A beauty instrument using graphene electrothermal effect and control method

Abstract

The present invention relates to the field of graphene technology and discloses a beauty instrument and a control method using the graphene electrothermal effect. The method comprises: pre-activating a graphene electrothermal film to obtain negative temperature coefficient resistance characteristic parameters; performing contact state detection and multi-parameter analysis on a target area to obtain personalized temperature control parameters; performing PWM segmented power control on the graphene electrothermal film based on the personalized temperature control parameters and the negative temperature coefficient resistance characteristic parameters to obtain a staged heating temperature output strategy; performing real-time feedback adjustment based on the staged heating temperature output strategy to obtain a stable temperature control signal; performing progressive cooling power adjustment on the graphene electrothermal film according to the stable temperature control signal, and simultaneously confirming a safe stop state of the beauty instrument. The present invention utilizes the unique characteristic of graphene materials that resistance decreases when temperature increases, and has higher temperature control accuracy and response speed than traditional linear resistance materials.

Description

Technical Field

[0001] The present invention relates to the field of graphene technology, and in particular to a beauty instrument applying the electrothermal effect of graphene and a control method thereof. Background Art

[0002] Traditional electrothermal beauty devices mostly use metal wire or ceramic materials as heating elements, which stimulate the regeneration of skin collagen through the thermal effect, thereby improving skin sagging and fine lines.

[0003] However, existing electrothermal beauty devices still have many technical deficiencies in practical applications. The resistance-temperature relationship of traditional electrothermal materials varies linearly, making precise temperature control difficult to achieve. This can easily lead to local overheating or uneven temperatures, which can affect the effectiveness of treatments and potentially cause skin discomfort. Existing devices often use single-point contact detection, which is unable to accurately identify multi-dimensional information such as contact area and pressure distribution. This results in a lack of personalized temperature control strategies, making it difficult to adapt to the skin characteristics of different users. Furthermore, traditional devices often use simple on-off modes or linear voltage regulation for temperature control, lacking intelligent feedback mechanisms and unable to dynamically optimize based on real-time temperature changes. Summary of the Invention

[0004] The present invention provides a beauty instrument and control method that utilizes the graphene electrothermal effect. The present invention utilizes the unique characteristic of graphene materials that their resistance decreases when their temperature increases. Compared with traditional linear resistor materials, the present invention has higher temperature control accuracy and response speed, thereby improving the safety and comfort of the use process.

[0005] A first aspect of the present invention provides a method for controlling a beauty instrument using the graphene electrothermal effect, the method comprising:

[0006] Pre-activate the graphene electric heating film to obtain the negative temperature coefficient resistance characteristic parameters;

[0007] Conduct contact status detection and multi-parameter analysis on the target area to obtain personalized temperature control parameters;

[0008] Based on the personalized temperature control parameters and the negative temperature coefficient resistance characteristic parameters, PWM segmented power control is performed on the graphene electric heating film to obtain a staged heating temperature output strategy;

[0009] Perform real-time feedback adjustment based on the staged heating temperature output strategy to obtain a stable temperature control signal;

[0010] The graphene electric heating film is gradually cooled and the power is adjusted according to the stable temperature control signal, and the safe stop state of the beauty instrument is confirmed at the same time.

[0011] In combination with the first aspect, in a first implementation of the first aspect of the present invention, the pre-activation of the graphene electric heating film to obtain the negative temperature coefficient resistance characteristic parameter includes:

[0012] Applying an excitation voltage pulse signal within a preset voltage range to the graphene electric heating film and collecting stable conductivity state data;

[0013] Performing real-time resistance change monitoring on the stable conductivity state data to obtain a dynamic resistance value sequence of the graphene heating film during the pre-activation process;

[0014] Performing resistance temperature characteristic curve modeling based on the dynamic resistance value sequence and corresponding temperature data to obtain a negative temperature coefficient resistance model;

[0015] Parameters are extracted based on the negative temperature coefficient resistor model to obtain negative temperature coefficient resistor characteristic parameters including a reference resistance value, a temperature coefficient, and a response time constant.

[0016] In combination with the first aspect, in a second implementation of the first aspect of the present invention, performing contact state detection and multi-parameter analysis on the target area to obtain personalized temperature control parameters includes:

[0017] Based on the capacitance change of each sensing electrode in the multi-point capacitive sensing electrode array, the target area is monitored in real time to obtain the capacitance change data of each sensing electrode;

[0018] Performing effective contact determination based on the capacitance change data of each sensing electrode and a preset capacitance threshold to obtain effective contact electrode distribution information;

[0019] Calculating contact parameters based on capacitance differences between different sensing electrodes in the effective contact electrode distribution information to obtain contact area distribution data and contact pressure distribution data;

[0020] A multi-parameter analysis is performed on the target area according to the contact area distribution data and the contact pressure distribution data to obtain personalized temperature control parameters.

[0021] In combination with the first aspect, in a third implementation of the first aspect of the present invention, performing a multi-parameter analysis on the target area based on the contact area distribution data and the contact pressure distribution data to obtain personalized temperature control parameters includes:

[0022] Performing regional characteristic detection on the target area based on the contact area distribution data and the contact pressure distribution data to obtain multi-dimensional regional characteristic data;

[0023] Performing type classification based on the multi-dimensional regional characteristic data to obtain a regional type recognition result;

[0024] querying a personalized temperature control database based on the area type identification result to obtain basic temperature control parameters;

[0025] Temperature correction is performed according to the basic temperature control parameters and the contact area distribution data to obtain personalized temperature control parameters.

