Centralized intelligent control method and system for air purifier

Abstract

The present invention relates to the field of air purification control technology, and in particular to a centralized intelligent control method and system for air purifiers. The method comprises the following steps: by integrating a pre-installed filter assembly, a UV assembly and a wall control assembly in the air purifier; by using the filter assembly to monitor the operation process of the filter on it in real time, and obtain a real-time parameter set of the operation process of the filter assembly; by using the UV assembly to monitor the light output intensity of the UV indicator on it in real time, and at the same time perform operation resistance calculation and component remaining service life estimation, obtain the remaining service life of the filter assembly and the remaining service life of the UV assembly, and perform visual display processing and centralized intelligent control processing, generate a centralized intelligent control strategy for system components, and execute the corresponding centralized control work of the air purifier system components. The present invention can realize centralized control and management of all components of the air purifier.

Description

Technical Field

[0001] The present invention relates to the technical field of air purification control, and in particular to a centralized intelligent control method and system for an air purifier. Background Art

[0002] With the acceleration of urbanization and the increase of industrial activities, indoor air quality problems are becoming increasingly serious. Air purifiers play a vital role in improving indoor air quality. The traditional centralized intelligent control method establishes a centralized intelligent control platform to connect multiple air purifiers to a unified control center, which can receive and process status data from each air purifier in real time, realize centralized monitoring and management, and automatically adjust the operation mode and parameters of the air purifier according to real-time air quality data and prediction models by applying intelligent control algorithms. It can dynamically adjust the wind speed, operating time, etc. of the equipment to ensure optimized purification effect and energy efficiency. However, in the prior art, although there are many air purifiers equipped with high-efficiency filters and UV sterilization components, they usually rely on a single control mode, but often cannot timely understand the service life of the filter and UV lamp, resulting in reduced purification effect and excessive use of equipment components. Summary of the invention

[0003] Based on this, it is necessary for the present invention to provide a centralized intelligent control method and system for an air purifier to solve at least one of the above technical problems.

[0004] To achieve the above object, a centralized intelligent control method for an air purifier comprises the following steps:

[0005] Step S1: pre-installing a filter assembly, a UV assembly and a wall control assembly by integrating a fresh air fan ventilation system in the air purifier, wherein the filter assembly and the UV assembly are electrically connected to the wall control assembly; monitoring the operation process of the filter on the filter assembly in real time through a time monitor, a pressure sensor and an air particle flow meter built into the filter assembly, and obtaining a real-time parameter set of the filter assembly operation process, wherein the real-time parameter set of the filter assembly operation process includes the filter operation time, the filter operation pressure change and the air particle flow rate of the filter operation process; monitoring the light output intensity of the UV indicator light on the UV assembly in real time through a light intensity sensor built into the UV assembly, and obtaining the light output intensity of the UV assembly; transmitting the real-time parameter set of the filter assembly operation process and the light output intensity of the UV assembly to the central intelligent control unit in the wall control assembly;

[0006] Step S2: using the central intelligent control unit to calculate the operating resistance of the filter mesh operating time and the filter mesh operating pressure change in the real-time parameter set of the filter mesh component operating process, so as to obtain the filter mesh operating resistance; based on the filter mesh operating time, the filter mesh operating resistance and the air particle flow rate during the filter mesh operating process, the filter mesh component is estimated to have a remaining service life, so as to obtain the remaining service life of the filter mesh component;

[0007] Step S3: estimating the remaining service life of the UV component based on the light output intensity of the UV component to obtain the remaining service life of the UV component;

[0008] Step S4: Visually display the remaining service life of the filter component and the remaining service life of the UV component through the display system in the wall control component to obtain the service life display results of the air purifier system components; based on the preset component service life risk threshold, use the central intelligent control unit to centrally intelligently control the fresh air fan ventilation system components corresponding to the service life display results of the air purifier system components, and generate a centralized intelligent control strategy for the system components to execute the corresponding centralized control work of the air purifier system components.

[0009] Further, step S1 includes the following steps:

[0010] Step S11: pre-installing a filter assembly, a UV assembly and a wall control assembly by integrating a fresh air fan ventilation system in the air purifier, wherein the filter assembly and the UV assembly are electrically connected to the wall control assembly;

[0011] Step S12: monitoring the operation time of the filter on the filter assembly in real time by using the built-in time monitor of the filter assembly to obtain the operation time of the filter; monitoring the operation pressure of the filter on the filter assembly in real time by using the built-in pressure sensor of the filter assembly to obtain the operation pressure change of the filter; monitoring the operation particle flow of the filter on the filter assembly in real time by using the built-in air particle flow meter of the filter assembly to obtain the air particle flow during the operation of the filter;

[0012] Step S13: merging the filter operation parameters including the filter operation time, the filter operation pressure change, and the air particle flow rate during the filter operation process to obtain a real-time parameter set of the filter component operation process;

[0013] Step S14: Using the built-in light intensity sensor of the UV component to monitor the light output intensity of the UV indicator light on the UV component in real time, to obtain the light output intensity of the UV component;

[0014] Step S15: The real-time parameter set of the filter component operation process and the light output intensity of the UV component are transmitted to the central intelligent control unit in the wall control component through the wireless transmission network.

[0015] Further, step S2 includes the following steps:

[0016] Step S21: using the central intelligent control unit to perform an operation pressure simulation analysis on the filter operation time and the filter operation pressure change in the real-time parameter set of the filter assembly operation process, to obtain a filter operation pressure fluid simulation change field;

[0017] Step S22: calculating the running resistance of the filter screen running pressure fluid simulation change field to obtain the running resistance of the filter screen;

[0018] Step S23: evaluating and calculating the particle capture efficiency according to the filter operation time and the air particle flow rate during the filter operation process, and obtaining the filter operation particle capture efficiency;

[0019] Step S24: performing a wind speed calibration calculation on the filter wind speed on the filter assembly based on the filter running resistance and the filter running particle capture efficiency using the filter wind speed calibration calculation formula to obtain the filter running calibration wind speed;

[0020] Step S25: estimating the remaining service life of the filter assembly based on the filter operation time and the calibrated wind speed used in the filter operation to obtain the remaining service life of the filter assembly.

[0021] Further, step S22 includes the following steps:

[0022] Perform pressure distribution analysis on the simulated change field of the filter screen's operating pressure fluid to obtain distribution values ​​of operating pressure changes at different coordinate positions of the filter screen;

[0023] The pressure difference between the positions is calculated for the distribution values ​​of the operating pressure changes at different coordinate positions of the filter screen, so as to obtain the operating distribution pressure difference between different positions of the filter screen;

[0024] Performing statistical analysis on the air fluid flow rate of the filter screen operating pressure fluid simulation change field to obtain the air fluid flow rate of the filter screen operating;

[0025] The filter resistance coefficient is calculated according to the operating distribution pressure difference between different positions of the filter and the air fluid flow rate of the filter, so as to obtain the air distribution resistance coefficient of the filter;

[0026] The running resistance of the filter is calculated based on the air distribution resistance coefficient of the filter, and the running resistance of the filter is obtained.

[0027] Further, step S23 includes the following steps:

[0028] Step S231: dividing the air particle flow rate during the operation of the filter into the filter inlet and outlet components to obtain the air particle flow rate during the operation of the filter and the air particle flow rate during the operation of the filter;

[0029] Step S232: based on the filter operation time, a particle flow hyperbola is plotted for the inlet air particle flow rate and the outlet air particle flow rate during the filter operation process, so as to generate a filter operation inlet and outlet air particle flow hyperbola;

[0030] Step S233: analyzing the particle concentration change of the air particle flow rate at the inlet of the filter and the air particle flow rate at the outlet of the filter during operation to obtain the particle concentration change at the inlet of the filter and the particle concentration change at the outlet of the filter during operation;

[0031] Step S234: based on the change concentration of the inlet particulate matter during the operation of the filter and the change concentration of the outlet particulate matter during the operation of the filter, the particle capture efficiency is evaluated and calculated using the particle capture efficiency evaluation calculation formula for the inlet and outlet air particle flow hyperbola of the filter operation to obtain the particle capture efficiency of the filter operation;

[0032] Among them, the particle capture efficiency evaluation calculation formula is as follows:

[0033] ;

[0034] In the formula, To operate the particle capture efficiency of the filter, The concentration of inlet particles changes during the filter operation process. The concentration of particulate matter at the outlet of the filter during operation. For the evaluation period, is the time variable parameter, Hyperbolic internal time of the air particle flow rate at the inlet and outlet of the filter The air particle flow rate at the filter inlet at Hyperbolic internal time of the air particle flow rate at the inlet and outlet of the filter The air particle flow rate at the filter outlet at is the differential attenuation coefficient of the air particle flow rate at the inlet and outlet of the filter, A correction factor for the filter's operating particle capture efficiency.

[0035] Furthermore, the filter screen in step S24 uses the wind speed calibration calculation formula as follows:

[0036] ;

[0037] In the formula, Use the calibrated air speed for filter operation. Use the wind speed for the filter on the filter assembly. To operate the particle capture efficiency of the filter, is the effective diameter of the filter space, is the total airflow pressure at the filter inlet, For the diameter distance The filter pressure loss at is the filter running resistance, is the constant affecting the particle deposition efficiency of the filter, is the particle diameter parameter, is the nonlinear influence coefficient of particle deposition behavior, Use the correction factor for the calibrated air speed for filter operation.

