Temperature measurement method for aerosol generation device, temperature measurement system for aerosol generation device, temperature measurement device for aerosol generation device, and storage medium

Abstract

Disclosed is a temperature measurement method for an aerosol generation device. The aerosol generation device comprises a feed end, a load, an equivalent connection circuit connecting the feed end and the load, and an external circuit connected to the equivalent connection circuit. The method comprises: acquiring preset measurement parameters of the aerosol generation device, the preset measurement parameters being extracted by the external circuit (S100); and determining a target measurement temperature on the basis of the preset measurement parameters and a preset temperature prediction model, wherein the temperature prediction model is determined on the basis of measurement parameter samples and temperature samples (S200). The present invention can improve the accuracy and stability of temperature measurement, and can be widely applied to the technical field of temperature measurement. Also disclosed are a temperature measurement system for an aerosol generating device, a temperature measurement device for an aerosol generating device, an aerosol generating device, and a computer-readable storage medium.

Description

Temperature measurement methods, systems, devices, and storage media for aerosol generating devices

[0001] Cross-references to related applications

[0002] This application claims priority to Chinese Patent Application No. 202510231900.5, filed on February 28, 2025, entitled “Temperature Measurement Method, System, Apparatus and Storage Medium for Aerosol Generating Device”, the entire contents of which are incorporated herein by reference. Technical Field

[0003] This application relates to the field of temperature measurement technology, and in particular to a temperature measurement method, system, device and storage medium for an aerosol generating device. Background Technology

[0004] Currently, aerosol generating devices include resonant cavities. Temperature measurement inside these cavities commonly uses methods such as temperature sensors and temperature-sensing films, but each has its limitations. For example, thermocouple sensors are easily interfered with in microwave fields, leading to inaccurate measurements, while thermistor sensors are limited in accuracy and stability due to the heat generated by the current. Although temperature-sensing films are resistant to high temperatures, they also suffer from low measurement accuracy and stability issues. Summary of the Invention

[0005] In view of this, the purpose of the embodiments of this application is to provide a temperature measurement method, system, device and storage medium for an aerosol generating device, which can improve the accuracy and stability of temperature measurement.

[0006] On one hand, embodiments of this application provide a temperature measurement method for an aerosol generating device, the aerosol generating device including a feed end, a load, an equivalent connection circuit connecting the feed end and the load, and an external circuit connected to the equivalent connection circuit, the method including:

[0007] Acquire preset measurement parameters of the aerosol generating device; the preset measurement parameters are extracted by the external circuit.

[0008] The target measurement temperature is determined based on the preset measurement parameters and the preset temperature prediction model; wherein the temperature prediction model is determined based on the measurement parameter sample and the temperature sample.

[0009] Optionally, the temperature prediction model is determined by the following method:

[0010] Based on the categories of the measured parameter samples, several sensitive datasets of measured parameters to the predicted temperature range are determined, and the predicted temperature range is segmented according to the sensitive datasets to obtain several temperature sub-ranges.

[0011] Based on the sensitivity of various measurement parameters, a prediction sub-model is determined for each of the temperature sub-ranges, and a temperature prediction model is determined based on several of the prediction sub-models.

[0012] Optionally, the step of segmenting the predicted temperature range according to the sensitivity dataset to obtain several temperature sub-ranges includes:

[0013] Extract the initial temperature range of various measurement parameters with sensitivity greater than a preset value from the sensitivity dataset;

[0014] The initial temperature range of various measurement parameters is processed to determine several temperature sub-ranges.

[0015] Optionally, the step of determining a prediction sub-model for each of the temperature sub-ranges based on the sensitivity of various measurement parameters, and determining a temperature prediction model based on several prediction sub-models, includes:

[0016] The prediction model corresponding to the measurement parameter with the highest sensitivity in each temperature sub-range is determined as the prediction sub-model;

[0017] The temperature prediction model is determined by merging several of the predicted sub-models.

[0018] Optionally, the temperature prediction model is determined by the following method:

[0019] The measured parameter samples are used as independent variables, and the temperature samples are used as dependent variables.

[0020] The temperature prediction model is determined by performing a polynomial fitting on the dependent variable and the independent variable.

[0021] On the other hand, embodiments of this application provide a temperature measurement system for an aerosol generating device. The aerosol generating device includes a feed end, a load, an equivalent connection circuit connecting the feed end and the load, and an external circuit connected to the equivalent connection circuit. The system includes:

[0022] The first module is used to acquire preset measurement parameters of the aerosol generating device; the preset measurement parameters are extracted by the external circuit.