[0026] In combination with the first aspect, in a fourth implementation of the first aspect of the present invention, the graphene electric heating film is subjected to PWM segmented power control based on the personalized temperature control parameter and the negative temperature coefficient resistance characteristic parameter to obtain a staged heating temperature output strategy, including:

[0027] Calculating PWM basic control parameters according to the personalized temperature control parameters and the negative temperature coefficient resistance characteristic parameters, wherein the PWM basic control parameters include a control frequency and a duty cycle adjustment range;

[0028] Based on the PWM basic control parameters, the duty cycles of the preheating stage, the stable heating stage and the heat preservation stage are set in sections to obtain the PWM duty cycle control sequence corresponding to each heating stage;

[0029] Establishing a nonlinear response relationship between power and temperature of the graphene electric heating film according to the negative temperature coefficient resistance characteristic parameters, and obtaining power-temperature response relationship data;

[0030] Based on the PWM duty cycle control sequence and the power-temperature response relationship data, a staged temperature output strategy analysis is performed on the graphene electric heating film to obtain a staged heating temperature output strategy.

[0031] In combination with the first aspect, in a fifth implementation of the first aspect of the present invention, establishing a nonlinear response relationship between power and temperature of the graphene electric heating film according to the negative temperature coefficient resistance characteristic parameters to obtain power-temperature response relationship data includes:

[0032] Based on the reference resistance value and temperature coefficient in the negative temperature coefficient resistance characteristic parameter, the resistance change law of the graphene electric heating film in different temperature ranges is analyzed to obtain temperature range resistance change curve data;

[0033] Performing a resistance-temperature reverse mapping relationship analysis based on the resistance change curve data in the temperature range to obtain a temperature calculation model that reversely infers the temperature through the resistance value;

[0034] Perform real-time power calculation based on the temperature calculation model to obtain a power output value sequence corresponding to different temperature intervals;

[0035] Nonlinear fitting is performed based on the power output numerical sequence to obtain power-temperature response relationship data of the nonlinear response relationship between power and temperature of the graphene electric heating film.

[0036] In combination with the first aspect, in a sixth implementation of the first aspect of the present invention, performing real-time feedback adjustment based on the staged heating temperature output strategy to obtain a stable temperature control signal includes:

[0037] Based on a multi-level temperature monitoring system, the temperature of the graphene heating film itself, the contact surface temperature of the target area and the ambient temperature are synchronously collected to obtain multi-channel temperature feedback data;

[0038] Perform multi-sensor data fusion based on the multi-channel temperature feedback data to obtain fused temperature monitoring data;

[0039] Performing PID control based on the fusion temperature monitoring data and the target temperature in the staged heating temperature output strategy to obtain temperature deviation control parameters including proportional deviation, integral deviation and differential deviation;

[0040] The PWM control parameter of the graphene electric heating film is dynamically adjusted according to the temperature deviation control parameter to obtain a stable temperature control signal.

[0041] In combination with the first aspect, in a seventh implementation of the first aspect of the present invention, the step of gradually adjusting the temperature of the graphene electric heating film according to the stable temperature control signal and confirming the safe stop state of the beauty instrument includes:

[0042] Performing an end timing judgment on the temperature change trend and usage time of the target area based on the stable temperature control signal to obtain end timing judgment data;

[0043] Performing a progressive PWM duty cycle reduction control on the graphene electric heating film according to the end timing judgment data to obtain a PWM reduction control sequence;

[0044] Perform multiple safety protection status detection based on the PWM decrement control sequence to obtain safety status monitoring data including temperature overheat protection, contact abnormality protection and time limit protection;

[0045] The stop state is confirmed based on the safety state monitoring data and the condition that the temperature of the target area returns to the ambient temperature range to obtain the safety stop state of the beauty instrument.

[0046] In combination with the first aspect, in an eighth implementation of the first aspect of the present invention, the graphene electric heating film is subjected to progressive PWM duty cycle decreasing control according to the end timing judgment data to obtain a PWM decreasing control sequence, including:

[0047] Determining an initial PWM duty cycle based on the temperature stability evaluation index in the end timing judgment data to obtain an initial PWM duty cycle value and a target cooling rate parameter for progressive cooling;

[0048] Calculating the decreasing interval time and decreasing amplitude according to the initial PWM duty cycle value and the target cooling rate parameter to obtain a PWM decreasing control strategy including a time interval and a decreasing percentage;

[0049] Generating a duty cycle decreasing timing sequence based on the PWM decreasing control strategy to obtain PWM timing decreasing data that gradually reduces the duty cycle value according to a preset time interval;

[0050] The total duration of the cooling process and the termination condition are set according to the PWM timing decrement data to obtain a PWM decrement control sequence.

[0051] A second aspect of the present invention provides a beauty instrument using the graphene electrothermal effect, the beauty instrument using the graphene electrothermal effect comprising:

[0052] A pre-activation module is used to pre-activate the graphene electric heating film to obtain negative temperature coefficient resistance characteristic parameters;

[0053] The contact state detection module is used to perform contact state detection and multi-parameter analysis on the target area to obtain personalized temperature control parameters;

[0054] A power control module, configured to perform PWM segmented power control on the graphene electric heating film based on the personalized temperature control parameter and the negative temperature coefficient resistance characteristic parameter, to obtain a staged heating temperature output strategy;

[0055] A real-time feedback adjustment module is used to perform real-time feedback adjustment based on the staged heating temperature output strategy to obtain a stable temperature control signal;

[0056] The cooling power adjustment module is used to gradually adjust the cooling power of the graphene electric heating film according to the stable temperature control signal, and at the same time confirm the safe stop state of the beauty instrument.

