Method and device for detecting the state of a filter screen of an air purification device

Abstract

The application discloses a kind of detection method and device of air purification equipment filter screen state, it is related to filter screen state monitoring technical field, including, quantum dot material and intelligent response type indicator material are selected, respectively coated and woven to filter screen, the original fluorescence intensity of new filter screen is measured using fluorescence spectrometer, according to the change of fluorescence intensity, the color change of pH sensitive dye and the influence of coating thickness calculate comprehensive evaluation function, acoustic resonance frequency determination is carried out using the data of initial state, the resonance frequency characteristic curve when not being polluted is obtained, the resonance frequency characteristic curve when not being polluted is obtained;The difference between current fluorescence intensity and initial fluorescence intensity is compared, the change of resonance frequency characteristic curve is compared with the resonance frequency characteristic curve when not being polluted, the color of current pH sensitive dye is compared with the first high-quality photo, judge whether there is abnormal condition of intelligent response type indicator material in combination with all comparison results.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of filter screen state monitoring, in particular to a detection method and device for filter screen state of an air purification equipment. BACKGROUND

[0002] Air purification equipment plays a vital role in modern environmental control, and one of its core components is the filter screen. As air quality issues have attracted increasing attention, monitoring and maintaining the filter screen state have become particularly important. Traditional filter screen detection methods mainly include manual inspection, pressure difference measurement, and sensor-based technology. However, these methods have many limitations. For example, manual inspection relies on the experience and technical level of the operator and cannot achieve accurate quantification. Pressure difference measurement can provide some reference information, but it cannot directly reflect the distribution of internal pollutants in the filter screen. Sensor-based methods have some accuracy, but in complex and variable practical application environments, sensors are easily disturbed, leading to inaccurate data. In addition, existing technologies generally lack real-time dynamic monitoring capability for the pollution level of the filter screen, especially in microscopic aspects (such as quantum dot fluorescence intensity changes) and chemical properties (such as pH value changes).

[0003] In recent years, with the development of nanotechnology and smart materials, there has been a new trend of using quantum dots and smart responsive indicators for environmental monitoring. Quantum dots are widely used in biomedical, optoelectronic, and other fields due to their unique optical properties. Smart responsive indicators can sense changes in the surrounding environment and respond accordingly. However, in the field of air purification, the combination of these two advanced materials for filter screen state monitoring is still in its early stages. Existing technical solutions usually only focus on changes in a single parameter, such as temperature or humidity, and lack comprehensive evaluation of the filter screen state. At the same time, traditional methods often overlook the internal relationship between physical structure changes (such as resonance frequency characteristic curves) and chemical property changes (such as pH-sensitive dye color changes), which limits the in-depth understanding of the health status of the filter screen. SUMMARY

[0004] In view of the above existing problems, the present application is proposed.

[0005] Therefore, the present application provides a detection method for filter screen state of an air purification equipment to solve the problem that traditional methods often overlook the internal relationship between physical structure changes (such as resonance frequency characteristic curves) and chemical property changes (such as pH-sensitive dye color changes).

[0006] To solve the above technical problems, the present application provides the following technical solutions:

[0007] The application provides a filter screen state detection method for an air purification device.

[0008] The quantum dot material and the intelligent response type indicator material are selected, coated and woven on the filter screen respectively; the original fluorescence intensity of the new filter screen is measured by using a fluorescence spectrometer, and a high-quality photo is taken to record the color of the intelligent response type indicator material; a comprehensive evaluation function is calculated according to the change of the fluorescence intensity, the color change of the pH sensitive dye and the influence of the coating thickness, and data of the new filter screen coated with the quantum dot and the intelligent response type indicator material and the initial state thereof are obtained;

[0009] In the non-running state of the air purification device, the initial state data are used to determine the acoustic resonance frequency, and a resonance frequency characteristic curve in the non-polluted state is obtained;

[0010] The fluorescence intensity of the new filter screen coated with the quantum dot and the intelligent response type indicator material is measured by using the fluorescence spectrometer regularly, the difference between the current fluorescence intensity and the initial fluorescence intensity is compared, the change of the resonance frequency characteristic curve is compared with the resonance frequency characteristic curve in the non-polluted state, and the current color of the pH sensitive dye is compared with the initial high-quality photo;

[0011] All the comparison results are combined to determine whether the intelligent response type indicator material has an abnormal condition;

[0012] When the abnormal condition occurs, the user is immediately informed to take cleaning measures; after cleaning, the fluorescence intensity and the resonance frequency characteristic curve are measured again, and whether the filter screen returns to normal is confirmed.