[0023] The second module is used to determine the target measurement temperature based on the preset measurement parameters and the preset temperature prediction model; wherein the temperature prediction model is determined based on the measurement parameter sample and the temperature sample.

[0024] On the other hand, embodiments of this application provide a temperature measuring device for an aerosol generating apparatus, comprising:

[0025] At least one processor;

[0026] At least one memory for storing at least one program;

[0027] When the at least one program is executed by the at least one processor, the at least one processor implements the temperature measurement method described above.

[0028] On the other hand, embodiments of this application provide a computer-readable storage medium storing a processor-executable program, which, when executed by a processor, is used to perform the temperature measurement method described above.

[0029] On the other hand, embodiments of this application provide a temperature measurement system for an aerosol generating device, including an external circuit and a computer device connected to the external circuit; wherein,

[0030] The external circuit is used to measure the preset measurement parameters of the aerosol generating device;

[0031] The computer device includes:

[0032] At least one processor;

[0033] At least one memory for storing at least one program;

[0034] When the at least one program is executed by the at least one processor, the at least one processor performs the method described above.

[0035] Optionally, the external circuit includes a power supply, a filter, an amplifier, a converter, and a microcontroller connected in sequence.

[0036] On the other hand, embodiments of this application provide an aerosol generating device, including the temperature measurement system described above, or the aerosol generating device includes the computer-readable storage medium described above.

[0037] Optionally, the aerosol generating device includes a microwave generating circuit, a feed terminal, a load, an equivalent connection circuit, and an external circuit, wherein,

[0038] The output terminal of the microwave generator circuit is connected to the feedin terminal;

[0039] The equivalent connection circuit is connected between the feed terminal and the load, the load including a resonant cavity for accommodating the aerosol forming matrix, and the microwave generating circuit emits microwaves to the resonant cavity through the feed terminal and the equivalent connection circuit to heat the aerosol forming matrix;

[0040] The external circuit is connected to the equivalent connection circuit and is used to collect and extract preset measurement parameters of the aerosol generating device.

[0041] Implementing the embodiments of this application has the following beneficial effects: In this embodiment, preset measurement parameters are extracted through the external circuit of the aerosol generating device, and the target measurement temperature is determined according to the preset measurement parameters and the preset temperature prediction model. The temperature prediction model is determined based on the measurement parameter sample and the temperature sample. The external circuit is less affected by the environmental factors of the aerosol generating device and has good stability. The preset measurement parameters extracted through the external circuit are more accurate, thereby improving the accuracy and stability of temperature measurement. Attached Figure Description

[0042] Figure 1 is a schematic flowchart of the steps of a temperature measurement method for an aerosol generating device provided in an embodiment of this application;

[0043] Figure 2 is a schematic flowchart of the steps for determining a temperature prediction model according to an embodiment of this application;

[0044] Figure 3 is a schematic flowchart of a step-by-step method for determining a temperature sub-range according to an embodiment of this application;

[0045] Figure 4 is a schematic flowchart of another step in determining a temperature prediction model provided in an embodiment of this application;

[0046] Figure 5 is a schematic flowchart of another step in determining a temperature prediction model provided in an embodiment of this application;

[0047] Figure 6 is a structural block diagram of a temperature measurement system for an aerosol generating device provided in an embodiment of this application;

[0048] Figure 7 is a structural block diagram of a temperature measuring device for an aerosol generating apparatus provided in an embodiment of this application;

[0049] Figure 8 is a structural block diagram of a computer device provided in an embodiment of this application;

[0050] Figure 9 is another structural block diagram of a temperature measurement system for an aerosol generating device provided in an embodiment of this application;

[0051] Figure 10 is a schematic diagram of the temperature measurement circuit of an aerosol generating device provided in an embodiment of this application;

[0052] Figure 11 is a schematic diagram of the temperature measurement circuit of another aerosol generating device provided in an embodiment of this application. Detailed Implementation

[0053] The present application will now be described in further detail with reference to the accompanying drawings and specific embodiments. The step numbers in the following embodiments are only for ease of explanation and do not limit the order of the steps. The execution order of each step in the embodiments can be adapted according to the understanding of those skilled in the art.

[0054] It should be noted that although functional modules are divided in the device schematic diagram and a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart. The terms "first," "second," etc., used in the specification, claims, and the foregoing drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented, for example, in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatuses.

