An aerosol-generating device, a temperature control method thereof, and a storage medium

Abstract

The application provides an aerosol generating device and a temperature control method and a storage medium thereof, the temperature control method comprising: step S1: the control component acquires the sensing data; step S2: the control component identifies the sensing data according to a scene identification model to obtain a scene identification result; and step S3: the control component controls the heating component according to the scene identification result. According to different use scenarios (preheating, puffing, standby) of the aerosol generating device, the application dynamically adjusts the weights of heterogeneous sensor data such as temperature, airflow, pressure and acceleration, thereby effectively improving the accuracy of state identification of the aerosol generating device.

Description

Technical Field

[0001] This application belongs to the field of novel tobacco products, specifically relating to an aerosol generating device, its temperature control method, and storage medium. Background Technology

[0002] Accurately identifying the operating status of heated smoke appliances (such as preheating, suction, and standby) is crucial for optimizing heating control strategies, improving user experience, and ensuring product safety. Currently, various sensors (such as temperature sensors, airflow sensors, pressure sensors, and acceleration sensors) are commonly used to monitor the operating status of heated smoke appliances. However, the contribution of different types of sensors to accurately identifying the status of heated smoke appliances varies depending on the usage scenario. For example, during the preheating stage, temperature sensor data plays a key role in determining whether the heating process is proceeding normally; while during the suction stage, airflow and pressure sensor data better reflect user behavior.

[0003] Among them, CN113876044A discloses a segmented heating and temperature control method, device, and electronic device for electronic cigarettes. This patent divides the inside of the cigarette device into several cigarette heating sections. By simulating and adjusting the temperature changes of each cigarette heating section during the smoking process under certain smoking conditions, it ensures that the temperature of the smoke that is finally drawn out is relatively uniform, thus avoiding the situation of burning the user's mouth when smoking.

[0004] CN113729311A discloses a method for detecting cigarette insertion / removal and smoke extraction based on audio frequency measurement. This patent, based on the principle of audio measurement, detects the characteristics of noise from cigarette insertion / removal and the friction between the cigarette and the device wall, as well as airflow noise during smoke extraction. It can accurately identify the user's cigarette insertion / removal and smoke extraction actions, helping to improve the intelligence of the device and enhance the user's smoking experience.

[0005] Existing methods for identifying the status of heated smoke appliances often fuse data from various sensors using fixed weights, failing to dynamically adjust the weights of each sensor's data based on changes in the usage scenario. This means that in some situations, noise or interference from certain sensor data can significantly impact the status identification results, thereby reducing the accuracy of status identification.

[0006] How to rationally design the weight allocation of sensors and dynamically adjust the weight of sensor data according to different usage scenarios to achieve more accurate state recognition and a better user experience remains a technical challenge that urgently needs to be solved. Summary of the Invention

[0007] In view of this, the purpose of this application is to provide an aerosol generating apparatus, its temperature control method, and a storage medium to solve the above-mentioned problems.

[0008] To solve the above-mentioned technical problems, this application adopts the following technical solution:

[0009] In a first aspect, this application provides a temperature control method for an aerosol generating device. The aerosol generating device includes a heating chamber, a heating component, a sensing component, and a control component. The heating component heats an aerosol forming matrix contained in the heating chamber during operation to generate aerosols. The sensing component collects sensing data related to the operating state of the aerosol generating device. The control component controls the heating component to heat. The temperature control method includes: step S1: the control component acquires sensing data; step S2: the control component performs recognition processing on the sensing data according to a scene recognition model to obtain a scene recognition result; step S3: the control component controls the heating component to heat according to the scene recognition result.

[0010] Furthermore, the sensing data includes at least one of the following: heating component temperature data, aerosol forming matrix temperature data, suction airflow velocity data, suction airflow flow rate data, heating chamber pressure data, and aerosol generating device motion status data.

[0011] Furthermore, step S2 includes: step S21: the control component preprocesses the sensing data to obtain preprocessed feature data; step S22: the control component inputs the preprocessed feature data into the scene recognition model for recognition processing to obtain the scene recognition result.

[0012] Further, preprocessing includes data filtering and data normalization.

[0013] Furthermore, step S3 includes: step S31: the control component assigns weight parameters to the sensing component according to the scene recognition result; step S32: the control component obtains the weighted sensing data of the sensing component, the weighted sensing data being the data obtained by the sensing component in combination with the weight parameters; step S33: the control component inputs the weighted sensing data into the heating state recognition model to obtain the heating state recognition result, and controls the heating component according to the scene recognition result and the heating state recognition result.

[0014] Furthermore, step S33 includes: step S331: the control component adjusts the heating parameters of the heating component according to the scene recognition result and the heating status recognition result; step S332: the control component controls the heating component to heat according to the heating parameters and monitors the sensing change data of the sensing component; step S333: the control component determines whether the sensing change data exceeds the preset threshold: if so, the control component generates an alarm signal and provides a prompt.

[0015] Secondly, this application provides an aerosol generating device, which includes: a heating chamber, a heating component, a sensing component, and a control component. The heating component is used to heat an aerosol forming matrix contained in the heating chamber during operation to generate aerosols. The sensing component collects sensing data related to the operating state of the aerosol generating device. The control component controls the heating component to heat. The control component is configured to: acquire sensing data; perform recognition processing on the sensing data according to a scene recognition model to obtain a scene recognition result; and control the heating component to heat according to the scene recognition result.