[0038] Further, step S25 includes the following steps:

[0039] Step S251: Obtain the total filtration service life of the filter assembly to obtain the total service life of the filter assembly;

[0040] Step S252: performing filter performance evaluation and analysis on the filter assembly based on the filter operation time to obtain filter performance change data during the filter operation time;

[0041] Step S253: analyzing the wind speed performance attenuation impact of the filter performance change data during the filter operation period based on the filter operation calibration wind speed, and obtaining the filter operation wind speed performance attenuation impact factor;

[0042] Step S254: Estimate the remaining service life of the filter assembly according to the total service life of the filter assembly, the operating time of the filter, and the attenuation factor affecting the wind speed performance of the filter operation to obtain the remaining service life of the filter assembly.

[0043] Further, step S3 includes the following steps:

[0044] Step S31: Performing light intensity environment attenuation analysis on the UV component to obtain light intensity environment attenuation parameters of the UV component;

[0045] Step S32: Calculate the effective use time of the UV component based on the UV component light output intensity and the UV component light intensity environment attenuation parameter to obtain the effective use time of the UV component light output;

[0046] Step S33: obtaining the standard light intensity output intensity of the UV component, and performing a performance status evaluation and analysis on the UV component based on the light output intensity of the UV component and the standard light intensity output intensity, to obtain the actual performance status percentage of the UV component lamp;

[0047] Step S34: estimating the remaining service life of the UV component based on the effective use time of the UV component light output and the actual performance status percentage of the UV component lamp to obtain the remaining service life of the UV component.

[0048] Further, step S4 includes the following steps:

[0049] Step S41: Visually display the remaining service life of the filter assembly and the remaining service life of the UV assembly through the display system in the wall control assembly to obtain the service life display result of the air purifier system assembly;

[0050] Step S42: performing component life risk warning processing on the corresponding air purifier system component life display result according to the preset component life risk threshold, and obtaining air purifier system component life risk warning information;

[0051] Step S43: using the central intelligent control unit to perform component life intelligent control response to the air purifier system component life risk warning information to generate a system component life intelligent control response instruction;

[0052] Step S44: Based on the system component service life intelligent control response instruction, the fresh air fan ventilation system components corresponding to the air purifier system component service life risk warning information are centrally intelligently controlled and processed to generate a system component centralized intelligent control strategy to execute the corresponding air purifier system component centralized control work.

[0053] Furthermore, the present invention also provides an air purifier centralized intelligent control system for executing the above-mentioned air purifier centralized intelligent control method, and the air purifier centralized intelligent control system includes:

[0054] The purifier system component operation parameter monitoring module is used to integrate the pre-installed filter assembly, UV assembly and wall control assembly in the fresh air fan ventilation system in the air purifier, wherein the filter assembly and the UV assembly are electrically connected to the wall control assembly; the operation process of the filter on the filter assembly is monitored in real time through the built-in time monitor, pressure sensor and air particle flow meter of the filter assembly to obtain the real-time parameter set of the filter assembly operation process, wherein the real-time parameter set of the filter assembly operation process includes the filter operation time, the filter operation pressure change and the air particle flow rate of the filter operation process; the light output intensity of the UV indicator light on the UV assembly is monitored in real time through the built-in light intensity sensor of the UV assembly to obtain the light output intensity of the UV assembly; the real-time parameter set of the filter assembly operation process and the light output intensity of the UV assembly are transmitted to the central intelligent control unit in the wall control assembly;

[0055] The filter component life estimation module is used to calculate the operating resistance of the filter component in the real-time parameter set of the filter component operation process and the filter component operation pressure change using the central intelligent control unit to obtain the filter component operation resistance; based on the filter component operation time, the filter component operation resistance and the air particle flow rate during the filter component operation process, the filter component remaining service life is estimated to obtain the remaining service life of the filter component;

[0056] The UV component service life estimation module is used to estimate the UV remaining service life of the UV component based on the light output intensity of the UV component, thereby obtaining the remaining service life of the UV component;

[0057] The centralized intelligent control module of the purifier system components is used to visualize the remaining service life of the filter component and the remaining service life of the UV component through the display system in the wall control component to obtain the service life display results of the air purifier system components; according to the preset component service life risk threshold, the fresh air fan ventilation system components corresponding to the service life display results of the air purifier system components are centrally intelligently controlled and processed to generate a centralized intelligent control strategy for the system components to execute the corresponding centralized control work of the air purifier system components.

[0058] Beneficial effects of the present invention:

[0059] 1. Compared with the prior art, the centralized intelligent control method for air purifiers proposed in the present invention has the beneficial effect of integrating and pre-installing corresponding filter components, UV components and wall control components in the fresh air fan ventilation system in the air purifier, wherein the filter component can effectively capture tiny particles and harmful substances, thereby providing high-quality air purification effects, and the UV component can further improve the cleanliness of the air through ultraviolet lamp disinfection, which can kill bacteria and viruses in the air and enhance air hygiene protection. The wall control component, as a control center, is not only convenient for users to operate, but also can monitor and adjust the working status of the filter and UV components in real time through electrical connection, providing basic data guarantee for the subsequent centralized control and management of the service life of the filter components and UV components. By using the time monitor, pressure sensor and air particle flow meter integrated in the filter assembly to monitor the operating parameters of the filter on the filter assembly in real time, the operating status of the filter can be fully monitored. The time monitor provides real-time filter usage time data to help users understand the specific usage time of the filter during the air purification process. The pressure sensor can detect the working pressure changes of the filter and promptly reflect the blockage of the filter to avoid equipment damage or poor air circulation caused by excessive blockage. The air particle flow meter monitors the flow of particulate matter in the air in real time, providing a more intuitive air quality indicator. The real-time monitoring of these data enables timely maintenance and adjustment when necessary. By using the built-in light intensity sensor of the UV component to monitor the light output intensity of the UV indicator on the UV component in real time, the light intensity sensor can detect the actual output intensity of the UV lamp and compare it with the preset standard, thereby providing data support for the subsequent UV component service life analysis. At the same time, by using a wireless transmission network to transmit the real-time parameter set of the filter component and the light output intensity of the UV component to the central intelligent control unit in the wall control component, the instant sharing and intelligent processing of data can be realized. This mechanism not only enhances the intelligence of the air purifier, but also provides users with a convenient information acquisition channel. Users can view the service life and working status of the air purifier system components in real time through the wall control component, and timely understand the air quality and equipment performance. This transparent information exchange method greatly improves the user experience and enables users to manage equipment more actively, thereby providing data guarantee for the subsequent centralized control processing process. Secondly, by using the central intelligent control unit to calculate the operating resistance of the filter running time and the filter running pressure change in the real-time parameter set of the filter component running process, the resistance encountered by the filter during operation can be effectively evaluated. This process can quantify the fluid resistance of the filter in actual operation, revealing the impact of the filter on the airflow and its actual effect in air purification. Through the accurate calculation of the resistance, the performance changes of the filter at different stages of use can be identified, thereby providing data support for subsequent maintenance and replacement.By estimating the remaining service life of the filter assembly based on the filter operation time, filter operation resistance, and air particle flow rate during the filter operation process, users can effectively plan the maintenance and replacement cycle of the filter assembly. This estimation not only takes into account the actual use of the filter, but also combines the current operating conditions, such as operating resistance and operating air particle flow rate. The evaluation of the remaining life of the corresponding filter assembly through the above parameters can provide a more accurate service life expectation, allowing users to perform maintenance at the appropriate time to avoid the decline in air purification effect and excessive use of the filter assembly due to filter failure. Then, by estimating the remaining service life of the UV assembly based on the light output intensity of the UV assembly, an important reference can be provided for the subsequent control and management of the UV assembly. This step calculates the light output intensity of the UV assembly through a certain algorithm model, and finally obtains the remaining service life of the UV assembly, so that operators can make reasonable maintenance and replacement plans before the UV assembly approaches the use limit, reducing the decline in purification effect and excessive use caused by UV assembly failure. Finally, by using the display system in the wall control component to visualize the remaining service life of the filter component and the remaining service life of the UV component, the user's intuitive understanding of the use status of the air purifier system components can be improved. This visual information display can promptly remind users to replace or maintain components to avoid the decline in air purification effect due to the aging of the filter or UV lamp. The visualization of the service life can effectively reduce the user's operating burden and improve the use efficiency of the air purifier. By using the central intelligent control unit to centrally and intelligently control the fresh air fan ventilation system components corresponding to the service life display results of the air purifier system components based on the preset component service life risk threshold, a set of systematic system component centralized replacement control strategies can be formed. This centralized management method enables different components to work effectively together to maximize overall efficiency, ensure that each component coordinates and cooperates in the best operating state, and further improve the efficiency of air purification.

[0060] 2. The centralized intelligent control system of air purifier proposed in the present invention is generally composed of a purifier system component operating parameter monitoring module, a filter component service life estimation module, a UV component service life estimation module and a purifier system component centralized intelligent control module. It can implement any air purifier centralized intelligent control method described in the present invention, and is used to combine the operations between computer programs running on each module to implement the air purifier centralized intelligent control method. The internal structures of the system cooperate with each other, which can greatly reduce duplication of work and manpower investment, and can quickly and effectively provide a more accurate and efficient air purifier centralized intelligent control process, thereby simplifying the operation process of the air purifier centralized intelligent control system. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments thereof made with reference to the following drawings:

[0062] Figure 1 A schematic diagram of the steps of the centralized intelligent control method for an air purifier of the present invention;

[0063] Figure 2 for Figure 1 Detailed step flow diagram of step S1;

[0064] Figure 3 for Figure 1 Detailed step flow chart of step S2 in FIG. DETAILED DESCRIPTION

[0065] The technical method of the present invention is described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by technicians in this field without creative work are within the scope of protection of the present invention.

