for the influence coefficient of air quality at each time in each time period is:

[0012] ; In the formula, is the influence coefficient of air quality at the jth moment in the i-th time period, , are the local density and relative distance at the jth moment in the i-th time period after clustering, is the mean of the indoor and outdoor pressure difference and power consumption data at the jth moment in the i-th time period.

[0013] Preferably, the construction of the characteristic sequence of each pollutant content further includes:

[0014] The product of the air quality influence coefficient and the pollutant content at each moment in each time period is arranged in ascending time order to form a pollutant content characteristic sequence for each time period.

[0015] Preferably, the abnormal fluctuation coefficient of each pollutant content is the product of the fractal dimension of the characteristic sequence of each pollutant content and the trend statistic.

[0016] Preferably, the random change amount of the pollutant trend in each time period is the sum of the abnormal fluctuation coefficients of all pollutant contents in each time period.

[0017] Preferably, the airflow disturbance coefficient of each time period is the product of the standard deviation and the mean of all wind speed data in each time period.

[0018] Preferably, the determination of the air purification influencing factor further includes: arranging the random change amount of the pollutant trend and the airflow disturbance coefficient in each time period in ascending time order to form a vector, and taking the product of the average value of all pollutant contents in all time periods and the similarity between the two vectors as the air purification influencing factor.

[0019] Preferably, the regulating of air purification further comprises:

[0020] The air purification influencing factor is normalized, and the sum of the normalized result of the air purification influencing factor calculated for the previous collection time of the current collection time and the preset initial parameter of the proportional term is used as the proportional term parameter of the PID controller for the current collection time, and the PID controller is used to adjust the wind speed of the fan in the air purification device.

[0021] An embodiment of the present application also provides an air purification device for use in a ventilation system, wherein the system includes a memory, a processor, and a computer program stored in the memory and running on the processor, and when the processor executes the computer program, the steps of any one of the above methods are implemented.

[0022] From the above, it can be seen that the air purification method and device for ventilation system provided by the present application have at least the following beneficial effects:

[0023] Centralized air handling systems are usually used in large buildings to uniformly purify indoor air. However, due to environmental changes and the influence of airflow disturbance on the rotation state of the fan of the purification device, the stability and efficiency of air purification are insufficient. In this application, the distribution characteristics of the data set composed of indoor and outdoor pressure difference data and production equipment power consumption data are used to calculate the influence coefficient of air quality. Its beneficial effect is to obtain the potential impact of environmental changes on air quality, and obtain the corresponding pollutant content characteristic sequence in combination with the pollutant content in the air, analyze the trend and random changes of the pollutant content characteristic sequence, and calculate the random change amount of pollutant trend, so as to reflect the change of pollutant content data in the air. Further analyze the influence of airflow disturbance on the fan's ability to generate wind pressure, and obtain the air purification influence factor in combination with the relevant characteristics of air quality changes. Its beneficial effect is to accurately reflect the state of air quality, calculate the proportional term parameters of PID control based on the air purification influence factor, and accurately control the air purification equipment. Different adjustment rates are set for different spaces to improve the stability and efficiency of air purification. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0025] Figure 1 A flow chart of the steps of the air purification method applied to the ventilation system provided in the present application;

[0026] Figure 2 Schematic diagram of the air purification device provided for this application. DETAILED DESCRIPTION

[0027] In order to further explain the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the following is a detailed description of the air purification method and device for ventilation system proposed in the present application, its specific implementation, structure, features and effects, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0028] Unless otherwise specified and limited, terms such as "comprises", "comprising" or any other variants thereof are intended to cover non-exclusive inclusion, so that a circuit structure, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such articles or devices. In the absence of further restrictions, an element defined by the sentence "comprising a ..." does not exclude the presence of other identical elements in the article or device including the element. In addition, the term "and\or" used herein includes any and all combinations of one or more related listed items. All technical and scientific terms used herein have the same meaning as those commonly understood by technicians in the technical field of this application.

[0029] The specific scheme of the air purification method and device for ventilation system provided by the present application is described in detail below with reference to the accompanying drawings.

