Filter screen clogging detection method, system, ventilation device, and storage medium

Abstract

The application relates to a filter screen dirty block detection method, system, ventilation equipment and storage medium. The method comprises the following steps: arranging a conductive target area in a horizontal manner behind the airflow of a filter screen in an air duct assembly; arranging an electrostatic detection module in a non-contact manner with the conductive target area to detect an electrostatic signal generated by friction between dust particle flux passing through the filter screen and the conductive target area; and then using a filter screen dirty block detection device to identify the dirty block degree of the filter screen according to the electrostatic signal. Since the electrostatic detection module is not arranged in the air duct assembly and is not exposed to the dust-containing airflow, compared with being directly exposed to the dust-containing airflow, the replacement frequency of the electrostatic detection module can be reduced, the disassembly frequency of the ventilation equipment is reduced, the maintenance cost of the ventilation equipment is reduced, and the problem that the maintenance cost of the ventilation equipment is high due to the existing filter screen dirty block detection mode is solved.

Description

Technical Field

[0001] This application relates to the field of filter clogging detection, and more particularly to a filter clogging detection method, system, ventilation device, and storage medium. Background Technology

[0002] After prolonged operation, the filters of air conditioning equipment and air purifiers are prone to clogging. Clogging filters will affect the operating energy consumption of air conditioning equipment. In order to detect the clogging of the filter, most traditional differential pressure detection methods and light reflection / refraction methods are used. However, the core components such as the detection sensors of these methods are exposed to the dusty airflow, which leads to the need to replace the sensors frequently. Moreover, the disassembly, installation and maintenance of the ventilation equipment are very laborious. Therefore, these methods result in high maintenance costs for ventilation equipment. Summary of the Invention

[0003] This application provides a method, system, ventilation device, and storage medium for detecting filter clogging, in order to solve the problem that existing filter clogging detection methods result in high maintenance costs for ventilation devices.

[0004] In a first aspect, this application provides a filter clogging detection system, the filter clogging detection system comprising: A duct assembly, wherein a filter screen and a conductive target area are sequentially arranged along the airflow direction, the conductive target area is parallel to the airflow direction, and an electric field penetration window is opened on the duct wall at a position opposite to the bottom of the conductive target area; An electrostatic detection module is provided below the electric field penetration window. The electrostatic detection module is used to detect the electrostatic signal generated by the friction between the dust particle flux passing through the filter and the conductive target area through the electric field penetration window. A filter clogging detection device is electrically connected to the electrostatic detection module and is used to determine the current clogging status of the filter based on the electrostatic signal.

[0005] Optionally, the sidewall of the conductive target area is bonded to the wall of the air duct, or the conductive target area is fixedly connected to the wall of the air duct by embedding an insulating frame, and the target surface of the conductive target area is a first preset distance away from the wall of the air duct.

[0006] Secondly, this application provides a method for detecting filter clogging, applied to the filter clogging detection system described above, the filter clogging detection method comprising: Electrostatic parameters are determined based on the electrostatic signals of the conductive target area obtained within a preset time period. The current state of dirt and clogging of the filter is determined based on the electrostatic parameters.

[0007] Optionally, determining the current clogging status of the filter screen based on the electrostatic parameters includes: Based on the electrostatic parameters, determine the electrostatic potential enhancement ratio and the electrostatic fluctuation enhancement ratio; The clogging index of the filter screen is determined by the weighted sum of the electrostatic potential enhancement ratio and the electrostatic fluctuation enhancement ratio. The current clogging status of the filter is determined based on the clogging index.

[0008] Optionally, the electrostatic parameters include the average electrostatic voltage and the voltage fluctuation intensity, and determining the electrostatic potential enhancement ratio and the electrostatic fluctuation enhancement ratio based on the electrostatic parameters includes: The electrostatic potential enhancement ratio is determined based on the ratio between the average electrostatic voltage and the voltage reference value; The electrostatic fluctuation enhancement ratio is determined based on the ratio between the voltage fluctuation intensity and the fluctuation reference value.

[0009] Optionally, determining the electrostatic potential enhancement ratio based on the ratio between the average electrostatic voltage and the voltage reference value includes: Obtain local air quality factors; The electrostatic voltage threshold is determined based on the sum of the current air quality factor and the voltage reference value; The electrostatic potential enhancement ratio is determined based on the ratio of the average electrostatic voltage to the electrostatic voltage threshold.

[0010] Optionally, determining the current clogging state of the filter screen based on the clogging index includes: If the clogging index is less than the first threshold, the normal clean state is taken as the current clogging state of the filter screen. If the number of consecutive detections where the clogging index is greater than or equal to the first threshold and less than the second threshold is greater than a preset number, the first clogging state is taken as the current clogging state of the filter. If the number of consecutive detections where the clogging index is greater than or equal to the second threshold is greater than a preset number, the second clogging state is taken as the current clogging state of the filter, wherein the degree of clogging in the second clogging state is greater than the degree of clogging in the first clogging state.

[0011] Optionally, after determining the current clogging state of the filter based on the clogging index, the method further includes: Based on the current clogging status of the filter, determine the corresponding target early warning method and early warning message; The warning message is output according to the target warning method.

[0012] Thirdly, this application provides a ventilation device, which includes the filter clogging detection system described above.

[0013] Fourthly, this application also provides a computer storage medium storing computer-executable instructions for executing the above-described filter clogging detection method.