[0013] As a preferred scheme of the filter screen state detection method for the air purification device, the quantum dot material is CdSe / ZnS quantum dots selected as the fluorescent marker;

[0014] The intelligent response type indicator material is a pH sensitive dye;

[0015] The CdSe / ZnS quantum dots are uniformly coated on the filter screen by using a spraying method, and the pH sensitive dye is integrated into the filter screen structure by weaving;

[0016] Before the new filter screen is installed, the original fluorescence intensity thereof is measured by using the fluorescence spectrometer, and the original fluorescence intensity is saved as a reference value;

[0017] The intelligent response type indicator material is photographed to obtain a high-quality photo, the color change of the pH sensitive dye is recorded in detail, and a specific time stamp is marked.

[0018] As a preferred scheme of the air purification equipment filter screen state detection method, wherein: the comprehensive evaluation function is calculated according to the change of fluorescence intensity, the color change of pH sensitive dye and the influence of coating thickness, the new filter screen coated with quantum dots and intelligent response indicator and the initial state data thereof are obtained, and the specific steps are as follows:

[0019] The comprehensive evaluation function S(t) is constructed according to the change of fluorescence intensity, the color change of pH sensitive dye and the influence of coating thickness, and the state change of the filter screen is evaluated, and the expression is as follows:

[0020]

[0021] Wherein, S(t) represents the state of the filter screen at time t, F(t) represents the measured fluorescence intensity at time t, F0 represents the initial measured fluorescence intensity, a represents the weight coefficient of the change of fluorescence intensity, The weight coefficient of color change is represented by β, ΔC(t) represents the color change amount at time t relative to the initial state F0, β represents the weight coefficient of coating thickness, and P represents the quantum dot vector.

[0022] As a preferred scheme of the air purification equipment filter screen state detection method, wherein: the acoustic resonance frequency measurement is performed using the initial state data under the non-running state of the air purification equipment, and the resonance frequency characteristic curve when not contaminated is obtained, and the specific steps are as follows:

[0023] Before installing the new filter screen, the original fluorescence intensity F0 is measured using a high-sensitivity fluorescence spectrometer, and the data is saved as a reference value;

[0024] The pH sensitive dye is photographed to obtain high-quality photos, the color change is recorded in detail, and the specific time stamp is marked;

[0025] A small loudspeaker is installed on one side of the filter screen, and a microphone is installed on the other side;

[0026] A small loudspeaker is used to emit short pulse sound to the filter screen, covering all frequency bands causing resonance, and the reflected waveform data received from the microphone is recorded synchronously;

[0027] The reflected waveform data collected is filtered by a band-pass filter to remove unnecessary noise and interference signals; the Hilbert transform is used to identify the peak positions in the reflected waveform data, and these peaks correspond to the resonance frequency points;

[0028] All measured resonance frequency points are plotted into a frequency response curve using MATLAB, and the resonance frequency characteristic curve when not contaminated is obtained.

[0029] As a preferred embodiment of the method for detecting the filter status of the air purification device according to the present invention, the specific steps of comparing the difference between the current fluorescence intensity and the initial fluorescence intensity, and comparing the change of the resonance frequency characteristic curve with the resonance frequency characteristic curve when it is not polluted, are as follows:

[0030] The fluorescence intensity of the filter was measured using a portable fluorescence spectrometer, and the fluorescence intensity was recorded at time t.

[0031] Compare the current fluorescence intensity with the initial fluorescence intensity F0 measured when the new filter is installed to assess the change in fluorescence intensity. When the fluorescence intensity decreases, it indicates that the filter has been contaminated. The greater the decrease, the more serious the contamination.

[0032] Analyze the reflected waveform data, extract the resonant frequency points, and use MATLAB to plot the resonant frequency points as frequency response curves;

[0033] Compare the current frequency response curve with the resonant frequency characteristic curve initially measured when the filter is uncontaminated. When the resonant frequency decreases, it indicates that the filter is clogged. When the resonant frequency increases, it indicates that the filter is cleaner.

[0034] The comparison of the current pH-sensitive dye color with the initial high-quality photograph refers to taking a color photograph of the smart-response indicator material, especially the pH-sensitive dye color, and comparing the currently taken color photograph of the smart-response indicator material with the initially recorded high-quality photograph to check for any color changes. When the pH value changes, it indicates that the filter is contaminated.

[0035] In a preferred embodiment of the method for detecting the filter status of the air purification device described in this invention, the step of determining whether the intelligent response indicator material has any abnormalities by combining all comparison results specifically involves:

[0036] Based on the comparison results of fluorescence intensity changes, resonance frequency characteristic curve changes, and pH-sensitive dye color changes, a comprehensive evaluation function E(t) is constructed, with the following expression:

[0037]

[0038] Among them, f max (t) represents the maximum resonant frequency measured at time t, f max(t0) represents the maximum resonance frequency at the initial measurement, F(t) represents the fluorescence intensity measured at time t, F0 represents the fluorescence intensity at the initial measurement, AC(t) represents the color change amount at time t with respect to the initial state F0, γ represents a weight coefficient of the resonance frequency characteristic curve change, δ represents a weight coefficient of the fluorescence intensity change, and η represents a weight coefficient of the color change of the pH-sensitive dye;

[0039] Setting an abnormal threshold When E(t) exceeds and the color of the pH-sensitive dye changes to red or blue, it is considered that an abnormal situation has occurred.

