A dynamic detection method for ceramic atomizer core

Abstract

The present invention discloses a dynamic detection method for ceramic atomizer cores, which relates to the technical field of atomizer core detection. The method includes: analyzing the full production cycle record of the target ceramic atomizer core to obtain the target initial atomization coefficient; performing dynamic period detection on the target ceramic atomizer core through a sensor component to obtain the full use cycle record; reading the predetermined atomization effect characteristics; obtaining direct characteristic information and indirect characteristic information; activating a dynamic evaluation model to perform dynamic evaluation and analysis to obtain the target real-time atomization coefficient; judging whether the target atomization performance decline rate is within the predetermined decline rate threshold; if not, performing performance fault early warning maintenance on the target ceramic atomizer core. The method solves the technical problems existing in the prior art that the performance changes of the ceramic atomizer core during use cannot be accurately monitored in real time, the atomizer core performance monitoring is delayed, and the equipment operation stability and user experience are poor, and achieves the technical effect of improving the operation stability of the atomizer core and the user experience.

Description

Technical Field

[0001] The present application relates to the technical field related to atomizer core detection, and in particular to a dynamic detection method for ceramic atomizer cores. Background Art

[0002] Ceramic atomizer core is an important component widely used in atomization equipment, commonly found in electronic cigarettes, gas atomizers and other products. Its main function is to convert liquid into fine atomized particles to facilitate gas transmission or inhalation. With the continuous development of technology, the performance requirements of ceramic atomizer cores are getting higher and higher, especially in terms of atomization effect, service life and stability. However, traditional ceramic atomizer core detection methods focus more on static testing, such as evaluating the performance of atomizer cores through laboratory environmental simulation tests. Although it can reflect certain performance data, it cannot fully reflect the dynamic changes that may occur in the actual use of ceramic atomizer cores, which affects the judgment of the performance of ceramic atomizer cores and further affects the atomization effect of ceramic atomizer cores.

[0003] At present, there are technical problems in the technology related to ceramic atomizer core detection, such as the inability to accurately monitor the performance changes of the ceramic atomizer core during use in real time and the lag in atomizer core performance monitoring, which leads to poor equipment operation stability and user experience. Summary of the invention

[0004] This application solves the technical problems in the prior art that the performance changes of the ceramic atomizer core during use cannot be accurately monitored in real time, and the atomizer core performance monitoring is delayed, resulting in poor equipment operation stability and user experience by providing a dynamic detection method for the ceramic atomizer core, thereby achieving the technical effect of improving the operation stability of the atomizer core and the user experience.

[0005] The present application provides a dynamic detection method for ceramic atomizer cores, comprising: analyzing a full production cycle record of a target ceramic atomizer core to obtain a target initial atomization coefficient; performing dynamic periodic detection on the target ceramic atomizer core through a sensor component to obtain a full use cycle record; reading a predetermined atomization effect feature, wherein the predetermined atomization effect feature includes a predetermined direct feature and a predetermined indirect feature; sequentially traversing the full use cycle record based on the predetermined direct feature and the predetermined indirect feature to obtain direct feature information and indirect feature information, respectively; activating a dynamic evaluation model to dynamically evaluate and analyze the direct feature information and the indirect feature information to obtain a target real-time atomization coefficient; judging whether a target atomization performance reduction rate obtained by comparing the target real-time atomization coefficient with the target initial atomization coefficient is within a predetermined reduction rate threshold; if not, performing performance fault warning maintenance on the target ceramic atomizer core.

[0006] In a possible implementation, the full production cycle record of the target ceramic atomizer core is analyzed to obtain the target initial atomization coefficient, and the following processing is performed: extract the target slurry characteristic parameters of the target conductive slurry in the full production cycle record, the target slurry characteristic parameters including a plurality of slurry components with proportion identifications; vectorize the plurality of slurry components with proportion identifications to obtain a target electrode component vector; perform matching analysis on the target electrode component vector in the ceramic atomizer core conductive slurry database to obtain the most matching electrode component vector; obtain the initial atomization coefficient of the ceramic atomizer core corresponding to the most matching electrode component vector, and record the initial atomization coefficient as the target initial atomization coefficient.

[0007] In a possible implementation, after the initial atomization coefficient is recorded as the target initial atomization coefficient, the following processing is also performed: a target electrode image of a target alloy electrode made of the target conductive paste is obtained; texture structure feature collection is performed on the target electrode image to obtain target texture feature parameters; a normalized weighted calculation is performed on the target texture feature parameters to obtain a target electrode state index, and the target initial atomization coefficient is adjusted with the target electrode state index; wherein the target texture feature parameters include at least surface roughness data and porosity data.

[0008] In a possible implementation, the target ceramic atomization core is dynamically and periodically detected by a sensor component, and the following processing is also performed: the sensor component includes an atomization effect direct monitoring component and an atomization effect indirect monitoring component, wherein the atomization effect direct monitoring component includes at least a flow sensor, an image sensor and a gas sensor, and the atomization effect indirect monitoring component includes at least a temperature sensor, a humidity sensor, a sound sensor and a vibration sensor.

[0009] In a possible implementation, the dynamic evaluation model is activated to dynamically evaluate and analyze the direct feature information and the indirect feature information to obtain a target real-time atomization coefficient, and the following processing is also performed: the historical full-use cycle record of the same type of atomizer core of the target ceramic atomizer core is obtained, and the first record of the first historical cycle in the historical full-use cycle record is extracted; the first direct feature information and the first indirect feature information in the first record are sequentially varied and weighted to obtain a first direct detection index and a first indirect detection index, respectively; a first data group is formed based on the first direct feature information and the first direct detection index, and the first data group is supervised and trained to obtain a first primary model; a second data group is formed based on the first indirect feature information and the first indirect detection index, and the second data group is supervised and trained to obtain a second primary model; a third data group is formed by combining the first output information of the first primary model, the second output information of the second primary model and the first real-time atomization coefficient in the first record; the first primary model, the second primary model and the meta-evaluation model obtained by the supervised training of the third data group are constructed to obtain the dynamic evaluation model.