[0014] Compared with the prior art, the above-mentioned technical solution provided in this application has the following advantages: The filter clogging detection system provided in this application has a conductive target area laid flat behind the airflow of the filter in the air duct assembly. An electrostatic detection module that is not in contact with the conductive target area detects the electrostatic signal generated by the friction between the dust particle flux passing through the filter and the conductive target area. Then, the filter clogging detection device identifies the degree of filter clogging based on the electrostatic signal. Since the electrostatic detection module is not located in the air duct assembly and is not exposed to the dust-laden airflow, the number of times the electrostatic detection module can be replaced can be reduced compared to direct exposure to the dust-laden airflow. This reduces the frequency of disassembly of the ventilation equipment, thereby reducing the maintenance cost of the ventilation equipment and solving the problem of high maintenance cost of ventilation equipment caused by the existing filter clogging detection method. Attached Figure Description

[0015] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] One or more embodiments are illustrated by way of example with reference numerals in the accompanying drawings. These illustrations do not constitute a limitation on the embodiments. Elements with the same reference numerals in the drawings are denoted as similar elements. Unless otherwise stated, the figures in the drawings are not to be limited by scale.

[0018] Figure 1 This application provides an illustration of the environment for a filter clogging detection method according to an embodiment of the present application. Figure 2 A schematic flowchart illustrating a filter clogging detection method provided in this application embodiment; Figure 3 A flowchart illustrating another method for detecting filter clogging provided in this application embodiment; Figure 4A structural block diagram of a filter clogging detection device provided in this application embodiment; Figure 5 This is a schematic diagram of the internal structure of a ventilation device provided in an embodiment of this application. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0020] The following disclosure provides numerous different embodiments or examples for implementing various structures of the invention. To simplify the disclosure, specific examples of components and arrangements are described below. These are merely examples and are not intended to limit the scope of the invention. Furthermore, reference numerals and / or letters may be repeated in different examples. Such repetition is for simplification and clarity and does not in itself indicate a relationship between the various embodiments and / or arrangements discussed.

[0021] Figure 1 This is a diagram illustrating the application environment of a filter clogging detection method in one embodiment. (Refer to...) Figure 1 This filter clogging detection method is applied to ventilation equipment, which can be a purifier, air conditioning equipment, fresh air equipment, etc. The ventilation equipment includes a housing and a filter clogging detection system installed inside the housing, with the filter clogging detection system located near the air outlet of the ventilation equipment.

[0022] Reference Figure 1 The filter clogging detection system includes: The air duct assembly 110 has a filter screen 111 and a conductive target area 112 arranged sequentially along the airflow direction. The conductive target area 112 is parallel to the air duct wall of the air duct assembly 110. An electric field penetration window 113 is opened on the air duct wall at a position opposite to the bottom of the conductive target area 112. An electrostatic detection module 120 is vertically disposed below the electric field penetration window 113 and at a first preset distance from the electric field penetration window 113. The electrostatic detection module 120 is used to detect the electrostatic signal generated by the friction between the dust particle flux passing through the filter screen 111 and the conductive target area 112 through the electric field penetration window 113. The filter screen clogging detection device 130 is electrically connected to the electrostatic detection module 120 and is used to determine the current clogging status of the filter screen 111 based on the electrostatic parameters.

[0023] Specifically, the air duct assembly 110 is supported by a non-bottom material, which can be made of metal. The filter screen 111 is intercepted and disposed inside the air duct assembly 110 along the cross-sectional direction of the air duct assembly 110. The conductive target area 112 is laid flat inside the air duct assembly 110, that is, the conductive target area 112 is perpendicular to the filter screen 111 and is located at the bottom of the conductive target area 112. An electric field penetration window 113 is opened on the air duct wall. The area of ​​the conductive target area 112 is larger than the area of ​​the electric field penetration window 113. If the electric field penetration window 113 is not opened, the grounded equipment casing will generate an opposite and equal electric field to completely shield the internal electrostatic field inside the metal, and no electrostatic signal can be detected from the outside. Therefore, the electric field penetration window 113 is required so that the electrostatic signal of the conductive target area 112 can be detected from the outside.

[0024] The electrostatic detection module 120 is a non-contact electrostatic potentiometer, which is vertically installed at the bottom of the electric field penetration window 113 and at a second preset distance from the electric field penetration window 113. The second preset distance is 3 to 8 centimeters, so as to realize non-contact electrostatic detection of the conductive target area 112 and transmit the detected electrostatic signal to the filter screen clogging detection device 130. The filter screen clogging detection device 130 analyzes and processes the electrostatic signal to identify the degree of clogging of the filter screen 111. The filter screen clogging detection device 130 can be implemented using a microcontroller or a main control chip.

[0025] When the dust-laden airflow flows through the air duct at the rear end of the filter screen 111 under the drive of the fan, the dust particles collide and rub frequently with the conductive target area 112, causing static charge to accumulate on the surface of the conductive target area 112, forming a suspended surface potential that can be detected by an external potentiometer. The electrostatic intensity Q of the conductive target area 112 is equal to the dust particle flux N multiplied by the charge e of a single dust particle, that is, Q=N×e.