[0066] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor methods and / or microcontroller methods.

[0067] It should be understood that, although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another unit. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0068] To achieve this, please refer to Figures 1 to 3 The present invention provides a centralized intelligent control method for an air purifier, the method comprising the following steps:

[0069] Step S1: pre-installing a filter assembly, a UV assembly and a wall control assembly by integrating a fresh air fan ventilation system in the air purifier, wherein the filter assembly and the UV assembly are electrically connected to the wall control assembly; monitoring the operation process of the filter on the filter assembly in real time through a time monitor, a pressure sensor and an air particle flow meter built into the filter assembly, and obtaining a real-time parameter set of the filter assembly operation process, wherein the real-time parameter set of the filter assembly operation process includes the filter operation time, the filter operation pressure change and the air particle flow rate of the filter operation process; monitoring the light output intensity of the UV indicator light on the UV assembly in real time through a light intensity sensor built into the UV assembly, and obtaining the light output intensity of the UV assembly; transmitting the real-time parameter set of the filter assembly operation process and the light output intensity of the UV assembly to the central intelligent control unit in the wall control assembly;

[0070] Step S2: using the central intelligent control unit to calculate the operating resistance of the filter mesh operating time and the filter mesh operating pressure change in the real-time parameter set of the filter mesh component operating process, so as to obtain the filter mesh operating resistance; based on the filter mesh operating time, the filter mesh operating resistance and the air particle flow rate during the filter mesh operating process, the filter mesh component is estimated to have a remaining service life, so as to obtain the remaining service life of the filter mesh component;

[0071] Step S3: estimating the remaining service life of the UV component based on the light output intensity of the UV component to obtain the remaining service life of the UV component;

[0072] Step S4: Visually display the remaining service life of the filter component and the remaining service life of the UV component through the display system in the wall control component to obtain the service life display results of the air purifier system components; based on the preset component service life risk threshold, use the central intelligent control unit to centrally intelligently control the fresh air fan ventilation system components corresponding to the service life display results of the air purifier system components, and generate a centralized intelligent control strategy for the system components to execute the corresponding centralized control work of the air purifier system components.

[0073] In the embodiment of the present invention, please refer to Figure 1 FIG. 1 is a flow chart of the steps of the centralized intelligent control method for an air purifier according to the present invention. In this example, the centralized intelligent control method for an air purifier includes the following steps:

[0074] Step S1: pre-installing a filter assembly, a UV assembly and a wall control assembly by integrating a fresh air fan ventilation system in the air purifier, wherein the filter assembly and the UV assembly are electrically connected to the wall control assembly; monitoring the operation process of the filter on the filter assembly in real time through a time monitor, a pressure sensor and an air particle flow meter built into the filter assembly, and obtaining a real-time parameter set of the filter assembly operation process, wherein the real-time parameter set of the filter assembly operation process includes the filter operation time, the filter operation pressure change and the air particle flow rate of the filter operation process; monitoring the light output intensity of the UV indicator light on the UV assembly in real time through a light intensity sensor built into the UV assembly, and obtaining the light output intensity of the UV assembly; transmitting the real-time parameter set of the filter assembly operation process and the light output intensity of the UV assembly to the central intelligent control unit in the wall control assembly;

[0075] In an embodiment of the present invention, a fresh air fan ventilation system is integrated in the design process of the air purifier, and the system includes two pre-installed filter components, two UV components and a wall control component, wherein the filter component and the UV component are electrically connected to the wall control component via a cable to ensure that they can work in coordination. At the same time, a time monitor, a pressure sensor and an air particle flow meter are integrated inside the filter component, wherein the time monitor is used to track the operating time of the filter on the filter component in real time, the pressure sensor continuously monitors the operating pressure change of the filter, and the air particle flow meter monitors the air particle flow on the filter, and a hot wire or ultrasonic flow measurement technology is used to obtain flow data in real time, thereby obtaining the corresponding filter operating time, filter operating pressure change and air particle flow during the filter operation process. Secondly, the data processing module is used to combine the filter operation time, filter operation pressure change and air particle flow rate obtained by real-time monitoring in the past, so as to transmit the data obtained from the time monitor, pressure sensor and air particle flow meter to the data processing unit through the communication interface. The unit adopts a data fusion algorithm to combine various parameters and generate a real-time parameter set, thereby obtaining a real-time parameter set for the operation process of the filter assembly. Then, the light output intensity of the UV indicator light is monitored in real time by using the built-in light intensity sensor of the UV assembly. The light intensity sensor adopts a photodiode or a photoresistor, which can accurately measure the light intensity emitted by the UV lamp, thereby obtaining the light output intensity of the UV assembly. Finally, the real-time parameter set of the filter assembly operation process and the light output intensity of the UV assembly are transmitted to the central intelligent control unit of the wall control assembly by using a wireless transmission network. The process uses Bluetooth or Wi-Fi modules for data transmission to ensure efficient and stable connection.

[0076] Step S2: using the central intelligent control unit to calculate the operating resistance of the filter mesh operating time and the filter mesh operating pressure change in the real-time parameter set of the filter mesh component operating process, so as to obtain the filter mesh operating resistance; based on the filter mesh operating time, the filter mesh operating resistance and the air particle flow rate during the filter mesh operating process, the filter mesh component is estimated to have a remaining service life, so as to obtain the remaining service life of the filter mesh component;

[0077] In an embodiment of the present invention, a central intelligent control unit uses fluid dynamics simulation software to simulate and model the operating pressure of the filter operating time and the filter operating pressure change previously obtained by quantitative calculation, so as to establish a fluid simulation model of the filter. During the simulation process, the air flow rate, particle concentration and environmental conditions are considered, and the pressure change field of the filter is generated by numerical calculation. The pressure change behavior of the fluid in the filter is simulated by using computational fluid dynamics software, that is, the pressure change field of the filter is obtained. By setting different boundary conditions and initial conditions, the simulation calculation is performed to obtain the corresponding pressure distribution value, and the pressure difference between different positions is calculated, so as to calculate the pressure difference between each position by selecting a key position, and the air flow rate is statistically calculated by collecting the air flow changes at different positions and averaging them, so as to quantitatively calculate the air fluid flow rate when the filter is running. At the same time, the resistance coefficient is quantitatively calculated by combining the pressure difference and air fluid flow rate obtained by the previous quantitative calculation, for example ,in is the drag coefficient, is the calculated pressure difference, is the air density, The air flow rate is used to quantify the resistance coefficient of the filter, and the corresponding filter operation pressure fluid simulation change field is calculated by combining the resistance coefficient obtained by the previous quantitative calculation, so as to calculate the operation resistance through the following calculation formula ,in is the running resistance of the filter, is the drag coefficient, The total resistance of the filter under actual operation is calculated by combining the previously obtained air inflow and outflow particle flow rates at the filter, and the air inflow and outflow concentrations at the filter by combining the filter operation time statistics. A suitable calculation formula is constructed by combining the air inflow and outflow particle flow rates and concentrations. , to quantify the capture efficiency in different time periods, and then, by combining the operating resistance, capture efficiency and related parameters, a suitable calculation formula is formed to calibrate the wind speed of the filter assembly in the current process, thereby affecting the calibration calculation to obtain the actual use wind speed of the filter in the current operating state, and by obtaining the total service life of the filter assembly before the purification and filtration process of the air purifier is started, which is generally , by combining the filter operation time obtained by previous real-time monitoring, the performance evaluation and analysis of the corresponding filter assembly is performed, so as to detect the filtration efficiency of the filter at different operation time nodes by using a high-precision particle counter, and by comparing the performance data of the initial and later stages of the operation, the filtration performance change data of the filter during the entire operation time is recorded, and the impact of performance attenuation is evaluated and analyzed on the corresponding filter performance change data by combining the actual filter usage wind speed obtained after the impact calibration, so as to determine the impact on the filtration performance under different wind speed conditions by using a regression analysis method, that is, the ratio between the standard operating wind speed of the filter and the actual operating wind speed, so as to evaluate and analyze the attenuation factor of the actual wind speed, and finally, by combining the total service life, operation time and attenuation factor obtained previously, the remaining service life of the corresponding filter assembly is estimated and calculated, so as to calculate the remaining service life of the filter by multiplying the total service life by the ratio between the operation time and the attenuation factor, and finally obtain the remaining service life of the filter assembly.

[0078] Step S3: estimating the remaining service life of the UV component based on the light output intensity of the UV component to obtain the remaining service life of the UV component;

[0079] In the embodiment of the present invention, a dedicated light intensity measuring instrument is used to collect light intensity data of the UV component under different environmental conditions. The specific operation includes recording the output light intensity of the UV component under multiple environmental light intensities and modeling its attenuation. By using a data regression method, the attenuation parameters under various environmental conditions are calculated. The effective use time of the corresponding UV component is quantitatively calculated by combining the UV component light output intensity and the UV component light intensity environmental attenuation parameters obtained by previous monitoring and quantitative calculation, so as to use the following formula: , where The effective usage time of UV component light output. is the UV component light intensity environment attenuation parameter, The UV component light output intensity is combined with the attenuation parameter to calculate the effective use time of the UV component. At the same time, the standard light output intensity of the UV component is obtained in advance, and measured by using standardized test instruments. The performance status is evaluated by comparing the current UV component light output intensity with the standard light output intensity. The remaining service life of the corresponding UV component is estimated by combining the effective use time obtained by the previous quantitative calculation and the actual performance status percentage, so as to establish a mathematical calculation formula , the effective use time is combined with the performance status percentage to calculate the remaining service life of the UV component, and finally the remaining service life of the UV component is obtained.