[0057] Compared to existing technologies, the present invention offers the following advantages: By establishing the negative temperature coefficient resistance characteristic parameters of graphene heating films and leveraging the unique property of graphene materials—their resistance decreases as temperature rises—this method achieves precise temperature control by real-time monitoring of resistance changes and inferring temperature. This method offers higher temperature control accuracy and response speed than traditional linear resistor materials. The use of a multi-point distributed capacitance sensing electrode array simultaneously detects multiple dimensions, including contact area, pressure distribution, and contact angle. Compared to existing single-point contact detection technologies, this significantly improves the accuracy and comprehensiveness of contact state identification, providing a reliable data foundation for subsequent personalized control. By performing multi-parameter analysis of the target area and establishing a personalized temperature control database based on contact characteristics, the system automatically adjusts temperature parameters based on different skin types and characteristics, achieving a technological leap from traditional fixed temperature control to intelligent personalized control. Pulse-width modulation technology is employed to implement segmented power control of the graphene heating films. Through refined management of the preheating, steady-state heating, and insulation phases, the system leverages the advantages of graphene materials for rapid heating and precise temperature control, achieving higher energy efficiency and control accuracy than traditional linear voltage regulation methods. A multi-level temperature monitoring system, utilizing multi-sensor data fusion and PID control algorithms, enables real-time monitoring and dynamic adjustment of the temperature control process, effectively avoiding the temperature fluctuations associated with traditional on-off control modes and ensuring temperature stability during the treatment process. Intelligent end-of-life timing determination and PWM duty cycle reduction control enable a smooth transition from treatment temperature to ambient temperature, avoiding the discomfort caused by the sudden cessation of heating in traditional devices. Multiple integrated safety protection mechanisms significantly enhance safety and comfort during use. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0059] The structures, proportions, sizes, etc. depicted in the drawings of this specification are only used to match the contents disclosed in the specification so as to facilitate understanding and reading by persons familiar with this technology. They are not intended to limit the conditions under which the present invention can be implemented and therefore have no substantive technical significance. Any structural modifications, changes in proportional relationships, or adjustments in size should still fall within the scope of the technical contents disclosed in the present invention without affecting the effects and objectives that can be achieved by the present invention.

[0060] Figure 11 is a flow chart of a method for controlling a beauty instrument using the graphene electrothermal effect, provided by an embodiment of the present invention;

[0061] Figure 2 This is a schematic block diagram of the structure of a beauty instrument using the graphene electrothermal effect provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0062] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0063] The flowcharts shown in the accompanying drawings are for illustrative purposes only and do not necessarily include all contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may be decomposed, combined, or partially merged, so the actual execution order may vary depending on the actual situation.

[0064] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the present invention. As used in the specification and appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms unless the context clearly indicates otherwise.

[0065] It should be further understood that the term "and / or" used in the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations. Figure 1 In one embodiment of the present invention, a method for controlling a beauty device using the graphene electrothermal effect includes:

[0066] Step 100: pre-activate the graphene electric heating film to obtain negative temperature coefficient resistance characteristic parameters;

[0067] It is understood that the execution subject of the present invention can be a beauty device that uses the graphene electrothermal effect, or a terminal or a server, and the specific implementation is not limited here. The embodiment of the present invention is described by taking the server as the execution subject as an example.

[0068] Specifically, a set of excitation voltage pulses within a preset voltage range (0.5V to 1.2V) is applied to the graphene heating film, with a pulse frequency set between 50Hz and 100Hz and a duration of 3 to 5 seconds. This ensures that during the excitation process, the carbon lattice structure within the graphene material gradually approaches a stable conductivity state. In this state, the graphene material exhibits significant carrier mobility enhancement, manifested by a gradual approach of resistance to a dynamic equilibrium range. To capture the microscopic conductivity changes during this process, an integrated high-precision resistance detection circuit is simultaneously activated to monitor the resistance changes of the graphene heating film in real time during the excitation period. This complete conductivity conversion trajectory is captured, resulting in a dynamic resistance sequence over time. This dynamic resistance sequence is synchronously collected with ambient temperature data, and the two are jointly analyzed based on their correspondence to establish a resistance-temperature relationship model for the graphene heating film during the pre-activation process. During the modeling process, the negative temperature coefficient (NTC) characteristic of graphene materials was taken into account. Within the typical skin care temperature range of 25°C to 65°C, increasing temperature leads to a significant decrease in the material's resistance. This nonlinear behavior differs fundamentally from the positive temperature coefficient (PTC) behavior of traditional metal or ceramic heating elements. Therefore, modeling techniques such as multi-segment fitting or nonlinear least squares regression were employed to correlate the dynamic resistance value sequence with synchronized temperature data, generating a resistance-temperature characteristic curve that accurately reflects the physical response characteristics of the graphene material. This curve was then encapsulated into a NTC resistor model. Through mathematical analysis and statistical regression analysis of this model, several key parameters were extracted, including the graphene material's baseline resistance value (R0) in its unheated state, the resistance change rate per unit temperature change (i.e., the temperature coefficient α), and the response time constant τ, a quantitative indicator of the time required for the system to respond to steady-state conditions. Ultimately, these parameters yielded the NTC resistor characteristic parameters.