[0026] When the filter screen 111 is relatively new, the dust particle flux is small. The airflow through the filter screen 111 experiences low resistance and a uniform and gentle flow velocity. The airflow has a weak effect on removing dust adhering to the filter screen surface, resulting in a low total amount of dust particles reaching the target area. Consequently, the amount of charge accumulated in the conductive target area 112 due to triboelectric charging remains at a low level, and the static electricity accumulation in the target area is weak. As the filter screen 111 gradually becomes clogged, the pores of the filter screen 111 are slowly blocked by dust, and the overall effective ventilation area continues to decrease. The airflow volume delivered by the fan remains basically stable, and the airflow is forced to accelerate. The airflow velocity on the filter screen surface and in the pores inside the filter screen increases significantly. With the increase in airflow velocity, the airflow shear force and scouring force are significantly enhanced, continuously tearing and peeling off the dust that was originally trapped on the filter screen surface and inside the pores. The dust that is blown off is no longer trapped by the filter screen and directly passes through the filter screen 111 with the airflow, entering the rear air duct and impacting the conductive target area 112. That is, when the high-speed airflow passes through, it peels off the dust particles on its surface and in the pores, resulting in an exponential increase in the dust particle flux. This growth can be directly converted into a change in the electrostatic intensity of the conductive target area 112. This change can be converted into a voltage signal by the electrometer and output to the signal processing unit, becoming the core characteristic quantity characterizing the degree of blockage of the filter screen 111. This provides an accurate physical basis for subsequent multi-level state judgment, namely, electrostatic voltage V=F(Q). The representation function mapping relationship means that the accumulated charge Q in the target area is the independent variable, and the potential voltage V measured by the electrometer is uniquely determined by Q. V is a function of Q. That is, the amount of electrostatic charge accumulated in the conductive target area 112 corresponds to the corresponding detection voltage output by the electrometer. There is a fixed correspondence between the two.

[0027] Therefore, the electrostatic signal mentioned above is the electrostatic voltage corresponding to the accumulated electrostatic charge. The amount of accumulated electrostatic charge on the conductive target area 112 is determined by the magnitude of the electrostatic voltage, and thus the degree of clogging of the filter screen 111 is determined. That is, the larger the electrostatic voltage, the more serious the clogging of the filter screen 111, and vice versa.

[0028] Compared to traditional methods that use differential pressure sensors to detect filter clogging, this solution eliminates the need for two pressure-sensing holes in the air ducts before and after filter 111, preventing the differential pressure detection from becoming completely ineffective due to dust accumulation and blockage in the pressure-sensing holes. It also solves the problem of significant accuracy degradation caused by dust contamination of the sensor itself after long-term operation. Furthermore, compared to traditional methods that indirectly infer the degree of clogging based on fan current and speed, this solution avoids inaccuracies in clogging assessment due to fan performance aging over long-term operation, and is also unaffected by power fluctuations caused by grid voltage variations. The reliability and long-term stability of the test results are significantly improved. In addition, this solution directly quantifies the actual degree of dirt clogging of filter 111 by the correspondence between dust flux and electrostatic intensity. The detection sensitivity is higher, and it can output a recognizable voltage signal when the degree of dirt clogging of filter 111 changes slightly. It can achieve accurate classification of multi-level dirt clogging states, avoiding the shortcomings of traditional detection methods that can only give dirt clogging alarms and cannot distinguish between light and heavy dirt clogging. It provides users with more accurate filter replacement prompts and also provides accurate data support for the adaptive adjustment of air temperature and air speed of ventilation equipment.

[0029] Furthermore, since the electrostatic detection module 120 is not located inside the air duct assembly 110 and is not exposed to the dusty airflow, compared to the detection sensor being directly exposed to the dusty airflow, the number of times the electrostatic detection module 120 needs to be replaced can be reduced, thereby reducing the frequency of disassembly of the ventilation equipment. Even if the electrostatic detection module 120 needs to be replaced, only the equipment casing needs to be disassembled, which reduces the maintenance cost of the ventilation equipment and solves the problem of high maintenance cost of ventilation equipment caused by the existing filter clogging detection method.

[0030] In one embodiment, the sidewall of the conductive target area 112 is adhered to the duct wall, or the conductive target area 112 is fixedly connected to the duct wall by embedding an insulating frame, and the target surface of the conductive target area 112 is a second preset distance away from the duct wall.

[0031] Specifically, the conductive target area 112 is laid flat inside the air duct assembly 110, and the part of the conductive target area 112 that contacts the air duct wall is bonded together so that the target surface of the conductive target area 112 is at a first preset distance from the air duct wall. The first preset distance is 5~10mm, which ensures that there is a certain insulating gap between the target surface of the conductive target area 112 and the air duct wall, and ensures that there is enough space to support the effective accumulation of charge.

[0032] Alternatively, a special insulating frame can be designed during processing, and the conductive target area 112 can be directly embedded into the insulating frame during assembly, similar to a photo frame covering a photo. The insulating frame lies flat inside the air duct wall, and the four top corners of the insulating frame are fixedly connected to the air duct wall. The insulating frame supports the conductive target area 112 to lie flat inside the pipe assembly.

[0033] The fixing method of bonding or embedding the insulating frame can ensure the connection stability between the conductive target area 112 and the duct wall. Under the conditions of continuous airflow impact and temperature fluctuation in the duct, it can prevent the conductive target area 112 from loosening and shifting, ensuring the long-term stability of the positional accuracy of the entire discharge structure and reducing the problem of decreased discharge uniformity caused by structural displacement. On the other hand, the setting of the second preset distance can accurately control the electric field distribution and airflow field state near the conductive target area 112. It can avoid the local distortion of the electric field caused by the small distance between the target surface and the duct wall, prevent abnormal discharge and abnormal ablation of the target material caused by excessively high local field strength, and extend the service life of the conductive target area 112. It can also avoid the decrease in ionization efficiency caused by the large distance, ensuring that the airflow to be processed in the duct can fully pass through the conductive target area 112, improving the electrostatic identification accuracy. At the same time, the embedding of the insulating frame can also block unnecessary current leakage between the conductive target area 112 and the duct wall while achieving fixation, reducing the useless power consumption of the whole machine and improving energy utilization efficiency.

