RU2840673C2 - Method, device, electronic device and computer-readable medium for controlling temperature of fragmentary heating for vaping kit - Google Patents

Abstract

FIELD: physics; smoking accessories.

SUBSTANCE: group of inventions relates to a method, a device, an electronic device and a computer-readable medium for controlling temperature of fragmentary heating for a vaping kit. Method for controlling a fragmented heating temperature for a vaping kit comprises steps of: obtaining vaping kit parameters information and obtaining at least two cigarette heating segments based on the vaping kit parameters information; determining an initial heating temperature of the vaping kit and constructing a neural convolutional network model based on the initial heating temperature of the vaping kit to calculate a first temperature variation curve of each of the at least two cigarette heating segments under predetermined vaping conditions; adjusting an initial heating temperature corresponding to each of the at least two cigarette heating segments separately based on the first temperature variation curve to obtain each adjustable heating temperature; entering each controlled heating temperature into the neural convolution network model to calculate a second curve of temperature variation of each of the at least two cigarette heating segments under predetermined vaping conditions. First temperature variation curve is a temperature curve corresponding to a heating process, wherein the vaping kit is uniformly heated from an initial heating temperature. Vaping conditions are environmental conditions when the vaping kit is being vaped and said vaping conditions comprise a vaping intensity and a vaping interval. Temperature range of the second temperature variation curve corresponding to each controlled heating temperature is within the pre-set range. Said obtaining vaping kit parameter information and obtaining at least two cigarette heating segments based on the vaping kit parameter information comprises steps of: obtaining vaping kit parameter information, wherein the vaping kit parameter information comprises the cigarette insertion slot depth and the cigarette insertion slot radius; determining an optimum heating distance based on a depth and a radius of the cigarette insertion slot and obtaining said at least two cigarette heating segments based on the optimum heating distance.

EFFECT: by controlling the variation temperature of each heating segment of the electronic cigarette during vaping of the vaping kit under certain vaping conditions, the temperature corresponding to the balanced in the end vaping vapour, ensuring and preventing the burning of the mouth when vaping.

9 cl, 3 dwg

Description

[0001] This application claims priority to Chinese Patent Application No. 202111244660.0, entitled "PIECEWISE HEATING TEMPERATURE CONTROL METHOD AND APPARATUS FOR VAPING SET AND ELECTRONIC DEVICE", filed on October 26, 2021, in the National Intellectual Property Administration (China), which is incorporated herein by reference in its entirety.

Field of technology to which the invention relates

[0002] The present disclosure relates to the field of heat control technology for vaping kits and, in particular, to a method and device for controlling the temperature of fragmentary heating for a vaping kit and to an electronic device.

State of the art

[0003] The emergence of low-temperature cigarette products changes the traditional cigarettes that burn to form visible smoke by using the heating method without combustion, thereby greatly reducing the release of tar and harmful components and causing almost no harm to the environment and people around. At present, the vaping kit with heating without combustion heats the cigarette through peripheral heating or by inserting a central heating element into the cigarette for heating. Compared with the heating method with combustion for traditional cigarettes, the cigarette is uniformly heated in the vaping kit in any of the above heating processes, and heat must be continuously accumulated in the smoke in the vaping kit during the heating process due to poor air circulation. The smoke must bring the internal temperature to the external position during vaping, which further increases the temperature at the external position. Ultimately, the user may burn his mouth when smoking, and this affects the user's smoking process.

The essence of the invention

[0004] In order to solve the above problem, a method and device for controlling the temperature of fragmentary heating for a vaping kit and an electronic device are provided according to embodiments of the present disclosure.

[0005] In a first aspect, a method for controlling a fragmentary heating temperature for a vaping kit is provided according to embodiments of the present disclosure, and the method includes:

- obtaining parameter information of a vaping kit and obtaining at least two cigarette heating segments based on the parameter information of the vaping kit;

- determining an initial heating temperature of the vaping kit and constructing a neural convolutional network model based on the initial heating temperature of the vaping kit to calculate a first temperature change curve of each of said at least two cigarette heating segments under predetermined vaping conditions; and

- regulating the initial heating temperature corresponding to each of said at least two cigarette heating segments separately on the basis of the first temperature change curve in order to obtain each adjustable heating temperature, wherein the temperature range of the second temperature change curve corresponding to each adjustable heating temperature is within a predetermined range.

[0006] Preferably, obtaining parameter information of the vaping kit and obtaining at least two cigarette heating segments based on the parameter information of the vaping kit includes:

- obtaining information about the parameters of the vaping kit, wherein the information about the parameters of the vaping kit includes the depth of the groove for inserting a cigarette and the radius of the groove for inserting a cigarette;

- determining the optimal heating distance based on the depth and radius of the cigarette insertion groove; and

- obtaining at least two cigarette heating segments based on the optimal heating distance.