[0080] Step S4: Visually display the remaining service life of the filter component and the remaining service life of the UV component through the display system in the wall control component to obtain the service life display results of the air purifier system components; based on the preset component service life risk threshold, use the central intelligent control unit to centrally intelligently control the fresh air fan ventilation system components corresponding to the service life display results of the air purifier system components, and generate a centralized intelligent control strategy for the system components to execute the corresponding centralized control work of the air purifier system components.

[0081] In the embodiment of the present invention, the remaining service life of the filter component and the remaining service life of the UV component obtained by quantitative calculation are visualized in real time by using the embedded display module of the display system in the wall control component, so as to display the remaining service life of the filter component and the UV component, and display them on the user interface, so as to ensure that the user can intuitively understand the use status of each component, thereby obtaining the service life display result of the air purifier system component. Secondly, by using the pre-set component service life risk threshold (including the filter component service life risk threshold and the UV component service life risk threshold), the previously visualized air purifier system component service life display result is subjected to early warning processing of the corresponding component service life risk situation, so as to judge by the preset risk threshold logic, for example, when the remaining service life of the filter is less than 15% or the remaining service life of the UV lamp is less than 15% (that is, when the UV indicator light flashes), the risk warning of the corresponding component in the air purifier is triggered, the components below the threshold are automatically identified and marked, and the corresponding system component service life risk warning response signal is generated. At the same time, by using the central intelligent control unit, the control instruction response processing is performed on the system component service life risk warning response signal generated by the response, so as to trigger the intelligent control response mechanism of the corresponding system component, And based on the warning information, an intelligent control response instruction for the service life is generated. This instruction includes suggestions for operating adjustments to each component, such as reducing the operating frequency or starting a replacement program. Then, by combining the intelligent control response instructions generated by the previous response, the fresh air fan ventilation system components (such as filter components or UV components) corresponding to the service life risk warning response signal are centrally controlled. After receiving the instruction, the control module dynamically adjusts the corresponding components in the fresh air fan ventilation system according to the risk warning response signal, such as changing the fan speed or replacing the corresponding filter component or UV component and resetting it, to ensure that the entire air purifier system can still maintain optimal working efficiency and air quality when the service life of the components is reduced. Finally, the control generates the corresponding system component centralized intelligent control strategy to execute the corresponding air purifier system component centralized control work.

[0082] Further, step S1 includes the following steps:

[0083] Step S11: pre-installing a filter assembly, a UV assembly and a wall control assembly by integrating a fresh air fan ventilation system in the air purifier, wherein the filter assembly and the UV assembly are electrically connected to the wall control assembly;

[0084] Step S12: monitoring the operation time of the filter on the filter assembly in real time by using the built-in time monitor of the filter assembly to obtain the operation time of the filter; monitoring the operation pressure of the filter on the filter assembly in real time by using the built-in pressure sensor of the filter assembly to obtain the operation pressure change of the filter; monitoring the operation particle flow of the filter on the filter assembly in real time by using the built-in air particle flow meter of the filter assembly to obtain the air particle flow during the operation of the filter;

[0085] Step S13: merging the filter operation parameters including the filter operation time, the filter operation pressure change, and the air particle flow rate during the filter operation process to obtain a real-time parameter set of the filter component operation process;

[0086] Step S14: Using the built-in light intensity sensor of the UV component to monitor the light output intensity of the UV indicator light on the UV component in real time, to obtain the light output intensity of the UV component;

[0087] Step S15: The real-time parameter set of the filter component operation process and the light output intensity of the UV component are transmitted to the central intelligent control unit in the wall control component through the wireless transmission network.

[0088] As an embodiment of the present invention, refer to Figure 2 As shown, Figure 1 Detailed step flow diagram of step S1 in FIG. 1 , in this embodiment, step S1 includes the following steps:

[0089] Step S11: pre-installing a filter assembly, a UV assembly and a wall control assembly by integrating a fresh air fan ventilation system in the air purifier, wherein the filter assembly and the UV assembly are electrically connected to the wall control assembly;

[0090] In an embodiment of the present invention, a fresh air fan ventilation system is integrated in the design process of the air purifier, the system includes two pre-installed filter assemblies, two UV assemblies and a wall control assembly, wherein the filter assembly and the UV assembly are electrically connected to the wall control assembly via cables to ensure that they can work in coordination. When air enters the purifier, the fresh air fan is started, and the air is first filtered through the filter assembly, and then disinfected by ultraviolet rays through the UV assembly, and finally the purified air is sent out. The connection design of the system ensures real-time data sharing of all components and rapid transmission of control instructions.

[0091] Step S12: monitoring the operation time of the filter on the filter assembly in real time by using the built-in time monitor of the filter assembly to obtain the operation time of the filter; monitoring the operation pressure of the filter on the filter assembly in real time by using the built-in pressure sensor of the filter assembly to obtain the operation pressure change of the filter; monitoring the operation particle flow of the filter on the filter assembly in real time by using the built-in air particle flow meter of the filter assembly to obtain the air particle flow during the operation of the filter;

[0092] In an embodiment of the present invention, a time monitor, a pressure sensor and an air particle flow meter are integrated inside the filter assembly, wherein the time monitor is used to track the operating time of the filter on the filter assembly in real time, the pressure sensor continuously monitors the operating pressure change of the filter, and the air particle flow meter monitors the air particle flow on the filter, and a hot wire or ultrasonic flow measurement technology is used to obtain flow data in real time. Through the coordinated work of these monitoring tools, accurate acquisition of operating status information is ensured, and finally the corresponding filter operating time, filter operating pressure change and air particle flow during the filter operation process are obtained.

[0093] Step S13: merging the filter operation parameters including the filter operation time, the filter operation pressure change, and the air particle flow rate during the filter operation process to obtain a real-time parameter set of the filter component operation process;

[0094] In an embodiment of the present invention, a data processing module is used to combine the filter operating time, filter operating pressure change and air particle flow during the filter operation process previously monitored in real time, so that the data obtained from the time monitor, pressure sensor and air particle flow meter are transmitted to the data processing unit through the communication interface. The unit adopts a data fusion algorithm to merge various parameters to generate a real-time parameter set. The data set includes the working status and performance indicators of the filter. This process ensures the accuracy of multiple data at the same time point, and finally obtains the real-time parameter set of the filter component operation process.

[0095] Step S14: Using the built-in light intensity sensor of the UV component to monitor the light output intensity of the UV indicator light on the UV component in real time, to obtain the light output intensity of the UV component;

[0096] In an embodiment of the present invention, the light output intensity of the UV indicator light is monitored in real time by using a light intensity sensor built into the UV component, wherein the light intensity sensor adopts a photodiode or a photoresistor, and can accurately measure the light intensity emitted by the UV lamp. The sensor converts the light intensity value into an electrical signal, and the corresponding electrical signal is converted into a digital signal through an analog-to-digital converter, thereby obtaining the corresponding specific numerical value, and finally obtaining the light output intensity of the UV component light.

[0097] Step S15: The real-time parameter set of the filter component operation process and the light output intensity of the UV component are transmitted to the central intelligent control unit in the wall control component through the wireless transmission network.

[0098] In an embodiment of the present invention, the real-time parameter set of the filter component operation process and the UV component light output intensity collected above are transmitted to the central intelligent control unit of the wall control component by using a wireless transmission network. The process uses Bluetooth or Wi-Fi modules for data transmission to ensure efficient and stable connection.

[0099] Further, step S2 includes the following steps:

[0100] Step S21: using the central intelligent control unit to perform an operation pressure simulation analysis on the filter operation time and the filter operation pressure change in the real-time parameter set of the filter assembly operation process, to obtain a filter operation pressure fluid simulation change field;

[0101] Step S22: calculating the running resistance of the filter screen running pressure fluid simulation change field to obtain the running resistance of the filter screen;

[0102] Step S23: evaluating and calculating the particle capture efficiency according to the filter operation time and the air particle flow rate during the filter operation process, and obtaining the filter operation particle capture efficiency;

[0103] Step S24: performing a wind speed calibration calculation on the filter wind speed on the filter assembly based on the filter running resistance and the filter running particle capture efficiency using the filter wind speed calibration calculation formula to obtain the filter running calibration wind speed;

[0104] Step S25: estimating the remaining service life of the filter assembly based on the filter operation time and the calibrated wind speed used in the filter operation to obtain the remaining service life of the filter assembly.

[0105] As an embodiment of the present invention, refer to Figure 3 As shown, Figure 1 Detailed step flow diagram of step S2 in FIG. 1 , in this embodiment, step S2 includes the following steps:

[0106] Step S21: using the central intelligent control unit to perform an operation pressure simulation analysis on the filter operation time and the filter operation pressure change in the real-time parameter set of the filter assembly operation process, to obtain a filter operation pressure fluid simulation change field;

[0107] In an embodiment of the present invention, a central intelligent control unit uses fluid dynamics simulation software to perform simulation modeling of the operating pressure of the filter operating time and the filter operating pressure change in the real-time parameter set of the filter assembly operating process previously obtained by quantitative calculation, so as to establish a fluid simulation model of the filter. During the simulation process, the air flow rate, particle concentration and environmental conditions are taken into consideration, and the pressure change field of the filter is generated through numerical calculation to ensure a comprehensive understanding of the working state of the filter, and finally obtain a fluid simulation change field of the filter operating pressure.