[0010] In a possible implementation, a third data group is formed by combining the first output information of the first primary model, the second output information of the second primary model and the first real-time atomization coefficient in the first record, and the following processing is also performed: extracting the second record of the second historical period in the historical full usage cycle record; inputting the second direct feature information in the second record into the first primary model to obtain the third output information; inputting the second indirect feature information in the second record into the second primary model to obtain the fourth output information; taking the average of the third output information and the first output information, replacing the first output information to form the third data group, and taking the average of the fourth output information and the second output information, replacing the second output information to form the third data group.

[0011] In a possible implementation, the sensor assembly also includes a current sensor and a voltage sensor. After activating the dynamic evaluation model to dynamically evaluate and analyze the direct feature information and the indirect feature information to obtain the target real-time atomization coefficient, the following processing is also performed: sequentially extract the current cycle timing detected by the current sensor and the voltage cycle timing detected by the voltage sensor in the full usage cycle record; combine the current cycle timing and the voltage cycle timing to obtain the target power cycle timing of the target ceramic atomization core; perform stability analysis on the target power cycle timing to obtain a target power stability index; and calibrate the target real-time atomization coefficient using the target power stability index as a weight coefficient.

[0012] In a possible implementation, a stability analysis is performed on the target power cycle timing to obtain a target power stability index, and the following processing is also performed: a power spectral density analysis is performed on the target power cycle timing to obtain a target spectral density analysis result; a first energy distribution corresponding to a first frequency component in the target spectral density analysis result is compared with a second energy distribution corresponding to a second frequency component to obtain a target comparison result; and the target power stability index is determined based on the target comparison result.

[0013] Through the dynamic detection method of ceramic atomizer core proposed in this application, the full production cycle record of the target ceramic atomizer core is analyzed to obtain the target initial atomization coefficient; the target ceramic atomizer core is dynamically detected through the sensor component to obtain the full use cycle record; the predetermined atomization effect characteristics are read; direct feature information and indirect feature information are obtained; the dynamic evaluation model is activated for dynamic evaluation and analysis to obtain the target real-time atomization coefficient; it is determined whether the target atomization performance decline rate is within the predetermined decline rate threshold; if not, the target ceramic atomizer core is subjected to performance fault warning maintenance. It solves the technical problems existing in the prior art that the performance changes of the ceramic atomizer core during use cannot be accurately monitored in real time, and the atomizer core performance monitoring is delayed, resulting in poor equipment operation stability and user experience, and achieves the technical effect of improving the operation stability of the atomizer core and user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solution of the embodiment of the present invention, the accompanying drawings of the embodiment of the present invention will be briefly introduced below. A flow chart is used in the present application to illustrate the operations performed by the system according to the embodiment of the present application. It should be understood that the preceding or following operations are not necessarily performed accurately in order. On the contrary, various steps can be processed in reverse order or simultaneously as needed. At the same time, other operations can also be added to these processes, or one or more operations can be removed from these processes.

[0015] Figure 1 A schematic diagram of a flow chart of a dynamic detection method for a ceramic atomizer core provided in an embodiment of the present application;

[0016] Figure 2 A schematic diagram of the process of recording and analyzing the production cycle in a dynamic detection method for ceramic atomizer cores provided in an embodiment of the present application. DETAILED DESCRIPTION

[0017] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0018] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0019] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict, and the terms "first\second" involved are merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "including" and "having" and any variations are intended to cover non-exclusive inclusions, for example, a process, method, product, or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by technicians in the technical field of this application. The terms used herein are for the purpose of describing the embodiments of the present application only.

[0020] The present application embodiment provides a method for dynamic detection of ceramic atomizer cores, such as Figure 1 As shown, the method includes:

[0021] Step S100, analyzing the full production cycle record of the target ceramic atomizer core to obtain a target initial atomization coefficient.

[0022] Preferably, by analyzing the data records of the ceramic atomizer core at various stages from production to delivery, its initial atomization performance is calculated, that is, the atomization effect index when it is just produced and has not been used for a long time or worn out. Specifically, after the atomizer core is just produced and has passed quality inspection, a certain number of tests (such as simulating several smoking or usage scenarios) are usually carried out to verify whether its performance meets the requirements, and a simulation test is carried out on the target ceramic atomizer core within a predetermined frequency range to determine the initial performance state of the target atomizer core, that is, to obtain the target initial atomization coefficient, wherein the initial atomization coefficient is a quantitative representation of the performance of the ceramic atomizer core, which is usually obtained through testing (such as simulated smoking tests or using other sensor detection methods), reflecting the atomization effect of the atomizer core, such as the ratio of liquid converted to mist during the atomization process, the size distribution of atomized particles, changes in temperature and pressure during the atomization process, and other indicators, and is used as a benchmark value in the subsequent dynamic monitoring and evaluation process, and is used to compare with the performance of the atomizer core in actual use, so as to determine whether its performance has declined.