[0069] Step 200: Perform contact state detection and multi-parameter analysis on the target area to obtain personalized temperature control parameters;

[0070] Specifically, it is based on a multi-point capacitive sensing electrode array deployed on the surface of the beauty instrument head. The array adopts a 3×3 or 4×4 grid structure. Each electrode is made of copper foil with a thickness of 0.1mm-0.2mm and a unit area of ​​2mm. 2 Up to 4mm 2The sensors are precisely spaced at intervals of 5mm-8mm. When the beauty device comes into contact with human skin, the dielectric properties of human tissue cause the capacitance sensed by each sensing electrode to change. Therefore, the device collects capacitance change data from each sensing electrode in real time during contact and continuously feeds it into a high-speed sampling capacitance detection circuit. This circuit boasts a detection accuracy of 0.1pF, enabling it to capture subtle contact changes. The raw capacitance change data is then compared point by point with a set capacitance change threshold, which is set between 0.5pF and 1.0pF. When the capacitance increment for a particular electrode exceeds this range, it is considered to have made effective skin contact. This mechanism allows the system to quickly identify which electrodes are currently in effective contact, generating a two-dimensional spatial distribution map of multiple effective contact points—the effective contact electrode distribution information. Based on this distribution information, the capacitance differences between the electrodes are analyzed. These differences reflect subtle height differences and pressure distribution characteristics across the contact surface. A contact parameter model is constructed using multi-electrode comparison calculations, combined with the gradient trend of capacitance changes. Two key variables are derived: contact area distribution data and contact pressure distribution data. Among them, the size of the contact area is obtained by multiplying the number of effective electrodes by the unit electrode area, and the contact pressure is calculated based on the spatial gradient of the capacitance change amplitude of each electrode. The larger the capacitance value, the stronger the pressing force. Multi-parameter analysis of the target area is performed based on the contact area distribution data and the contact pressure distribution data. By comprehensively evaluating the continuity, uniformity and stability of the contact area and the center of pressure distribution, it is determined whether the contact is good, and based on the relationship between the concentration of the pressure distribution and the sensitive area of ​​the skin, it is determined whether the heating power needs to be locally adjusted. At this time, the system calls the personalized temperature regulation model associated with the contact area and pressure characteristics, and dynamically sets the core temperature control parameters such as the upper temperature limit, heating rate, and insulation time based on the existing user data and the default skin characteristic data, thereby outputting personalized temperature control parameters suitable for the current skin contact state.

[0071] The target area is tested for regional characteristics based on contact area distribution data and contact pressure distribution data. The target contact area is divided into multiple local sub-areas, each covered by several capacitive sensing electrodes. Local characteristic indicators are calculated based on the sensing intensity and pressure gradient information of the electrodes within each sub-area. Specifically, the system evaluates each sub-area's area integrity, pressure uniformity, edge contact stability, and central pressure peak location. This generates a multi-dimensional regional characteristic dataset that reflects the geometric composition of the contact state and demonstrates the dynamic stability and physical morphology of the skin contact surface. Feature engineering and cluster analysis are performed on this multi-dimensional regional characteristic data, combined with a machine learning-trained regional classification model. Each sub-area is identified and labeled to determine which standard regional type it belongs to, such as "high-pressure concentrated type," "widely uniform type," "edge sliding type," or "low-pressure unstable type." This classification not only reflects the current physical morphology of the skin-instrument contact pattern but also implies the skin's heat tolerance, sensitivity, and appropriate heat load level in that area. Through this classification and recognition mechanism, physical characteristics are effectively mapped to temperature control behavior, resulting in a clear regional type identification result. After identifying the target zone type, the system calls upon a built-in personalized temperature control database. This database pre-establishes a mapping between different zone types and basic temperature control parameters based on skin type, zone contact pattern, and clinical thermal response data. These basic temperature control parameters include key control variables such as the target temperature range (e.g., 38°C-42°C), heating rate (e.g., 1°C / minute), and hold time. Once the system retrieves the temperature control parameters matching the current zone type through query, it applies a temperature correction to these parameters based on the actual contact area data to improve temperature control accuracy. This correction algorithm adjusts based on the correlation between contact area and temperature transfer efficiency. For example, if the actual contact area is significantly smaller than the zone standard, the initial heating rate and target temperature upper limit are reduced to avoid heat concentration or skin irritation caused by insufficient contact. Conversely, if sufficient contact area and even pressure distribution are detected, the target temperature level is appropriately increased and the hold time is extended to enhance thermal penetration and treatment effectiveness. This results in personalized temperature control parameters.

[0072] Step 300: performing PWM segmented power control on the graphene electric heating film based on the personalized temperature control parameter and the negative temperature coefficient resistance characteristic parameter to obtain a staged heating temperature output strategy;