[0040] As a preferred solution of the method for detecting the state of the filter screen of the air purification device, when an abnormal situation occurs, the user is immediately notified to take cleaning measures; after cleaning, the fluorescence intensity and the resonance frequency characteristic curve are measured again to confirm whether the filter screen has returned to normal, and the specific steps are as follows:

[0041] Classify the abnormal situations according to the fluorescence intensity change, the resonance frequency characteristic curve change, and the color change of the pH-sensitive dye;

[0042] When the fluorescence intensity decreases, it indicates that the quantum dot coating is contaminated or damaged;

[0043] When the resonance frequency decreases, it indicates that the filter screen is clogged or the physical structure has changed;

[0044] When the color of the pH-sensitive dye changes, it indicates that the filter screen has accumulated acidic or alkaline contaminants;

[0045] The pH-sensitive dye is yellow in the initial state, when the filter screen accumulates acidic contaminants, the pH-sensitive dye changes from yellow to red, and when the filter screen accumulates alkaline contaminants, the pH-sensitive dye changes from yellow to blue;

[0046] When the quantum dot coating is contaminated or damaged, a special mild cleaning agent is used to wipe the surface of the filter screen;

[0047] When the filter screen is clogged or the physical structure has changed, a high-pressure water gun is used for flushing and a vacuum cleaner is used for cleaning the blockage;

[0048] When the filter screen accumulates acidic contaminants, an alkaline cleaning agent is used for neutralization, and when the filter screen accumulates alkaline contaminants, an acidic cleaning agent is used for neutralization;

[0049] After cleaning, an automatic re-evaluation process is started.

[0050] In a second aspect, the present application provides a detection device for the state of the filter screen of an air purification device, comprising a collection module, a state monitoring module, an anomaly detection module, an execution module and a review and evaluation module.

[0051] The collection module is used to select quantum dot materials and intelligent response indicator materials, use a spray method to uniformly coat quantum dots on the filter screen, and use a weaving method to integrate pH-sensitive dyes into the filter screen structure.

[0052] The state monitoring module is responsible for regularly measuring the fluorescence intensity, acoustic resonance frequency and color change of the pH-sensitive dye, and analyzing these data to track the state of the filter screen.

[0053] The anomaly detection module assesses the state of the filter screen by constructing a comprehensive evaluation function and classifies and identifies different types of abnormal situations.

[0054] The execution module recommends and guides the user to take appropriate cleaning measures according to the type of anomaly, ensuring the effectiveness and safety of the cleaning operation.

[0055] The review and evaluation module re-evaluates the state of the filter screen after cleaning, confirms whether it has returned to normal, and updates the maintenance log and performs long-term data analysis.

[0056] In a third aspect, the present application provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and wherein the computer program, when executed by the processor, implements any step of the detection method for the state of the filter screen of an air purification device according to the first aspect of the present application.

[0057] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements any step of the detection method for the state of the filter screen of an air purification device according to the first aspect of the present application.

[0058] The present application has the beneficial effects that: the present application realizes multi-parameter and high-precision monitoring of the filter screen state of the air purification equipment by introducing quantum dots and intelligent response indicator materials, the CdSe / ZnS quantum dots provide high-sensitivity optical signals, the pH-sensitive dye senses chemical changes, the sensitivity of the filter screen is enhanced, the original fluorescence intensity is measured by a fluorescence spectrometer and the color change is recorded, a reliable initial state benchmark is established, the monitoring error is reduced, the acoustic resonance frequency measurement technology accurately measures the physical state, distinguishes physical damage from chemical pollution, regular fluorescence intensity measurement realizes dynamic monitoring, early warning of potential problems, a comprehensive evaluation function integrates various parameter changes, ensures comprehensive and accurate state evaluation, when an anomaly is detected, the system immediately notifies the user and recommends personalized cleaning measures such as mild detergent wiping, high-pressure water gun flushing or acid-base neutralization, ensures effective and safe cleaning, re-measures after cleaning to confirm the effect, forms a closed-loop management, ensures efficient operation of the equipment, prolongs the service life of the filter screen, optimizes the maintenance process, and reduces operating costs, and in summary, the present application significantly improves the monitoring accuracy, reliability and maintenance efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0059] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0060] Figure 1 The flow chart of the detection method of the filter screen state of the air purification equipment in embodiment 1.

[0061] Figure 2 The schematic diagram of the detection device of the filter screen state of the air purification equipment in embodiment 1. DETAILED DESCRIPTION

[0062] In order to make the above-mentioned purposes, features and advantages of the present application more apparent and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the drawings of the specification.

[0063] In the following description, many specific details are set forth in order to provide a thorough understanding of the present application, but the present application can also be implemented in other ways different from those described herein, and those skilled in the art can make similar generalizations without departing from the connotation of the present application, therefore the present application is not limited to the specific embodiments disclosed below.