[0007] Preferably, adjusting the initial heating temperature of each of said at least two cigarette heating segments separately based on the first temperature change curve to obtain each adjustable heating temperature, wherein the temperature range of the second temperature change curve corresponding to each adjustable heating temperature is within a predetermined range, includes:

- regulating the initial heating temperature of each of said at least two cigarette heating segments separately on the basis of the first temperature change curve in order to obtain each regulated heating temperature;

- inputting each adjustable heating temperature into a neural convolutional network model to calculate a second temperature change curve of each of said at least two cigarette heating segments under preset vaping conditions;

- regulating each adjustable heating temperature of each of said at least two cigarette heating segments separately based on the second temperature change curve, in case the temperature range of the second temperature change curve is not entirely within a predetermined range; and

- repeating the step of inputting each adjustable heating temperature into the neural convolutional network model until the temperature range of the second temperature change curve is completely within the preset range.

[0008] Preferably, the method further comprises:

- recording each adjustable heating temperature when the vaping kit is detected to be off; and

- Adjust the heating temperature of the vaping kit based on each adjustable heating temperature when the vaping kit is restarted.

[0009] Preferably, the method further comprises:

- collecting user vaping habit data, wherein the user vaping habit data includes the vaping interval and the vaping gas volume each time; and

- Optimizing the neural convolutional network model based on user vaping habit data to re-calculate each adjustable heating temperature.

[0010] Preferably, the method further comprises:

- continuously collecting user vaping habit data to form a complete vaping habit curve for the user; and

- Adjust each adjustable heating temperature dynamically based on each vaping node in the user's complete vaping habit curve when the vaping kit is launched next time.

[0011] Preferably, the method further comprises:

- forming, after at least three complete vaping habit curves for the user are formed, a standard complete vaping habit curve by integrating the at least three complete vaping habit curves for the user; and

- Adjust each adjustable heating temperature dynamically based on each vaping node in the standard full vaping habit curve when the vaping kit is started next time.

[0012] In a second aspect, a fragmentary heating temperature control device for a vaping kit is provided according to embodiments of the present disclosure, and the device includes:

- a receiving module configured to receive parameter information of the vaping kit and to receive at least two cigarette heating segments based on the parameter information of the vaping kit;

- a determining module configured to determine an initial heating temperature of the vaping kit and to construct a neural convolutional network model based on the initial heating temperature of the vaping kit to calculate a first temperature change curve of each of said at least two cigarette heating segments under predetermined vaping conditions; and

- a control module configured to control the initial heating temperature of each of said at least two cigarette heating segments separately on the basis of a first temperature change curve in order to obtain each adjustable heating temperature, wherein the temperature range of the second temperature change curve corresponding to each adjustable heating temperature is within a predetermined range.

[0013] In a third aspect, an electronic device is provided according to embodiments of the present disclosure, and the electronic device includes a memory, a processor, and a computer program stored in the memory and executed by the processor, wherein the processor, when executing the computer program, performs the steps in the method according to the first aspect or any possible implementation in the first aspect.

[0014] In a fourth aspect, a computer-readable storage medium is provided according to embodiments of the present disclosure. The computer-readable storage medium stores a computer program, wherein the computer program, when executed in a processor, implements the steps in the method according to the first aspect or any possible implementation in the first aspect.

[0015] The advantages of the present disclosure are as follows. A plurality of cigarette heating segments are provided in a vaping kit, and by simulating and adjusting the temperature change of each cigarette heating segment during the vaping process under certain vaping conditions, different cigarette heating segments have different heating temperatures, which ensures that the temperature corresponding to the ultimately vaped smoke is relatively uniform, which protects the user from burning the mouth when vaping. In addition, the heating processing of each cigarette heating segment is continuously adjusted according to the vaping habit of the user, thereby improving the vaping experience of the user.

Brief description of the drawings

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings referred to for describing the embodiments are briefly described hereinafter. It is obvious that the drawings in the following description represent only some embodiments of the present disclosure, and for those skilled in the art, other drawings can be obtained based on the provided drawings without any creative efforts at all.

[0017] Fig. 1 is a flow chart of a method for controlling a fragmentary heating temperature for a vaping kit according to an embodiment of the present disclosure;

[0018] Fig. 2 is a schematic block diagram of a fragmentary heating temperature control device for a vaping kit according to an embodiment of the present disclosure; and

[0019] Fig. 3 is a schematic block diagram of an electronic device according to an embodiment of the present disclosure.