[0023] Further, such as Figure 2 As shown, step S100 also includes step S110, extracting target slurry characteristic parameters of the target conductive slurry in the full production cycle record, wherein the target slurry characteristic parameters include a plurality of slurry components with proportion identifications; step S120, vectorizing the plurality of slurry components with proportion identifications to obtain a target electrode component vector; step S130, traversing and matching the target electrode component vector in the ceramic atomization core conductive slurry database to obtain the most matching electrode component vector; step S140, obtaining the initial atomization coefficient of the ceramic atomization core corresponding to the most matching electrode component vector, and recording the initial atomization coefficient as the target initial atomization coefficient.

[0024] Preferably, the electrode component characteristics of the target ceramic atomizer core are extracted from the full production cycle records, and these characteristics are used for matching analysis to obtain the initial atomization coefficient related to the electrode component. The core is to vectorize the components of the conductive slurry and match them in the database to obtain the initial atomization performance data of the ceramic atomizer core that best matches the electrode component. Specifically, the target conductive slurry is the material used for conductivity in the target ceramic atomizer core, which is usually mixed with multiple chemical components in a specific proportion. The target slurry characteristic parameters refer to the detailed parameters describing the components in the conductive slurry, including the proportion of each component, that is, the proportion of each chemical component in The relative content ratio in the slurry can reflect the composition of the slurry, thus affecting the performance of the atomizer core. For example, the characteristic parameters of the target slurry may include the content ratio of different metal oxides, conductive polymers and other components; vectorization of multiple slurry components with ratio identification is to convert the ratio identification of each component in the target slurry into a mathematical vector. For example, if there are three components in the target slurry, namely A, B and C, and their ratios are 30%, 40% and 30%, then the vectorized representation is a vector containing these three ratios, such as (0.3, 0.4, 0.3), which is the target electrode component vector and represents the characteristics of the conductive slurry.

[0025] Preferably, the target electrode component vector is traversed and matched in the ceramic atomizer core conductive slurry database, that is, by comparing the target electrode component vector with all the slurry component vectors already in the database, the best matching component vector is found. The matching degree is usually determined by some similarity metric (such as Euclidean distance, cosine similarity, etc.), and the purpose is to find the one that is closest to the target slurry component. The ceramic atomizer core conductive slurry database is a database that stores the conductive slurry component data of different ceramic atomizer cores. The conductive slurry component of each atomizer core can be represented by characteristic parameters and stored in the database. The best matching electrode component vector is in the database. The component vector closest to the target electrode component vector represents the composition of an actual ceramic atomizer core conductive slurry similar to the target conductive slurry composition. Then, the initial atomization coefficient corresponding to the most matching electrode component vector is obtained. The initial atomization coefficient of each ceramic atomizer core represents the performance state of the atomizer core at the time of initial use, which is used to reflect the atomization effect of the atomizer core just after production or in the initial stage of use. The initial atomization coefficient of the ceramic atomizer core corresponding to the most matching electrode component vector is used as the target initial atomization coefficient, and as the performance benchmark of the ceramic atomizer core under normal conditions, which is used to compare with the real-time atomization coefficient in actual use to determine whether the performance of the equipment has declined.

[0026] Furthermore, step S140 also includes step S141, obtaining a target electrode image of a target alloy electrode made of the target conductive paste; step S142, collecting texture structure features of the target electrode image to obtain target texture feature parameters; step S143, performing normalized weighted calculation on the target texture feature parameters to obtain a target electrode state index, and adjusting the target initial atomization coefficient with the target electrode state index; step S144, wherein the target texture feature parameters include at least surface roughness data and porosity data.

[0027] Preferably, the electrode made of the conductive paste of the target ceramic atomization core is image analyzed to extract the surface texture features, and the electrode state index is calculated based on these features, and the initial atomization coefficient of the atomization core is adjusted. Specifically, the target electrode image of the target alloy electrode made of the target conductive paste is obtained. The target alloy electrode is the part of the ceramic atomization core used for electrical conduction, usually made of metal or alloy material, made of conductive paste, and may be embedded in the ceramic substrate through processes such as spraying and printing. The surface image of the target electrode is obtained by an image acquisition device such as a camera to analyze the surface characteristics of the electrode, such as texture, structure, etc., and then the image is processed. The electrode surface image is analyzed by the physical technology to extract its surface texture structural characteristics, including at least surface roughness data, porosity data, etc., as the target texture feature parameters to quantify the texture characteristics of the electrode surface. Among them, the surface roughness indicates the microscopic unevenness of the electrode surface. The surface with higher roughness usually affects the atomization effect and changes the contact angle and evaporation rate of the liquid on the electrode surface. The porosity refers to the number and size of pores on the electrode surface, which is usually measured by scanning electron microscope (SEM) images or other high-resolution imaging technologies. The surface with higher porosity may cause the contact area between the electrode surface and the liquid to change, thereby affecting the atomization effect.

[0028] Preferably, the target texture feature parameters are normalized and weighted. Specifically, different texture feature parameters (such as surface roughness and porosity) may have different degrees of influence on the electrode performance. It is necessary to emphasize the importance of certain features through weighting, and adjust the values ​​of each feature parameter to the same range (such as between 0 and 1) through normalization processing so that they have the same comparison benchmark in the calculation, thereby calculating the target electrode state index, which reflects the state of the electrode and is used to measure the influence of the electrode surface characteristics on the atomization performance. The higher the electrode state index, the more suitable the structure of the electrode surface is for the atomization process and the better the atomization performance. Then, by analyzing the target electrode state index, if the surface state of the electrode (such as roughness, porosity, etc.) changes, it may affect its atomization effect. The initial atomization coefficient is adjusted according to the actual surface characteristics of the electrode, so as to more accurately evaluate and adjust the performance of the ceramic atomization core.

[0029] Step S200, performing dynamic period detection on the target ceramic atomizer core through a sensor assembly to obtain a full usage cycle record.