[0034] In one embodiment, Figure 2 This is a flowchart illustrating a method for detecting filter clogging in one embodiment. (Refer to...) Figure 2 This paper provides a method for detecting filter clogging. This embodiment primarily applies this method to the aforementioned... Figure 1 Taking a filter clogging detection system as an example, the specific steps of this filter clogging detection method are as follows: Step S210: Determine electrostatic parameters based on the electrostatic signal of the conductive target region 112 obtained within a preset time period.

[0035] Specifically, the preset duration is the time for collecting electrostatic voltage. It can be customized based on the needs of judging the degree of dirt clogging, or it can be dynamically determined based on the previous dirt clogging state. That is, the more severe the dirt clogging in the previous state, the shorter the corresponding preset duration, so as to increase the frequency of dirt clogging state recognition and require more frequent detection of the dirt clogging degree of filter 111 to promptly identify more severe dirt clogging states and remind users to clean or replace filter 111 in a timely manner. Conversely, the less severe the dirt clogging in the previous state, the longer the corresponding preset duration, so as to reduce the frequency of dirt clogging state recognition and thus save the resources consumed in dirt clogging degree recognition.

[0036] The electrostatic signal is electrostatic voltage. Electrostatic parameters are determined based on the electrostatic voltage collected at different times within a preset time period. The electrostatic parameters include the average electrostatic voltage and the voltage fluctuation intensity.

[0037] Step S220: Determine the current clogging status of filter screen 111 based on the electrostatic parameters.

[0038] Specifically, the current state of dirt and blockage can be queried based on the mapping relationship between the average electrostatic voltage, voltage fluctuation intensity, and dirt and blockage status. Alternatively, the current state of dirt and blockage can be determined using a dirt and blockage identification model, which is a neural network model pre-trained based on electrostatic training parameters.

[0039] This method of identifying the clogging status of filter 111 based on electrostatic parameters significantly improves the sensitivity and accuracy of clogging identification compared to traditional differential pressure detection and manual inspection methods. When filter 111 is only slightly clogged and has not yet caused a significant change in airflow pressure, the minute change in the amount of charged dust flowing through filter 111 will be captured by the electrostatic signal of conductive target area 112. The degree of clogging can be accurately quantified by the average electrostatic voltage and the intensity of voltage fluctuation, avoiding the problem of missing mild clogging. At the same time, relying on the quantitative characteristics of electrostatic parameters, both mapping query and model recognition methods can achieve automated online identification of clogging status without the need for manual disassembly and inspection, reducing the cost of manual operation and maintenance, and not affecting the normal operation of the equipment. Furthermore, the design of dynamically adjusting the collection time based on the clogging status mentioned above further achieves a balance between identification accuracy and operating power consumption. This ensures that severe clogging can be detected in time to avoid affecting the operating efficiency of the equipment and air quality, while reducing meaningless calculations and signal collection when the degree of clogging is mild, thus reducing the computing load and energy consumption of the controller of air conditioners, air purifiers and other equipment with filters 111.

[0040] In one embodiment, refer to Figure 3 The step of determining the current clogging status of filter 111 based on the electrostatic parameters includes: Based on the electrostatic parameters, determine the electrostatic potential enhancement ratio and the electrostatic fluctuation enhancement ratio; The clogging index of filter screen 111 is determined by the weighted sum of the electrostatic potential enhancement ratio and the electrostatic fluctuation enhancement ratio. The current clogging status of the filter 111 is determined based on the clogging index.

[0041] Specifically, the electrostatic potential enhancement ratio represents the average increase in the total accumulated electrostatic charge in the conductive target area 112 over a preset time period. This reflects the overall average amount of dust passing through the filter screen 111 per unit time, characterizing the overall average increase in dust flux caused by clogging. When the filter screen 111 is clean, very little dust penetrates it, resulting in weak charge accumulation in the conductive target area 112 and a low electrostatic potential enhancement ratio. Approximately equal to the average electrostatic voltage ,Right now As filter 111 gradually becomes clogged, the airflow velocity increases. A large amount of dust that was originally trapped on the filter surface and in the pores is stripped away by the high-speed airflow and continuously impacts the conductive target area 112 through filter 111. The total amount of charge accumulated per unit time steadily increases, the average electrostatic potential steadily rises, and the average electrostatic voltage increases. As it continues to increase, the electrostatic potential enhancement ratio also continuously increases.

[0042] The electrostatic fluctuation enhancement ratio reflects the degree of airflow turbulence and the intermittent and unstable nature of dust impact. It is a quantitative representation of the non-steady-state clogging characteristics of filter 111, such as localized blockage and dust flakes falling off. When filter 111 is clean, the airflow is stable, with only sporadic trace dust particles randomly impacting the target area, resulting in gentle potential fluctuations and a higher electrostatic fluctuation enhancement ratio. When filter 111 becomes clogged, some pores of the filter become blocked while others remain open, causing turbulent airflow within the duct and fluctuating airflow speed. Large dust particles on the filter surface are intermittently peeled off by the airflow, resulting in concentrated dust clumps impacting the target area. Both of these situations cause the electrostatic voltage of the conductive target area 112 to fluctuate wildly, significantly increasing the dispersion of the sampling data, and significantly increasing the intensity of voltage fluctuations, with S rising synchronously.