[0073] Specifically, personalized temperature control parameters are integrated with the negative temperature coefficient resistance characteristic parameters extracted from the graphene material during the pre-activation phase to establish a basic PWM control framework that responds to skin differences and material nonlinear behavior. In this process, the temperature control parameters set for the target area, including the target temperature value, heating rate, and insulation duration, are combined with the resistance change curve, temperature coefficient, and response time constant of the graphene heating film to derive matching basic PWM control parameters, mainly including the control frequency and duty cycle adjustment range. To ensure a balance between adjustment accuracy and response speed, the control frequency is set between 1kHz and 5kHz, and the duty cycle range is between 10% and 90%, forming a heating power control domain with adjustable resolution. Based on the basic PWM control parameters, the heating process is divided into three stages according to the personalized temperature control curve: preheating, stable heating, and insulation. Duty cycle ranges are set accordingly to the heat demand of each stage. The preheating stage requires that the temperature of the graphene heating film be quickly raised to approximately 80% of the target temperature. At this time, the duty cycle should be set in the high-energy zone of 70%-90%. After entering the stable heating stage, to avoid the risk of thermal burns caused by excessively rapid temperature surges, the duty cycle is reduced to the intermediate range of 40%-60%, allowing the temperature to slowly approach the target value. In the insulation stage, the duty cycle is reduced to 20%-40%, forming a platform area for dynamic temperature maintenance, ensuring that temperature fluctuations are controlled within ±0.5°C, thereby improving thermal comfort and consistency of care. The PWM duty cycle control sequence of each stage needs to be dynamically recursively combined with a time-stepping algorithm to ensure that the entire heating process is both in line with physiological thermal adaptability and has stable heat output characteristics. After the staged PWM control logic is set, the nonlinear response relationship between power and temperature of the graphene heating film is established based on the pre-extracted negative temperature coefficient resistance characteristic parameters. This response relationship comprehensively considers the resistance variation of graphene across different temperature zones. Specifically, as temperature rises, its resistance gradually decreases, resulting in an increase in current under a constant voltage input, creating a nonlinear effect of increasing power. Therefore, by combining the resistance-temperature model with the voltage-current relationship, a power-temperature response data table is generated, containing the actual temperature output at different input powers. Based on the PWM duty cycle control sequence and the power-temperature response data, a staged temperature output strategy for the graphene heating film is analyzed. The power output is dynamically adjusted according to the duty cycle set for each stage, and the temperature curves of the graphene heating film surface and the skin contact area under the current power are calculated in real time. If the temperature rise rate falls below the set personalized heating rate, the system temporarily increases the duty cycle within a safe range to compensate. Conversely, if the temperature rise trend is too rapid, the duty cycle period is shortened to quickly suppress it, ensuring that the temperature output at each stage closely matches the personalized control target. Finally, a staged heating temperature output strategy is generated, describing the required PWM duty cycle, corresponding duration, predicted temperature curve, and adjustment rules for each stage.

[0074] Based on the negative temperature coefficient resistance parameters of the graphene heating film, specifically the two core variables, the base resistance value and the temperature coefficient, the full range of graphene resistance variation with temperature within the target temperature control range is modeled, generating a temperature range resistance curve. This curve reflects the fundamental physical law that the resistance of graphene materials decreases nonlinearly with increasing temperature, with varying rates of change in different temperature zones: a more pronounced resistance drop at lower temperatures and a more gradual change near the target temperature limit. Based on these temperature range resistance curves, a resistance-temperature inverse mapping model is performed. Given the actual resistance value of the graphene heating film at any given moment, the corresponding temperature value of the current film surface can be inferred. To maximize the accuracy of this mapping, a temperature calculation model with high fitting accuracy and strong robustness to input perturbations is constructed. The inverse functional relationship between resistance and temperature is quantified using methods such as polynomial regression, piecewise exponential fitting, or spline interpolation. This model is then integrated into the temperature monitoring and feedback control module to achieve real-time temperature estimation. This model allows the system to identify the current heating temperature zone in real time based solely on resistance measurements, even in the absence of direct temperature sensors. This provides immediate basis for adjusting the control strategy's response. Based on a stable and reliable temperature estimation model, Ohm's law and the power formula are used to calculate the actual power output of the graphene heating film at each temperature range. Specifically, the power output level during the current heating phase is calculated by collecting the applied voltage and measured resistance values. Because the resistance of the graphene heating film changes significantly with temperature, its power output exhibits a strong temperature dependence under a fixed voltage, reflecting the material's nonlinear thermal response. By continuously calculating power values ​​at multiple temperature points and constructing a raw numerical sequence of the temperature-power relationship, the system depicts an asymmetric and non-uniform power increase with temperature. The response speed and power dissipation are particularly sensitive at the boundary between preheating and holding. This discrete power output sequence is fed into a fitting algorithm for nonlinear curve construction, resulting in a response function describing the graphene heating film's power-temperature relationship, or power-temperature response data.

[0075] Step 400: Perform real-time feedback adjustment based on the staged heating temperature output strategy to obtain a stable temperature control signal;

[0076] Specifically, during the actual operation of the beauty instrument, a multi-level temperature monitoring system is used to simultaneously collect three key temperature information: the temperature of the graphene heating film itself, the temperature of the target area's skin contact surface, and the current ambient temperature. The temperature of the graphene film itself is acquired through a high-sensitivity platinum resistance sensor integrated inside the film, with a response time of less than 0.1 seconds and an accuracy of ±0.2°C; the temperature of the skin contact surface is detected through a distributed NTC thermistor array, with each sensor covering 2cm 2 The spatial distribution characteristics of surface temperature are captured in the region. Ambient temperature is measured in real time by an independent external temperature sensor and used to perform environmental compensation correction to eliminate interference from external temperature fluctuations on system judgment. These multiple temperature signals are fed into the central control processing unit via high-sampling-rate channels to form a temperature feedback data set. Before entering the feedback control module, the temperature feedback data from multiple temperature sensors undergoes multi-sensor data fusion. A weighted average algorithm, combined with a time-window sliding mean and outlier rejection, smoothes out fluctuations caused by sensor contact quality, response speed, and noise interference, generating highly confident fused temperature monitoring data. The difference between the fused temperature monitoring data and the current target temperature in the staged heating temperature output strategy is calculated. Based on this difference, a PID control algorithm is executed to construct a temperature deviation control parameter set. In the PID calculation process, the proportional term represents the direct response strength of the current temperature deviation and is used to quickly adjust the power output direction. The integral term accumulates temperature difference history, corrects long-term drift, and prevents static error accumulation. The differential term reflects the temperature trend and provides predictive suppression of sudden or drastic temperature fluctuations to prevent overshoot or oscillation in the temperature control system. Specifically, the proportional, integral, and differential deviations calculated in real time are weighted and combined to form an immediate, comprehensive temperature control output coefficient. The PID parameters (such as Kp, Ki, and Kd) are dynamically modified based on the actual control objectives to adapt to the thermal response inertia characteristics of the graphene heating film and the upper limit of skin thermal sensitivity. After obtaining the temperature deviation control parameters, they are input into the PWM control module as adjustment commands, dynamically adjusting the PWM signal parameters of the graphene heating film. These key control factors include duty cycle, cycle frequency, and waveform smoothness. For example, if the temperature is low and the deviation value is increasing, the duty cycle is appropriately increased to enhance power output. However, if the temperature approaches the upper limit or shows a rapid upward trend, the PWM duty cycle is reduced, or even short intermittent pulses are used, to ensure a stable heating curve, thereby avoiding thermal shock and overheating risks. Through this closed-loop regulation mechanism, the final output is a highly stable, dynamically optimized, and real-time temperature control signal.