Detailed description of the invention

[0020] The technical solutions of the embodiments of the present disclosure are clearly and completely described hereinafter in conjunction with the drawings of the embodiments of the present disclosure.

[0021] In the introduction hereinafter, the terms "first", "second" are merely for the purposes of description and should not be understood as indicating or implying relative importance. The introduction below provides several embodiments according to the present disclosure, and different embodiments may be substituted or combined. Therefore, the present disclosure may also be considered to include all possible combinations of the described identical and/or different embodiments. Thus, if one embodiment comprises features A, B and C, and another embodiment comprises features B and D, then the present disclosure shall also be considered to include all other possible combinations comprising one or more of A, B, C and D, although this embodiment may not be clearly written in the content below.

[0022] The following description provides examples and does not limit the scope, applicability, or examples described in the claims. Changes may be made in the function and arrangement of the described elements without departing from the scope of the present disclosure. Various examples may be omitted, replaced, or added with respect to various procedures or components as appropriate. For example, the described methods may be performed in an order different from the order described, and various steps may be added, omitted, or combined. In addition, features described with respect to some examples may be combined in other examples.

[0023] Refer to Fig. 1, which is a flow chart of a method for controlling a fragmentary heating temperature for a vaping kit according to an embodiment of the present disclosure. In this embodiment of the present disclosure, the method includes a step S101-S103.

[0024] In step S101, parameter information of the vaping kit is obtained, and at least two cigarette heating segments are obtained based on the parameter information of the vaping kit.

[0025] An executable subject matter in the present disclosure may be a controller in a heat-not-burn vaping kit.

[0026] In an embodiment of the present disclosure, during use of the combustion-free heating vaping kit, the combustion-free heating cigarette is inserted into the corresponding combustion-free heating vaping kit, and the combustion-free heating vaping kit is heated to thereby heat the cigarette so as to generate smoke for vaping by the user. Different vaping kits with different models correspond to different parameter information of the vaping kit. In other words, the insertion depth of the cigarette and the corresponding size of the inserted cigarette vary in the vaping kits with different models, resulting in different heating lengths of the cigarette when the cigarette is heated by the vaping kit. In the present disclosure, in order to ensure that the smoke ultimately vaped from each part of the vaping kit does not burn the mouth, the inserted part of the cigarette is segmented for fragmentary heating. Therefore, firstly, the parameter information of the vaping kit is obtained, and the number of cigarette heating segments is determined based on the parameter information of the vaping kit.

[0027] In an embodiment, obtaining parameter information of a vaping kit and obtaining at least two cigarette heating segments based on the parameter information of the vaping kit includes:

- obtaining information about the parameters of the vaping kit, wherein the information about the parameters of the vaping kit includes the depth of the groove for inserting a cigarette and the radius of the groove for inserting a cigarette;

- determining the optimal heating distance based on the depth and radius of the cigarette insertion groove; and

- obtaining at least two cigarette heating segments based on the optimal heating distance.

[0028] In this embodiment of the present disclosure, the controller can obtain the depth and radius of the cigarette insertion groove from the parameter information of the vaping kit. In order to ensure the effect of fragmentary heating, the length of the segment may not be too large, and the temperature for heating the inside of the cigarette increases when the radius of the cigarette insertion groove increases, which also affects the temperature at the intersection of adjacent heating segments. Therefore, a suitable optimal heating distance is determined according to the depth and radius of the cigarette insertion groove, on the basis of which the cigarette heating segments are obtained.

[0029] In S102, an initial heating temperature of the vaping kit is determined, and a neural convolutional network model is constructed according to the initial heating temperature of the vaping kit to calculate a first temperature change curve of each of said at least two cigarette heating segments under preset vaping conditions.

[0030] Vaping conditions in an embodiment of the present disclosure may be understood as simulated environmental conditions when the vaping kit is vaping, such as vaping intensity, vaping interval, etc.

[0031] In an embodiment of the present disclosure, the heating temperature of each part of the conventional vaping kit is identical. The controller determines an initial heating temperature, which is a default heating temperature of the vaping kit, obtains a learning model to perform simulated heating learning based on the initial heating temperature of the vaping kit, to thereby construct a neural convolutional network model suitable for the vaping kit. The specific design and formation process are common knowledge that can be easily understood by those skilled in the art, and the model construction process is not the focus of the present disclosure, so it is not described in detail here. Through the constructed neural convolutional network model, the first temperature change curve of each of the cigarette heating segments is determined during the heating process in which the vaping kit is uniformly heated internally from the initial heating temperature of the vaping kit under preset vaping conditions (i.e., with a certain vaping time interval and vaping intensity).