[0016] Thirdly, this application provides a computer system including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the temperature control method of the above-described aerosol generating apparatus.

[0017] Fourthly, this application provides a computer-readable storage medium storing a computer program / instructions thereon, which, when executed by a processor, implements the steps of the temperature control method for the aerosol generating apparatus described above.

[0018] Fifthly, this application provides a computer program product, including a computer program / instructions, which, when executed by a processor, implement the steps of the temperature control method for the aerosol generating apparatus described above.

[0019] Among them, aerosol-generating products are smoking products, including aerosol-forming matrix, which generates aerosols through heating that can be directly inhaled into the lungs of the user through the user's mouth.

[0020] Preferably, the aerosol forming matrix is ​​a solid aerosol forming matrix. The aerosol forming matrix may include both solid and liquid components.

[0021] Preferably, the aerosol-forming matrix includes nicotine. In some preferred embodiments, the aerosol-forming matrix includes tobacco.

[0022] An aerosol generating device is used to describe an apparatus that interacts with an aerosol-forming matrix of an aerosol-generating article to generate an aerosol. Preferably, the aerosol generating device is a smoking device that interacts with the aerosol-generating matrix of the aerosol-generating article to generate an aerosol that can be directly inhaled into the user's lungs through the user's mouth. The aerosol generating device may be a fixator for a smoking article.

[0023] The power source can be any suitable power source, such as a DC voltage source, like a battery. In one embodiment, the power source is a lithium-ion battery. Alternatively, the power source can be a nickel-metal hydride battery, a nickel-cadmium battery, or a lithium-based battery, such as a lithium cobalt, lithium iron phosphate, lithium titanate, or lithium polymer battery.

[0024] The control element can be a simple switch. Alternatively, the control element can be a circuit and may include one or more microprocessors or microcontrollers.

[0025] An aerosol generation system may include an aerosol generation device and one or more aerosol generation articles, wherein the aerosol generation device is configured with a corresponding number of heating chambers to contain the aerosol generation articles.

[0026] As can be seen from the above technical solutions, the advantages and positive effects of the aerosol generating device, its temperature control method, and storage medium proposed in this application are as follows:

[0027] 1. By integrating various heterogeneous sensors such as temperature sensors, airflow sensors, pressure sensors, and acceleration sensors, comprehensive monitoring of the working status of the aerosol generation device is achieved. It can accurately identify the user's actions such as inserting and removing cigarettes and inhaling smoke, effectively improving the user's smoking experience and meeting personalized smoking needs.

[0028] 2. By adopting a scene recognition model based on machine learning or deep learning, the aerosol generator can accurately identify the current scene of the device, namely the preheating scene, the suction scene, or the standby scene, according to the feature patterns of the data under different usage scenarios, thus realizing intelligent scene perception and control.

[0029] 3. By constructing a real-time weight calculation function, weights are dynamically assigned to the sensor data in different scenarios based on the scene recognition results, which fully considers the importance of each sensor in different scenarios and significantly improves the accuracy and reliability of state recognition.

[0030] 4. By using a weighted fusion method, the data from each sensor after real-time weight allocation are fused, realizing the effective combination of multi-sensor data. This improves the system's real-time feedback and analysis capabilities on user suction behavior, providing users with better suction suggestions and health tips.

[0031] 5. Through a real-time weighted adaptive algorithm, the weight of sensor data can be dynamically adjusted according to the user's suction habits and environmental changes, realizing intelligent control of parameters such as temperature, airflow, pressure and acceleration, and providing a more user-friendly suction experience. Attached Figure Description

[0032] The above description of this application and the following detailed embodiments will be better understood when read in conjunction with the accompanying drawings. It should be noted that the drawings are merely examples of the claimed technical solutions.

[0033] Figure 1 This is a structural diagram of the aerosol generating apparatus of this application;

[0034] Figure 2This is a flowchart of the temperature control method for the aerosol generation device of this application;

[0035] Figure 3 This is a logic diagram of the operating temperature control method for the aerosol generation device of this application.

[0036] The reference numerals in the attached figures are explained as follows:

[0037] Aerosol generating device: 10;

[0038] Heating components: 11;

[0039] Power supply: 12;

[0040] Control components: 13;

[0041] Heating chamber: 14;

[0042] Aerosol forming matrix: 20. Detailed Implementation

[0043] The following detailed description of the features and advantages of this application is sufficient to enable any person skilled in the art to understand the technical content of this application and implement it accordingly. Based on the specification, claims and drawings disclosed in this specification, those skilled in the art can easily understand the related objectives and advantages of this application.

[0044] The invention will now be described with reference to the accompanying drawings, in which similar reference numerals denote similar elements. While specific structures and arrangements are discussed, it should be understood that this is done merely for illustrative purposes. Those skilled in the art will recognize that other structures and arrangements can be used without departing from the spirit and scope of the invention. It will be apparent to those skilled in the art that the invention can also be used in a variety of other applications.