[0064] Second, the "one embodiment" or "an embodiment" referred to herein can include a particular feature, structure, or characteristic. The various embodiments appearing at different places in the specification are not necessarily all cumulative or alternative embodiments of each other. Moreover, terms such as "first" and "second" are used herein only to describe a certain feature, structure, or characteristic, and do not imply that the features, structures, or characteristics are in any way prioritized, except where the context clearly indicates otherwise.

[0065] Embodiment 1, Reference Figure 1 and Figure 2 The first embodiment of the present application provides a method for detecting the state of the filter screen of an air purification device, comprising the following steps:

[0066] S1, select quantum dot materials and intelligent response indicator materials, respectively coated and woven on the filter screen; use a fluorescence spectrometer to measure the original fluorescence intensity of the new filter screen, and take high-quality photos to record the color of the intelligent response indicator material, calculate the comprehensive evaluation function according to the change of fluorescence intensity, the color change of pH sensitive dye and the influence of coating thickness, and obtain the data of the new filter screen coated with quantum dots and intelligent response indicator materials and its initial state;

[0067] The intelligent response indicator material refers to a pH sensitive dye;

[0068] Use the spray method to uniformly coat CdSe / ZnS quantum dots on the filter screen, and integrate the pH sensitive dye into the filter screen structure by weaving;

[0069] Before installing the new filter screen, use a high-sensitivity fluorescence spectrometer to measure its original fluorescence intensity, and save the original fluorescence intensity as a reference value;

[0070] Take photos of the intelligent response indicator material to obtain high-quality photos, and record the color change of the pH sensitive dye in detail, and mark the specific time stamp;

[0071] According to the change of fluorescence intensity, the color change of pH sensitive dye and the influence of coating thickness, a comprehensive evaluation function S(t) is constructed to evaluate the state change of the filter screen, and the expression is:

[0072]

[0073] Wherein, S(t) represents the state of the filter screen at time t, the value range of S(t) is [0, 3], wherein the smaller the value of S(t) represents the more serious pollution, the larger the value of S(t) represents the less pollution, F(t) represents the measured fluorescence intensity at time t, F0 represents the initial measured fluorescence intensity, and a represents the weight coefficient of fluorescence intensity change, Weight coefficient representing color change, ΔC(t) represents the color change amount at time t relative to the initial state F0, β represents the weight coefficient of coating thickness, P represents the quantum dot vector, including the influence of the specific type of quantum dots, quantum dot concentration and coating thickness;

[0074] The expression of P is:

[0075] P=[Q,C,T];

[0076] Wherein, Q represents the specific type of quantum dots, C represents the quantum dot concentration, and T represents the coating thickness;

[0077] The initial state data includes the initial measured fluorescence intensity F0, the color change of the pH-sensitive dye, the coating thickness, the time stamp and the initial value of the comprehensive evaluation function S(t).

[0078] S2, in the state that the air purification equipment is not running, the initial state data is used to determine the acoustic resonance frequency, and the resonance frequency characteristic curve when not contaminated is obtained;

[0079] Before installing a new filter screen, use a high-sensitivity fluorescence spectrometer to measure its original fluorescence intensity F0, and save this data as a reference value;

[0080] Take pictures of the pH-sensitive dye, get high-quality photos, record the color change in detail, and mark the specific time stamp;

[0081] Install a small loudspeaker on one side of the filter screen and a microphone on the other side, ensuring a moderate distance between the two to capture clear reflected waveforms;

[0082] Use a small loudspeaker to emit short pulse sounds to the filter screen, covering all frequency bands that cause resonance, and record the reflected waveform data received from the microphone simultaneously, especially those specific frequencies that exhibit strong reflection characteristics;

[0083] Analyze the reflected waveform data, extract and save these frequency information as the resonance frequency characteristic curve when not contaminated; analyzing the reflected waveform data specifically includes:

[0084] Use band-pass filtering to collected reflected waveform data to remove unnecessary noise and interference signals, and retain useful frequency components; use Hilbert transform to identify the peak positions in the reflected waveform data, which correspond to the resonance frequency points;

[0085] Use MATLAB to plot all measured resonance frequency points into a frequency response curve, showing the amplitude change at different frequencies, and obtain the resonance frequency characteristic curve when not contaminated;

[0086] The frequency information includes a resonance frequency point and a frequency response curve.