[0043] Slow changes in ambient humidity and a uniform, slight increase in background dust in the air will also gradually raise the electrostatic potential enhancement ratio. However, the electrostatic potential enhancement ratio alone cannot distinguish whether the problem is filter clogging or simply a uniform increase in ambient dust. Only a blockage of the filter 111 itself will cause airflow distortion in the duct and intermittent dust shedding, resulting in drastic potential fluctuations. Simple uniform dust in the environment will not cause airflow turbulence or intermittent dust impacts, and the electrostatic fluctuation enhancement ratio will not increase significantly. Therefore, the electrostatic fluctuation enhancement ratio can be used to corroborate that the potential rise is indeed caused by filter clogging, ruling out misjudgments caused by simple uniform dust in the environment. Therefore, by using the weighted sum of the electrostatic potential enhancement ratio and the electrostatic fluctuation enhancement ratio, the clogging index of the filter 111 can be accurately determined. The clogging index is calculated using the formula I = K1 × R + K2 × S, where... , These are weighting coefficients. , The parameters can be customized by the manufacturer based on the sales location after being calibrated through experiments according to different environments, filter types, and other conditions.

[0044] Based on the clogging status corresponding to the clogging index range, the current clogging status of filter 111 is determined. The higher the clogging index, the more severe the clogging; conversely, the lower the clogging index, the less severe the clogging.

[0045] By combining two dimensions of features, the accuracy of dirt and clogging detection is significantly improved in different application environments. Compared to traditional solutions that rely solely on cumulative pressure difference to determine dirt and clogging, this approach avoids detection biases caused by the loosening of filter materials and the natural decrease in air pressure resistance after long-term use. It also avoids misjudgments due to differences in the basic dust concentration in different areas, thus improving detection accuracy. Furthermore, it can trigger alerts before significant filter blockage and a decline in output air quality, allowing users to perform timely filter maintenance and replacement. Simultaneously, this solution relies on electrostatic induction signals for detection, eliminating the need for bulky differential pressure sensors installed in the duct. Only a thin conductive target area 112 is required, minimizing duct space occupation, reducing airflow design complexity, and avoiding additional ventilation resistance, thus reducing overall air pressure loss. This advantage is even more pronounced when adapting to small to medium-sized air purification devices. In addition, the electrostatic induction signal acquisition frequency can reach 100Hz, capturing real-time potential changes caused by dirt and clogging. This allows for timely detection of sudden blockages caused by large amounts of dust accumulation in a short period, further improving the stability of equipment operation and the reliability of output air quality.

[0046] In one embodiment, refer to Figure 3 The electrostatic parameters include the average electrostatic voltage and the voltage fluctuation intensity. Determining the electrostatic potential enhancement ratio and the electrostatic fluctuation enhancement ratio based on the electrostatic parameters includes: The electrostatic potential enhancement ratio is determined based on the ratio between the average electrostatic voltage and the voltage reference value; The electrostatic fluctuation enhancement ratio is determined based on the ratio between the voltage fluctuation intensity and the fluctuation reference value.

[0047] Specifically, voltage reference value In the initial stage of use of filter 111, multiple electrostatic voltages (such as...) are collected according to the sampling window. The mean of ), i.e. Where n represents the number of electrostatic voltages collected within the sampling window, used to represent the long-term average voltage of the electrostatic potential of the conductive target area 112 under clean and unclogging conditions. The formula for calculating the electrostatic potential enhancement ratio is R=V1 / V0.

[0048] Volatility benchmark To measure the overall standard deviation of multiple electrostatic voltages collected during the initial use of filter 111 according to the sampling window, It is used to characterize the natural small fluctuation range of the electrostatic potential of filter 111 in a clean state. That is, when the filter is brand new, the electrostatic voltage will fluctuate normally and randomly due to slight disturbances in airflow and slight fluctuations in ambient temperature and humidity. It is used to distinguish between normal small fluctuations and substantial drastic increases in potential caused by filter clogging in subsequent judgments, so as to prevent misjudgment.

[0049] The formula for calculating the electrostatic fluctuation enhancement ratio is as follows: ,in The voltage fluctuation intensity is calculated based on multiple electrostatic voltages collected within a preset time period. The calculation formula for the voltage fluctuation intensity is the same as that for the fluctuation reference value, except that the electrostatic voltages involved in the calculation are different.

[0050] The calculation method based on the average electrostatic potential and voltage fluctuation intensity to determine the enhancement ratio can simultaneously capture two core changes in the electrostatic signal during the clogging process of filter 111: On the one hand, after filter 111 accumulates dust and dirt, charged particles carried by the airflow are more likely to accumulate on the filter and cannot be released smoothly by the conductive layer, causing the overall electrostatic potential to rise continuously. The electrostatic potential enhancement ratio can intuitively quantify this overall trend change. Compared with the solution that only detects the absolute value of electrostatic potential, it normalizes based on the initial state of a brand-new filter, which can offset the benchmark deviation caused by different operating conditions, different filter materials, and different background electrostatics in the environment, and adapt to the detection needs of different installation scenarios. On the other hand, as the degree of clogging intensifies, the blockage of filter pores will cause uneven airflow velocity through filter 111, and the deposition distribution of charged particles will also gradually become uneven. The random fluctuation amplitude of electrostatic voltage will be significantly higher than that of the initial clean state. The electrostatic fluctuation enhancement ratio can accurately capture this abnormal fluctuation change, effectively eliminate the interference of normal shaking of the brand-new filter itself, and significantly reduce the false judgment rate of clogging. When the two are combined, mild clogging can be identified through trend changes, and early clogging characteristics caused by uneven dirt accumulation can be captured through fluctuation changes. Compared with detection schemes that rely solely on the average value of electrostatic potential, this can improve the accuracy of identifying filter clogging of different degrees and types.