[0055] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0056] In order to minimize the volume occupied by the measuring element within a limited space and reduce costs as much as possible while ensuring measurement and control performance, an external circuit can be added. The preset parameters extracted by the external circuit can be used to estimate the temperature to be measured.

[0057] When studying microwave radio frequency heating components and aerosol generation devices, it is often difficult to intuitively analyze some key parameters in the radio frequency microwaves. However, these key parameters have a crucial impact on the temperature measurement of the aerosol generation device. If these parameters can be obtained directly or indirectly and analyzed, the intrinsic relationship between the temperature of the aerosol generation device and these key parameters can be clearly revealed. This not only greatly simplifies the analysis process and reduces the research difficulty, but also allows for a more intuitive grasp of the essence of the problem, thereby significantly improving work efficiency and providing strong support for the research and optimization of aerosol generation devices. For aerosol generation devices, by introducing an external circuit, these required parameters can be obtained relatively accurately, greatly facilitating the research.

[0058] The aerosol generating device includes a microwave generating circuit, a power amplifier, a circulator, a coupler, a resonator, and a controller. The microwave generating circuit generates microwave radio frequency signals, which are amplified by the amplifier and then enter the resonant cavity through the circulator and coupler. In this embodiment, the output terminal of the microwave generating circuit is used as the feed port, the resonant cavity is used as the load, and the circuit between the feed port and the load is used as an equivalent connection circuit.

[0059] As shown in Figure 1, this application embodiment provides a temperature measurement method for an aerosol generating device, including:

[0060] S100. Obtain the preset measurement parameters of the aerosol generating device; the preset measurement parameters are extracted from the external circuit of the aerosol generating device.

[0061] S200. Determine the target measurement temperature based on the preset measurement parameters and the preset temperature prediction model; wherein, the temperature prediction model is determined based on the measurement parameter sample and the temperature sample.

[0062] It should be noted that the types of preset measurement parameters are determined based on the actual application, and this embodiment does not impose specific limitations. For example, preset measurement parameters include, but are not limited to, impedance parameters, frequency parameters, phase noise parameters, and scattering parameters. The external circuit extracts the preset measurement parameters based on the test results. The temperature prediction model represents the relationship model for predicting the target measurement temperature based on the preset measurement parameters. The target measurement temperature refers to the final predicted temperature of the aerosol generating device. The measurement parameter sample refers to the actual measured sample value of the preset measurement parameters, and the temperature sample refers to the actual measured sample value of the aerosol generating device.

[0063] Specifically, firstly, preset measurement parameters for temperature prediction are determined and extracted based on the test results of the external circuit. Then, the preset measurement parameters are input into a preset temperature prediction model to obtain the target measurement temperature. Those skilled in the art will understand that before the preset temperature prediction model is used to predict the target measurement temperature, its specific structure and parameters need to be determined based on actual measured parameter samples and temperature samples.

[0064] It should be noted that the preset temperature prediction model is determined based on the actual application, and this embodiment does not impose specific limitations. For example, the preset temperature prediction model may be a linear model, a nonlinear model, an exponential model, or a piecewise model, etc.

[0065] Alternatively, as shown in Figure 2, the temperature prediction model is determined using the following method:

[0066] S010. Determine the sensitivity datasets of several types of measurement parameters to the predicted temperature range based on the categories of the measurement parameter samples, and segment the predicted temperature range according to the sensitivity datasets to obtain several temperature sub-ranges.

[0067] S020. Determine the prediction sub-model for each temperature sub-range based on the sensitivity of various measurement parameters, and determine the temperature prediction model based on several prediction sub-models.

[0068] Sensitivity characterizes the significance of temperature changes relative to changes in measured parameters. Higher sensitivity indicates greater significance of temperature changes with measured parameters, leading to higher prediction accuracy and precision. The sensitivity dataset contains sensitivity data for various types of measured parameters on the predicted temperature range. A temperature subrange represents a specific temperature segment within the predicted temperature range. A prediction sub-model for a temperature subrange represents the model used to predict temperatures within that subrange.

[0069] Specifically, firstly, the sensitivity data of the measurement parameters to the predicted temperature range is determined according to the category of each type of measurement parameter sample. The sensitivity data of the measurement parameter samples of multiple categories are collected to form a sensitivity dataset. The predicted temperature range is then segmented according to the sensitivity data in the sensitivity dataset to obtain several temperature sub-ranges. Then, the prediction sub-model for each temperature sub-range is determined according to the sensitivity of each type of measurement parameter. Finally, the temperature prediction model is determined based on the several prediction sub-models.