[0030] Step S200 further includes that the sensor component includes an atomization effect direct monitoring component and an atomization effect indirect monitoring component, wherein the atomization effect direct monitoring component includes at least a flow sensor, an image sensor and a gas sensor, and the atomization effect indirect monitoring component includes at least a temperature sensor, a humidity sensor, a sound sensor and a vibration sensor.

[0031] Preferably, a sensor assembly (including multiple sensors) is used to monitor the performance changes of the target ceramic atomizer core during its use. Specifically, multiple different sensors are used to detect and collect the working status data of the target atomizer core in different ways to form a dynamic monitoring record of the entire use cycle, that is, a full use cycle record is obtained, wherein the sensor assembly includes an atomization effect direct monitoring assembly and an atomization effect indirect monitoring assembly. The atomization effect direct monitoring assembly is mainly used to directly detect the atomization effect, that is, the direct performance of the atomizer core in actual work. The data obtained by these sensors can directly reflect the working status of the atomizer core, the quality and efficiency of the atomization effect, and at least include a flow sensor, an image sensor and a gas sensor. The flow sensor is used to measure gas or liquid The flow rate of the body. During the use of the ceramic atomizer core, the flow sensor can detect the flow rate of the liquid (such as e-cigarette liquid) or gas passing through the atomizer core. The flow change may affect the atomization effect. By monitoring the flow, it is possible to determine whether the airflow and liquid supply of the atomizer core are normal; the image sensor (such as a camera or infrared imaging) is used to monitor the size and distribution of the atomized particles and the visualization of the atomization effect. The image sensor can help determine whether there are problems such as excessively large particles and uneven atomization during the atomization process; the gas sensor is used to detect changes in gas composition during the atomization process, such as gas concentration (such as water vapor, smoke components, etc.). In applications such as e-cigarettes, the gas sensor can be used to monitor whether the atomized gas meets the expected composition and whether the atomization effect is normal.

[0032] Preferably, the indirect monitoring component of the atomization effect indirectly infers the quality of the atomization effect by monitoring some relevant factors in the atomization process, rather than directly measuring the atomization effect itself. These factors may affect the atomization effect, and therefore can be used to evaluate the overall working state and performance of the device. Specifically, the indirect monitoring component of the atomization effect includes at least a temperature sensor, a humidity sensor, a sound sensor, and a vibration sensor. The temperature sensor is used to monitor the temperature of the atomization core. The temperature fluctuation during the atomization process directly affects the vaporization efficiency of the liquid. Too high or too low a temperature may cause unstable atomization effect. The temperature sensor helps to detect the working temperature in real time to ensure that the atomization core operates within the normal temperature range; the humidity sensor is used to monitor the humidity in the air. Humidity changes may affect the atomization effect. Especially when the ambient humidity is high or low, the atomization effect may be affected. The humidity sensor can be used to determine whether the surrounding environment affects the stability of the atomization process; the sound sensor is used to monitor the noise during the atomization process. The working state of the atomizer core (such as vibration, working frequency, etc.) may produce sounds of specific frequencies. The sound sensor can capture these sound data and determine whether the atomizer core is working properly by analyzing the sound pattern. Abnormal sound changes may be an indication of decreased performance of the atomizer core; the vibration sensor is used to detect the vibration generated by the atomizer core during operation. Excessive vibration may indicate that there is some kind of fault in the atomizer core (such as blockage or wear), affecting its normal atomization effect. The vibration sensor helps monitor these abnormal vibrations and further reflects the working state of the atomizer core.

[0033] Preferably, through the multiple sensors of the sensor assembly, the actual working state of the ceramic atomizer core can be dynamically monitored, and data records of the entire use cycle can be obtained. Direct monitoring components such as flow sensors, image sensors and gas sensors can provide direct data on the atomization effect, while indirect monitoring components such as temperature, humidity, sound and vibration sensors can indirectly infer changes in the atomization effect by monitoring other environmental and mechanical factors related to the atomization effect. Combining these data provides support for dynamic evaluation of the atomizer core performance, thereby more accurately judging the service life and performance change trend of the target atomizer core.

[0034] Step S300, reading predetermined atomization effect characteristics, wherein the predetermined atomization effect characteristics include predetermined direct characteristics and predetermined indirect characteristics.

[0035] Preferably, in the dynamic detection of the ceramic atomizer core, the key index of the atomization effect, i.e., the predetermined atomization effect characteristic, is defined according to a preset standard or reference value as the evaluation standard for the atomizer core performance, and is used to compare with the actually measured data, so as to judge whether the performance of the atomizer core is normal or has declined. Specifically, the predetermined atomization effect characteristic includes a predetermined direct characteristic and a predetermined indirect characteristic. The predetermined direct characteristic is an indicator directly related to the atomization effect, and is usually used to quantify and evaluate the direct working performance of the atomizer core, obtained through actual measurement and analysis, and directly reflects the effect and efficiency of the atomizer core, and may include atomization particle size, atomization efficiency, atomization flow rate, and gas composition or concentration, wherein the size of the atomization particle is obtained through image Sensor detection, preset atomization particle size range, the atomization core with better atomization effect should be able to atomize the liquid into tiny, uniform particles; atomization efficiency refers to the ratio of liquid to mist, which can be directly measured by flow sensors, etc. The predetermined atomization efficiency characteristics will define an ideal atomization efficiency value as a standard for normal operation; the atomization flow rate is detected by a flow sensor, setting a standard flow range, which indicates the gas or liquid flow rate that the atomization core should achieve under normal working conditions; the gas composition or concentration is detected using a gas sensor, and the predetermined atomization effect characteristics may also include the gas composition and concentration after atomization. For example, an electronic cigarette device may require a certain concentration of steam or gas to provide a suitable inhalation experience.