[0051] In one embodiment, refer to Figure 3 The step of determining the electrostatic potential enhancement ratio based on the ratio between the average electrostatic voltage and the voltage reference value includes: Obtain local air quality factors; The electrostatic voltage threshold is determined based on the sum of the current air quality factor and the voltage reference value; The electrostatic potential enhancement ratio is determined based on the ratio of the average electrostatic voltage to the electrostatic voltage threshold.

[0052] Specifically, the local air quality factor L can be obtained from the ventilation equipment connected to the filter clogging detection system, or the local air quality factor corresponding to the installation location can be obtained from the installation location of the ventilation equipment. Alternatively, the local air quality factor can be obtained from the terminal bound to the ventilation equipment. The local air quality factor is used to compensate for the voltage reference value and fluctuation reference value, where L is a function that decreases with air quality.

[0053] Electrostatic voltage threshold is The electrostatic potential enhancement ratio is R= By combining air quality factors to calculate the electrostatic potential enhancement ratio, the systematic deviation of electrostatic voltage detection caused by different air quality environments can be effectively offset. When the air quality is poor, the concentration of suspended particulate matter in the air is higher, making it easier to induce static electricity and raise the baseline voltage level. The L value decreases accordingly with the decrease in air quality, and the final electrostatic potential enhancement ratio R is corrected to a value that is closer to the actual dirt and clogging state, avoiding misjudgment of the degree of dirt and clogging due to the increased baseline voltage caused by poor air quality. Conversely, when the air quality is good, the L value is larger, which can also avoid missing the detection of dirt and clogging of filter 111 due to the low baseline voltage. Through air quality compensation correction, the accuracy of dirt and clogging detection can be improved in different environments. Especially in areas with large fluctuations in air quality, the stability of the detection results is more significantly improved, which can greatly reduce the probability of false triggering of dirt and clogging alarms, extend the effective service life of filter 111, and avoid affecting the working efficiency of ventilation equipment due to failure to detect dirt and clogging in time.

[0054] In one embodiment, refer to Figure 3 The step of determining the current clogging status of the filter 111 based on the clogging index includes: If the clogging index is less than the first threshold, the normal clean state is taken as the current clogging state of the filter 111. If the number of consecutive detections where the clogging index is greater than or equal to the first threshold and less than the second threshold is greater than a preset number, the first clogging state is taken as the current clogging state of the filter 111. If the number of consecutive detections where the clogging index is greater than or equal to the second threshold is greater than a preset number, the second clogging state is taken as the current clogging state of the filter 111, wherein the degree of clogging in the second clogging state is greater than the degree of clogging in the first clogging state.

[0055] Specifically, the first threshold is denoted as The second threshold is denoted as If the dirt and clogging index is less than the first threshold, that is... This indicates that filter 111 is in a clean state and no maintenance command or prompt is required. The normal clean state will be taken as the current dirty and clogged state.

[0056] If the number of consecutive detections where the dirt / clogging index is greater than or equal to the first threshold and less than the second threshold is greater than a preset number, that is, if multiple consecutive detections are detected... If the filter 111 is found to be slightly clogged, then the first clogged state will be taken as the current clogged state.

[0057] If the number of consecutive detections with a contamination index greater than or equal to the second threshold is greater than a preset number, it indicates that multiple consecutive detections have been detected. If the filter 111 is severely clogged, the second clogged state will be taken as the current clogged state.

[0058] This embodiment uses only three index ranges as an example for illustration. Based on this, the number of index ranges can be reduced, or even expanded to include more ranges, to achieve more refined differentiation of congestion conditions. The first and second thresholds mentioned above can also be customized according to actual application requirements.

[0059] This method of determining the clogging status through multiple consecutive tests effectively filters out abnormal jumps in the clogging index caused by airflow fluctuations and environmental interference in a single test. Compared to single-test determination methods, it reduces the false judgment rate and significantly improves the accuracy of clogging status assessment. The customizable threshold and adjustable range design can adapt to the clogging detection needs of different usage scenarios, power levels, and filter specifications: for scenarios with high comfort requirements, such as household air conditioners, the threshold range can be narrowed and the status level increased to trigger a light cleaning reminder in advance, preventing filter clogging from affecting heat exchange efficiency and air quality; for scenarios with high filter replacement costs, such as industrial fresh air systems, the threshold range can be widened and the preset number of tests adjusted to extend the filter's lifespan and reduce maintenance costs while ensuring ventilation effectiveness.

[0060] In one embodiment, refer to Figure 3 After determining the current clogging state of the filter 111 based on the clogging index, the method further includes: Based on the current clogging status of the filter 111, determine the corresponding target early warning method and early warning information; The warning message is output according to the target warning method.

[0061] Specifically, if the current clogging status is mild clogging of filter 111 (i.e., the first clogging status), the user will be prompted to clean filter 111 through gentle warning methods such as the indicator lights on the main control panel and the indicator lights on the ventilation equipment. This will not affect the normal operation of the ventilation equipment.

[0062] If the current clogging status is that the filter screen 111 is severely clogged, the fan will be activated to increase its speed, and a warning message will be sent to the user terminal. The corresponding voice broadcast will also be issued, and the warning message will be "Clean or replace the filter screen 111 immediately". By increasing the fan speed, the airflow to the filter screen 111 will be increased, thereby reducing the amount of dust particles adhering to the filter screen 111.