[0032] In step S103, the initial heating temperature corresponding to each of said at least two cigarette heating segments is separately adjusted based on the first temperature change curve to obtain each adjustable heating temperature, wherein the temperature range of the second temperature change curve corresponding to each adjustable heating temperature is within a predetermined range.

[0033] In an embodiment of the present disclosure, the threshold temperature range of each of the cigarette heating segments is obtained from the first temperature change curve, in the case that the vaping kit is heated uniformly from the initial heating temperature. In order not to burn the mouth and ensure the vaping experience, the temperature of the vaped smoke cannot be too high or too low, that is, during the entire vaping process, the temperature change of each of the cigarette heating segments must be within a preset range. Therefore, the heating temperature of each cigarette heating segment is separately adjusted according to the first temperature change curve corresponding to each of the cigarette heating segments, and as a result, an adjustable heating temperature corresponding to the second temperature change curve, the temperature range of which is completely within the preset range, is obtained. By maintaining the adjustable heating temperature of each of the cigarette heating segments, the vaping experience of the user during the entire vaping process is improved without burning the mouth. In addition, such an adjustment process is relatively simple and can be used in various vaping kits.

[0034] In an embodiment, adjusting the initial heating temperature of each of said at least two cigarette heating segments based on the first temperature change curve to obtain each adjustable heating temperature, wherein the temperature range of the second temperature change curve corresponding to each adjustable heating temperature is within a predetermined range, includes:

- regulating the initial heating temperature of each of said at least two cigarette heating segments separately on the basis of the first temperature change curve in order to obtain each regulated heating temperature;

- inputting each adjustable heating temperature into a neural convolutional network model to calculate a second temperature change curve of each of said at least two cigarette heating segments under preset vaping conditions;

- regulating each adjustable heating temperature of each of said at least two cigarette heating segments separately based on the second temperature change curve, in case the temperature range of the second temperature change curve is not entirely within a predetermined range; and

- repeating the step of inputting each adjustable heating temperature into the neural convolutional network model until the temperature range of the second temperature change curve is completely within the preset range.

[0035] In an embodiment of the present disclosure, the initial heating temperature is adjusted according to the first temperature change curve to obtain the adjusted heating temperature, and a simulation calculation is performed in a neural convolutional network model based on the adjusted heating temperature to determine whether or not the generated second temperature change curve is completely within a predetermined range. When the generated second temperature change curve is not completely within the predetermined range, the adjusted heating temperature is adjusted again based on the second temperature change curve. The simulation process in the model is repeated until the adjusted heating temperature satisfying the conditions is obtained.

[0036] In an embodiment, the method further includes:

- recording each adjustable heating temperature when the vaping kit is detected to be off; and

- Adjust the heating temperature of the vaping kit based on each adjustable heating temperature when the vaping kit is restarted.

[0037] In an embodiment of the present disclosure, after the adjustable heating temperature suitable for the vaping kit is calculated, the adjustable heating temperature is recorded when the vaping kit is turned off, so that the heating temperature of the vaping kit can be directly adjusted based on each adjustable heating temperature when the vaping kit is started again. In this way, it is not necessary to calculate the adjustable heating temperature with the neural convolutional network model each time, which ensures the vaping efficiency of the vaping kit.

[0038] In an embodiment, the method further includes:

- collecting user vaping habit data, wherein the user vaping habit data includes the vaping interval and the vaping gas volume each time; and

- Optimizing the neural convolutional network model based on user vaping habit data to re-calculate each adjustable heating temperature.

[0039] In an embodiment of the present disclosure, in the above-described process, the adjustable heating temperature is obtained under preset vaping conditions, that is, based on the average vaping interval and the average vaping volume determined according to a large amount of user data. In practice, for individual users, their vaping habits are different, and different vaping habits affect the air flow in the vaping kit and the heat accumulation time, which leads to an inaccurate calculation of the adjustable heating temperature and therefore to the occurrence of mouth burning. Therefore, when the user actually vapes, the user's vaping habit data is collected, and the imitation process of the neural convolutional network model is optimized based on the user's vaping habit data, so as to repeatedly calculate the adjustable heating temperature. In this way, it is ensured that the finally obtained adjustable heating temperature can best suit the user.

[0040] In an embodiment, the method further includes:

- continuously collecting user vaping habit data to form a complete vaping habit curve for the user; and

- Adjust each adjustable heating temperature dynamically based on each vaping node in the user's complete vaping habit curve when the vaping kit is launched next time.