[0077] Step 500: gradually adjust the temperature of the graphene heating film according to the stable temperature control signal, and confirm the safe stop state of the beauty instrument.

[0078] Specifically, based on the current heating state reflected by the stable temperature control signal, the temperature change trend of the target area is continuously evaluated in both the time and numerical domains. By calculating the duration of the skin contact surface temperature within the stable range and the overall usage duration, and combining the slope and fluctuation range of the temperature change curve, it is determined whether the optimal end time of the treatment process has been reached. If the system detects that the target temperature has been maintained continuously and stably for more than a set time (e.g., 5 minutes) and the total usage duration is close to the upper limit (e.g., 15 to 20 minutes), it generates end time judgment data as a trigger condition for the cooling control logic. Based on this judgment result, a gradual duty cycle reduction strategy is implemented for the PWM control parameters of the graphene heating film. Specifically, the PWM duty cycle is gradually reduced by 10% or a fixed ratio within a preset time window (e.g., every 30 seconds). This gradually reduces the heating power in a non-abrupt manner, forming a temperature control curve with a smooth heat output decay. This PWM decrement control sequence ensures a gradual transition in the temperature gradient between the skin's surface and deeper layers, preventing the irritation of a sudden temperature drop caused by heating cessation. It also helps maintain the integrity of the microcirculatory heat diffusion process, providing a buffer for the permeation and absorption of thermal effects. Simultaneously, multiple safety protection status detection mechanisms are activated to monitor key safety indicators during the cooling process in real time, ensuring full protection during power reduction. Three key parameters are monitored: First, overheat protection: If any temperature monitoring point locally rises and exceeds the safety limit (e.g., 50°C), all PWM outputs are immediately interrupted and an overtemperature alarm is triggered. Second, contact anomaly protection: If the sensing electrodes detect unstable skin contact, such as a sudden change in pressure or a sharp decrease in contact area, the system deems it out of service and prematurely terminates the process. Third, time limit protection: If the actual heating time exceeds the maximum allowable value (e.g., 20 minutes), the system is forced to enter the shutdown phase regardless of the current temperature. These protection mechanisms collectively generate safety status monitoring data, which serves as a key constraint for determining whether to safely exit the power delivery process. At the end of the power reduction and safety monitoring phase, the actual temperature change in the target area is compared with the ambient temperature based on real-time temperature feedback data. When the skin surface temperature is detected to have dropped to within ±2°C of the ambient temperature and remains stable for a period of time (e.g., 30 to 60 seconds), the system determines that the temperature has basically returned to its natural state and the heat output effect has ended. This condition is then logically cross-validated with the previously generated safety status monitoring data. If all safety conditions are met, the beauty device is confirmed to have reached a safe stop state. Based on the confirmation result, all PWM output channels are shut down, and key data of the care process is recorded, including usage time, heating stability, contact quality score, and cooling process curve. The device then automatically enters standby mode.

[0079] By integrating the temporal stability indicator, fluctuation amplitude analysis results, and average calorific value trend curve from the temperature data, the system confirms that the current thermal stability plateau is in place. Based on this, the initial PWM duty cycle for progressive cooling is set, typically between 20% and 40%. Furthermore, a target cooling rate parameter is set, typically between 1°C per minute, based on the user's skin thermal sensitivity and the system's built-in physiological thermal buffer model. This ensures that the skin does not experience irritation due to sudden temperature changes. The decrement interval and decrement percentage are calculated based on the initial PWM duty cycle and the target cooling rate parameter. This process is modeled based on the thermal inertia response characteristics of the skin and the nonlinear power-temperature relationship of the graphene material, resulting in a control strategy that couples the time interval and decrement percentage. The time interval is set between 30 and 45 seconds, and the decrement percentage is set using a linear or exponential decay curve, for example, decreasing the duty cycle by 5% every 30 seconds or exponentially decaying from the initial value to the minimum power hold state. This approach establishes a PWM decrement control strategy in which the decrement percentage and interval at each stage are automatically adjusted based on the balance between heat release and the rate of change of the temperature response. Based on the aforementioned control strategy, a time-series decrementing PWM duty cycle data is generated, forming a PWM control signal sequence that continuously decreases over time. This sequence follows the aforementioned time and amplitude decrementing patterns. The feedback effect of the duty cycle changes on the actual temperature curve is monitored in real time to ensure that the skin surface temperature exhibits a corresponding downward trend after each reduction in amplitude, without temperature rebound or system lag. This sequential control logic is maintained in real time by a built-in time stepper and feedback correction module, enabling dynamic tracking and fine-tuning to ensure stable temperature control and user comfort throughout the cooling process. Based on the PWM decrementing data, a termination trigger mechanism is set based on the set target cooling duration (e.g., 3 to 5 minutes) and the ambient temperature convergence criteria. When the skin surface temperature is detected to have steadily dropped to within ±2°C of the ambient temperature, or the cooling time has reached the set maximum duration, and the trend stability of all temperature sensing points meets the termination criteria, the system automatically determines that the cooling process is complete, outputs a PWM decrementing control sequence, and ceases all heating control commands. At the same time, the control sequence is saved as part of the temperature control record and used as a reference for next use, thereby achieving continuous optimization of personalized cooling strategies.