[0070] Optionally, as shown in Figure 3, the predicted temperature range is segmented based on the sensitivity dataset to obtain several temperature sub-ranges, including:

[0071] S011. Extract the initial temperature range of various measurement parameters with sensitivity greater than the preset value from the sensitivity dataset;

[0072] S012. Process the initial temperature range of various measurement parameters to determine several temperature sub-ranges.

[0073] It should be noted that the preset value is determined based on the actual application, and this embodiment does not impose specific limitations. For example, the preset value is determined based on the prediction accuracy of the predicted temperature. The initial temperature range characterizes the temperature range within which the sensitivity of the measured parameters meets the requirements.

[0074] Specifically, firstly, the initial temperature ranges of various measurement parameters with sensitivities greater than preset values ​​are extracted from the sensitivity dataset. For example, the initial temperature range of the first measurement parameter with a sensitivity greater than the preset value is extracted as 20-60℃, and the initial temperature range of the second measurement parameter with a sensitivity greater than the preset value is extracted as 60-150℃. Then, the initial temperature ranges of various measurement parameters are processed to determine several temperature sub-ranges. It should be noted that the method of processing the initial temperature ranges of various measurement parameters is determined according to the actual application, and this embodiment does not impose specific limitations; for example, overlapping temperature ranges are selected and eliminated, and missing temperature ranges are filled, thereby obtaining several temperature sub-ranges covering the entire predicted temperature range.

[0075] Optionally, as shown in Figure 4, a prediction sub-model for each temperature sub-range is determined based on the sensitivity of various measurement parameters, and a temperature prediction model is determined based on several prediction sub-models, including:

[0076] S021. The prediction model corresponding to the measurement parameter with the highest sensitivity in each temperature sub-range is determined as the prediction sub-model;

[0077] S022. Merge several prediction sub-models to determine the temperature prediction model.

[0078] A predictive sub-model represents a temperature prediction model for a specific temperature sub-range. Specifically, firstly, the predictive model corresponding to the most sensitive measurement parameter within each temperature sub-range is determined as the predictive sub-model; that is, the predictive model corresponding to the measurement parameter with the most accurate prediction within each temperature sub-range is determined as the predictive sub-model. Then, the predictive sub-models corresponding to multiple temperature sub-ranges are merged to determine the final temperature prediction model. For example, the predictive sub-model corresponding to the first temperature sub-range is the first model, and the predictive sub-model corresponding to the second temperature sub-range is the second model. A segmented temperature prediction model is determined based on the first temperature sub-range, the first model, the second temperature sub-range, and the second model.

[0079] Alternatively, as shown in Figure 5, the temperature prediction model is determined using the following method:

[0080] S030. Use the measured parameter sample as the independent variable and the temperature sample as the dependent variable.

[0081] S040. Perform polynomial fitting on the dependent and independent variables to determine the temperature prediction model.

[0082] The independent variable is the variable that is actively manipulated or changed to observe its effect on other variables; it is the "cause" or "input" in the experiment. The dependent variable is the variable that is observed or measured; it is the result of changes in the independent variable; it is the "outcome" or "output" in the experiment. Changes in the independent variable will lead to changes in the dependent variable.

[0083] In certain scenarios, if a certain type of measurement parameter exhibits good sensitivity across the entire temperature prediction range, using this type of measurement parameter for temperature prediction across the entire range can improve accuracy while reducing computational load. Specifically, firstly, the measurement parameter samples are used as independent variables, and the temperature samples as dependent variables; then, a polynomial fitting is performed on the dependent and independent variables to determine the temperature prediction model. During the fitting process, the fitting polynomial or fitting tool can be determined based on empirical values.