[0041] In an embodiment of the present disclosure, during the actual vaping process of the user, it is unlikely that he/she should vape completely at a constant interval and intensity, but may have a personal habit such as vaping twice and tasting the smoke before continuing, so that it may still be unlikely to obtain the most suitable adjustable heating temperature only according to the user's vaping habit data. Therefore, the user's vaping habit data is continuously collected, and a habit curve of the user's complete vaping process is formed accordingly. The dynamic change of the user's vaping habit during the complete vaping process can be accurately characterized through the habit curve. Therefore, when the vaping kit is started next time, data such as the time interval and the change in vaping intensity between vaping nodes can be determined based on the vaping nodes in the vaping habit curve. Adjustable heating temperature is dynamically adjusted accordingly, better adapting to user's vaping.

[0042] In an embodiment, the method further includes:

- forming, after at least three complete vaping habit curves for the user are formed, a standard complete vaping habit curve by integrating the at least three complete vaping habit curves for the user; and

- Adjust each adjustable heating temperature dynamically based on each vaping node in the standard full vaping habit curve when the vaping kit is started next time.

[0043] In an embodiment of the present disclosure, each time the user completes the complete vaping process, a complete vaping habit curve for the user is formed. The controller integrates and adjusts at least three vaping habit curves and eliminates errors to obtain a standard complete vaping habit curve. Then, the adjustable heating temperature is adjusted based on the standard complete vaping habit curve in the next process.

[0044] The device for controlling the temperature of the fragmentary heating for the vaping kit according to the embodiments of the present disclosure will be described in detail below with reference to Fig. 2. It should be noted that the device for controlling the temperature of the fragmentary heating for the vaping kit shown in Fig. 2 is configured to implement the method according to the embodiment shown in Fig. 1 of the present disclosure, and only the parts thereof relevant to the embodiment of the present disclosure are shown for illustration. For specific technical details not disclosed, reference should be made to the embodiment shown in Fig. 1 according to the present disclosure.

[0045] Referring to Fig. 2, which is a schematic block diagram of a fragmentary heating temperature control device for a vaping kit according to an embodiment of the present disclosure. As shown in Fig. 2, the device includes:

- a receiving module 201 configured to receive parameter information of the vaping kit and to receive at least two cigarette heating segments based on the parameter information of the vaping kit;

- a determining module 202 configured to determine an initial heating temperature of the vaping kit and to construct a neural convolutional network model based on the initial heating temperature of the vaping kit to calculate a first temperature change curve of each of said at least two cigarette heating segments under predetermined vaping conditions; and

- a control module 203, configured to control the initial heating temperature of each of said at least two cigarette heating segments separately on the basis of a first temperature change curve in order to obtain each adjustable heating temperature, wherein the temperature range of the second temperature change curve corresponding to each adjustable heating temperature is within a predetermined range.

[0046] In an embodiment, the obtaining module 201 includes:

- a receiving unit configured to receive information about the parameters of a vaping kit, wherein the information about the parameters of a vaping kit includes the depth of the groove for inserting a cigarette and the radius of the groove for inserting a cigarette;

- a unit for determining the optimal heating distance, configured to determine the optimal heating distance based on the depth and radius of the groove for inserting a cigarette;

- a heating segment obtaining unit configured to obtain said at least two cigarette heating segments based on an optimal heating distance.

[0047] In an embodiment, the control module 203 includes:

- a first control unit configured to control the initial heating temperature of each of said at least two cigarette heating segments separately based on the first temperature change curve in order to obtain each controlled heating temperature;

- an input unit configured to input each adjustable heating temperature into a neural convolutional network model and calculate a second curve of temperature change of each of said at least two cigarette heating segments under preset vaping conditions;

- a second control unit configured to control each adjustable heating temperature of each of said at least two cigarette heating segments separately based on the second temperature change curve, if the temperature range of the second temperature change curve is not entirely within a predetermined range; and repeating the step of inputting each adjustable heating temperature into the neural convolutional network model until the temperature range of the second temperature change curve is entirely within a predetermined range.

[0048] In an embodiment, the device further includes:

- a recording module configured to record each adjustable heating temperature when a shutdown of the vaping kit is detected; and

- a trigger module configured to regulate the heating temperature in the vaping kit based on each adjustable heating temperature in the event that the vaping kit is restarted.

[0049] In an embodiment, the device further includes:

- a collection module configured to collect user vaping habit data, wherein the user vaping habit data includes a vaping interval and a vaping gas volume each time; and

- an optimization module configured to optimize the neural convolutional network model based on user vaping habit data to re-calculate each adjustable heating temperature.