[0045] In this specification and claims, several terms will be used, and unless otherwise indicated, these terms will be defined to have the following meanings:

[0046] The singular forms “a” and “the” include their corresponding plural forms. “At least one” means one or more, and “more” means two or more. “At least one of the following” or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can be expressed as: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0047] All figures used to represent component amounts, properties (e.g., molecular weight), reaction conditions, etc., should be considered to be modified in all cases by the terms "within the unavoidable margin of error" or "about". Therefore, the numerical values ​​set forth herein are approximate and may vary depending on the desired properties sought to be obtained by the present invention. The principles of equivalents, which are applied to a minimum and not intended to limit the scope of the claims, should be applied, for example, each value should be interpreted at least according to the reported significant digits and by applying conventional rounding techniques.

[0048] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0049] In the description of this embodiment, it should be noted that the terms "upper", "lower", "inner", "bottom", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship in which the product is usually placed during use. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0050] Unless otherwise indicated, the following abbreviations have the following meanings, and any other abbreviations used herein but not defined have their generally accepted standard meanings:

[0051] All other terms used herein for special definition are intended to have the general meaning understood by one of ordinary skill in the art, and in particular, meaning that one of ordinary skill in the art, upon reading the claims, specification and drawings of this patent, can directly and without doubt determine how the technical solution of this patent can be implemented.

[0052] Even if there are incomplete descriptions, omissions, or ambiguities in the grammar, words, punctuation, graphics, symbols, etc. of the claims, specification, and drawings of this patent, a person skilled in the art can still arrive at the only correct understanding by reading the claims, specification, and drawings as a whole without extensive reasoning or experimentation, and effectively exclude various incorrect interpretations that are not aimed at achieving the purpose of this patent.

[0053] Those skilled in the art would first choose to read the claims, specification, and drawings of this patent to reasonably interpret the terms; secondly, they would choose to refer to the relevant definitions in other documents published by the applicant before the filing date to reasonably interpret the terms; thirdly, they would choose the references cited in this patent to reasonably interpret the terms; and finally, they would choose to combine the technical dictionaries, technical manuals, reference books, textbooks, national or industry technical standards, etc., commonly used by those skilled in the art to reasonably interpret the terms.

[0054] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0055] Please refer to Figure 1 This application provides an aerosol generating device 10, which includes a heating chamber 14, a heating component 11, a sensing component (not shown) and a control component 13.

[0056] The heating component 11 is used to heat the aerosol forming matrix 20 contained in the heating chamber 14 during operation to generate aerosols.

[0057] The sensing component collects sensing data related to the working state of the aerosol generating device 10, and the control component 13 controls the heating component 11 to heat.

[0058] The sensing components include a temperature sensor, an airflow sensor, a pressure sensor, and an acceleration sensor, which are installed inside the aerosol generating device 10.

[0059] For example, a temperature sensor is installed near the heating element and the tobacco placement area to accurately measure temperature changes during the heating process.

[0060] An airflow sensor is installed on the airflow channel to detect relevant airflow parameters; a pressure sensor is installed on the heating chamber wall to monitor the pressure inside the heating chamber.

[0061] An accelerometer is installed on the main structure of the aerosol generating device 10 to sense the motion state of the aerosol generating device 10.

[0062] Each sensor is connected to the control component 13 through a corresponding interface circuit, and the collected analog signals are converted into digital signals and transmitted to the control component 13 for further processing.

[0063] Heating chamber 14 is the heating space for aerosol forming matrix 20. Its internal environment has been calculated to ensure that the matrix can be uniformly and efficiently converted into aerosols during heating. Power module 12 acts as the power source for aerosol generating device 10, continuously providing electrical energy to the entire system. Its stability and efficiency directly affect the heating effect.

[0064] The heating component 11 is responsible for converting electrical energy into heat energy to heat the aerosol forming matrix 20. It adopts advanced heating technology and materials, which can accurately control the temperature while rapidly heating up, avoiding overheating and damage to the matrix, thereby preserving the flavor and texture of the matrix. The heating component 11 can be an internal heating component 11, an external heating component 11, or a combination of internal and external heating components 11, and this application is not limited to this.

[0065] Internal heating refers to the heating component 11 being at least partially positioned inside the aerosol forming matrix 20, directly heating the aerosol forming matrix. Internal heating is achieved through the design of specific heating tubes or heating elements. For example, a heating cavity is formed inside the heating tube to accommodate the aerosol forming matrix, and a heating layer is provided on the outer or inner side of the heating tube, generating heat to heat the matrix by passing electricity through it.

[0066] Additionally, auxiliary structures such as a heat spreader layer and a dielectric layer can be added as needed to improve heating uniformity and efficiency. Because the heating component 11 is in closer contact with the substrate, the required heating temperature can be reached more quickly. The internal heating method allows for more direct heating of the aerosol-generating substrate, improving heating efficiency.

[0067] External heating refers to the heating component 11 being positioned outside the aerosol forming matrix 20, heating the matrix through heat conduction or radiation. External heating typically involves designing a specific heating cavity or tubular body to house the aerosol forming matrix 20. The heating component 11 (such as a heating element, planar helical coil, etc.) is then positioned outside the heating cavity or tubular body.