[0030] See also Figure 1 , which shows a flow chart of the steps of an air purification method applied to a ventilation system provided by an embodiment of the present application, including the following steps:

[0031] Step 1: Obtain the content of each pollutant in the indoor air, the indoor and outdoor pressure difference, the wind speed data near the purification device and the power consumption data of each nearby device at each time period within the preset collection time.

[0032] Occupational diseases are various diseases that occur in workplaces in different fields. Occupational diseases mainly come from chemical factors, that is, the influence of environmental factors. When the air in the workplace is polluted, workers work in a polluted environment for a long time, which will have a great impact on the body and cause pneumoconiosis, dermatitis and allergic rhinitis. These diseases are usually caused by long-term inhalation of pollutants such as dust and harmful gases. The harm of air pollution to the human body is not limited to occupational diseases, but may also cause other health problems, such as respiratory diseases, cardiovascular diseases, etc. Therefore, this embodiment aims to efficiently purify toxic substances in the air of each workplace to reduce the risk of high incidence of occupational diseases due to low air quality in the workplace, where toxic substances in the air include many pollutants and particulate matter.

[0033] Furthermore, this embodiment takes industrial buildings as an example to purify the indoor air of the workplace. Air pollutants may be generated in industrial buildings due to the operation of production equipment. At present, indoor pollutants mainly include dust particles and gaseous pollutants. Gaseous pollutants are divided into gaseous organic pollutants and gaseous inorganic pollutants. Gaseous organic pollutants include formaldehyde, benzene, toluene, alkanes, etc., and gaseous inorganic pollutants include carbon monoxide, nitrogen dioxide, sulfur dioxide, etc.

[0034] Preferably, in this embodiment, an air quality detector is used to collect the pollutant content near the purification device. The pollutant content data in this embodiment include particulate matter content, formaldehyde content data, and nitrogen dioxide content data. Data analysis is performed on the particulate matter content, formaldehyde content data, and nitrogen dioxide content data to ultimately achieve air purification regulation.

[0035] In this embodiment, the data of particulate matter content, formaldehyde content and nitrogen dioxide content are mainly analyzed. In order to maintain ventilation and improve indoor air quality, an air purification device needs to be installed at a certain distance to meet the requirements of today's green buildings. The specific installation location and interval can be determined according to actual conditions. In this embodiment, the schematic diagram of the air purification device is as follows Figure 2 shown. Figure 2 Number 1 is the air inlet; number 2 is the fan; number 3 is the air purification module, which includes a filter, an electrostatic dust removal device, and a negative ion generator; number 4 is an intelligent control module, which is used to implement the air purification method of this embodiment, analyze the data and output control information, and adjust the fan speed; number 5 is the air outlet.

[0036] A square area with a length of M meters, centered on the air purification device, is used as the vicinity of the air purification device. The implementer can determine the value of M according to the actual situation of the industrial building. In this embodiment, M is set to 15. There may be one or more devices in the vicinity, which may easily produce harmful substances during operation. In this embodiment, the power consumption data of all devices near the purification device is obtained through a power meter. An air quality detector is used to collect the pollutant content near the purification device, including particulate matter content, formaldehyde content data, and nitrogen dioxide content data in this embodiment. An anemometer is installed near the purification device to collect wind speed data. A pressure sensor is used to collect pressure data indoors and outdoors of industrial buildings.

[0037] In this embodiment, the time interval for collecting each data is 1 second, and the collection time is set to 5 minutes. The difference between the indoor and outdoor pressure data collected at the same time is calculated as the indoor and outdoor pressure difference.

[0038] Furthermore, in this embodiment, in order to facilitate data analysis and expression and avoid dimensional influence, the collected data are normalized and arranged in ascending time order to obtain power consumption sequence, indoor and outdoor pressure difference sequence, pollutant content sequence and wind speed sequence, respectively. Among them, the pollutant content sequence in this embodiment includes formaldehyde content sequence, nitrogen dioxide content sequence, and particulate matter content sequence.