[0108] Step S22: calculating the running resistance of the filter screen running pressure fluid simulation change field to obtain the running resistance of the filter screen;

[0109] In the embodiment of the present invention, computational fluid dynamics software is used to simulate the pressure change behavior of the fluid in the filter, that is, to obtain the simulated change field of the filter operation pressure fluid, to set different boundary conditions and initial conditions, to run the simulation calculation to obtain the corresponding pressure distribution value, and to calculate the pressure difference between different positions, to calculate the pressure difference between each position by selecting the key position, and to perform statistical calculation of the air flow rate by collecting the air flow changes at different positions and to calculate the average value, so as to quantitatively calculate the air fluid flow rate when the filter is running. At the same time, the resistance coefficient is quantitatively calculated by combining the operation distribution pressure difference and the air fluid flow rate obtained by the previous quantitative calculation, for example ,in is the drag coefficient, is the calculated pressure difference, is the air density, is the air flow velocity, thereby calculating the air distribution resistance coefficient of the filter, and calculating the operation resistance of the corresponding filter operation pressure fluid simulation change field by combining the resistance coefficient obtained by previous quantitative calculation, so as to calculate the following calculation formula ,in is the running resistance of the filter, is the drag coefficient, is the effective cross-sectional area of ​​the filter, and the total resistance of the filter under actual operation is calculated, and finally the operating resistance of the filter is obtained.

[0110] Step S23: evaluating and calculating the particle capture efficiency according to the filter operation time and the air particle flow rate during the filter operation process, and obtaining the particle capture efficiency of the filter operation;

[0111] In the embodiment of the present invention, the air particle flow rate of the filter operation process obtained by combining the previously analyzed air particle flow rate is obtained to obtain the particle flow rate of the air flowing in and out of the filter, and the concentration of the air flowing in and out of the filter is calculated by combining the filter operation time statistics, and a suitable calculation formula is constructed by combining the particle flow rate and concentration of the air flowing in and out. , to quantify the capture efficiency in different time periods, and finally obtain the particle capture efficiency of the filter.

[0112] Step S24: performing a wind speed calibration calculation on the filter wind speed on the filter assembly based on the filter running resistance and the filter running particle capture efficiency using the filter wind speed calibration calculation formula to obtain the filter running calibration wind speed;

[0113] In an embodiment of the present invention, a suitable filter wind speed calibration calculation formula is constructed by combining the filter operating resistance, the filter operating particle capture efficiency, the filter wind speed on the filter assembly in the current process, the effective diameter of the filter space, the total airflow pressure at the filter inlet, the filter pressure loss, the filter particle deposition efficiency influence constant, the particle diameter parameter, the nonlinear influence coefficient of the particle deposition behavior and related parameters to perform a wind speed calibration calculation on the filter wind speed on the filter assembly, thereby affecting the calibration calculation to obtain the actual use wind speed of the filter in the current operating state, and finally obtaining the filter operation use calibration wind speed.

[0114] Step S25: estimating the remaining service life of the filter assembly based on the filter operation time and the calibrated wind speed used in the filter operation to obtain the remaining service life of the filter assembly.

[0115] In the embodiment of the present invention, the total service life of the filter assembly before the purification and filtering process of the air purifier is started is obtained in advance, which is generally , and by combining the filter operation time obtained by previous real-time monitoring, the performance evaluation and analysis of the corresponding filter assembly is performed on the filter, so as to detect the filtration efficiency of the filter at different operation time nodes by using a high-precision particle counter, and by comparing the performance data at the beginning and the end of the operation, the filtration performance change data of the filter during the entire operation time is recorded, and the impact of performance attenuation is evaluated and analyzed on the corresponding filter performance change data by combining the actual filter operation calibration wind speed obtained after the previous impact calibration, so as to determine the impact on the filtration performance under different wind speed conditions by using a regression analysis method, that is, the ratio between the standard operating wind speed of the filter and the actual operating wind speed, so as to evaluate and analyze the attenuation factor of the actual wind speed, and then, by combining the total service life, operation time and attenuation factor obtained previously, the corresponding filter assembly is estimated to calculate the remaining service life, so as to calculate the remaining service life of the filter by multiplying the total service life by the ratio between the operation time and the attenuation factor, and finally obtain the remaining service life of the filter assembly.

[0116] Further, step S22 includes the following steps:

[0117] Perform pressure distribution analysis on the simulated change field of the filter screen's operating pressure fluid to obtain distribution values ​​of operating pressure changes at different coordinate positions of the filter screen;

[0118] In an embodiment of the present invention, computational fluid dynamics software is used to simulate the pressure change behavior of the fluid in the filter, that is, to obtain the simulated change field of the filter operating pressure fluid, and by setting different boundary conditions and initial conditions, a simulation calculation is run to obtain corresponding pressure distribution data, and the pressure change distribution values ​​at different coordinate positions are extracted from the analysis results to form a pressure distribution diagram, and finally the operating pressure change distribution values ​​at different coordinate positions of the filter are obtained.

[0119] Preferably, the pressure difference between positions is calculated for the distribution values ​​of the operating pressure changes at different coordinate positions of the filter screen to obtain the operating distribution pressure difference between different positions of the filter screen;

[0120] In the embodiment of the present invention, the pressure difference between different positions is calculated after the operating pressure change distribution value at different coordinate positions of the filter is obtained, so as to calculate the pressure difference between each position by selecting a key position. The specific formula is: ,in and They respectively represent the pressure values ​​of the two selected positions. Through this process, the operating distributed pressure difference data between each position of the filter is generated, and finally the operating distributed pressure difference between different positions of the filter is obtained.

[0121] Preferably, the air fluid flow rate statistics analysis is performed on the simulated change field of the filter screen operating pressure fluid to obtain the air fluid flow rate of the filter screen operating;

[0122] In an embodiment of the present invention, by collecting air flow changes at different positions at the inlet and outlet of the filter within the filter operation pressure fluid simulation change field, and by combining the monitoring time period and the collected air flow changes, the air flow rate is statistically calculated and the average value is obtained to quantify the air fluid flow rate of the filter during operation, and finally the air fluid flow rate of the filter operation is obtained.

[0123] Preferably, the filter resistance coefficient is calculated according to the operating distribution pressure difference between different positions of the filter and the air fluid flow rate of the filter to obtain the air distribution resistance coefficient of the filter;

[0124] In the embodiment of the present invention, a suitable calculation formula is formed to quantitatively calculate the resistance coefficient by combining the previously quantitatively calculated operating distribution pressure difference between different positions of the filter and the operating air fluid flow rate of the filter, for example: ,in is the drag coefficient, is the calculated pressure difference, is the air density, is the air fluid flow rate, and the air distribution resistance coefficient of the filter is calculated. This coefficient reflects the fluid resistance characteristics of the filter during actual operation, and finally the air distribution resistance coefficient of the filter is obtained.

[0125] Preferably, the operation resistance of the filter is calculated based on the air distribution resistance coefficient of the filter, so as to obtain the operation resistance of the filter.

[0126] In the embodiment of the present invention, the running resistance of the corresponding filter running pressure fluid simulation change field is calculated by combining the filter air distribution resistance coefficient obtained by the previous quantitative calculation, so as to calculate the following formula: ,in is the running resistance of the filter, is the drag coefficient, is the effective cross-sectional area of ​​the filter. Substitute all relevant parameters into the formula to calculate the total resistance of the filter under actual operating conditions, and finally obtain the operating resistance of the filter.

[0127] Further, step S23 includes the following steps:

[0128] Step S231: dividing the air particle flow rate during the operation of the filter into the filter inlet and outlet components to obtain the air particle flow rate during the operation of the filter and the air particle flow rate during the operation of the filter;

[0129] In an embodiment of the present invention, the air particle flow rate at the inlet and outlet of the filter is divided according to the air particle flow rate during the filter operation process previously monitored by a flow meter, so as to divide the flow components of the air particles flowing into and out of the filter assembly in real time, and finally obtain the air particle flow rate at the inlet of the filter operation process and the air particle flow rate at the outlet of the filter operation process.

[0130] Step S232: based on the filter operation time, a particle flow hyperbola is plotted for the inlet air particle flow rate and the outlet air particle flow rate during the filter operation process, so as to generate a filter operation inlet and outlet air particle flow hyperbola;

[0131] In an embodiment of the present invention, a hyperbola is drawn in the same time dimension for the corresponding inlet air particle flow rate of the filter operation process and the outlet air particle flow rate of the filter operation process in combination with the previous real-time monitoring of the filter operation time, so that the collected particle flow rate data is input and a hyperbola graph is generated by using a data visualization tool. The graph shows the changing trend of the inlet and outlet particle flow rates of the filter at different operation times. The shape and intersection of the hyperbola can intuitively reflect the working efficiency and flow balance of the filter, thereby ensuring the intuitiveness and accuracy of the filter performance evaluation, and finally drawing and generating a hyperbola of the inlet and outlet air particle flow rates of the filter operation.

[0132] Step S233: analyzing the particle concentration change of the air particle flow rate at the inlet of the filter and the air particle flow rate at the outlet of the filter during operation to obtain the particle concentration change at the inlet of the filter and the particle concentration change at the outlet of the filter during operation;

[0133] In an embodiment of the present invention, by combining the previously divided inlet air particle flow rate and outlet air particle flow rate during the operation of the filter, a statistical calculation of the particle concentration is performed at the air inlet and air outlet of the filter to calculate the change concentration of the inlet particulate matter and the change concentration of the outlet particulate matter. This analysis reveals the filter's processing capacity for air particles during operation, and ultimately the change concentration of the inlet particulate matter during the operation of the filter and the change concentration of the outlet particulate matter during the operation of the filter are obtained.