[0068] External heating can also be combined with structures such as heat insulation pipes and support frames to improve the uniformity and stability of heating. External heating avoids direct contact between the heating component 11 and the aerosol generation matrix, reducing contamination and damage to the heating component 11 from the matrix. Through proper design of the heating chamber and heat insulation structure, uniform heating of the matrix can be achieved, improving the quality of aerosol generation.

[0069] The control component 13 is the intelligent control center of the entire aerosol generating device 10. It can adjust the amount of electrical energy supplied by the power supply 12 to the heating component 11 according to preset heating parameters, such as target temperature and heating time, to achieve precise temperature control. Simultaneously, it can monitor the heating status in real time through built-in sensors, responding and adjusting promptly to abnormal situations to ensure a stable and safe heating process.

[0070] Please refer to Figure 2 Based on the same inventive concept, this application also provides a temperature control method for an aerosol generating apparatus 10, which may include the following steps:

[0071] Step S1: Control component 13 acquires sensor data.

[0072] The sensor data can be acquired by the sensor component, and then the sensor component transmits the acquired sensor data to the control component 13.

[0073] The sensing data includes at least one of the following: temperature data of heating component 11, temperature data of aerosol forming matrix 20, suction airflow velocity data, suction airflow flow rate data, pressure data of heating chamber 14, and motion status data of aerosol generating device 10.

[0074] For example, the aerosol generating device 10 can be equipped with temperature sensors, airflow sensors, pressure sensors and acceleration sensors with appropriate accuracy and range specifications, and the installation layout can be scientifically and reasonably arranged according to the characteristics of each sensor and the internal structure of the device.

[0075] Specifically, the temperature sensor is installed near the heating element 11 and the tobacco placement area. Since the heating element 11 is the core component that generates heat, and the tobacco placement area is the key location where heat energy is applied, installing a temperature sensor here can capture the dynamic changes in temperature during the heating process in real time and accurately, providing a reliable basis for precise control of the heating temperature.

[0076] The airflow sensor needs to be installed on the airflow channel. The airflow channel is the necessary path for gas flow during aerosol generation. Placing the airflow sensor here allows for comprehensive and accurate detection of airflow speed, flow rate, and other related parameters, which helps to optimize the aerosol generation effect and ensures that users have a stable and comfortable inhalation experience.

[0077] The pressure sensor should be installed on the wall of the heating chamber 14. The heating chamber 14 is the core reaction space for aerosol generation, and changes in its internal pressure directly affect the quality and generation efficiency of the aerosol. By installing a pressure sensor on the wall of the heating chamber 14, the pressure inside the heating chamber 14 can be monitored in real time, abnormal pressure fluctuations can be detected in a timely manner, and corresponding measures can be taken to ensure the safe and stable operation of the device.

[0078] An accelerometer is mounted on the main structure of the aerosol generating device 10. The accelerometer can detect changes in the acceleration of an object during its motion. Mounted on the main structure of the device, it allows for real-time monitoring of the aerosol generating device 10's motion state, such as whether shaking or tilting occurs, providing crucial information for the device's intelligent control and safety protection.

[0079] Set the initial operating status and sampling frequency for each sensor.

[0080] For example, the initial operating temperature of the temperature sensor is 20°C, and the sampling frequency is 1kHz.

[0081] The airflow sensor is initially switched off, and the sampling frequency is 100Hz.

[0082] The initial operating pressure of the pressure sensor is 0 Pa, and the sampling frequency is 1 kHz.

[0083] The accelerometer is initially switched off, and the sampling frequency is 100Hz.

[0084] Step S2: The control component 13 performs recognition processing on the sensing data according to the scene recognition model to obtain the scene recognition result.

[0085] Specifically, step S2 includes:

[0086] Step S21: The control component 13 preprocesses the sensing data to obtain preprocessed feature data.

[0087] Preprocessing includes data filtering and data normalization.

[0088] A temperature sensor collects real-time temperature data from the heating element and the tobacco section, with a temperature range of 200-400℃. An airflow sensor detects the airflow velocity and flow rate, with a velocity range of 0-10 m / s and a flow rate range of 0-100 m³ / h. A pressure sensor measures pressure changes within the heating chamber, with a pressure range of 0-0.2 MPa. An acceleration sensor detects the motion state of the aerosol generating device 10, with an acceleration range of -2g to 2g.

[0089] The control component 13 receives raw data collected by various sensors, including temperature, airflow, pressure and acceleration data, and performs data filtering and normalization preprocessing on the raw data.

[0090] Step S22: The control component 13 inputs the preprocessed feature data into the scene recognition model for recognition processing to obtain the scene recognition result.

[0091] The steps for training a scene recognition model may include the following:

[0092] 1. Data collection: Collect a large number of sensor data samples in different scenarios (preheating, suction, standby) in laboratory environment and during actual user trials, and accurately label each sample with the scenario.

[0093] 2. Feature Extraction: Feature extraction is performed on the collected raw sensor data. For example, for temperature data, features such as temperature change rate and average temperature can be extracted; for airflow data, features such as airflow peak value and average flow velocity can be extracted; for pressure data, features such as pressure fluctuation amplitude and average pressure can be extracted; and for acceleration data, features such as average acceleration value and acceleration variation range can be extracted.