[0087] S3, periodically measuring the fluorescence intensity of the new filter screen coated with quantum dots and smart responsive indicator materials using a fluorescence spectrometer, comparing the difference between the current fluorescence intensity and the initial fluorescence intensity, comparing the change of the resonance frequency characteristic curve with the resonance frequency characteristic curve when not contaminated, comparing the current color of the pH sensitive dye with the initial high quality photo;

[0088] Measuring the fluorescence intensity of the filter screen using a portable fluorescence spectrometer, recording the fluorescence intensity at time t;

[0089] Comparing the current fluorescence intensity with the initial fluorescence intensity F0 measured when the new filter screen is installed, evaluating the change of the fluorescence intensity, when the fluorescence intensity decreases, it indicates that the filter screen has been contaminated, the more the decrease, the more serious the contamination;

[0090] In the state that the air purification equipment is not running, a small loudspeaker is used to emit short pulse sound to the filter screen, covering all frequency bands (from 20Hz to 20kHz) that cause resonance, and the reflected waveform data received from the microphone is recorded synchronously;

[0091] Analyzing the reflected waveform data, extracting the resonance frequency point, and using MATLAB to draw the resonance frequency point into a frequency response curve;

[0092] Comparing the current frequency response curve with the initially measured resonance frequency characteristic curve when not contaminated, when the resonance frequency is weakened, it indicates that the filter screen is clogged, when the resonance frequency is enhanced, it indicates that the cleanliness of the filter screen is improved;

[0093] Comparing the current color of the pH sensitive dye with the initial high quality photo means taking a color photo of the smart responsive indicator materials, especially the color of the pH sensitive dye, comparing the currently taken color photo of the smart responsive indicator materials with the initially recorded high quality photo, checking whether there is a color change, when the pH value changes, it indicates that the filter screen is contaminated;

[0094] The pH value of the pH sensitive dye is set to fluctuate in the range of 5 to 9 in the initial state, when the pH value of the pH sensitive dye is 7, the dye presents yellow, when the pH value of the pH sensitive dye is less than 5, the dye turns red, indicating that the filter screen accumulates acidic pollutants, when the pH value of the pH sensitive dye is greater than 9, the dye turns blue, indicating that the filter screen accumulates alkaline pollutants.

[0095] S4, combining all the comparison results to determine whether the smart responsive indicator materials are abnormal;

[0096] According to the fluorescence intensity change comparison result, the resonance frequency characteristic curve change comparison result and the pH sensitive dye color change comparison result, a comprehensive evaluation function E(t) is constructed, and the expression is:

[0097]

[0098] Wherein, f max (t) represents the maximum resonance frequency measured at time t, f max (t0) represents the maximum resonance frequency measured at the initial time as a reference value, F(t) represents the fluorescence intensity measured at time t, F0 represents the initial fluorescence intensity, ΔC(t) represents the color change amount at time t relative to the initial state F0, which is calculated using the color difference algorithm, γ represents the weight coefficient of the resonance frequency characteristic curve change, δ represents the weight coefficient of the fluorescence intensity change, and η represents the weight coefficient of the pH sensitive dye color change.

[0099] The value range of E(t) is [0, 3], and the larger the value of E(t) is, the better the filter screen state is, and no special maintenance is needed, and the smaller the value of E(t) is, the more serious the filter screen blockage is, and immediate cleaning or replacement is needed.

[0100] According to the actual demand, the abnormal threshold is set When E(t) exceeds , and the color of the pH sensitive dye changes to red or blue, it is considered that an abnormal situation has occurred.

[0101] S5, when the abnormal situation occurs, immediately notify the user to take cleaning measures; after cleaning, measure the fluorescence intensity and the resonance frequency characteristic curve again to confirm whether the filter screen returns to normal;

[0102] Classify the abnormal situations of the fluorescence intensity change, the resonance frequency characteristic curve change and the pH sensitive dye color change;

[0103] When the fluorescence intensity decreases, it indicates that the quantum dot coating is contaminated or damaged;

[0104] When the resonance frequency decreases, it indicates that the filter screen is blocked or the physical structure is changed;

[0105] When the pH sensitive dye color changes, it indicates that the filter screen accumulates acidic or alkaline pollutants;

[0106] The pH sensitive dye is yellow in the initial state, when the filter screen accumulates acidic pollutants, the pH sensitive dye changes from yellow to red, and when the filter screen accumulates alkaline pollutants, the pH sensitive dye changes from yellow to blue;

[0107] When the quantum dot coating is contaminated or damaged, gently wipe the filter screen surface with a dedicated mild cleaning agent to avoid damaging the quantum dot coating;

[0108] When the filter screen is clogged or the physical structure changes, use a high-pressure water gun to flush and a vacuum cleaner to clean the clogs;

[0109] When the filter screen accumulates acidic contaminants, neutralize them with an alkaline cleaning agent, and when the filter screen accumulates basic contaminants, neutralize them with an acidic cleaning agent, then thoroughly rinse with clean water to ensure no residual chemicals;

[0110] After cleaning, automatically start the re-evaluation process, which includes:

[0111] Use a portable fluorescence spectrometer to measure the fluorescence intensity of the filter screen and record the fluorescence intensity at time t;

[0112] In the state of non-operation of the air purification equipment, use a small loudspeaker to emit short pulse sound to the filter screen, covering all frequency bands (from 20Hz to 20kHz) that cause resonance, and simultaneously record the reflected waveform data received from the microphone;