[0036] Preferably, the predetermined indirect feature is an indicator that indirectly reflects the atomization effect. The atomization effect is usually inferred by monitoring other environmental factors related to the atomization process or the operating status of the equipment. Although the atomization effect cannot be directly measured, it has important reference value for evaluating the atomization performance. Specifically, the predetermined indirect feature may include temperature range, humidity level, sound feature, and vibration feature. Among them, the atomizer core should maintain a certain temperature range during normal operation. Too high or too low temperature may affect the atomization effect. The predetermined temperature feature sets an ideal operating temperature range as a standard for normal performance; changes in ambient humidity may affect the atomization effect, especially for some fine-grained atomization effect requirements. The predetermined humidity feature defines a normal working environment humidity range; by monitoring the sound emitted during the operation process by the sound sensor, it can be inferred whether the equipment is operating normally. For example, abnormal noise or vibration generated by the atomizer core may indicate a problem with the atomization process. The predetermined sound feature may include a frequency range and noise level during normal operation; the equipment vibration information monitored by the vibration sensor can also reflect the working status of the equipment. Excessive vibration usually means that the equipment is operating abnormally. The predetermined vibration feature sets a normal vibration range.

[0037] Preferably, these predetermined atomization effect characteristics (direct characteristics and indirect characteristics) will be used as performance evaluation benchmarks and compared with the actually measured data. By comparing the difference between the actual atomization effect and the predetermined characteristics, it is possible to analyze in real time whether the atomizer core has performance degradation or failure. For example, during the dynamic detection process, the actually measured atomizer core performance data (such as flow rate, temperature, humidity, gas composition, etc.) is read and compared with the predetermined standard. If there is a significant deviation between the actual data and the predetermined standard (for example, the flow rate is lower than the predetermined range, the temperature is too high, etc.), it indicates that the atomizer core may be at risk of performance degradation or failure, thereby triggering an early warning and performing maintenance.

[0038] Step S400, traversing the full usage cycle record based on the predetermined direct feature and the predetermined indirect feature in turn to obtain direct feature information and indirect feature information respectively.

[0039] Preferably, predetermined direct features and predetermined indirect features are applied to the monitoring records of the entire use cycle of the ceramic atomizer core to analyze and extract the performance data of the atomizer core, that is, the preset performance standards (i.e., the characteristics of the atomization effect) are compared with the data collected during actual use, so as to extract specific information related to the performance of the atomizer core, including direct feature information and indirect feature information. Specifically, the full use cycle record refers to all operating data of the ceramic atomizer core from production to final use, including the operating data of the atomizer core under different working conditions, such as temperature, humidity, flow, gas composition, vibration, sound, etc. The monitoring data recorded in the full use cycle is traversed, the working state of the atomizer core at each moment is analyzed, and the direct feature information and indirect feature information are extracted from the monitoring data according to the predetermined direct features and the predetermined indirect features.

[0040] Preferably, direct feature information is directly related to the atomization effect and can directly reflect the working performance of the atomizer core. The data obtained by direct monitoring components such as flow sensors, image sensors, and gas sensors are used to measure the atomization effect of the atomizer core in actual use. For example, the flow rate of the atomizer core recorded by the flow sensor and the size of the atomized particles monitored by the image sensor are all direct feature information, which can be directly used to judge the quality of the atomization effect. Indirect feature information does not directly measure the atomization effect, but is environmental or working status information closely related to the atomization effect. The data obtained by indirect monitoring components such as temperature sensors, humidity sensors, sound sensors, and vibration sensors are used to infer the performance of the atomizer core. For example, the equipment temperature recorded by the temperature sensor, the environmental humidity monitored by the humidity sensor, the working noise captured by the sound sensor, and the vibration reflected by the vibration sensor are all indirect feature information, which can reveal whether the atomizer core is working stably and whether there is any abnormality. By judging the working status and performance changes of the atomizer core in real time, it is ensured that the equipment can be maintained or adjusted in time.

[0041] Step S500, activating a dynamic evaluation model to perform dynamic evaluation and analysis on the direct feature information and the indirect feature information to obtain a target real-time atomization coefficient.

[0042] Preferably, the collected direct feature information and indirect feature information are input as input data into a dynamic evaluation model to calculate the working state index of the atomizer core in real time, that is, the target real-time atomization coefficient. Specifically, the dynamic evaluation model is a prediction model for real-time evaluation of the working performance of the ceramic atomizer core. The dynamic evaluation model may be trained using machine learning (such as neural networks, decision trees, etc.), based on different input data (such as direct feature information and indirect feature information), to analyze the input data and dynamically calculate the atomization performance of the output atomizer core at the current moment, that is, the target real-time atomization coefficient. The dynamic evaluation means that this evaluation model can be used according to different time periods or The data changes under different working conditions are analyzed in real time rather than statically evaluated, to ensure that the performance of the target atomizer core can be evaluated according to the constantly changing conditions (such as temperature, humidity, flow rate, etc.) during actual use; the target real-time atomization coefficient is used to reflect the atomization effect and working efficiency of the atomizer core during actual use, which may be a comprehensive evaluation of the atomization efficiency (the working efficiency of the atomizer core), particle uniformity (the size and distribution of atomized particles) and equipment stability (such as indirect characteristic information such as temperature, humidity, vibration, etc.). For example, the atomization efficiency, particle uniformity and equipment stability are weighted to obtain the target real-time atomization coefficient, which reflects the atomization effect of the target atomizer core.