[0094] 3. Model Selection and Training: Select a suitable machine learning or deep learning model, such as Support Vector Machine (SVM), Convolutional Neural Network (CNN), or Recurrent Neural Network (RNN), and input the extracted features and corresponding scene annotations as training data into the model for training. By continuously adjusting the model's parameters, the model can accurately identify sensor data feature patterns in different scenes, achieving a high scene recognition accuracy.

[0095] The control component 13 inputs the preprocessed data into the scene recognition model for recognition, and can obtain a scene recognition result with a recognition accuracy of 98%.

[0096] The scene recognition results can include preheating scene, suction scene, or standby scene.

[0097] It is understandable that the scene recognition model is built based on machine learning or deep learning. This scene recognition model takes the raw data collected by each sensor or the data after preliminary feature extraction as input, and learns the feature patterns of data under different usage scenarios through training, so as to accurately identify the current scenario of the aerosol generating device 10, namely the preheating scenario, the suction scenario, or the standby scenario.

[0098] Step S3: Control component 13 controls heating component 11 to heat according to scene recognition results.

[0099] Specifically, step S3 includes:

[0100] Step S31: The control component 13 assigns weight parameters to the sensing component based on the scene recognition results.

[0101] The control component 13 assigns weights to each sensor based on the stability of historical and current data.

[0102] For example, the control component 13 can assign real-time weights to the sensor data in different scenarios based on the output of the scene recognition module.

[0103] Specifically, a weight calculation function is constructed, which takes scene category and factors such as the accuracy of historical data from each sensor and the stability of current data as input parameters.

[0104] For example, in a preheating scenario, the accuracy and stability of temperature sensor data are crucial for determining the completion of the preheating process. Therefore, a weighting function is used to assign a higher weight to temperature sensor data, while the weights of other sensor data are relatively lower.

[0105] In suction scenarios, the data from airflow and pressure sensors are directly related to the user's suction behavior, so these two sensors are assigned higher weights, while the weights of sensor data, such as accelerometers, which are less related to suction behavior, are reduced.

[0106] In standby mode, since the aerosol generating device 10 is in a relatively static state, the changes in the data of each sensor are relatively small. Appropriate weights can be assigned to each sensor based on its importance in detecting abnormal situations in standby mode.

[0107] When the aerosol generating device 10 is working, the microcontroller obtains the output results of the scene recognition module in real time and determines the current scene.

[0108] Then, based on the pre-established weight calculation rules, and combining the historical data accuracy and current data stability of each sensor, the real-time weight of each sensor in the current scenario is calculated.

[0109] For example, the accuracy of historical data for a temperature sensor can be assessed by calculating the error between measured temperature values ​​and actual temperature reference values ​​over a past period, while the stability of current data can be measured by calculating the variance of temperature data over the current period. Based on these factors, a weighting function is used to derive the weight of the temperature sensor in the current scenario.

[0110] The data collected by each sensor is multiplied by its corresponding real-time weight, and then weighted and fused.

[0111] For example, suppose the temperature sensor data is T with a weight of W_T; the airflow sensor data is A with a weight of W_A; the pressure sensor data is P with a weight of W_P; and the acceleration sensor data is G with a weight of W_G. Then the fused feature value is F = T×W_T + A×W_A + P×W_P + G×W_G.

[0112] Finally, the fused feature value F is input into the pre-trained state recognition model or determined according to the set state recognition rules to determine the current working state of the aerosol generating device 10.

[0113] For example, the weight of the temperature sensor is 0.4 in the preheating scenario and 0.3 in the suction scenario; the weight of the airflow sensor is 0.35 in the suction scenario; the weight of the pressure sensor is 0.25 in the suction scenario; and the weight of the acceleration sensor is 0.05 in the preheating scenario.

[0114] It is understandable that the proposed heterogeneous sensor real-time weighted adaptive algorithm will be deployed on an actual aerosol generating device 10 product, and a large number of test experiments will be conducted. By comparing the state recognition results output by the algorithm with the actual observed working state of the aerosol generating device 10, the accuracy and reliability of the algorithm will be evaluated.

[0115] Based on the problems identified in the testing experiments, the algorithm is optimized. For example, if the state recognition accuracy is found to be low in a certain scenario, the analysis suggests that the weight calculation rules may be unreasonable or the scene recognition model may not be accurate enough. The parameters of the weight calculation function are adjusted accordingly, or the scene recognition model is retrained and optimized to continuously improve the algorithm's performance.

[0116] Step S32: Control component 13 acquires weighted sensing data from sensing component.

[0117] Among them, the weighted sensing data is the data obtained by the sensing component in combination with the weight parameters.

[0118] Step S33: The control component 13 inputs the weighted sensing data into the heating state recognition model to obtain the heating state recognition result, and controls the heating component 11 according to the scene recognition result and the heating state recognition result.

[0119] It is understandable that a weighted fusion method is used to fuse the data from various sensors after real-time weight allocation. This involves multiplying the measurement value of each sensor by its corresponding real-time weight, and then summing the weighted results of all sensors or performing other appropriate fusion operations to obtain a comprehensive feature value.