[0063] This tiered approach to early warning and intervention avoids excessive warnings that disturb users during mild clogging, while ensuring timely status updates through multiple channels during severe clogging. The intervention of temporarily increasing the fan speed alleviates insufficient airflow and increased intake resistance caused by filter 111 clogging before the user completes cleaning or replacement, maintaining the basic ventilation efficiency of the air exchange equipment, reducing the risk of overheating and overload from prolonged high-load motor operation, and extending the lifespan of core components. Compared to fixed, single warning methods, this solution adapts to different levels of clogging and user experience, combining status warnings with temporary performance adjustments to achieve intelligent, closed-loop management of filter 111 maintenance, thus improving the overall stability and energy efficiency of the equipment.

[0064] Figure 2 and Figure 3 This is a flowchart illustrating a filter clogging detection method in one embodiment. It should be understood that, although... Figure 2 and Figure 3 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 2 and Figure 3 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0065] In one embodiment, such as Figure 4 As shown, a filter clogging detection device 130 is provided, comprising: Analysis module 310 is used to determine electrostatic parameters based on the electrostatic signal of the conductive target region 112 obtained within a preset time period; The detection module 320 is used to determine the current clogging status of the filter screen 111 based on the electrostatic parameters.

[0066] In one embodiment, the detection module 320 is further configured to: Based on the electrostatic parameters, determine the electrostatic potential enhancement ratio and the electrostatic fluctuation enhancement ratio; The clogging index of filter screen 111 is determined by the weighted sum of the electrostatic potential enhancement ratio and the electrostatic fluctuation enhancement ratio. The current clogging status of the filter 111 is determined based on the clogging index.

[0067] In one embodiment, the detection module 320 is further configured to: The electrostatic potential enhancement ratio is determined based on the ratio between the average electrostatic voltage and the voltage reference value; The electrostatic fluctuation enhancement ratio is determined based on the ratio between the voltage fluctuation intensity and the fluctuation reference value.

[0068] In one embodiment, the detection module 320 is further configured to: Obtain local air quality factors; The electrostatic voltage threshold is determined based on the sum of the current air quality factor and the voltage reference value; The electrostatic potential enhancement ratio is determined based on the ratio of the average electrostatic voltage to the electrostatic voltage threshold.

[0069] In one embodiment, the detection module 320 is further configured to: If the clogging index is less than the first threshold, the normal clean state is taken as the current clogging state of the filter 111. If the number of consecutive detections where the clogging index is greater than or equal to the first threshold and less than the second threshold is greater than a preset number, the first clogging state is taken as the current clogging state of the filter 111. If the number of consecutive detections where the clogging index is greater than or equal to the second threshold is greater than a preset number, the second clogging state is taken as the current clogging state of the filter 111, wherein the degree of clogging in the second clogging state is greater than the degree of clogging in the first clogging state.

[0070] In one embodiment, the detection module 320 is further configured to: Based on the current clogging status of the filter 111, determine the corresponding target early warning method and early warning information; The warning message is output according to the target warning method.

[0071] It should be noted that the examples and application scenarios implemented by the above modules and corresponding steps are the same, but are not limited to the content disclosed in the above embodiments. It should also be noted that the above modules, as part of the system, can run in environments such as... Figure 1 The hardware environment shown can be implemented either through software or through hardware.

[0072] like Figure 5As shown, this application embodiment provides a ventilation device, including a processor 711, a communication interface 712, a memory 713, and a communication bus 714. The processor 711, the communication interface 712, and the memory 713 communicate with each other through the communication bus 714. The memory 713 is used to store computer programs. When the processor 711 executes the program stored in the memory 713, it implements the filter clogging detection method provided in any of the aforementioned method embodiments.

[0073] The memory and processor in the aforementioned electronic devices communicate with each other via a communication bus and a communication interface. The communication bus can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into an address bus, a data bus, a control bus, etc.

[0074] The memory may include random access memory (RAM) or non-volatile memory, such as at least one disk storage device. Optionally, the memory may also be at least one storage system located remotely from the aforementioned processor.

[0075] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0076] Those skilled in the art will understand that Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the ventilation equipment to which the present application is applied. Specific ventilation equipment may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0077] According to another aspect of the embodiments of this application, a computer program product or computer program is also provided, which includes computer instructions stored in a computer-readable storage medium. A processor of the ventilation device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the ventilation device to perform the steps of any of the above embodiments.

[0078] In one embodiment, the filter clogging detection system provided in this application can be implemented as a computer program, which can be implemented in various ways, such as... Figure 5 The ventilation equipment shown operates on this system. The ventilation equipment's memory can store the various program modules that make up the filter clogging detection system, for example... Figure 4 The analysis module 310 and the detection module 320 are shown. The computer program, composed of these modules, causes the processor to execute the filter clogging detection methods described in the various embodiments of this application.

[0079] Figure 5 The ventilation equipment shown can be used as follows Figure 4 The analysis module 310 in the filter clogging detection system shown determines electrostatic parameters based on the electrostatic signals of the conductive target area 112 acquired within a preset time period. The ventilation equipment can then determine the current clogging status of the filter 111 based on the electrostatic parameters through the detection module 320.

[0080] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the filter clogging detection method provided in any of the foregoing method embodiments.