[0043] Further, step S500 also includes step S510, obtaining the historical full-use cycle record of the same type of atomizer core of the target ceramic atomizer core, and extracting the first record of the first historical cycle in the historical full-use cycle record; step S520, sequentially performing variation weighted analysis on the first direct feature information and the first indirect feature information in the first record to obtain a first direct detection index and a first indirect detection index, respectively; step S530, forming a first data group based on the first direct feature information and the first direct detection index, and performing supervised training on the first data group to obtain a first primary model; step S540, forming a second data group based on the first indirect feature information and the first indirect detection index, and performing supervised training on the second data group to obtain a second primary model; step S550, combining the first output information of the first primary model, the second output information of the second primary model and the first real-time atomization coefficient in the first record to form a third data group; step S560, constructing the first primary model, the second primary model and the meta-evaluation model obtained by supervised training of the third data group to obtain the dynamic evaluation model.

[0044] Preferably, the dynamic evaluation model evaluates the real-time performance and future usage status of the atomizer core by analyzing the usage cycle, characteristic data and model output of the ceramic atomizer core. Specifically, the historical full usage cycle records of similar atomizer cores of the target ceramic atomizer core are obtained, that is, the historical data of other atomizer cores with similar structures or performance characteristics as the target ceramic atomizer core, including their usage cycles, performance changes and other information, and the corresponding records of a certain historical period are randomly extracted from the historical data of similar atomizer cores as the first record of the first historical period, which contains the initial atomization performance information and other related parameters; then, the direct features (such as atomization flow, temperature, etc.) and indirect features (such as ambient humidity, sound, etc.) in the first record are subjected to variation weighted analysis, that is, considering the change trend and volatility of the data, different weights are assigned according to the importance of each feature, and the first direct detection index is obtained, which reflects the atomization effect of the atomizer core at this stage (such as atomization flow, atomization particle size, etc.), and the first indirect detection index reflects other factors affecting the atomization effect (such as temperature, humidity, vibration, etc.).

[0045] Preferably, a first data group is composed of the first direct feature information and the first direct detection index, and a supervised learning algorithm is used to train the data group based on the labeled data (i.e., historical data with clear atomization performance identification) to obtain a first primary model, which can predict the atomization performance according to the direct features and the detection index; a second data group is composed of the first indirect feature information and the first indirect detection index, and a supervised learning method similar to the above is used to train the data group to obtain a second primary model, which predicts that the atomization performance is affected by indirect factors (such as temperature, humidity, etc.), and the model can predict the atomization performance of the target atomization core based on the indirect features and the detection index; a first output information of the first primary model, a second output information of the second primary model, and a first real-time atomization coefficient in the first record are combined to form a second primary model. Three data groups contain multi-dimensional atomization performance prediction information, wherein the first output information is the atomization performance data based on direct feature prediction, the second output information is the atomization performance data based on indirect feature prediction, and the first real-time atomization coefficient represents the real-time atomization effect of the target ceramic atomization core in the first historical period. Similarly, the third data group is supervised and trained to obtain a meta-evaluation model, which is used to provide a more accurate atomization performance evaluation by integrating various feature information (direct, indirect features and real-time atomization coefficient). Finally, a dynamic evaluation model is constructed based on the first primary model, the second primary model and the meta-evaluation model, which can evaluate the current performance of the ceramic atomization core in real time, and can not only predict the current state of the atomization core, but also predict the performance changes during future use, to help with early warning and maintenance.

[0046] Furthermore, step S550 also includes step S551, extracting the second record of the second historical period in the historical full usage cycle record; step S552, inputting the second direct feature information in the second record into the first primary model to obtain third output information; step S553, inputting the second indirect feature information in the second record into the second primary model to obtain fourth output information; step S554, taking the average of the third output information and the first output information, replacing the first output information to form the third data group, and taking the average of the fourth output information and the second output information, replacing the second output information to form the third data group.

[0047] Preferably, the corresponding record of a certain historical period is randomly extracted from the historical full usage cycle record as the second record of the second historical period, including the specific performance data of the atomizer core in the second period (such as atomization effect, temperature, flow rate, etc.), and direct feature data is extracted from the second record of the second historical period as the second direct feature information, including atomization flow rate, atomization intensity, spray effect, etc., which are input into the first primary model, and the output result is used as the third output information; indirect feature data is extracted from the second record of the second historical period as the second indirect feature information, including environmental conditions (such as humidity, temperature), vibration, sound, etc., which are input into the second primary model, and the output result is used as the fourth output information; then the mean of the third output information and the first output information is calculated to balance the evaluation results of the past (first period) and current (second period) models, and the mean replaces the original first output information as part of the third data group; the mean of the fourth output information and the second output information is calculated to integrate past and present data to avoid over-reliance on data at a single time point, and the mean replaces the original second output information as part of the third data group.

[0048] Furthermore, step S500 also includes step S570, sequentially extracting the current cycle timing detected by the current sensor and the voltage cycle timing detected by the voltage sensor in the full usage cycle record; step S580, combining the current cycle timing and the voltage cycle timing to obtain the target power cycle timing of the target ceramic atomization core; step S590, performing stability analysis on the target power cycle timing to obtain a target power stability index; step S5100, using the target power stability index as a weight coefficient to calibrate the target real-time atomization coefficient.

[0049] Preferably, the current cycle timing detected by the current sensor and the voltage cycle timing detected by the voltage sensor in the full use cycle record are extracted from the current cycle timing. Specifically, the current cycle timing records the intensity and changes of the current at each moment. During the working process of the ceramic atomizer core, the current will fluctuate with the working state (such as electrode load, atomization process, etc.), so the current data can reflect the workload and performance state of the atomizer core; the voltage cycle timing reflects the change of the voltage of the ceramic atomizer core during the working process. The fluctuation of voltage and the fluctuation of current complement each other, which helps to more comprehensively understand the interactive relationship between power supply and load; according to the timing data of current and voltage, the power of the target ceramic atomizer core at each moment is calculated and the target power cycle timing is formed, that is, the power change of the ceramic atomizer core at each moment in the entire use cycle.