[0120] Finally, based on the pre-set state recognition rules or the trained heating state recognition model, the current working state of the aerosol generating device 10 is determined based on the fused feature values.

[0121] For example, control component 13 multiplies each sensor data point by its corresponding weight. The weighted results of each sensor are summed to obtain a weighted sum of 1.0. The summed result is input into the heating state recognition model for identification. The state recognition result is obtained, including preheating state, suction state, or standby state.

[0122] Specifically, step S33 includes:

[0123] Step S331: The control component 13 adjusts the heating parameters of the heating component 11 based on the scene recognition result and the heating status recognition result.

[0124] Step S332: The control component 13 controls the heating component 11 to heat according to the heating parameters, and monitors the sensing change data of the sensing component.

[0125] Step S333: Control component 13 determines whether the sensor change data exceeds a preset threshold: if so, control component 13 generates an alarm signal and provides a prompt.

[0126] For example, the control component 13 adjusts the heating parameters according to the current scene and the recognition result.

[0127] If it is a preheating scenario, set the initial heating temperature to 200℃.

[0128] In the case of a suction scenario, the target temperature is calculated as the weighted average of the data from each sensor based on real-time weights.

[0129] If it is in standby mode, keep the current temperature unchanged.

[0130] The heating element was heated to 300°C for 30 seconds. Temperature, airflow, pressure, and acceleration data were collected every second and compared with historical data.

[0131] If the temperature data deviation exceeds ±5℃, the airflow data deviation exceeds ±0.5m / s, or the pressure data deviation exceeds ±0.01MPa, an abnormal alarm will be triggered immediately to remind the user to check the equipment status.

[0132] For example, please refer to Figure 3 The temperature control method of this application, specifically applied to the aerosol generating device 10, may include the following steps:

[0133] Step 1: Initialize system configuration:

[0134] Step 101: Set the system operating parameters, including the initial operating status and sampling frequency of each sensor. The initial operating temperature of the temperature sensor is 25℃, and the sampling frequency is 500Hz.

[0135] The airflow sensor is initially enabled with a sampling frequency of 200Hz.

[0136] The pressure sensor has an initial operating pressure of 0.05 MPa and a sampling frequency of 2 kHz.

[0137] The accelerometer is initially turned on with a sampling frequency of 500Hz.

[0138] Step 102: Load the preset scene recognition model and weight calculation model.

[0139] The scene recognition model uses a machine learning-based decision tree algorithm, while the weight calculation model uses a multinomial regression algorithm.

[0140] Step 103: Initialize the working status flag of the aerosol generating device 10.

[0141] The preheating scenario flag is 1, the suction scenario flag is 0, and the standby scenario flag is 2.

[0142] Step 2: Collect data from various heterogeneous sensors:

[0143] Step 201: Collect temperature data of the heating element and tobacco part in real time through temperature sensor, with a temperature range of 150-500℃.

[0144] Step 202: Use an airflow sensor to detect the airflow velocity and flow rate. The velocity range is 0-15 m / s, and the flow rate range is 0-150 m³ / h.

[0145] Step 203: Measure the pressure change inside the heating chamber using a pressure sensor, with a pressure range of 0-0.3 MPa.

[0146] Step 204: Use an accelerometer to sense the motion state of the aerosol generating device 10, with an acceleration range of -3g to 3g.

[0147] Step 3: Perform scene recognition:

[0148] Step 301: Receive raw data collected by each sensor, including temperature, airflow, pressure and acceleration data.

[0149] Step 302: Preprocess the raw data, including data filtering and normalization.

[0150] Step 303: Input the preprocessed data into the scene recognition model for recognition, with a recognition accuracy of 95%.

[0151] Step 304: Obtain scene recognition results, including preheating scene, suction scene, or standby scene.

[0152] Step 4: Calculate real-time weights:

[0153] Step 401: Obtain scene recognition results.

[0154] Step 402: Call the corresponding weight calculation function based on the recognition results.

[0155] Step 403: Assign weights to each sensor based on the stability of historical and current data. The temperature sensor has a weight of 0.35 in the preheating scenario and a weight of 0.45 in the suction scenario; the airflow sensor has a weight of 0.4 in the suction scenario; the pressure sensor has a weight of 0.3 in the suction scenario; and the acceleration sensor has a weight of 0.1 in the preheating scenario.

[0156] Step 5: Perform data fusion and status recognition.

[0157] Step 501: Multiply each sensor data by its corresponding weight.

[0158] Step 502: Sum the weighted results of each sensor to obtain a weighted sum of 1.0.

[0159] Step 503: Input the accumulated result into the state recognition model for recognition.

[0160] Step 504: Obtain the status identification result, including preheating status, suction status, or standby status.

[0161] Step 6: Execute heating control:

[0162] Step 601: Adjust the heating parameters according to the current scenario and recognition results. If it is a preheating scenario, set the initial heating temperature to 250℃; if it is a suction scenario, calculate the weighted average of the data from each sensor based on real-time weights as the target temperature; if it is a standby scenario, keep the current temperature unchanged.