[0113] Analyze these waveform data, extract the resonance frequency points, and plot these frequency information into a frequency response curve;

[0114] Take a color photo of the smart response indicator material, especially the color of the pH-sensitive dye, and compare it with the high-quality photo recorded initially to check for any color changes;

[0115] This step ensures that users can know the abnormal state of the filter screen in the shortest time through the introduction of an instant notification mechanism, so that timely cleaning measures can be taken;

[0116] Traditional methods often rely on periodic checks or user subjective judgments, which can lead to delayed processing and affect the performance of air purification equipment. The present invention avoids these problems by monitoring in real time and automatically notifying the user, significantly improving the timeliness and efficiency of maintenance;

[0117] For cases where the quantum dot coating is contaminated or damaged, a mild cleaning agent is used to avoid further damage;

[0118] Traditional cleaning methods may cause irreversible damage to sensitive materials. The mild cleaning agent recommended by the present invention can effectively remove contaminants while maximizing the protection of the quantum dot coating, maintaining its optical properties and ensuring the accuracy of subsequent monitoring.

[0119] The embodiment also provides a detection device for the state of a filter screen of an air purification equipment, which comprises a collection module, a state monitoring module, an abnormality detection module, an execution module, and a review and evaluation module.

[0120] A collection module is used to select quantum dot materials and smart response indicator materials, uniformly coat the quantum dots on the filter screen using a spray method, and integrate the pH-sensitive dye into the filter screen structure through a weaving method. Before installing a new filter screen, the original fluorescence intensity is measured using a high-sensitivity fluorescence spectrometer, and the data is saved as a baseline value.

[0121] A state monitoring module is responsible for regularly measuring the fluorescence intensity, acoustic resonance frequency, and color change of the pH-sensitive dye, and analyzing these data to track the state of the filter screen.

[0122] An anomaly detection module assesses the state of the filter screen by constructing a comprehensive evaluation function and classifies different types of abnormal situations.

[0123] An execution module recommends and guides users to take appropriate cleaning measures according to the type of anomaly, ensuring the effectiveness and safety of the cleaning operation.

[0124] A review and evaluation module re-evaluates the state of the filter screen after cleaning, confirms whether it has returned to normal, and updates the maintenance log and conducts long-term data analysis.

[0125] The embodiment also provides a computer device suitable for the detection method of the state of the filter screen of the air purification device, which includes a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions to realize the detection method of the state of the filter screen of the air purification device proposed in the above embodiment.

[0126] The computer device can be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected through a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to perform wired or wireless communication with external terminals. The wireless communication can be achieved through WIFI, an operator network, NFC (near field communication), or other technologies. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer overlaid on the display screen, or a key, trackball, or touchpad arranged on the shell of the computer device. In addition, the input device can be an external keyboard, touchpad, or mouse, etc.

[0127] The embodiment also provides a storage medium having a computer program stored thereon, the program being executed by a processor to implement the method for detecting the state of the filter screen of the air purification device according to the above embodiment; and the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as a static random access memory (SRAM), an electrically erasable programmable read-only memory (EEPROM), an erasable programmable read-only memory (EPROM), a programmable read-only memory (PROM), a read-only memory (ROM), a magnetic storage, a flash memory, a magnetic disk, or an optical disk.

[0128] To sum up, the present application realizes multi-parameter and high-precision monitoring of the state of the filter screen of the air purification device by introducing quantum dots and smart response indicator materials, the CdSe / ZnS quantum dots provide high-sensitivity optical signals, the pH-sensitive dye senses chemical changes, the sensitivity of the filter screen is enhanced, the original fluorescence intensity is measured by a fluorescence spectrometer and the color change is recorded, a reliable initial state benchmark is established, monitoring errors are reduced, the acoustic resonance frequency measurement technology accurately measures the physical state, physical damage and chemical pollution are distinguished, regular fluorescence intensity measurement realizes dynamic monitoring, potential problems are warned in advance, a comprehensive evaluation function integrates various parameter changes, ensuring comprehensive and accurate state evaluation, when an anomaly is detected, the system immediately notifies the user and recommends personalized cleaning measures, such as wiping with a mild cleaning agent, flushing with a high-pressure water gun, or acid-base neutralization, ensuring effective and safe cleaning, the effect is confirmed after re-measurement after cleaning, forming a closed-loop management, ensuring efficient operation of the equipment, prolonging the service life of the filter screen, optimizing the maintenance process, and reducing operating costs, to sum up, the present application significantly improves the monitoring accuracy, reliability, and maintenance efficiency.

[0129] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present application but not limit the present application, although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or replaced equivalently without departing from the spirit and scope of the technical solutions of the present application, and all of them should be covered in the scope of the claims of the present application.