[0050] Preferably, a stability analysis is performed on the target power cycle timing, specifically, the volatility and uniformity of the power signal are evaluated, the purpose is to determine whether the power remains stable, or whether there are drastic fluctuations or abnormal changes. A power timing with good stability indicates that the working process of the ceramic atomizer core is stable and the atomization effect is relatively uniform; conversely, a timing with large power fluctuations may indicate that the atomizer core has a risk of performance degradation or failure, thereby obtaining a target power stability index, which is used to measure the degree of power fluctuation. A higher index value means that the power is more stable and the performance of the atomizer core is more reliable; a lower index value may mean that the atomizer core has unstable performance; finally, the target power stability index is used as a weight coefficient to calibrate the real-time atomization coefficient. For example, if the power stability is good (that is, the stability index is high), it can be considered that the working state of the atomizer core is good, and the real-time atomization coefficient at this time is more reliable; if the power stability is poor, the real-time atomization coefficient may need to be adjusted to reduce its accuracy or make corrections. The accuracy of the real-time atomization coefficient can be improved through calibration to ensure that it more truly reflects the actual performance of the atomizer core.

[0051] Furthermore, step S590 also includes step S591, performing power spectral density analysis on the target power cycle timing to obtain a target spectral density analysis result; step S592, comparing a first energy distribution corresponding to a first frequency component in the target spectral density analysis result with a second energy distribution corresponding to a second frequency component to obtain a target comparison result; and step S593, determining the target power stability index based on the target comparison result.

[0052] Preferably, a power spectrum density analysis is performed on the target power periodic time series, that is, the power signal is converted from the time domain to the frequency domain by Fourier transform, and the energy distribution of the signal on different frequency components is analyzed to reveal the energy intensity of different frequency components in the signal, thereby evaluating the stability of the power signal, and obtaining a target spectrum density analysis result, which is usually a plurality of frequency components and corresponding energy distributions, which can help reveal the periodic fluctuation of the power signal and its frequency characteristics. A stable power signal usually has a relatively uniform frequency distribution, while an unstable signal may show abnormal energy aggregation at certain frequencies; two frequency components are randomly obtained as the first frequency component and the second frequency component, and the corresponding first energy distribution and the second energy distribution are respectively obtained for comparison to evaluate whether the energy at different frequencies is balanced, and a target comparison result is obtained. If the energy of one frequency component is significantly higher than that of another frequency component, it indicates that the signal is unstable or has abnormal fluctuations at the frequency; finally, the target power stability index is determined according to the target comparison result, that is, if the energy comparison result of the first frequency component and the second frequency component shows a large fluctuation (that is, the energy difference of the frequency components is large), it means that the instability of the power signal is strong and the target stability index is low. On the contrary, if the energy distribution is relatively uniform, it indicates that the signal is stable and the target stability index is high. The target power stability index is used to calibrate and adjust the real-time atomization coefficient to further improve the accuracy of the ceramic atomization core performance evaluation.

[0053] Step S600, determining whether a target atomization performance reduction rate obtained by comparing the target real-time atomization coefficient with the target initial atomization coefficient is within a predetermined reduction rate threshold.

[0054] Preferably, the degradation of the atomizer core performance is evaluated by comparing the target real-time atomization coefficient with the target initial atomization coefficient, and it is determined whether the target atomization performance degradation rate reaches a predetermined degradation rate threshold, thereby triggering a maintenance or fault warning. Specifically, the target initial atomization coefficient refers to the atomization coefficient obtained according to the optimal working state of the atomizer core at the initial use of the atomizer core, representing the ideal performance level of the atomizer core under normal working conditions, that is, the performance state of the target atomizer core after it has not been used or has only been used in small quantities, for example, by measuring direct characteristics such as atomization efficiency, flow rate, and atomized particle size when it is used for the first time. The target atomization performance degradation rate refers to a ratio calculated by comparing the target real-time atomization coefficient with the target initial atomization coefficient, which is used to measure the degree of performance degradation of the atomizer core. For example, the ratio of the difference between the target initial atomization coefficient and the target real-time atomization coefficient to the target initial atomization coefficient reflects the degree of performance degradation of the atomizer core. A higher decline rate may mean that the performance of the atomizer core has significantly declined, affecting the atomization effect of the target atomizer core. Among them, the predetermined decline rate threshold is a pre-set critical value for judging whether the performance of the atomizer core has declined to the extent that maintenance or replacement is required. It is usually set based on the service life, performance requirements and fault prediction factors of the atomizer core, while taking into account the normal wear and tear of the atomizer core in long-term use and the extent of performance degradation. For example, if the predetermined decline rate threshold is set to 10%, then when the target atomization performance decline rate exceeds 10%, it is determined that the performance of the atomizer core has significantly declined and fault warning or maintenance is required.

[0055] Step S700: If not, a performance fault warning maintenance is performed on the target ceramic atomizer core.

[0056] Preferably, when the atomization performance decrease rate calculated by judging the target real-time atomization coefficient and the target initial atomization coefficient is not within the set predetermined decrease rate threshold, the target ceramic atomization core is subjected to performance fault warning maintenance, that is, a fault warning is issued to remind the operator that the performance of the atomization core has declined and may affect the overall effect of the equipment, and then the target atomization core is maintained, inspected and repaired, such as cleaning the e-liquid clogged in the pores of the atomization core, to ensure the normal operation of the equipment and reduce performance losses caused by equipment failure.