[0163] Step 602: Control the heating element to heat according to the adjusted parameters. For example, heat the heating element to 350°C for 45 seconds.

[0164] Step 603: Monitor changes in data from each sensor in real time. Collect temperature, airflow, pressure, and acceleration data every 0.5 seconds and compare them with historical data. If the temperature data deviation exceeds ±3℃, the airflow data deviation exceeds ±0.3m / s, or the pressure data deviation exceeds ±0.02MPa, immediately trigger an alarm.

[0165] Step 604: If an abnormality is detected, an alarm will be triggered to remind the user to check the device status.

[0166] It is understood that, unlike traditional fixed-weight fusion methods, the real-time weight adaptive algorithm proposed in this invention can dynamically adjust the weights of heterogeneous sensor data according to the actual usage scenario of the aerosol generating device 10. This dynamic weight allocation mechanism enables the system to fully utilize the advantages of each sensor's data under different scenarios, thereby improving the accuracy of state recognition.

[0167] For example, in preheating scenarios, the focus is on temperature sensor data, while in suction scenarios, the role of airflow and pressure sensor data is emphasized, effectively avoiding the impact of sensor data interference on state recognition accuracy in certain scenarios caused by fixed weights.

[0168] By establishing a scene recognition model, the three main usage scenarios of the aerosol generator 10—preheating, suction, and standby—can be accurately identified, and a weight allocation strategy can be designed for each scenario. This multi-scenario adaptive design allows the algorithm to better adapt to the characteristics of the aerosol generator 10 at different working stages, comprehensively improving the accuracy and reliability of state recognition.

[0169] The real-time weight calculation model considers not only the current usage scenario but also the accuracy of historical sensor data and the stability of current data when determining the weights of each sensor's data. This multi-factor weight calculation method allows for a more scientific and reasonable allocation of weights to sensor data in different scenarios, further improving the algorithm's performance.

[0170] The temperature control method of the above-mentioned aerosol generating device can be implemented in the form of a computer-readable instruction, which can run on a computer system.

[0171] This application also provides a computer system including a memory, a processor, and computer-readable instructions stored in the memory and executable on the processor. When the processor executes the program, it implements the temperature control method of the aerosol generating device described above.

[0172] The computer system can be a server. The computer system includes a processor, non-volatile storage medium, internal memory, input device, display screen, and network interface connected via a system bus. The non-volatile storage medium of the computer system can store an operating system and computer-readable instructions. When executed, these computer-readable instructions can cause the processor to execute a temperature control method for an aerosol generating apparatus according to various embodiments of this application. The specific implementation process of this method can be found in [reference needed]. Figure 2 The specific details will not be elaborated here.

[0173] The processor of this computer system provides computing and control capabilities, supporting the operation of the entire system. The internal memory stores computer-readable instructions, which, when executed by the processor, enable the processor to perform a temperature control method for an aerosol generating device. The computer system's input devices are used for inputting various parameters, its display screen is used for display, and its network interface is used for network communication.

[0174] Based on the same inventive concept, this application provides a computer-readable storage medium storing computer-readable instructions, which, when executed by a processor, implement the steps in the temperature control method of the aerosol generating apparatus described above.

[0175] The memory in this application embodiment can be volatile memory or non-volatile memory, or it can include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache.

[0176] By way of example, but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous DRAM (DDR SDRAM), enhanced synchronous DRAM (ESDRAM), synchronous linked DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0177] The above embodiments can be implemented, in whole or in part, by software, hardware (such as circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions or computer programs.

[0178] When computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions according to the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means.

[0179] Computer-readable storage media can be any available medium that a computer can access, or a data storage device such as a server or data center that includes one or more sets of available media. Available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. Semiconductor media can be solid-state drives (SSDs).

[0180] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0181] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0182] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the devices, apparatuses, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0183] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0184] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0185] In this specification, references to "an embodiment" or "a specific implementation" mean that a particular feature, structure, or characteristic described in connection with that embodiment / specific implementation is included in at least one embodiment / specific implementation of the invention. Therefore, the phrase "in one embodiment / specific implementation" appearing in various places in this specification does not necessarily refer to the same embodiment / setting, but rather to potentially different embodiments. Furthermore, specific features, structures, or characteristics may be combined in one or more embodiments / settings in any suitable manner, as will be apparent to those skilled in the art from this disclosure.

[0186] Similarly, it should be understood that in the above description of exemplary embodiments / specific implementations of the invention, various features of the invention are sometimes combined in a single embodiment / specific implementation or its figures and description, with the aim of simplifying the disclosure and aiding in the understanding of one or more of the various aspects of the invention. However, the method of description in this patent should not be construed as reflecting an intention that the claimed features of the invention are more than those expressly stated in each claim, except where explicitly stated otherwise or in obvious technical contradiction or exclusion. Rather, the inventive aspect reflected in the claims lies in not all the features of a single foregoing disclosed embodiment / specific implementation. Therefore, the claims following the detailed description are expressly incorporated herein by reference, each claim existing independently as a separate embodiment / specific implementation of the invention.