[0039] Step 2: The indoor and outdoor pressure difference and equipment power consumption data at each moment in each time period are combined into two-dimensional data, and all two-dimensional data in each time period are clustered. The influence coefficient of air quality at each moment in each time period is determined through the local density and relative distance of the two-dimensional data at each moment after clustering, as well as the average value of the indoor and outdoor pressure difference and equipment power consumption at each moment.

[0040] Industrial buildings use ventilation systems to maintain indoor air quality. Due to the pressure difference that may exist outdoors, the pressure difference causes indoor and outdoor air to circulate through doors, windows or gaps instead of flowing through the ventilation system, and brings outdoor air pollutants into the room, reducing air quality. Therefore, the pressure difference between indoor and outdoor has a certain impact on the efficiency of air purification. The greater the pressure difference, the greater the impact.

[0041] In addition, the production equipment in industrial buildings will also produce certain pollutants during operation, such as dust, smoke and other particulate matter, formaldehyde, nitrogen dioxide, etc. And the greater the power consumption of the equipment in the nearby area, the larger its production scale and equipment operation time are usually, the more pollutants may be generated. In the operation process of green buildings, it is necessary to effectively remove pollutants in indoor air through the efficient use of air purification devices to ensure that the indoor air quality meets health standards.

[0042] According to the above analysis, the indoor and outdoor pressure difference and the power consumption of production equipment are the key factors that lead to changes in air quality in industrial buildings, and the smaller the indoor and outdoor pressure difference and the equipment power consumption, the smaller the impact on air purification regulation. Taking the air purification device as an example, since the changes in the indoor and outdoor pressure difference and equipment power consumption have a certain randomness, it may cause a large change in indoor air in a short period of time. In order to accurately analyze the air state in different time periods, in this embodiment, the acquisition time is divided into 5 time periods of equal length, so as to analyze based on the data of each time period. Further, the impact of the indoor and outdoor pressure difference and equipment power consumption on air quality is comprehensively analyzed, and the indoor and outdoor pressure difference data and power consumption data at the same time are merged into a two-dimensional data, and all the two-dimensional data in each time period constitute the data set of each time period. Thus, each time period obtains a data set for subsequent analysis of the distribution characteristics of each data set.

[0043] Taking any of the air purification devices as an example, for the data set of the i-th time period, this embodiment uses the Density Peaks Clustering (DPC) algorithm for cluster analysis. The input of the DPC algorithm is the data set of the i-th time period, that is, all the two-dimensional data of the i-th time period. The cutoff distance is set to 2% of the total data, and the local density and relative distance of each two-dimensional data are output, where the local density reflects the concentration of the two-dimensional data within the cutoff distance range, and the relative distance is used to reflect the distance from the two-dimensional data to its nearest high-density two-dimensional data point. Each two-dimensional data corresponds to a moment, and the degree of influence on the air quality at each moment is analyzed based on the local density and relative distance of the two-dimensional data corresponding to each moment.

[0044] For ease of understanding and expression, in this embodiment, the local density and relative distance at the jth moment in the i-th time period after clustering are recorded as , If there is no significant change in the pressure difference and power data within a time period, the distribution of the data set is relatively concentrated, and the air quality is less affected.

[0045] Income The smaller it is, the fewer data points there are around the two-dimensional data. The larger it is, the farther the two-dimensional data is from the high-density data point. Then calculate the mean of the indoor and outdoor pressure difference and power consumption data at the jth moment in the i-th time period, and record it as , the income The larger the value, the more harmful substances may be produced in the air at that moment. Therefore, the influence coefficient of air quality at each moment in each time period is determined by clustering the local density and relative distance of the two-dimensional data at each moment, as well as the average value of the indoor and outdoor pressure difference and the equipment power consumption at each moment. The air quality influence coefficient calculation formula in this embodiment is:

[0046] ; In the formula, is the influence coefficient of air quality at the jth moment in the i-th time period, and The ratio reflects the difference between the two-dimensional data and other two-dimensional data. The larger the ratio, the greater the difference between the indoor and outdoor pressure difference data and the power consumption data at this moment and other moments, that is, the indoor and outdoor pressure difference or power consumption may change to a greater extent. The larger it is, the greater the impact of environmental changes on air quality at that moment.