[0081] Optionally, in embodiments of this application, the computer-readable medium is configured to store program code for the processor to perform the following steps: Based on the electrostatic signal of the conductive target region 112 obtained within a preset time period, the electrostatic parameters are determined; The current clogging status of filter 111 is determined based on the electrostatic parameters.

[0082] Optionally, specific examples in this embodiment can refer to the examples described in the above embodiments, and will not be repeated here.

[0083] It is understood that the embodiments described herein can be implemented in hardware, software, firmware, middleware, microcode, or a combination thereof. For hardware implementation, the processing unit can be implemented in one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), general-purpose processors, controllers, microcontrollers, microprocessors, other electronic units for performing the functions described herein, or combinations thereof.

[0084] For software implementation, the techniques described herein can be implemented by units that perform the functions described herein. The software code can be stored in memory and executed by a processor. The memory can be implemented in the processor or external to the processor.

[0085] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0086] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, units, and processes described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0087] In the embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, indirect coupling or communication connection between systems or units, and may be electrical, mechanical, or other forms.

[0088] The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0089] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0090] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented using software plus a general-purpose hardware platform, or of course, using hardware. Based on this understanding, the above technical solutions, in essence or the parts that contribute to the related technology, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a USB flash drive, mobile hard drive, ROM, RAM, magnetic disk, or optical disk, or other media capable of storing program code, including several instructions to cause a ventilation device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0091] It should be understood that the terminology used herein is for the purpose of describing particular exemplary embodiments only and is not intended to be limiting. Unless the context clearly indicates otherwise, the singular forms “a,” “an,” and “described” as used herein may also mean including the plural forms. The terms “comprising,” “including,” “containing,” and “having” are inclusive and therefore indicate the presence of the stated features, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, elements, components, and / or combinations thereof. The method steps, processes, and operations described herein are not construed as requiring them to be performed in a particular order described or illustrated unless the order of performance is explicitly indicated. It should also be understood that alternatives or substitutions may be used.

[0092] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily 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 invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A filter clogging detection system, characterized in that, The filter clogging detection system includes: A duct assembly, wherein a filter screen and a conductive target area are sequentially arranged along the airflow direction, the conductive target area is parallel to the airflow direction, and an electric field penetration window is opened on the duct wall of the duct assembly at a position opposite to the bottom of the conductive target area; An electrostatic detection module is provided below the electric field penetration window. The electrostatic detection module is used to detect the electrostatic signal generated by the friction between the dust particle flux passing through the filter and the conductive target area through the electric field penetration window. A filter clogging detection device is electrically connected to the electrostatic detection module and is used to determine the current clogging status of the filter based on the electrostatic signal.

2. The filter clogging detection system according to claim 1, characterized in that, The sidewall of the conductive target area is adhered to the wall of the air duct, or the conductive target area is fixedly connected to the wall of the air duct by embedding an insulating frame, and the target surface of the conductive target area is at a first preset distance from the wall of the air duct.

3. A method for detecting filter clogging, characterized in that, The filter clogging detection method, applied to the filter clogging detection system as described in any one of claims 1-2, comprises: Electrostatic parameters are determined based on the electrostatic signals of the conductive target area obtained within a preset time period. The current state of dirt and clogging of the filter is determined based on the electrostatic parameters.

4. The method according to claim 3, characterized in that, Determining the current clogging status of the filter screen based on the electrostatic parameters includes: Based on the electrostatic parameters, determine the electrostatic potential enhancement ratio and the electrostatic fluctuation enhancement ratio; The clogging index of the filter screen is determined by the weighted sum of the electrostatic potential enhancement ratio and the electrostatic fluctuation enhancement ratio. The current clogging status of the filter is determined based on the clogging index.

5. The method according to claim 4, characterized in that, The electrostatic parameters include the average electrostatic voltage and the voltage fluctuation intensity. Determining the electrostatic potential enhancement ratio and the electrostatic fluctuation enhancement ratio based on the electrostatic parameters includes: The electrostatic potential enhancement ratio is determined based on the ratio between the average electrostatic voltage and the voltage reference value; The electrostatic fluctuation enhancement ratio is determined based on the ratio between the voltage fluctuation intensity and the fluctuation reference value.

6. The method according to claim 5, characterized in that, Determining the electrostatic potential enhancement ratio based on the ratio between the average electrostatic voltage and the voltage reference value includes: Obtain local air quality factors; The electrostatic voltage threshold is determined based on the sum of the current air quality factor and the voltage reference value; The electrostatic potential enhancement ratio is determined based on the ratio of the average electrostatic voltage to the electrostatic voltage threshold.

7. The method according to claim 4, characterized in that, Determining the current clogging status of the filter screen based on the clogging index includes: If the clogging index is less than the first threshold, the normal clean state is taken as the current clogging state of the filter screen. If the number of consecutive detections where the clogging index is greater than or equal to the first threshold and less than the second threshold is greater than a preset number, the first clogging state is taken as the current clogging state of the filter. If the number of consecutive detections where the clogging index is greater than or equal to the second threshold is greater than a preset number, the second clogging state is taken as the current clogging state of the filter, wherein the degree of clogging in the second clogging state is greater than the degree of clogging in the first clogging state.

8. The method according to claim 7, characterized in that, After determining the current clogging state of the filter screen based on the clogging index, the method further includes: Based on the current clogging status of the filter, determine the corresponding target early warning method and early warning message; The warning message is output according to the target warning method.

9. A ventilation device, characterized in that, The ventilation equipment includes the filter clogging detection system as described in any one of claims 1-2.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 3 to 8.

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