[0187] Furthermore, while some embodiments / specific implementations described herein include, but are not limited to, other features included in other embodiments / specific implementations, combinations of features from different embodiments / specific implementations are intended to be within the scope of the invention and form different embodiments / specific implementations, as will be understood by those skilled in the art. For example, in the following claims, embodiments / specific implementations of any claim can be used in any combination.

[0188] The terms and expressions used in this specification are for illustrative purposes and not for limitation. In using these terms and expressions, it is not intended to exclude any equivalents of the features or portions thereof shown and described, but rather to recognize that various modifications may be possible within the scope of the invention.

[0189] Therefore, it should be understood that although the invention has been specifically disclosed through preferred embodiments, exemplary embodiments and optional features, those skilled in the art may take variations or modifications of the concepts disclosed herein, and such variations and modifications are therefore considered to be within the scope of the invention as defined by the appended claims.

[0190] The specific embodiments given in this specification are examples of useful implementations of the present invention. It will be apparent to those skilled in the art that the present invention can be implemented using many variations of the devices, device components, and method steps disclosed in this specification.

[0191] The foregoing description of specific embodiments fully discloses the general features of the present invention, enabling others to easily modify and / or adapt such specific embodiments for various applications by applying knowledge within the scope of the art, without conducting excessive experimentation and without departing from the general concept of the present invention.

[0192] Therefore, based on the teachings and guidance provided herein, it is intended that such modifications and alterations be included within the meaning and scope of equivalents of the disclosed embodiments. It should be understood that the wording or terminology used herein is for descriptive purposes and is not intended to be limiting; thus, the wording or terminology in this specification will be interpreted by those skilled in the art based on the foregoing teachings and guidance.

[0193] Furthermore, the scope of the invention should not be limited to any of the exemplary embodiments described above, but only to the appended claims and their equivalents.

Claims

1. A temperature control method for an aerosol generating device, the aerosol generating device comprising: The device comprises a heating chamber, a heating assembly, a sensing assembly, and a control assembly. The heating assembly heats an aerosol-forming matrix contained within the heating chamber during operation to generate aerosols. The sensing assembly collects sensing data related to the operating state of the aerosol generating device. The control assembly controls the heating assembly to heat the aerosol. The temperature control method includes: Step S1: The control component acquires the sensing data; Step S2: The control component performs recognition processing on the sensing data according to the scene recognition model to obtain the scene recognition result, which includes a preheating scene, a suction scene, or a standby scene. Step S3: The control component controls the heating component to heat up according to the scene recognition result; Step S3 includes: Step S31: The control component assigns weight parameters to the sensing component according to the scene recognition result; Step S32: The control component obtains weighted sensing data of the sensing component, wherein the weighted sensing data is data obtained by the sensing component in combination with the weight parameters; Step S33: The control component inputs the weighted sensing data into the heating state recognition model to obtain the heating state recognition result, and controls the heating component according to the scene recognition result and the heating state recognition result.

2. The temperature control method for the aerosol generating device according to claim 1, characterized in that, The sensing data includes at least one of the following: heating component temperature data, aerosol forming matrix temperature data, suction airflow velocity data, suction airflow flow rate data, heating chamber pressure data, and aerosol generating device motion status data.

3. The temperature control method for the aerosol generating device according to claim 1, characterized in that, Step S2 includes: Step S21: The control component preprocesses the sensing data to obtain preprocessed feature data; Step S22: The control component inputs the preprocessed feature data into the scene recognition model for recognition processing to obtain the scene recognition result.

4. The temperature control method for the aerosol generating device according to claim 3, characterized in that, The preprocessing includes data filtering and data normalization.

5. The temperature control method for the aerosol generating device according to claim 1, characterized in that, Step S33 includes: Step S331: The control component adjusts the heating parameters of the heating component according to the scene recognition result and the heating state recognition result; Step S332: The control component controls the heating component to heat according to the heating parameters, and monitors the sensing change data of the sensing component; Step S333: The control component determines whether the sensing change data exceeds a preset threshold. If so, the control component generates an alarm signal and provides a notification.

6. An aerosol generating apparatus, the aerosol generating apparatus comprising: The device includes a heating chamber, a heating assembly, a sensing assembly, and a control assembly. The heating assembly heats an aerosol-forming matrix contained within the heating chamber during operation to generate an aerosol. The sensing assembly collects sensing data related to the operating state of the aerosol generating device. The control assembly controls the heating assembly to heat the aerosol. The control assembly is configured to: Acquire the sensor data; The sensor data is processed according to the scene recognition model to obtain the scene recognition result, which includes a preheating scene, a suction scene, or a standby scene. Based on the scene recognition results, the heating component is controlled to heat up; Based on the scene recognition result, weight parameters are assigned to the sensing component; weighted sensing data of the sensing component is obtained, which is the data obtained by the sensing component in combination with the weight parameters; the weighted sensing data is input into the heating state recognition model to obtain the heating state recognition result, and the heating component is controlled according to the scene recognition result and the heating state recognition result.

7. A computer system comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the temperature control method for the aerosol generating apparatus according to any one of claims 1-5.

8. A computer-readable storage medium having a computer program / instructions stored thereon, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the temperature control method for the aerosol generating apparatus according to any one of claims 1-5.

9. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the temperature control method for the aerosol generating apparatus according to any one of claims 1-5.

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