[0057] The above specific implementation manner does not constitute a limitation to the protection scope of the present application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application should be included in the protection scope of the present application. In some cases, the actions or steps recorded in the present application can be performed in an order different from that in the embodiment and can still achieve the desired results. In addition, the process depicted in the accompanying drawings does not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A dynamic detection method for ceramic atomizer core, characterized in that: include: Analyze the full production cycle records of the target ceramic atomizer core to obtain the target initial atomization coefficient; Performing dynamic periodic detection on the target ceramic atomizer core through a sensor assembly to obtain a full usage cycle record; Reading a predetermined atomization effect characteristic, wherein the predetermined atomization effect characteristic includes a predetermined direct characteristic and a predetermined indirect characteristic; The full usage cycle record is traversed sequentially based on the predetermined direct feature and the predetermined indirect feature to obtain direct feature information and indirect feature information respectively; Activating a dynamic evaluation model to dynamically evaluate and analyze the direct feature information and the indirect feature information to obtain a target real-time atomization coefficient; Determine whether a target atomization performance decrease rate obtained by comparing the target real-time atomization coefficient with the target initial atomization coefficient is within a predetermined decrease rate threshold; If not, performing performance fault warning maintenance on the target ceramic atomizer core; Among them, the full production cycle record of the target ceramic atomizer core is analyzed to obtain the target initial atomization coefficient, including: Extracting target slurry characteristic parameters of the target conductive slurry in the full production cycle record, wherein the target slurry characteristic parameters include a plurality of slurry components with proportion identifications; Performing vector processing on the plurality of slurry components with ratio identifications to obtain a target electrode component vector; Perform matching analysis on the target electrode component vector in the ceramic atomizer core conductive slurry database to obtain the most matching electrode component vector; Obtaining an initial atomization coefficient of the ceramic atomization core corresponding to the most matching electrode component vector, and recording the initial atomization coefficient as the target initial atomization coefficient; The dynamic evaluation model is activated to dynamically evaluate and analyze the direct feature information and the indirect feature information to obtain the target real-time atomization coefficient, including: Obtaining a historical full-use cycle record of a similar atomizer core of the target ceramic atomizer core, and extracting a first record of a first historical cycle in the historical full-use cycle record; Sequentially performing weighted analysis on the first direct feature information and the first indirect feature information in the first record to obtain a first direct detection index and a first indirect detection index respectively; Forming a first data group based on the first direct feature information and the first direct detection index, and performing supervised training on the first data group to obtain a first primary model; Building a second data set based on the first indirect feature information and the first indirect detection index, and performing supervised training on the second data set to obtain a second primary model; Combining the first output information of the first primary model, the second output information of the second primary model and the first real-time atomization coefficient in the first record to form a third data set; Building the first primary model, the second primary model, and a meta-evaluation model obtained by supervised training of the third data set to obtain the dynamic evaluation model; The third data set is formed by combining the first output information of the first primary model, the second output information of the second primary model and the first real-time atomization coefficient in the first record, including: Extracting a second record of a second historical period from the historical full usage period record; inputting the second direct feature information in the second record into the first primary model to obtain third output information; inputting the second indirect feature information in the second record into the second primary model to obtain fourth output information; The average of the third output information and the first output information is taken to replace the first output information to form the third data group, and the average of the fourth output information and the second output information is taken to replace the second output information to form the third data group.

2. According to the method for dynamic detection of ceramic atomizer cores according to claim 1, it is characterized in that: After recording the initial atomization coefficient as the target initial atomization coefficient, the method further includes: Acquire a target electrode image of a target alloy electrode made of the target conductive paste; Collecting texture structure features of the target electrode image to obtain target texture feature parameters; Performing normalized weighted calculation on the target texture feature parameters to obtain a target electrode state index, and adjusting the target initial atomization coefficient according to the target electrode state index; Wherein, the target texture characteristic parameters at least include surface roughness data and porosity data.

3. According to the method for dynamic detection of ceramic atomizer cores according to claim 1, it is characterized in that: The sensor component includes a direct monitoring component for atomization effect and an indirect monitoring component for atomization effect, wherein the direct monitoring component for atomization effect includes at least a flow sensor, an image sensor and a gas sensor, and the indirect monitoring component for atomization effect includes at least a temperature sensor, a humidity sensor, a sound sensor and a vibration sensor.

4. According to claim 3, a dynamic detection method for ceramic atomizer core is characterized in that: The sensor assembly further includes a current sensor and a voltage sensor, and the dynamic evaluation model is activated to dynamically evaluate and analyze the direct feature information and the indirect feature information to obtain a target real-time atomization coefficient, and then the following steps are further included: Sequentially extracting the current cycle timing detected by the current sensor and the voltage cycle timing detected by the voltage sensor in the full use cycle record; Combining the current cycle timing with the voltage cycle timing to obtain a target power cycle timing of the target ceramic atomizer core; Performing stability analysis on the target power cycle timing to obtain a target power stability index; The target real-time atomization coefficient is calibrated using the target power stability index as a weight coefficient.

5. According to claim 4, a dynamic detection method for ceramic atomizer core is characterized in that: Performing stability analysis on the target power cycle timing to obtain a target power stability index includes: Performing power spectrum density analysis on the target power cycle timing to obtain a target spectrum density analysis result; Comparing a first energy distribution corresponding to a first frequency component with a second energy distribution corresponding to a second frequency component in the target spectral density analysis result to obtain a target comparison result; The target power stability index is determined according to the target comparison result.

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