[0050] In an embodiment, the device further includes:

- a continuous collection module configured to continuously collect user vaping habit data so as to form a complete vaping habit curve for the user; and

- a first dynamic regulation module configured to dynamically regulate each adjustable heating temperature based on each vaping node in the complete vaping habit curve of the user when the vaping kit is started next time.

[0051] In an embodiment, the device further includes:

- an integration module configured to generate, after at least three complete vaping habit curves for the user are generated, a standard complete vaping habit curve by integrating the at least three complete vaping habit curves for the user; and

- a second dynamic regulation module configured to dynamically regulate each adjustable heating temperature based on each vaping node in a standard full vaping habit curve when the vaping kit is started next time.

[0052] Those skilled in the art may clearly understand that the technical solutions of the embodiments of the present disclosure may be implemented by software and/or hardware. "Block" and "module" in this specification mean software and/or hardware that can independently completely execute or interact with other components to completely execute specific functions, where the hardware may, for example, be a field programmable gate array (FPGA), an integrated circuit (IC), etc.

[0053] Each block and/or processing module in an embodiment of the present disclosure may be implemented by analog circuitry to implement the functions described in the embodiments of the present disclosure, or may be implemented by software to perform the functions described in the embodiments of the present disclosure.

[0054] Refer to Fig. 3, which is a schematic block diagram of an electronic device according to an embodiment of the present disclosure. The device may be used to implement the method in the embodiment shown in Fig. 1. As shown in Fig. 3, the electronic device 300 may include: at least one central processor 301, at least one network interface 304, a user interface 303, a memory 305, and at least one communication bus 302.

[0055] The communication bus 302 is used to implement connection and communication between modules.

[0056] The user interface 303 may include a display screen (display) and a camera (camera), and optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0057] Optionally, the network interface 304 may include a standard wired interface and a wireless interface (such as a Wi-Fi interface).

[0058] The central processor 301 may include one or more processing cores. The central processor 301 uses various interfaces and lines to connect various parts in the electronic device 300, and performs various functions of the terminal 300 and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 305, and calling up data stored in the memory 305. Optionally, the central processor 301 may be implemented by at least one hardware method selected from digital signal processing (digital signal processing, DSP), a field programmable gate array (field programmable gate array, FPGA) and a programmable logic array (programmable logic array, PLA). The central processing unit 301 may integrate one or a combination of a central processing unit (CPU), a graphic central processing unit (GPU), a modem, etc. The CPU mainly processes an operating system, a user interface, and application programs, etc.; the GPU is used to prepare by rendering and draw content to be displayed on a display screen; the modem is used to process wireless communication. It can be understood that the above-mentioned modem may not be integrated into the central processing unit 301 and may be realized by a single chip.

[0059] The memory 305 may include a random access memory (RAM) or may include a read-only memory (ROM). Optionally, the memory 305 includes a non-volatile computer-readable storage medium (non-volatile computer-readable storage medium). The memory 305 may be used to store an instruction, a program, a code, a code set, or a set of instructions. The memory 305 may include a program storage area and a data storage area, where the program storage area may store instructions for implementing an operating system, instructions for at least one function (for example, a touch function, a sound reproduction function, an image reproduction function, etc.) and for implementing instructions in the method of the above-mentioned embodiments; the data storage area may store data, etc., provided in the method of the embodiments described above. Optionally, the memory device 305 may alternatively be at least one data storage device located separately from the above-mentioned central processor 301. As shown in Fig. 3, the memory device 305 as a computer data storage medium may include an operating system, a network communication module, a user interface module and program instructions.

[0060] In the electronic device 300 shown in Fig. 3, the user interface 303 is mainly used to provide the user with an input interface for receiving user input; and the central processor 301 can be used to activate the application program for controlling the temperature of the fragmentary heating for the vaping kit, which is stored in the memory 305, to perform the following operations:

- obtaining parameter information of a vaping kit and obtaining at least two cigarette heating segments based on the parameter information of the vaping kit;

- determining an initial heating temperature of the vaping kit and constructing a neural convolutional network model based on the initial heating temperature of the vaping kit to calculate a first temperature change curve of each of said at least two cigarette heating segments under predetermined vaping conditions; and

- adjusting the initial heating temperature corresponding to each of at least one of the cigarette heating segments separately on the basis of the first temperature change curve in order to obtain each adjustable heating temperature, wherein the temperature range of the second temperature change curve corresponding to each adjustable heating temperature is within a predetermined range.