[0084] In a specific embodiment, taking the aerosol generating device using microwave heating as an example (i.e., the aerosol generating device includes a resonant cavity and a microwave generator connected to the resonant cavity, with the microwave generator feeding microwaves into the resonant cavity through the feed port of the resonant cavity), to achieve temperature detection, an external circuit with a parallel structure is additionally introduced into the system topology. This parallel node is selected in the sensitive region of the resonant cavity's electromagnetic field mode, and its spatial coordinates are selected based on the eigenfunction distribution characteristics of the cavity mode field. Using the system characteristics of this external circuit, relevant parameters are extracted. The external circuit is connected in parallel at a point in the resonant cavity. When the temperature in the resonant cavity changes, the resonant frequency will inevitably change, indirectly causing changes in the electric field distribution and field mode. Therefore, the impedance value at that point will also change. Using the dataset of impedance changes at that point and the dataset of temperature changes, mathematical analysis is performed to establish a corresponding mathematical model. Therefore, measuring the impedance value at that point yields the temperature value. In addition to the methods mentioned above, the system noise figure can also be measured by introducing a parallel external circuit. Temperature and noise figure are extremely sensitive to temperature in the low-temperature range (0K-77K). The Johnson-Nyquist noise formula shows that at low temperatures, noise power is directly proportional to temperature, and even slight temperature changes can lead to significant changes in the noise figure. Within the room temperature range, near room temperature (approximately 290K), the noise figure is relatively less sensitive to temperature, requiring a high-precision system for temperature measurement. In the high-temperature range (above 473.15K), thermal noise increases significantly, and the noise figure becomes significantly more sensitive to temperature again. At this point, the relationship between noise figure and temperature may be non-linear, especially over a wide temperature range. In this case, by introducing a circuit system containing a low-noise amplifier and mathematically fitting the extracted noise figure and temperature datasets, the relationship between noise figure and temperature can be obtained, allowing for temperature measurement. Although both reflection coefficient and noise figure can be used to measure temperature at high temperatures, the accuracy of temperature measurement will still differ within a specific temperature range. Therefore, these two temperature measurement methods can be compared, and the appropriate method can be selected for temperature measurement in a specific range. In addition to these two methods of measuring parameters with external circuits, there are many other methods for extracting parameters from external circuits. Here, we will only use these two methods as examples.

[0085] Implementing the embodiments of this application has the following beneficial effects: In this embodiment, preset measurement parameters are extracted through the external circuit of the aerosol generating device, and the target measurement temperature is determined according to the preset measurement parameters and the preset temperature prediction model. The temperature prediction model is determined based on the measurement parameter sample and the temperature sample. The external circuit is less affected by the environmental factors of the aerosol generating device and has good stability. The preset measurement parameters extracted through the external circuit are more accurate, thereby improving the accuracy and stability of temperature measurement.

[0086] As shown in Figure 6, this application embodiment provides a temperature measurement system for an aerosol generating device, including:

[0087] The first module is used to acquire preset measurement parameters of the aerosol generating device; the preset measurement parameters are extracted from the external circuit of the aerosol generating device.

[0088] The second module is used to determine the target measurement temperature based on preset measurement parameters and a preset temperature prediction model; wherein, the temperature prediction model is determined based on measurement parameter samples and temperature samples.

[0089] It is evident that the content of the above method embodiments is applicable to this system embodiment. The specific functions implemented in this system embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0090] As shown in Figure 7, this application embodiment provides a temperature measuring device for an aerosol generating apparatus, including:

[0091] At least one processor;

[0092] At least one memory for storing at least one program;

[0093] When at least one program is executed by at least one processor, the at least one processor implements the temperature measurement method described above.

[0094] The memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. The memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory may optionally include remote memory located remotely relative to the processor, which can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0095] It is evident that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented in this device embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0096] Furthermore, this application also discloses a computer program product or computer program stored in a computer-readable storage medium. A processor of a computer device can read the computer program from the computer-readable storage medium, and the processor executes the computer program, causing the computer device to perform the described method. Similarly, the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0097] This application also provides a computer-readable storage medium storing a processor-executable program, which, when executed by a processor, is used to implement the above-described method.

[0098] It is understood that all or some of the steps and systems in the methods disclosed above can be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components can be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, which can include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, as is known to those skilled in the art, communication media typically contain computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0099] Specifically, referring to Figure 8, the computer device 800 may include an RF (Radio Frequency) circuit 810, a memory 820 including one or more computer-readable storage media, an input unit 830, a display unit 840, a sensor 850, an audio circuit 860, a short-range wireless transmission module 870, a processor 880 including one or more processing cores, and a power supply 890, among other components. Those skilled in the art will understand that the device structure shown in Figure 8 does not constitute a limitation on the electronic device, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0100] The RF circuit 810 can be used for receiving and transmitting signals during information transmission or calls. Specifically, it receives downlink information from the base station and hands it over to one or more processors 880 for processing; additionally, it transmits uplink data to the base station. Typically, the RF circuit 810 includes, but is not limited to, an antenna, at least one amplifier, a tuner, one or more oscillators, a Subscriber Identity Module (SIM) card, a transceiver, a coupler, an LNA (Low Noise Amplifier), a duplexer, etc. Furthermore, the RF circuit 810 can also communicate wirelessly with networks and other devices. Wireless communication can use any communication standard or protocol, including but not limited to GSM (Global System for Mobile communication), GPRS (General Packet Radio Service), CDMA (Code Division Multiple Access), WCDMA (Wideband Code Division Multiple Access), LTE (Long Term Evolution), email, SMS (Short Messaging Service), etc.