[0080] In an embodiment of the present invention, by establishing the negative temperature coefficient resistance characteristic parameters of a graphene heating film and leveraging the unique property of graphene materials—their resistance decreases as temperature rises—this method achieves precise temperature control by real-time monitoring of resistance changes and inferring temperature. This method offers higher temperature control accuracy and response speed than traditional linear resistor materials. A multi-point distributed capacitance sensing electrode array is employed to simultaneously detect multi-dimensional information such as contact area, pressure distribution, and contact angle. Compared to existing single-point contact detection technologies, this significantly improves the accuracy and comprehensiveness of contact state identification, providing a reliable data foundation for subsequent personalized control. By performing multi-parameter analysis of the target area and establishing a personalized temperature control database based on contact characteristics, temperature parameters can be automatically adjusted based on different skin types and characteristics, achieving a technological leap from traditional fixed temperature control to intelligent personalized control. Pulse width modulation technology is employed to implement segmented power control of the graphene heating film. Through refined management of the preheating, steady-state heating, and insulation phases, the advantages of graphene materials—rapid heating and precise temperature control—are fully utilized, achieving higher energy efficiency and control accuracy than traditional linear voltage regulation methods. A multi-level temperature monitoring system, utilizing multi-sensor data fusion and PID control algorithms, enables real-time monitoring and dynamic adjustment of the temperature control process, effectively avoiding the temperature fluctuations associated with traditional on-off control modes and ensuring temperature stability during the treatment process. Intelligent end-of-life timing determination and PWM duty cycle reduction control enable a smooth transition from treatment temperature to ambient temperature, avoiding the discomfort caused by the sudden cessation of heating in traditional devices. Multiple integrated safety protection mechanisms significantly enhance safety and comfort during use.

[0081] In a specific embodiment, the process of executing step 100 may specifically include the following steps:

[0082] Applying an excitation voltage pulse signal within a preset voltage range to the graphene electric heating film and collecting stable conductivity state data;

[0083] Performing real-time resistance change monitoring on the stable conductivity state data to obtain a dynamic resistance value sequence of the graphene heating film during the pre-activation process;

[0084] Performing resistance temperature characteristic curve modeling based on the dynamic resistance value sequence and corresponding temperature data to obtain a negative temperature coefficient resistance model;

[0085] Parameters are extracted based on the negative temperature coefficient resistor model to obtain negative temperature coefficient resistor characteristic parameters including a reference resistance value, a temperature coefficient, and a response time constant.

[0086] Specifically, a set of low-power pre-excitation voltage pulse signals adapted to the graphene film electrothermal structure is designed, with a voltage range controlled between 0.5V and 1.2V, an excitation frequency set to 50Hz to 100Hz, and a pulse action time maintained within 3 to 5 seconds to avoid transient lattice damage or heat accumulation. The excitation signal has a certain volatility to stimulate the rearrangement of carrier migration paths in the carbon-carbon covalent bond grid system inside the graphene, so that it enters a dynamic conductivity self-adjustment state under a low stability threshold in the initial conductive state. This state is manifested as a rapid decrease in resistance to a certain stable range under high-frequency, low-amplitude pulse excitation, and the convergence of resistance fluctuations is enhanced, that is, the system conductivity tends to be stable. In the process of completing the voltage excitation and stabilizing the conductivity behavior, a parallel high-precision resistance detection path is started, and the voltage-current data collected in real time at both ends of the graphene electrothermal film are processed in isochronous segments to calculate the resistance value change per unit time and generate a complete dynamic resistance value sequence. To ensure resistance measurement accuracy, a high-resolution ADC module (at least 12 bits) and an operational amplifier with high common-mode rejection ratio and low temperature drift are used. Each measured resistance value is paired and stored with the corresponding ambient temperature data or the value measured by an infrared non-contact temperature probe, thus implementing a data pairing logic that maps resistance to temperature. This sequence demonstrates the nonlinear behavior of the graphene material's resistance with temperature. Specifically, within the comfortable skin contact range of 25°C to 65°C, its resistance exhibits a decreasing trend with increasing temperature, demonstrating a negative temperature coefficient (NTC) characteristic, in contrast to the positive temperature coefficient (PTC) effect of traditional metal wire or ceramic heating elements. The dynamic resistance sequence and temperature-paired data are then modeled to construct a resistance-temperature curve. This curve is fitted using nonlinear fitting methods such as exponential, hyperbolic, or piecewise polynomial functions to capture the differences in the graphene material's resistance response slope across different temperature ranges, particularly the significant transitions in the 30°C to 45°C and 45°C to 65°C ranges. To improve the model's versatility, a spline interpolation algorithm was used for local fitting, and a least-squares optimization method was used to globally converge the residuals of the overall curve. This resulted in a high-precision fitting curve that reflects the nonlinear variation of the graphene heating film's resistance with temperature. A mathematical mapping model was also constructed to support subsequent temperature inversion and power regulation. After curve modeling was completed, in-depth parameter extraction was performed on the negative temperature coefficient resistance model.By analyzing the tangent of the temperature-resistance curve at room temperature (25°C), a baseline resistance value is obtained. This value represents the initial resistance of the graphene heating film under unpowered conditions or in a static environment and serves as a standard reference point for subsequent calculations of the relative magnitude of resistance changes. Secondly, by performing piecewise differentiation on the average slope of the curve in each temperature zone, the temperature coefficient α, the rate of change of resistance per unit temperature change, is calculated. To describe the response speed of the graphene heating film during the transition from one steady state to another, the time constant τ of the exponential fitting curve of the resistance change process is analyzed and fitted using a first-order inertial system model. The response time constant is then extracted. This time constant reflects the material's response delay to external thermal excitation signals. A smaller value indicates a faster temperature rise response and is used in the feedforward adjustment portion of the dynamic control algorithm. The reference resistance value, temperature coefficient, and response time constant are encapsulated as a negative temperature coefficient resistor characteristic parameter set, which serves as the underlying physical support template for subsequent PWM duty cycle calculation, PID adjustment gain optimization, and temperature estimation back-calculation algorithm. It also allows dynamic updating and compensation through periodic self-excitation according to the aging state of the electric heating film material during long-term use.