Claims

1. A method of detecting a state of a filter screen of an air cleaning apparatus, characterized by: The method comprises the following steps: Selecting quantum dot materials and smart response indicator materials, respectively coating and weaving on the filter screen; using a fluorescence spectrometer to measure the original fluorescence intensity of the new filter screen, and taking high-quality photos to record the color of the smart response indicator material; calculating a comprehensive evaluation function according to the changes of fluorescence intensity, the color changes of pH-sensitive dyes and the influence of coating thickness, and obtaining the data of the new filter screen coated with quantum dots and smart response indicator materials and the initial state thereof; In the non-running state of the air purification equipment, acoustic resonance frequency measurement is performed by using the initial state data to obtain the resonance frequency characteristic curve when the filter screen is not contaminated; Periodically measuring the fluorescence intensity of the new filter screen coated with quantum dots and smart response indicator materials by using a fluorescence spectrometer, comparing the difference between the current fluorescence intensity and the initial fluorescence intensity, comparing the change of the resonance frequency characteristic curve with the resonance frequency characteristic curve when the filter screen is not contaminated, and comparing the current color of the pH-sensitive dye with the initial high-quality photo; Combining all the comparison results to determine whether the smart response indicator material is abnormal; When an abnormal situation occurs, immediately notify the user to take cleaning measures, and after cleaning, measure the fluorescence intensity and the resonance frequency characteristic curve again to confirm whether the filter screen returns to normal.

2. The method of claim 1, wherein the method comprises: determining whether the filter is in the first state or the second state based on the comparison result. The quantum dot material refers to selecting CdSe / ZnS quantum dots as fluorescent markers; The smart response indicator material refers to pH-sensitive dyes; The CdSe / ZnS quantum dots are uniformly coated on the filter screen by using a spray method, and the pH-sensitive dyes are integrated into the filter screen structure by weaving; Before installing the new filter screen, the original fluorescence intensity thereof is measured by using a fluorescence spectrometer, and the original fluorescence intensity is saved as a reference value; The smart response indicator material is photographed to obtain a high-quality photo, and the color change of the pH-sensitive dye is recorded in detail, and a specific timestamp is marked.

3. The method of claim 2, wherein the method further comprises: determining whether the filter is in a state of being in use or not in use based on the detected state of the filter. The specific steps of calculating the comprehensive evaluation function according to the changes of fluorescence intensity, the color changes of pH-sensitive dyes and the influence of coating thickness, and obtaining the data of the new filter screen coated with quantum dots and smart response indicator materials and the initial state thereof are as follows: According to the changes of fluorescence intensity, the color changes of pH-sensitive dyes and the influence of coating thickness, a comprehensive evaluation function S(t) is constructed to evaluate the state change of the filter screen, and the expression is as follows: where S(t) represents the state of the filter at time t, F(t) represents the measured fluorescence intensity at time t, F0represents the initial measured fluorescence intensity, and a represents a weight coefficient of the change in fluorescence intensity, represents a weight coefficient of the color change, ΔC(t) represents the color change amount at time t with respect to the initial state F0, β represents a weight coefficient of the coating thickness, and P represents a quantum dot vector.

4. The method of claim 3, wherein the method further comprises: determining whether the filter is in the replacement state based on the detected state of the filter. The specific steps of measuring the acoustic resonance frequency by using the initial state data in the non-running state of the air purification equipment to obtain the resonance frequency characteristic curve when the filter screen is not contaminated are as follows: Before installing the new filter screen, the original fluorescence intensity F0 thereof is measured by using a high-sensitivity fluorescence spectrometer, and the data is saved as a reference value; The pH-sensitive dye is photographed to obtain a high-quality photo, and the color change is recorded in detail, and a specific timestamp is marked; A small loudspeaker is installed on one side of the filter screen, and a microphone is installed on the other side; A small loudspeaker is used to emit short pulse sound to the filter screen, covering all frequency bands causing resonance, and synchronous recording of reflected waveform data received from the microphone is performed; The collected reflection waveform data is filtered by a band-pass filter to remove unnecessary noise and interference signals; the Hilbert transform is used to identify the peak positions in the reflection waveform data, which correspond to the resonance frequency points; The measured resonance frequency points are plotted into a frequency response curve using MATLAB, and the resonance frequency characteristic curve in the non-polluted state is obtained.