[0101] The memory 820 can be used to store software programs and modules. The processor 880 executes various functional applications and data processing by running the software programs and modules stored in the memory 820. The memory 820 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, application programs required for at least one function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the device 800 (such as audio data, telephone book, etc.). In addition, the memory 820 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, the memory 820 may also include a memory controller to provide access to the memory 820 for the processor 880 and the input unit 830. Although Figure 8 shows the RF circuit 810, it is understood that it is not a necessary component of the device 800 and can be omitted as needed without changing the essence of the application.

[0102] The input unit 830 can be used to receive input digital or character information, and to generate keyboard, mouse, joystick, optical, or trackball signal inputs related to user settings and function control. Specifically, the input unit 830 may include a touch-sensitive surface 831 and other input devices 832. The touch-sensitive surface 831, also known as a touch display screen or touchpad, can collect touch operations performed by the user on or near it (such as operations performed by the user using a finger, stylus, or any suitable object or accessory on or near the touch-sensitive surface 831), and drive the corresponding connection device according to a pre-set program. Optionally, the touch-sensitive surface 831 may include two parts: a touch detection device and a touch controller. The touch detection device detects the user's touch position and the signal generated by the touch operation, and transmits the signal to the touch controller; the touch controller receives touch information from the touch detection device, converts it into touch point coordinates, sends it to the processor 880, and can receive and execute commands sent by the processor 880. In addition, the touch-sensitive surface 831 can be implemented using various types such as resistive, capacitive, infrared, and surface acoustic wave. In addition to the touch-sensitive surface 831, the input unit 830 may also include other input devices 832. Specifically, other input devices 832 may include, but are not limited to, one or more of the following: physical keyboard, function keys (such as volume control buttons, power buttons, etc.), trackball, mouse, joystick, etc.

[0103] Display unit 840 can be used to display information input by the user or information provided to the user, as well as various graphical user interfaces controlling 800. These graphical user interfaces can be composed of graphics, text, icons, video, and any combination thereof. Display unit 840 may include display panel 841, which may optionally be configured as an LCD (Liquid Crystal Display), OLED (Organic Light-Emitting Diode), or similar display panel. Further, touch-sensitive surface 831 may cover display panel 841. When touch-sensitive surface 831 detects a touch operation on or near it, it transmits the information to processor 880 to determine the type of touch event. Subsequently, processor 880 provides corresponding visual output on display panel 841 according to the type of touch event. Although in FIG. 8, touch-sensitive surface 831 and display panel 841 are implemented as two separate components to realize input and output functions, in some embodiments, touch-sensitive surface 831 and display panel 841 can be integrated to realize input and output functions.

[0104] The computer device 800 may also include at least one sensor 850, such as a light sensor, a motion sensor, and other sensors. Specifically, the light sensor may include an ambient light sensor and a proximity sensor. The ambient light sensor can adjust the brightness of the display panel 841 according to the ambient light level, and the proximity sensor can turn off the display panel 841 and / or backlight when the device 800 is moved to the ear. As a type of motion sensor, a gravity acceleration sensor can detect the magnitude of acceleration in various directions (generally three axes). When stationary, it can detect the magnitude and direction of gravity and can be used for applications that recognize the phone's posture (such as landscape / portrait switching, related games, magnetometer posture calibration), vibration recognition-related functions (such as pedometers, taps), etc. Other sensors that the device 800 may be equipped with, such as gyroscopes, barometers, hygrometers, thermometers, and infrared sensors, will not be described in detail here.

[0105] Audio circuitry 860, speaker 861, and microphone 862 provide an audio interface between the user and device 800. Audio circuitry 860 converts received audio data into electrical signals, which are then transmitted to speaker 861, where they are converted into sound signals for output. Conversely, microphone 862 converts collected sound signals into electrical signals, which are received by audio circuitry 860, converted back into audio data, and then processed by processor 880 before being transmitted via RF circuitry 810 to another control device, or output to memory 820 for further processing. Audio circuitry 860 may also include an earphone jack to facilitate communication between peripheral headphones and device 800.