[0134] Step S234: based on the change concentration of the inlet particulate matter during the operation of the filter and the change concentration of the outlet particulate matter during the operation of the filter, the particle capture efficiency is evaluated and calculated using the particle capture efficiency evaluation calculation formula for the inlet and outlet air particle flow hyperbola of the filter operation to obtain the particle capture efficiency of the filter operation;

[0135] In an embodiment of the present invention, a suitable particle capture efficiency evaluation calculation formula is formed by combining the change in particle concentration at the inlet of the filter during operation, the change in particle concentration at the outlet of the filter during operation, time variable parameters, the air particle flow rate at the inlet of the filter, the air particle flow rate at the outlet of the filter, the difference attenuation coefficient of the air particle flow rate at the inlet and outlet of the filter, and related parameters. The particle capture efficiency is evaluated and calculated on the hyperbola of the air particle flow rate at the inlet and outlet of the filter, so as to quantitatively calculate the particle capture efficiency of the filter during operation, and finally obtain the particle capture efficiency of the filter operation.

[0136] Among them, the particle capture efficiency evaluation calculation formula is as follows:

[0137] ;

[0138] In the formula, To operate the particle capture efficiency of the filter, The concentration of inlet particles changes during the filter operation process. The concentration of particulate matter at the outlet of the filter during operation. For the evaluation period, is the time variable parameter, Hyperbolic internal time of the air particle flow rate at the inlet and outlet of the filter The air particle flow rate at the filter inlet at Hyperbolic internal time of the air particle flow rate at the inlet and outlet of the filter The air particle flow rate at the filter outlet at is the differential attenuation coefficient of the air particle flow rate at the inlet and outlet of the filter, A correction factor for the filter's operating particle capture efficiency.

[0139] The present invention obtains a particle capture efficiency evaluation calculation formula by using a specific mathematical model and verifying it, which is used to evaluate the particle capture efficiency of the filter's inlet and outlet air particle flow hyperbola. The particle capture efficiency evaluation calculation formula can quantitatively evaluate the effect of the filter under different operating conditions by calculating the particle capture efficiency, which provides a basis for the selection, maintenance and replacement of the filter. The time variable in the formula allows the analysis of the particle flow of the filter at different time points, which helps to identify the changing trend of the particle capture efficiency. By comparing the inlet concentration and the outlet concentration, the filter's ability to remove particles can be intuitively understood, helping to optimize the design and use of the filter. At the same time, The introduction of the coefficient makes it possible to quantitatively analyze the impact of the difference in inlet and outlet flow rates on filtration efficiency, thereby better understanding the effect of flow rate changes on capture efficiency. It can be adjusted according to the actual application scenario to make the calculation results more adaptable and accurate, and suitable for different types of filters and operating environments. In summary, this formula fully considers the particle capture efficiency of the filter operation. , the concentration of inlet particulate matter changes during the filter operation process , the concentration of particulate matter at the outlet of the filter during operation , evaluation period , time variable parameter , the filter operation inlet and outlet air particle flow hyperbolic internal time Air particle flow rate at the filter inlet , the filter operation inlet and outlet air particle flow hyperbolic internal time Air particle flow at the filter outlet , filter inlet and outlet air particle flow difference attenuation coefficient , correction factor for the particle capture efficiency of the filter , according to the filter operation particle capture efficiency The correlation between the above parameters constitutes a functional relationship This formula can realize the particle capture efficiency evaluation and calculation process of the hyperbolic air particle flow rate of the filter net running inlet and outlet, and at the same time, the correction coefficient of the particle capture efficiency of the filter net running is calculated. The introduction of can be adjusted according to the errors occurring in the calculation process, thereby improving the accuracy and applicability of the particle capture efficiency evaluation calculation formula.

[0140] Furthermore, the filter screen in step S24 uses the wind speed calibration calculation formula as follows:

[0141] ;

[0142] In the formula, Use the calibrated air speed for filter operation. Use the wind speed for the filter on the filter assembly. To measure the particle capture efficiency of the filter, is the effective diameter of the filter space, is the total airflow pressure at the filter inlet, For the diameter distance The filter pressure loss at is the filter running resistance, is the constant affecting the particle deposition efficiency of the filter, is the particle diameter parameter, is the nonlinear influence coefficient of particle deposition behavior, Use the correction factor for the calibrated air speed for filter operation.

[0143] The present invention obtains a filter wind speed calibration calculation formula by using a specific mathematical model and after verification, which is used to perform wind speed calibration calculations on the filter wind speed on the filter assembly. The filter wind speed calibration calculation formula can accurately calculate the actual wind speed of the filter during operation by considering factors such as particle capture efficiency and pressure loss, thereby providing basic data guarantee for subsequent remaining service life estimation. By calculating the total airflow pressure at the filter inlet and the pressure loss at different diameter distances, the operating pressure changes of the filter can be evaluated in real time to help identify potential resistance problems. The constant in this formula and nonlinear influence coefficient This allows the complexity of the deposition behavior to be reflected, and can more accurately describe the behavior of particles in the filter and their impact on wind speed. , the calculation results can be adjusted according to different operating conditions and environments to improve the applicability and accuracy of the calculation formula. By continuously monitoring the operating time and wind speed changes of the filter, the operating strategy can be adjusted in time to ensure that the filter works under optimal conditions and reduce maintenance costs. The calculated filter operation calibration wind speed can more accurately estimate the remaining service life of the filter and help management formulate a more scientific maintenance and replacement plan. In summary, this formula fully takes into account the filter operation calibration wind speed. , the filter on the filter assembly uses the wind speed , filter operation particle capture efficiency , effective diameter of filter space , total airflow pressure at filter inlet , at a diameter distance Filter pressure loss at , filter running resistance , the filter particle deposition efficiency influence constant , particle diameter parameter , nonlinear influence coefficient of particle deposition behavior , the filter operates using the correction factor for the calibrated wind speed , use the calibrated wind speed according to the filter operation The correlation between the above parameters constitutes a functional relationship The formula can realize the wind speed calibration calculation process of the filter on the filter assembly using the wind speed, and at the same time, the correction factor of the calibrated wind speed is used by the filter operation. The introduction of can be adjusted according to the errors that occur in the calculation process, thereby improving the accuracy and applicability of the wind speed calibration calculation formula used by the filter.

[0144] Further, step S25 includes the following steps:

[0145] Step S251: Obtain the total filtration service life of the filter assembly to obtain the total service life of the filter assembly;

[0146] In the embodiment of the present invention, the total service life of the filter assembly before the purification and filtering process of the air purifier is started is obtained in advance, which is generally , and finally the total service life of the filter assembly is obtained.

[0147] Step S252: performing filter performance evaluation and analysis on the filter assembly based on the filter operation time to obtain filter performance change data during the filter operation time;

[0148] In an embodiment of the present invention, the performance of the filter is evaluated and analyzed by combining the filter operation time obtained by previous real-time monitoring with the corresponding filter assembly, so that the filtration efficiency of the filter is detected at different time nodes by using a high-precision particle counter, and the performance data at the initial and later stages of operation are compared to generate a performance change curve. The performance changes are analyzed through a data processing algorithm, and the filtration performance change data of the filter during the entire operation time is recorded to clearly show the performance attenuation trend, and finally the filter performance change data of the filter during the operation time is obtained.

[0149] Step S253: analyzing the wind speed performance attenuation impact of the filter performance change data during the filter operation period based on the filter operation calibration wind speed, and obtaining the filter operation wind speed performance attenuation impact factor;

[0150] In an embodiment of the present invention, the performance attenuation impact assessment and analysis is performed on the filter performance change data of the corresponding filter during the operating period by combining the actual filter operation calibration wind speed obtained after the impact calibration, so as to determine the impact on the filtration performance under different wind speed conditions by using a regression analysis method, that is, the ratio between the standard operating wind speed of the filter and the actual operating wind speed, so as to evaluate and analyze the attenuation factor of the actual wind speed. The evaluation calculation of this factor will help identify the specific impact of wind speed on filtration efficiency, and finally obtain the attenuation factor of the filter operation wind speed performance impact.

[0151] Step S254: Estimate the remaining service life of the filter assembly according to the total service life of the filter assembly, the operating time of the filter, and the attenuation factor affecting the wind speed performance of the filter operation to obtain the remaining service life of the filter assembly.

[0152] In an embodiment of the present invention, the remaining service life of the corresponding filter assembly is estimated by combining the total service life of the filter assembly, the operating time of the filter, and the attenuation factor of the wind speed performance affecting the operation of the filter obtained by previous quantitative calculations. By constructing a mathematical model, the total service life of the filter assembly is multiplied by the ratio of the operating time of the filter and the attenuation factor of the wind speed performance affecting the operation of the filter, and the remaining service life of the filter is calculated, and finally the remaining service life of the filter assembly is obtained.

[0153] Further, step S3 includes the following steps:

[0154] Step S31: Performing light intensity environment attenuation analysis on the UV component to obtain light intensity environment attenuation parameters of the UV component;

[0155] In an embodiment of the present invention, a dedicated light intensity measuring instrument is used to collect light intensity data of a UV component under different environmental conditions. The specific operation includes recording the output light intensity of the UV component under multiple environmental light intensities, and modeling its attenuation condition, so as to calculate the attenuation parameters under various environmental conditions by adopting a data regression method, thereby ensuring accurate quantification of the performance changes of the UV component, and finally obtaining the light intensity environmental attenuation parameters of the UV component.