[0047] At this point, the influence coefficient of air quality at each moment is obtained.

[0048] Step 3: According to the air quality impact coefficient at each moment in each time period, the characteristic sequence of each pollutant content is constructed in combination with the content of each pollutant in each time period.

[0049] According to the above process, the influence coefficient of air quality at each moment in each time period can be obtained, which reflects the potential impact of environmental changes on air quality at each moment. The particulate matter content data, formaldehyde content data and nitrogen dioxide content data collected at each moment reflect the air quality status at each moment. Potential environmental interference and air quality status may change the intensity of air purification. Therefore, the product of the influence coefficient of air quality at each moment in each time period and the pollutant content is arranged in ascending order of time to form a pollutant content characteristic sequence for each time period.

[0050] In this embodiment, taking the particulate matter content in the air in the i-th time period as an example, the product of the air quality influence coefficient and the particulate matter content at each moment is calculated, and the sequence formed by the products in ascending time order is used as the particulate matter content characteristic sequence of the i-th time period. Correspondingly, for the formaldehyde content data and the nitrogen dioxide content data, the formaldehyde content characteristic sequence and the nitrogen dioxide content characteristic sequence of the i-th time period are obtained, and the air quality in each time period is further evaluated based on this.

[0051] Step 4: By analyzing the changing trend and random change degree of the characteristic sequence of each pollutant content, the abnormal fluctuation coefficient of each pollutant content in each time period is obtained, and the random change amount of the pollutant trend in each time period is obtained by combining the abnormal fluctuation coefficient of all pollutant contents in each time period.

[0052] Furthermore, the changing trend of the pollutant content characteristic sequence is analyzed to detect the change of pollutants in the air. In this embodiment, the Mann-Kendall algorithm is used to perform a trend test on the particle content characteristic sequence. The input of the algorithm is the particle content characteristic sequence, and the output is the trend statistic of the sequence, which is recorded as The larger the trend statistic, the more significant the trend of increasing particulate matter content in the air during this time period.

[0053] In industrial buildings, factors such as material handling and personnel movement may cause disturbances in air flow and particulate matter, resulting in rapid changes in the particle content characteristic sequence in a short period of time. Therefore, in order to analyze the degree of disorder in the change of particulate matter content in the air, this embodiment uses the Higuchi algorithm to analyze its rapid change characteristics. The particle content characteristic sequence of the i-th time period is input, and the output is the fractal dimension of the particle content characteristic sequence, which is recorded as , which is used to characterize the random changes in the characteristic sequence of particle content. It can be understood that the obtained The larger it is, the more obvious the random fluctuation and rapid change characteristics in the characteristic sequence of particle content are.

[0054] Furthermore, in this embodiment, the product of the fractal dimension and the trend statistic of the characteristic sequence of the particle content is analyzed, that is, and The product of is taken as the abnormal fluctuation coefficient of the particle content in the i-th time period, recorded as , the income The larger it is, the more likely it is that the particulate matter content in that time period has increased abnormally.

[0055] According to the above process of this embodiment, for the characteristic sequence of formaldehyde content and the characteristic sequence of nitrogen dioxide content in each time period, the above same method steps can be used to obtain the abnormal fluctuation coefficients of formaldehyde content and nitrogen dioxide content in the i-th time period, which are recorded as , At the same time, it is understandable that as well as The larger the value, the more likely it is that the formaldehyde and nitrogen dioxide levels in that time period have increased abnormally.

[0056] The random change amount of pollutant trend in each time period is the sum of the abnormal fluctuation coefficients of all pollutant contents in each time period. In this embodiment, the pollutant content includes particulate matter content and formaldehyde and nitrogen dioxide content. Therefore, the corresponding calculation formula is specifically:

[0057] ; In the formula, represents the random change of pollutant trend in the i-th time period, and the obtained The larger it is, the more frequently the air quality status changes during this time period, and the greater the impact on the intensity of air conditioning.