[0061] A computer-readable storage medium is also provided according to the present disclosure. The computer-readable storage medium stores a computer program, wherein the computer program, when executed in a processor, implements the steps in the method described above. The computer-readable storage medium may include, but is not limited to, any type of disk, including a floppy disk, an optical disk, a DVD, a CD-ROM, a Microdrive, a magneto-optical disk, ROM, RAM, EPROM, EEPROM, DRAM, VRAM, a flash memory device, a magnetic or optical card, a nanosystem (including an IC on a molecular memory device), or any type of medium or device suitable for storing instructions and/or data.

[0062] It should be noted that for the above method for embodiments, for ease of description, they are expressed as a sequence of combinations of actions, but those skilled in the art should know that the present disclosure is not limited by the described sequence of actions. Depending on the present disclosure, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also know that the embodiments given in the description of the invention are some preferred embodiments, and the provided actions and modules are not necessarily required by the present disclosure.

[0063] In the above embodiments, the descriptions of each embodiment have their own emphasis, and for parts not described in detail in a particular embodiment, reference should be made to the relevant descriptions of other embodiments.

[0064] In several embodiments provided in the present disclosure, it should be understood that the disclosed device can be implemented in other ways. For example, the embodiments of the device described above are illustrative only. For example, the separation of the blocks is only a separation by logical functions. In an actual implementation, other methods of separation can be provided. For example, several blocks or components can be combined or integrated into another system, or some features can be ignored or not implemented. Additionally, the shown or explained mutual communication or direct communication or communication connection can be carried out through some service interfaces, and indirect communication or communication connection of devices or blocks can be carried out in electrical or other forms.

[0065] Blocks described as separate components may or may not be physically separate, and components shown as blocks may or may not represent physical blocks, i.e., they may be located in one place or may be distributed across several network blocks. Some or all of the blocks may be selected according to actual need to achieve the solution objective of the embodiments.

[0066] In addition, each functional block in each embodiment of the present disclosure may be integrated into one processing block, each block may exist separately physically, or two or more blocks may be integrated into one block. The above-mentioned integrated blocks may be implemented in the form of hardware or in the form of software functional blocks.

[0067] If the integrated block is implemented in the form of a software functional block and sold or used as an independent product, it can be stored in a computer-readable memory device. Based on this understanding, in the present disclosure, a basic or supporting part for the conventional technology of the technical solution or all or a part of the technical solution can be implemented in the form of a software product, and the computer program product is stored in the memory device. Several instructions are included in the computer program product to allow a computer device (may be a personal computer, a server or a network device, etc.) to perform all or some of the steps of the methods described in various embodiments of the present disclosure. The above-mentioned memory device includes: various media capable of storing program codes, such as a U disk, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk.

[0068] Those skilled in the art may understand that all or some of the steps in the various methods of the above-described embodiments may be completely performed by a program instructing the associated hardware. The program may be stored in a computer-readable memory device, and the memory device may include: a flash memory disk, a read-only memory device (ROM), a random access memory device (RAM), a magnetic disk, or an optical disk, etc.

[0069] The above are merely some exemplary embodiments of the present disclosure and are not intended to limit the scope of the present disclosure. That is, all equivalent changes and modifications made in accordance with the teachings of the present disclosure still fall within the scope of the present disclosure. Embodiments of the present disclosure will become apparent to those skilled in the art upon examination of the specification and practice of the disclosure herein. This application is intended to cover any modification, use or adaptation of the present disclosure, and these modifications, uses or adaptations adhere to the general principles of the present disclosure and include common knowledge or conventional techniques in the art not described in the present disclosure. The specifications and embodiments are to be considered exemplary only, and the scope and spirit of the present disclosure are defined by the claims.

Claims (42)