[0106] The short-range wireless transmission module 870 can be a WIFI (wireless fidelity) module, Bluetooth module, or infrared module, etc. Device 800 can transmit information with the wireless transmission module installed on the gaming equipment via the short-range wireless transmission module 870.

[0107] Processor 880 is the control center of device 800. It connects various parts of the control device via various interfaces and lines. By running or executing software programs and / or modules stored in memory 820, and by calling data stored in memory 820, it performs various functions of device 800 and processes data, thereby providing overall monitoring of the control device. Optionally, processor 880 may include one or more processing cores; optionally, processor 880 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the modem processor mainly handles wireless communication. It is understood that the aforementioned modem processor may not be integrated into processor 850.

[0108] The device 800 also includes a power supply 890 (such as a battery) to power various components. Preferably, the power supply can be logically connected to the processor 880 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system. The power supply 890 may also include one or more DC or AC power supplies, recharging systems, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components.

[0109] Although not shown, device 800 may also include a camera, Bluetooth module, etc., which will not be described in detail here.

[0110] Referring to Figure 9, an embodiment of this application provides a temperature measurement system for an aerosol generating device, including an external circuit and a computer device connected to the external circuit; wherein,

[0111] External circuitry is used to measure preset parameters of the aerosol generating device.

[0112] Computer equipment includes:

[0113] At least one processor;

[0114] At least one memory for storing at least one program;

[0115] When at least one program is executed by at least one processor, the at least one processor performs the method described above.

[0116] Referring to Figure 10, the resonant cavity body in the aerosol generating device is equivalent to the terminal load, and the transmission structure and lines between the microwave feed port and the terminal load in the aerosol generating device are equivalent to the equivalent connection circuit. An external circuit is connected in parallel between the feed port and the terminal load.

[0117] It should be noted that different temperature measurement methods have different sensitivities to temperature in different temperature ranges, which can lead to inaccuracies in temperature measurement. Therefore, different external circuit configurations can be used in different temperature measurement ranges.

[0118] Specifically, the computer device can be of different types of electronic devices, including but not limited to desktop computers, laptops, mobile phones, tablets, wearable devices and other terminals.

[0119] Optionally, the external circuitry includes a power supply, a filter, an amplifier, a converter, and a microcontroller connected in sequence.

[0120] Power supplies include, but are not limited to, DC or AC sources. Referring to Figure 11, a DC source provides a stable voltage or current to the entire circuit system, ensuring its normal operation. A DC / AC converter converts DC power to AC power to meet the AC power requirements of different devices. It also enables waveform modulation, frequency control, and voltage regulation. Filters improve signal quality, reduce interference, separate signals of different frequencies, or achieve specific frequency responses. An operational amplifier is a versatile amplifier with high gain, high input impedance, and low output impedance. Its most basic function is to amplify the input signal. With appropriate feedback circuitry, it can achieve voltage amplification, current amplification, or power amplification. It can also perform various signal processing functions. An analog-to-digital converter converts analog signals into digital signals. A microcontroller can automatically control the measurement process according to preset program logic. Its driver display module can display the measurement results to the user. Measurement data can be transmitted to external devices via serial port, USB, or other communication interfaces. Furthermore, it has fault detection and alarm functions.

[0121] This application provides an aerosol generating device, including the temperature measurement system described above, or the aerosol generating device includes the computer-readable storage medium described above.

[0122] Optionally, the aerosol generating device includes a microwave generating circuit, a feed terminal, a load, an equivalent connection circuit, and an external circuit, wherein,

[0123] The output terminal of the microwave generator circuit is connected to the feedin terminal;

[0124] An equivalent connection circuit is connected between the feed end and the load, the load including a resonant cavity for accommodating the aerosol forming matrix, and a microwave generating circuit emits microwaves into the resonant cavity through the feed end and the equivalent connection circuit to heat the aerosol forming matrix.

[0125] The external circuit is connected to the equivalent circuit and is used to collect preset measurement parameters of the aerosol generating device.

[0126] Specifically, the equivalent connection circuit includes, but is not limited to, the amplifier circuit, circulator, matching network, isolator, limiter, and overcurrent protection circuit between the microwave generating circuit and the resonant cavity. The aerosol forming matrix includes, but is not limited to, solid tobacco products, tobacco paste, and tobacco liquid.