5. The method of claim 4, wherein the method further comprises: determining whether the filter is in a state of being in use or not in use based on the detected state of the filter. The difference between the current fluorescence intensity and the initial fluorescence intensity is compared, and the change of the resonance frequency characteristic curve is compared with the resonance frequency characteristic curve in the non-polluted state, and the specific steps are as follows: The fluorescence intensity of the filter screen is measured using a portable fluorescence spectrometer, and the fluorescence intensity at time t is recorded; The current fluorescence intensity is compared with the initial measured fluorescence intensity F0 when the new filter screen is installed, and the change of the fluorescence intensity is evaluated. When the fluorescence intensity decreases, it indicates that the filter screen has been polluted, and the more the decrease, the more serious the pollution; The reflection waveform data is analyzed, the resonance frequency points are extracted, and the resonance frequency points are plotted into a frequency response curve using MATLAB; The current frequency response curve is compared with the initially measured resonance frequency characteristic curve in the non-polluted state. When the resonance frequency decreases, it indicates that the filter screen is clogged, and when the resonance frequency increases, it indicates that the cleanliness of the filter screen is improved. The current color of the pH-sensitive dye is compared with the initial high-quality photo, which means that the color photo of the smart responsive indicator material, especially the color of the pH-sensitive dye, is taken. The current color photo of the smart responsive indicator material is compared with the initially recorded high-quality photo to check whether there is a color change. When the pH value changes, it indicates that the filter screen is polluted.

6. The method of claim 5, wherein the method further comprises: determining whether the filter is in a state of being in use or not in use based on the detected state of the filter. The combination of all comparison results to determine whether the smart responsive indicator material has abnormal conditions is as follows: According to the comparison results of the fluorescence intensity change, the comparison results of the resonance frequency characteristic curve change, and the comparison results of the pH-sensitive dye color change, a comprehensive evaluation function E(t) is constructed, and the expression is as follows: wherein f max (t) represents the maximum resonance frequency measured at time t, f max (t0) represents the maximum resonance frequency at the initial measurement, F(t) represents the fluorescence intensity measured at time t, F0 represents the fluorescence intensity at the initial measurement, ΔC(t) represents the color change amount at time t with respect to the initial state F0, γ represents a weight coefficient of the resonance frequency characteristic curve change, δ represents a weight coefficient of the fluorescence intensity change, and η represents a weight coefficient of the color change of the pH-sensitive dye; Setting an abnormal threshold When E(t) exceeds and the color of the pH-sensitive dye changes to red or blue, it is considered that an abnormal situation has occurred.

7. The method of claim 6, wherein the method further comprises: determining whether the filter is in a state of being in use or not in use based on the detected state of the filter. When an abnormal condition occurs, the user is immediately notified to take cleaning measures; after cleaning, the fluorescence intensity and the resonance frequency characteristic curve are measured again to confirm whether the filter screen has returned to normal, and the specific steps are as follows: Classify the abnormal conditions of the fluorescence intensity change, the resonance frequency characteristic curve change, and the pH-sensitive dye color change; When the fluorescence intensity decreases, it indicates that the quantum dot coating is polluted or damaged; When the resonance frequency decreases, it indicates that the filter screen is clogged or the physical structure has changed; When the color of the pH-sensitive dye changes, it indicates that the filter screen has accumulated acidic or alkaline pollutants; The pH-sensitive dye is yellow in the initial state. When the filter screen accumulates acidic pollutants, the pH-sensitive dye changes from yellow to red. When the filter screen accumulates alkaline pollutants, the pH-sensitive dye changes from yellow to blue; When the quantum dot coating is polluted or damaged, a special mild cleaning agent is used to wipe the surface of the filter screen; When the filter screen is clogged or the physical structure has changed, a high-pressure water gun is used for flushing and a vacuum cleaner is used for cleaning the blockage; When the filter screen accumulates acidic pollutants, an alkaline cleaning agent is used for neutralization, and when the filter screen accumulates alkaline pollutants, an acidic cleaning agent is used for neutralization. After cleaning is completed, an automatic re-evaluation process is started.

8. An apparatus for detecting a state of a filter screen of an air cleaning device, based on the method for detecting a state of a filter screen of an air cleaning device according to any one of claims 1 to 7, characterized by: It includes a collection module, a state monitoring module, an anomaly detection module, an execution module, and a review and evaluation module: The collection module is used to select quantum dot materials and intelligent response indicator materials, use a spray method to uniformly coat quantum dots on a filter screen, and integrate pH-sensitive dyes into the filter screen structure through a weaving method. Before installing a new filter screen, a high-sensitivity fluorescence spectrometer is used to measure the original fluorescence intensity, and the data is saved as a baseline value. The state monitoring module is responsible for regularly measuring fluorescence intensity, acoustic resonance frequency, and color changes of pH-sensitive dyes, and analyzing these data to track the state of the filter screen. The anomaly detection module assesses the state of the filter screen by constructing a comprehensive evaluation function and classifies and identifies different types of abnormal situations. The execution module recommends and guides users to take appropriate cleaning measures according to the type of anomaly, ensuring the effectiveness and safety of cleaning operations. The review and evaluation module re-evaluates the state of the filter screen after cleaning, confirms whether it has returned to normal, and updates the maintenance log and conducts long-term data analysis. 9.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is characterized in that: The processor executes the computer program to implement the steps of the air purification equipment filter screen state detection method of any one of claims 1-7.

10. A computer readable storage medium having stored thereon a computer program, characterized in that: The computer program is executed by the processor to implement the steps of the air purification equipment filter screen state detection method of any one of claims 1-7.

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