[0156] Step S32: Calculate the effective use time of the UV component based on the UV component light output intensity and the UV component light intensity environment attenuation parameter to obtain the effective use time of the UV component light output;

[0157] In the embodiment of the present invention, the effective use time of the corresponding UV component is quantitatively calculated by combining the UV component light output intensity and the UV component light intensity environment attenuation parameter obtained by previous monitoring and quantitative calculation, so as to use the following formula: , where The effective usage time of UV component light output. is the UV component light intensity environment attenuation parameter, The light output intensity of the UV component is combined with the attenuation parameter to calculate the effective use time of the UV component, thereby accurately predicting the effective use time under specific environmental conditions, ensuring reliable time estimation under different working conditions, and finally obtaining the effective use time of the UV component light output.

[0158] Step S33: obtaining the standard light intensity output intensity of the UV component, and performing a performance status evaluation and analysis on the UV component based on the light output intensity of the UV component and the standard light intensity output intensity, to obtain the actual performance status percentage of the UV component lamp;

[0159] In the embodiment of the present invention, the standard light intensity output intensity of the UV component is obtained in advance, and is measured by using a standardized test instrument, and the UV component light output intensity of the current UV component is compared with the standard light intensity output intensity, and a performance status evaluation calculation formula such as The analysis is performed to quantitatively calculate the performance status percentage of the UV component, and finally the actual performance status percentage of the UV component lamp is obtained.

[0160] Step S34: estimating the remaining service life of the UV component based on the effective use time of the UV component light output and the actual performance status percentage of the UV component lamp to obtain the remaining service life of the UV component.

[0161] In the embodiment of the present invention, the remaining service life of the corresponding UV component is estimated by combining the effective use time of the UV component light output obtained by the previous quantitative calculation and the actual performance status percentage of the UV component lamp, so as to establish a mathematical calculation formula , the effective use time is combined with the performance status percentage to calculate the remaining service life of the UV component, and finally the remaining service life of the UV component is obtained.

[0162] Further, step S4 includes the following steps:

[0163] Step S41: Visually display the remaining service life of the filter assembly and the remaining service life of the UV assembly through the display system in the wall control assembly to obtain the service life display result of the air purifier system assembly;

[0164] In an embodiment of the present invention, the remaining service life of the filter assembly and the remaining service life of the UV assembly obtained by quantitative calculation previously are visualized in real time by using the embedded display module of the display system in the wall control assembly to display the remaining service life of the filter assembly and the UV assembly, and display them on the user interface to ensure that the user can intuitively understand the usage status of each component and finally obtain the service life display results of the air purifier system components.

[0165] Step S42: performing component life risk warning processing on the corresponding air purifier system component life display result according to the preset component life risk threshold, and obtaining air purifier system component life risk warning information;

[0166] In an embodiment of the present invention, by using pre-set component life risk thresholds (including filter component life risk thresholds and UV component life risk thresholds), the previously visualized air purifier system component life display results are used to perform early warning processing of corresponding component life risk situations, so as to make a logical judgment through the preset risk thresholds. For example, when the remaining life of the filter is less than 15% or the remaining life of the UV lamp is less than 15% (that is, when the UV indicator light is flashing), a risk warning of the corresponding component in the air purifier is triggered. This process uses a conditional judgment algorithm to automatically identify and mark components that are below the threshold, and generates corresponding system component life risk warning response signals, and finally obtains air purifier system component life risk warning information.

[0167] Step S43: using the central intelligent control unit to perform component life intelligent control response to the air purifier system component life risk warning information to generate a system component life intelligent control response instruction;

[0168] In an embodiment of the present invention, a central intelligent control unit is used to respond to and process the control instructions of the air purifier system component life risk warning information that has been generated through response, so as to trigger the intelligent control response mechanism of the corresponding system component, and based on the warning information, comprehensively analyze the status of each component to generate an intelligent control response instruction for the service life. This instruction includes suggestions for operating adjustments to each component, such as reducing the operating frequency or starting a replacement program, and finally responds to generate an intelligent control response instruction for the system component life.

[0169] Step S44: Based on the system component service life intelligent control response instruction, the fresh air fan ventilation system components corresponding to the air purifier system component service life risk warning information are centrally intelligently controlled and processed to generate a system component centralized intelligent control strategy to execute the corresponding air purifier system component centralized control work.

[0170] In an embodiment of the present invention, the system components are centrally controlled by combining the system component life intelligent control response instructions generated by the previous response to the fresh air fan ventilation system components (such as filter components or UV components) corresponding to the air purifier system component life risk warning information. After receiving the instructions, the control module dynamically adjusts the corresponding components in the fresh air fan ventilation system according to the risk warning information, such as changing the fan speed or replacing the corresponding filter components or UV components and resetting them, to ensure that the entire air purifier system can still maintain optimal working efficiency and air quality when the component life is reduced, and finally control to generate the corresponding system component centralized intelligent control strategy to execute the corresponding air purifier system component centralized control work.

[0171] Furthermore, the present invention also provides an air purifier centralized intelligent control system for executing the above-mentioned air purifier centralized intelligent control method, and the air purifier centralized intelligent control system includes:

[0172] The purifier system component operation parameter monitoring module is used to integrate the pre-installed filter assembly, UV assembly and wall control assembly in the fresh air fan ventilation system in the air purifier, wherein the filter assembly and the UV assembly are electrically connected to the wall control assembly; the operation process of the filter on the filter assembly is monitored in real time through the built-in time monitor, pressure sensor and air particle flow meter of the filter assembly to obtain the real-time parameter set of the filter assembly operation process, wherein the real-time parameter set of the filter assembly operation process includes the filter operation time, the filter operation pressure change and the air particle flow rate of the filter operation process; the light output intensity of the UV indicator light on the UV assembly is monitored in real time through the built-in light intensity sensor of the UV assembly to obtain the light output intensity of the UV assembly; the real-time parameter set of the filter assembly operation process and the light output intensity of the UV assembly are transmitted to the central intelligent control unit in the wall control assembly;

[0173] The filter component life estimation module is used to calculate the operating resistance of the filter component in the real-time parameter set of the filter component operation process and the filter component operation pressure change using the central intelligent control unit to obtain the filter component operation resistance; based on the filter component operation time, the filter component operation resistance and the air particle flow rate during the filter component operation process, the filter component remaining service life is estimated to obtain the remaining service life of the filter component;

[0174] The UV component service life estimation module is used to estimate the UV remaining service life of the UV component based on the light output intensity of the UV component, thereby obtaining the remaining service life of the UV component;

[0175] The centralized intelligent control module of the purifier system components is used to visualize the remaining service life of the filter component and the remaining service life of the UV component through the display system in the wall control component to obtain the service life display results of the air purifier system components; according to the preset component service life risk threshold, the fresh air fan ventilation system components corresponding to the service life display results of the air purifier system components are centrally intelligently controlled and processed to generate a centralized intelligent control strategy for the system components to execute the corresponding centralized control work of the air purifier system components.

[0176] Therefore, the embodiments should be regarded as illustrative and non-restrictive from all points, and the scope of the present invention is limited by the appended claims rather than the above description, and it is therefore intended that all changes falling within the meaning and range of equivalent elements of the application documents are included in the present invention.

[0177] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A centralized intelligent control method for an air purifier, characterized in that: The following steps are involved: Step S1: pre-installing a filter assembly, a UV assembly and a wall control assembly in a fresh air fan ventilation system in an air purifier, wherein the filter assembly and the UV assembly are electrically connected to the wall control assembly; monitoring the operation process of the filter on the filter assembly in real time through a time monitor, a pressure sensor and an air particle flow meter built into the filter assembly, and obtaining a real-time parameter set of the operation process of the filter assembly, wherein the real-time parameter set of the operation process of the filter assembly includes the operation time of the filter, the change in the operation pressure of the filter and the air particle flow rate of the filter operation process; The light output intensity of the UV indicator light on the UV component is monitored in real time through the built-in light intensity sensor of the UV component to obtain the light output intensity of the UV component; the real-time parameter set of the filter component operation process and the light output intensity of the UV component are transmitted to the central intelligent control unit in the wall control component; Step S2: using the central intelligent control unit to calculate the operating resistance of the filter mesh operating time and the filter mesh operating pressure change in the real-time parameter set of the filter mesh component operating process, so as to obtain the filter mesh operating resistance; based on the filter mesh operating time, the filter mesh operating resistance and the air particle flow rate during the filter mesh operating process, the filter mesh component is estimated to have a remaining service life, so as to obtain the remaining service life of the filter mesh component; Step S3: estimating the remaining service life of the UV component based on the light output intensity of the UV component to obtain the remaining service life of the UV component; Step S4: Visually display the remaining service life of the filter assembly and the remaining service life of the UV assembly through the display system in the wall control assembly to obtain the service life display result of the air purifier system assembly; Based on the preset component life risk threshold, the central intelligent control unit is used to perform centralized intelligent control processing on the fresh air fan ventilation system components corresponding to the service life display results of the air purifier system components, and a centralized intelligent control strategy for the system components is generated to execute the corresponding centralized control work of the air purifier system components.