[0058] Step 5: Determine the airflow disturbance coefficient for each time period based on the fluctuation degree and average level of wind speed data in each time period. Determine the air purification influencing factor based on the similarity between the airflow disturbance coefficient and the random change of pollutant trend, combined with the average level of all pollutant content in all time periods, and adjust the air purification.

[0059] Green buildings need to achieve the goals of high efficiency and energy saving in air purification and regulation, and can adjust the air quality near different air purification devices separately. The rotation state of the fan of the air purification device may be affected by the nearby air flow disturbance. The fan blades may generate more vortices and resistance due to the strong air flow nearby, which will reduce the fan's air volume and pressure, thereby affecting its air purification effect. In addition, air flow disturbances will also have a certain degree of impact on the change of air quality state. Therefore, the relationship between the correlation characteristics of the wind speed sequence and the random change amount of pollutant trends is further analyzed.

[0060] Furthermore, in this embodiment, the product of the standard deviation and the mean of the wind speed sequence in the i-th time period is calculated as the airflow disturbance coefficient in the i-th time period, which is recorded as . The larger it is, the stronger the airflow near the air purification device is during this time period and the greater its degree of variation, which has a greater impact on the fan rotation.

[0061] Furthermore, the random change amount of pollutant trend and airflow disturbance coefficient of each time period are arranged in ascending time order to form vectors, and are recorded as P and Q respectively. The absolute value of the cosine similarity between vectors P and Q is calculated and recorded as S. The larger the obtained S is, the closer the air quality change characteristics near the air purification device are to the airflow change characteristics, and the greater the impact on the air purification effect may be. Further, the air purification influencing factor is obtained in combination with the amount of air pollutants. Calculate the average value of all formaldehyde content, nitrogen dioxide content and particulate matter content within the collection time, recorded as U. The larger the obtained U is, the more pollutants there are in the air.

[0062] According to the similarity between the airflow disturbance coefficient and the random change of the pollutant trend, combined with the average level of all pollutant contents in all time periods, the air purification influence factor is determined, and the product of the average value of all pollutant contents in all time periods and the similarity between the above two vectors P and Q is used as the air purification influence factor. For ease of understanding, in this embodiment, the calculation formula of the air purification influence factor is as follows:

[0063] ; In the formula, W is the air purification influencing factor during the collection period. The larger the W is, the worse the air quality near the purification device is, and the more adjustment is needed.

[0064] This embodiment analyzes the changing characteristics of the air pollutant content in the industrial building and combines the impact of air flow disturbance on air quality to obtain the air purification impact factor W, which is used to reflect the air state and the degree of impact on air quality. The wind speed of the fan in the air purification device is adjusted based on the air purification impact factor, and the fan of the air purification device is regulated by a PID controller.

[0065] Specifically, the larger the W, the worse the air quality state is. At this time, the proportional term parameter in the PID should be increased to improve the response speed of the system and make adjustments quickly. The smaller the W, the better the air quality state is. At this time, the proportional term parameter in the PID can be reduced.

[0066] In this embodiment, the air purification influence factors of all air purification devices are normalized using the Z-Score method, and the proportional term, integral term, and differential term in the PID control initial parameters are set to 3, 0.5, and 0.5, respectively. With each acquisition time as the adjustment interval, for each air purification device, the sum of the normalized result of the air purification influence factor calculated for the previous acquisition time of the current acquisition time and the preset proportional term initial parameter (the value is 3 in this embodiment) is used as the PID controller proportional term parameter corresponding to the current acquisition time, and the PID controller is used to adjust the wind speed of the fan in the air purification device, which helps to realize intelligent air purification control in the operation of green buildings.

[0067] Thus, according to the above process of this embodiment, the air in the workplace can be purified, various occupational diseases of workers in the workplace caused by air pollution can be prevented, and the air purification effect can be improved.