[0127] It is evident that the content of the above method embodiments is applicable to this system embodiment. The specific functions implemented in this system embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0128] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) 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 (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0129] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between apparatuses or units through some interfaces, and may be electrical, mechanical, or other forms.

[0130] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0131] The above is a detailed description of the preferred embodiments of this application. However, the invention of this application is not limited to the embodiments described. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of this application. All such equivalent modifications or substitutions are included within the scope defined by the claims of this application.

Claims

1. A method for measuring the temperature of an aerosol generating device, the aerosol generating device comprising a feed end, a load, an equivalent connection circuit connecting the feed end and the load, and an external circuit connected to the equivalent connection circuit, the method comprising: Obtain the preset measurement parameters of the aerosol generating device; The preset measurement parameters are extracted by the external circuit; The target measurement temperature is determined based on the preset measurement parameters and the preset temperature prediction model; wherein the temperature prediction model is determined based on the measurement parameter sample and the temperature sample.

2. The method according to claim 1, wherein, The temperature prediction model was determined using the following method: Based on the categories of the measured parameter samples, several sensitive datasets of measured parameters to the predicted temperature range are determined, and the predicted temperature range is segmented according to the sensitive datasets to obtain several temperature sub-ranges. Based on the sensitivity of various measurement parameters, a prediction sub-model is determined for each of the temperature sub-ranges, and the temperature prediction model is determined based on several of the prediction sub-models.

3. The method according to claim 2, wherein, The predicted temperature range is segmented based on the sensitivity dataset to obtain several temperature sub-ranges, including: Extract the initial temperature range of various measurement parameters with sensitivity greater than a preset value from the sensitivity dataset; The initial temperature range of various measurement parameters is processed to determine several temperature sub-ranges.

4. The method according to claim 2, wherein, The step of determining a prediction sub-model for each temperature sub-range based on the sensitivity of various measurement parameters, and determining the temperature prediction model based on several prediction sub-models, includes: The prediction model corresponding to the measurement parameter with the highest sensitivity in each temperature sub-range is determined as the prediction sub-model; The temperature prediction model is determined by merging several of the prediction sub-models.

5. The method according to claim 1, wherein, The temperature prediction model was determined using the following method: The measured parameter samples are used as independent variables, and the temperature samples are used as dependent variables. The temperature prediction model is determined by performing a polynomial fitting on the dependent variable and the independent variable.

6. A temperature measurement system for an aerosol generating device, the aerosol generating device comprising a feed terminal, a load, an equivalent connection circuit connecting the feed terminal and the load, and an external circuit connected to the equivalent connection circuit, the system comprising: The first module is used to acquire preset measurement parameters of the aerosol generating device; The preset measurement parameters are extracted by an external circuit; The second module is used to determine the target measurement temperature based on the preset measurement parameters and the preset temperature prediction model; wherein the temperature prediction model is determined based on the measurement parameter sample and the temperature sample.

7. A temperature measuring device for an aerosol generating apparatus, comprising: At least one processor; At least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor performs the method as described in any one of claims 1-5.

8. A computer-readable storage medium storing a processor-executable program, which, when executed by a processor, is used to perform the method as claimed in any one of claims 1-5.

9. A temperature measurement system for an aerosol generating device, comprising an external circuit and a computer device connected to the external circuit; wherein, The external circuit is used to measure the preset measurement parameters of the aerosol generating device; The computer device includes: At least one processor; At least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor performs the method as described in any one of claims 1-5.

10. The temperature measurement system according to claim 9, wherein, The external circuit includes a power supply, a filter, an amplifier, a converter, and a microcontroller connected in sequence.

11. An aerosol generating apparatus, comprising the temperature measurement system as described in claim 6, 9 or 10, or the aerosol generating apparatus comprising the computer-readable storage medium as described in claim 8.

12. The aerosol generating apparatus according to claim 11, wherein, The aerosol generating device includes a microwave generating circuit, a feed terminal, a load, an equivalent connection circuit, and an external circuit, wherein... The output terminal of the microwave generator circuit is connected to the feedin terminal; The equivalent connection circuit is connected between the feed terminal and the load, the load including a resonant cavity for accommodating the aerosol forming matrix, and the microwave generating circuit emits microwaves to the resonant cavity through the feed terminal and the equivalent connection circuit to heat the aerosol forming matrix; The external circuit is connected to the equivalent connection circuit and is used to collect and extract preset measurement parameters of the aerosol generating device.

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