2. The air purifier centralized intelligent control method according to claim 1, characterized in that: Step S1 includes the following steps: Step S11: pre-installing a filter assembly, a UV assembly and a wall control assembly in a fresh air fan ventilation system in the air purifier, wherein the filter assembly and the UV assembly are electrically connected to the wall control assembly; Step S12: monitoring the operation time of the filter on the filter assembly in real time by using the built-in time monitor of the filter assembly to obtain the operation time of the filter; monitoring the operation pressure of the filter on the filter assembly in real time by using the built-in pressure sensor of the filter assembly to obtain the operation pressure change of the filter; monitoring the operation particle flow of the filter on the filter assembly in real time by using the built-in air particle flow meter of the filter assembly to obtain the air particle flow during the operation of the filter; Step S13: merging the filter operation parameters including the filter operation time, the filter operation pressure change, and the air particle flow rate during the filter operation process to obtain a real-time parameter set of the filter component operation process; Step S14: Using the built-in light intensity sensor of the UV component to monitor the light output intensity of the UV indicator light on the UV component in real time, to obtain the light output intensity of the UV component; Step S15: The real-time parameter set of the filter component operation process and the light output intensity of the UV component are transmitted to the central intelligent control unit in the wall control component through the wireless transmission network.

3. The centralized intelligent control method for air purifiers according to claim 1, characterized in that: Step S2 includes the following steps: Step S21: using the central intelligent control unit to perform an operation pressure simulation analysis on the filter operation time and the filter operation pressure change in the real-time parameter set of the filter assembly operation process, to obtain a filter operation pressure fluid simulation change field; Step S22: calculating the running resistance of the filter screen running pressure fluid simulation change field to obtain the running resistance of the filter screen; Step S23: evaluating and calculating the particle capture efficiency according to the filter operation time and the air particle flow rate during the filter operation process, and obtaining the particle capture efficiency of the filter operation; Step S24: performing a wind speed calibration calculation on the filter wind speed on the filter assembly based on the filter running resistance and the filter running particle capture efficiency using the filter wind speed calibration calculation formula to obtain the filter running calibration wind speed; Step S25: estimating the remaining service life of the filter assembly based on the filter operation time and the calibrated wind speed used in the filter operation to obtain the remaining service life of the filter assembly.

4. The air purifier centralized intelligent control method according to claim 3, characterized in that: Step S22 includes the following steps: Perform pressure distribution analysis on the simulated change field of the filter screen operating pressure fluid to obtain the distribution values ​​of the operating pressure change at different coordinate positions of the filter screen; The pressure difference between the positions is calculated for the distribution values ​​of the operating pressure changes at different coordinate positions of the filter screen, so as to obtain the operating distribution pressure difference between different positions of the filter screen; Performing statistical analysis on the air fluid flow rate of the filter screen operating pressure fluid simulation change field to obtain the air fluid flow rate of the filter screen operating; The filter resistance coefficient is calculated according to the operating distribution pressure difference between different positions of the filter and the air fluid flow rate of the filter, so as to obtain the air distribution resistance coefficient of the filter; The running resistance of the filter is calculated based on the air distribution resistance coefficient of the filter, and the running resistance of the filter is obtained.

5. The centralized intelligent control method for air purifiers according to claim 3, characterized in that: Step S23 includes the following steps: Step S231: dividing the air particle flow rate during the operation of the filter into the filter inlet and outlet components to obtain the air particle flow rate during the operation of the filter and the air particle flow rate during the operation of the filter; Step S232: based on the filter operation time, a particle flow hyperbola is plotted for the inlet air particle flow rate and the outlet air particle flow rate during the filter operation process, so as to generate a filter operation inlet and outlet air particle flow hyperbola; Step S233: analyzing the particle concentration change of the air particle flow rate at the inlet of the filter and the air particle flow rate at the outlet of the filter during operation to obtain the particle concentration change at the inlet of the filter and the particle concentration change at the outlet of the filter during operation; Step S234: based on the change concentration of the inlet particulate matter during the operation of the filter and the change concentration of the outlet particulate matter during the operation of the filter, the particle capture efficiency is evaluated and calculated using the particle capture efficiency evaluation calculation formula for the inlet and outlet air particle flow hyperbola of the filter operation to obtain the particle capture efficiency of the filter operation; Among them, the particle capture efficiency evaluation calculation formula is as follows: ； In the formula, To operate the particle capture efficiency of the filter, The concentration of inlet particles changes during the filter operation process. The concentration of particulate matter at the outlet of the filter during operation. For the evaluation period, is the time variable parameter, Hyperbolic internal time of the inlet and outlet air particle flow rate for the filter operation The air particle flow rate at the filter inlet at Hyperbolic internal time of the inlet and outlet air particle flow rate for the filter operation The air particle flow rate at the filter outlet at is the differential attenuation coefficient of the air particle flow rate at the inlet and outlet of the filter, A correction factor for the filter's operating particle capture efficiency.

6. The centralized intelligent control method for air purifiers according to claim 3, characterized in that: The filter screen wind speed calibration calculation formula in step S24 is specifically: ； In the formula, Use calibrated air speed for filter operation. Use the wind speed for the filter on the filter assembly. To operate the particle capture efficiency of the filter, is the effective diameter of the filter space, is the total airflow pressure at the filter inlet, For the diameter distance The filter pressure loss at is the filter running resistance, is the constant affecting the particle deposition efficiency of the filter, is the particle diameter parameter, is the nonlinear influence coefficient of particle deposition behavior, Use the correction factor for the calibrated air speed for filter operation.

7. The air purifier centralized intelligent control method according to claim 3, characterized in that: Step S25 includes the following steps: Step S251: Obtain the total filtration service life of the filter assembly to obtain the total service life of the filter assembly; Step S252: performing filter performance evaluation and analysis on the filter assembly based on the filter operation time to obtain filter performance change data during the filter operation time; Step S253: analyzing the wind speed performance attenuation impact of the filter performance change data during the filter operation period based on the filter operation calibration wind speed, and obtaining the filter operation wind speed performance attenuation impact factor; Step S254: Estimate the remaining service life of the filter assembly according to the total service life of the filter assembly, the operating time of the filter, and the attenuation factor affecting the wind speed performance of the filter operation to obtain the remaining service life of the filter assembly.

8. The centralized intelligent control method for air purifiers according to claim 1, characterized in that: Step S3 includes the following steps: Step S31: Performing light intensity environment attenuation analysis on the UV component to obtain light intensity environment attenuation parameters of the UV component; Step S32: Calculate the effective use time of the UV component based on the UV component light output intensity and the UV component light intensity environment attenuation parameter to obtain the effective use time of the UV component light output; Step S33: obtaining the standard light intensity output intensity of the UV component, and performing a performance status evaluation and analysis on the UV component based on the light output intensity of the UV component and the standard light intensity output intensity, to obtain the actual performance status percentage of the UV component lamp; Step S34: estimating the remaining service life of the UV component based on the effective use time of the UV component light output and the actual performance status percentage of the UV component lamp to obtain the remaining service life of the UV component.

9. The air purifier centralized intelligent control method according to claim 1, characterized in that: Step S4 includes the following steps: Step S41: Visually display the remaining service life of the filter assembly and the remaining service life of the UV assembly through the display system in the wall control assembly to obtain the service life display result of the air purifier system assembly; Step S42: performing component life risk warning processing on the corresponding air purifier system component life display result according to the preset component life risk threshold, and obtaining air purifier system component life risk warning information; Step S43: using the central intelligent control unit to perform component life intelligent control response to the air purifier system component life risk warning information to generate a system component life intelligent control response instruction; Step S44: Based on the system component service life intelligent control response instruction, the fresh air fan ventilation system components corresponding to the air purifier system component service life risk warning information are centrally intelligently controlled and processed to generate a system component centralized intelligent control strategy to execute the corresponding air purifier system component centralized control work.

10. A centralized intelligent control system for air purifiers, characterized in that: Used to execute the air purifier centralized intelligent control method according to claim 1, the air purifier centralized intelligent control system comprises: The purifier system component operation parameter monitoring module is used to integrate the pre-installed filter assembly, UV assembly and wall control assembly in the fresh air fan ventilation system in the air purifier, wherein the filter assembly and the UV assembly are electrically connected to the wall control assembly; the operation process of the filter on the filter assembly is monitored in real time through the built-in time monitor, pressure sensor and air particle flow meter of the filter assembly to obtain the real-time parameter set of the filter assembly operation process, wherein the real-time parameter set of the filter assembly operation process includes the filter operation time, the filter operation pressure change and the air particle flow rate of the filter operation process; the light output intensity of the UV indicator light on the UV assembly is monitored in real time through the built-in light intensity sensor of the UV assembly to obtain the light output intensity of the UV assembly; the real-time parameter set of the filter assembly operation process and the light output intensity of the UV assembly are transmitted to the central intelligent control unit in the wall control assembly; The filter component life estimation module is used to calculate the operating resistance of the filter component in the real-time parameter set of the filter component operation process and the filter component operation pressure change using the central intelligent control unit to obtain the filter component operation resistance; based on the filter component operation time, the filter component operation resistance and the air particle flow rate during the filter component operation process, the filter component remaining service life is estimated to obtain the remaining service life of the filter component; The UV component service life estimation module is used to estimate the UV remaining service life of the UV component based on the light output intensity of the UV component, thereby obtaining the remaining service life of the UV component; The centralized intelligent control module of the purifier system components is used to visualize the remaining service life of the filter component and the remaining service life of the UV component through the display system in the wall control component to obtain the service life display results of the air purifier system components; according to the preset component service life risk threshold, the fresh air fan ventilation system components corresponding to the service life display results of the air purifier system components are centrally intelligently controlled and processed to generate a centralized intelligent control strategy for the system components to execute the corresponding centralized control work of the air purifier system components.

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