[0068] Based on the same inventive concept as the above method, an embodiment of the present application also provides an air purification device applied to a ventilation system, including a memory, a processor, and a computer program stored in the memory and running on the processor, and when the processor executes the computer program, the steps of any one of the above-mentioned air purification methods applied to the ventilation system are implemented.

[0069] It is to be understood that the sequence of the embodiments of the present application described above is for description only and does not represent the advantages and disadvantages of the embodiments. The above describes specific embodiments of the present specification. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0070] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0071] The above content is only an implementation method of the present application and is not intended to limit the scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly used in other related technical fields, are also included in the protection scope of the present application.

Claims

1. An air purification method for a ventilation system, characterized in that: The following steps are involved: Obtain the content of each pollutant in the indoor air, the pressure difference between indoor and outdoor, and the wind speed data near the purification device and the power consumption data of each nearby device at each time period within the preset collection time; The indoor and outdoor pressure difference and equipment power consumption data at each time in each time period are combined into two-dimensional data, and all the two-dimensional data in each time period are clustered. The influence coefficient of air quality at each time in each time period is determined through the local density and relative distance of the two-dimensional data at each time after clustering, as well as the average value of the indoor and outdoor pressure difference and equipment power consumption at each time; According to the air quality impact coefficient at each time in each time period, the characteristic sequence of each pollutant content is constructed in combination with the content of each pollutant in each time period; by analyzing the change trend and random change degree of the characteristic sequence of each pollutant content, the abnormal fluctuation coefficient of each pollutant content in each time period is obtained, and the random change amount of the pollutant trend in each time period is obtained by combining the abnormal fluctuation coefficient of all pollutant contents in each time period; According to the fluctuation degree and average level of wind speed data in each time period, the airflow disturbance coefficient of each time period is determined. According to the similarity between the airflow disturbance coefficient and the random change of pollutant trend, combined with the average level of all pollutant content in all time periods, the air purification influencing factor is determined and the air purification is regulated.

2. The air purification method for a ventilation system according to claim 1, characterized in that: The pollutant contents further include particulate matter content, formaldehyde content, and nitrogen dioxide content.

3. The air purification method for a ventilation system according to claim 1, characterized in that: The calculation formula of the influence coefficient of air quality at each time in each time period is: ; In the formula, is the influence coefficient of air quality at the jth moment in the i-th time period, , are the local density and relative distance at the jth moment in the i-th time period after clustering, is the mean value of the indoor and outdoor pressure difference and power consumption data at the jth moment in the i-th time period.

4. The air purification method for a ventilation system according to claim 1, characterized in that: The construction of the characteristic sequence of each pollutant content further includes: The product of the air quality influence coefficient and the pollutant content at each moment in each time period is arranged in ascending time order to form a pollutant content characteristic sequence for each time period.

5. The air purification method for a ventilation system according to claim 1, characterized in that: The abnormal fluctuation coefficient of each pollutant content is the product of the fractal dimension of the characteristic sequence of each pollutant content and the trend statistic.

6. The air purification method for a ventilation system according to claim 1, characterized in that: The random variation of pollutant trends in each time period is the sum of the abnormal fluctuation coefficients of all pollutant contents in each time period.

7. The air purification method for a ventilation system according to claim 1, characterized in that: The airflow disturbance coefficient of each time period is the product of the standard deviation and the mean of all wind speed data in each time period.

8. The air purification method for a ventilation system according to claim 1, characterized in that: The determination of the air purification influencing factor further includes: arranging the random change amount of the pollutant trend and the airflow disturbance coefficient in each time period in ascending time order to form a vector, and taking the product of the average value of all pollutant contents in all time periods and the similarity between the two vectors as the air purification influencing factor.

9. The air purification method for a ventilation system according to claim 1, characterized in that: The control of air purification further comprises: The air purification influencing factor is normalized, and the sum of the normalized result of the air purification influencing factor calculated for the previous collection time of the current collection time and the preset initial parameter of the proportional term is used as the proportional term parameter of the PID controller for the current collection time, and the PID controller is used to adjust the wind speed of the fan in the air purification device.

10. An air purification device for a ventilation system, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 9 are implemented.

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