1. A method for controlling a fragmentary heating temperature for a vaping kit, comprising the steps of: obtaining parameter information of the vaping kit and obtaining at least two cigarette heating segments based on the parameter information of the vaping kit; determining an initial heating temperature of the vaping kit and constructing a neural convolutional network model based on the initial heating temperature of the vaping kit to calculate a first temperature change curve of each of at least two cigarette heating segments under preset vaping conditions; wherein the first temperature change curve is a temperature curve corresponding to a heating process in which the vaping kit is uniformly heated from an initial heating temperature; wherein the vaping conditions are environmental conditions when the vaping kit is vaping, and said vaping conditions comprise a vaping intensity and a vaping interval, and adjusting the initial heating temperature corresponding to each of said at least two cigarette heating segments separately on the basis of the first temperature change curve in order to obtain each adjustable heating temperature, inputting each adjustable heating temperature into a neural convolutional network model to calculate a second temperature change curve of each of the at least two cigarette heating segments under predetermined vaping conditions, wherein the temperature range of the second temperature change curve corresponding to each adjustable heating temperature is within a preset range, wherein said obtaining of vaping kit parameter information and obtaining of at least two cigarette heating segments based on the vaping kit parameter information comprises the steps of: obtaining parameter information of a vaping kit, wherein the parameter information of the vaping kit comprises a depth of a groove for inserting a cigarette and a radius of a groove for inserting a cigarette; determining the optimum heating distance based on the depth and radius of the cigarette insertion groove; and said at least two cigarette heating segments are obtained based on the optimal heating distance. 2. The method according to claim 1, wherein said adjusting the initial heating temperature of each of said at least two cigarette heating segments separately based on the first temperature change curve in order to obtain each adjustable heating temperature, wherein the temperature range of the second temperature change curve corresponding to said each adjustable heating temperature is within a predetermined range, comprises the steps of: adjusting the initial heating temperature of each of said at least two cigarette heating segments separately based on the first temperature change curve to obtain each adjustable heating temperature; inputting each adjustable heating temperature into a neural convolutional network model to calculate a second temperature change curve of each of said at least two cigarette heating segments under preset vaping conditions; adjusting each adjustable heating temperature of each of said at least two cigarette heating segments separately based on the second temperature change curve, in case the temperature range of the second temperature change curve is not entirely within a predetermined range; and repeating the step of inputting each adjustable heating temperature into the neural convolutional network model until the temperature range of the second temperature change curve is completely within the preset range. 3. The method according to item 1, additionally comprising the steps of: record each adjustable heating temperature when a shutdown of the vaping kit is detected; and adjust the heating temperature of the vaping kit based on each adjustable heating temperature in case the vaping kit is restarted. 4. The method according to item 1, further comprising the steps of: collect user vaping habit data, wherein the user vaping habit data includes the vaping interval and the vaping volume of gas each time; and optimize the neural convolutional network model based on user vaping habit data to re-calculate each adjustable heating temperature. 5. The method according to item 4, further comprising the steps of: continuously collect user vaping habit data to form a complete vaping habit curve for the user; and adjust each adjustable heating temperature dynamically based on each vaping node in the user's complete vaping habit curve when the vaping kit is started next time. 6. The method according to paragraph 5, further comprising the steps of: forming, after at least three complete vaping habit curves for the user are formed, a standard complete vaping habit curve by integrating the at least three complete vaping habit curves for the user; and Adjust each adjustable heating temperature dynamically based on each vaping node in the standard full vaping habit curve when the vaping kit is started next time. 7. A fragmentary heating temperature control device for a vaping kit, comprising: a receiving module configured to receive parameter information of the vaping kit and to receive at least two cigarette heating segments based on the parameter information of the vaping kit; a determining module configured to determine an initial heating temperature of the vaping kit and to construct a neural convolutional network model based on the initial heating temperature of the vaping kit to calculate a first temperature change curve of each of said at least two cigarette heating segments under predetermined vaping conditions, wherein the first temperature change curve is a temperature curve corresponding to a heating process in which the vaping kit is uniformly heated from an initial heating temperature; wherein the vaping conditions are environmental conditions when the vaping kit is vaping, and said vaping conditions comprise a vaping intensity and a vaping interval; and a control module configured to control an initial heating temperature of each of said at least two cigarette heating segments separately based on a first temperature change curve to obtain each adjustable heating temperature, input each adjustable heating temperature into a neural convolutional network model to calculate a second temperature change curve of each of the at least two cigarette heating segments under preset vaping conditions, wherein the temperature range of the second temperature change curve corresponding to each adjustable heating temperature is within a preset range, where the receiving module contains: - a receiving unit configured to receive information about the parameters of a vaping kit, wherein the information about the parameters of a vaping kit includes the depth of the groove for inserting a cigarette and the radius of the groove for inserting a cigarette; - a unit for determining the optimal heating distance, configured to determine the optimal heating distance based on the depth and radius of the groove for inserting a cigarette; - a heating segment obtaining unit configured to obtain at least two cigarette heating segments based on the optimal heating distance. 8. An electronic device for controlling the temperature of fragmentary heating for a vaping kit, comprising: memory; processor; and a computer program stored in a storage device and executed by a processor; wherein the processor, when executing the computer program, performs the steps in the method according to any of paragraphs 1-6. 9. A machine-readable data storage medium for controlling the temperature of a fragmentary heating for a vaping kit, storing a computer program, wherein the computer program, when executed in a processor, implements the steps in the method according to any of paragraphs. 1-6.