[0087] In a specific embodiment, the process of executing step 200 may specifically include the following steps:

[0088] Based on the capacitance change of each sensing electrode in the multi-point capacitive sensing electrode array, the target area is monitored in real time to obtain the capacitance change data of each sensing electrode;

[0089] Performing effective contact determination based on the capacitance change data of each sensing electrode and a preset capacitance threshold to obtain effective contact electrode distribution information;

[0090] Calculating contact parameters based on capacitance differences between different sensing electrodes in the effective contact electrode distribution information to obtain contact area distribution data and contact pressure distribution data;

[0091] A multi-parameter analysis is performed on the target area according to the contact area distribution data and the contact pressure distribution data to obtain personalized temperature control parameters.

[0092] Specifically, based on the multi-point capacitive sensing electrode array distributed on the active surface of the beauty instrument, the contact status of the target skin area is monitored in real time. These sensing electrodes are made of highly conductive copper foil or silver paste materials. The area of ​​a single electrode is between 2 and 4 square millimeters, and the electrode spacing is maintained between 5 mm and 8 mm to form a stable spatial density; the array is arranged in a 3×3, 4×4 or higher dimensional form, thereby covering the entire skin contact surface on a two-dimensional plane, forming a multi-point parallel detection channel. When the user brings the beauty instrument close to the skin and makes physical contact with the surface of the skin, the capacitance value of the local electrode pair will change significantly, especially as the capacitance increases rapidly, because human tissue has a higher dielectric constant than air. On this basis, the system starts a highly sensitive capacitance sampling circuit to collect and synchronously record the capacitance values ​​of each electrode at different time points at high speed to form an original capacitance change data set. This data is input to the main control unit via a high-speed ADC module and a differential detection front-end. The control system tracks the capacitance change trend with millisecond-level precision and compares the current capacitance value of each electrode with its baseline capacitance value at power-on to calculate the absolute change, ΔC. This ΔC is then compared with a preset capacitance threshold (between 0.5pF and 1.0pF) derived from extensive usage experience and user skin model training. If the ΔC of an electrode exceeds this threshold, it is considered to have effectively contacted the skin and is marked as a "valid contact electrode." By counting the positions of all electrodes in the array that meet the contact determination criteria, a distribution map of valid contact electrodes is generated at the current moment. Contact parameters are calculated based on the capacitance differences between different sensing electrodes in this distribution information. Because capacitance changes not only reflect contact but are also sensitive to contact pressure, particularly in skin-contact areas, the magnitude of the capacitance increase can vary significantly between electrodes due to differences in contact angle, skin elasticity, and pressure. Therefore, by extracting the ΔC amplitude for each electrode and establishing a spatial gradient model, two parameters, contact area distribution and contact pressure distribution, are derived. Contact area estimation uses the product of the number of effective contact electrodes and the unit electrode area as a basic model, while the capacitance difference between the boundary electrodes and the center electrode is combined to analyze the concentration and shape of the contact. The contact pressure distribution forms a heat map based on the normalized ΔC value of each contact electrode. By analyzing indicators such as the concentration, maximum value location, and change gradient of areas with high capacitance changes, it can be determined whether the skin is in a complex state such as overvoltage, bias, or light contact in a certain area. Based on the contact area distribution data and contact pressure distribution data, a multi-dimensional parameter analysis is performed on the current target area to determine the quality, stability, and safety of the contact behavior, and to derive personalized temperature control parameters adapted to this contact state. The system calls on a built-in temperature control strategy database, which has been pre-trained through machine learning to model a large number of regular skin temperature responses under different contact areas and pressure modes.For example, if the contact area is large and the pressure is evenly distributed, the system will set the target temperature in the medium-high range (such as 42°C to 45°C) and the heating rate at 1.2°C / minute to 1.5°C / minute to fully penetrate the dermis. Conversely, if the contact area is small and the pressure is concentrated in a single area, the system will lower the target temperature to 38°C to 40°C and limit the heating rate to less than 0.8°C / minute to avoid discomfort caused by heat concentration. For scenarios where the pressure is extremely uneven or there is edge drift in the contact area, the system will delay the start of the heating behavior, give priority to contact correction prompts, or adjust the electric heating film partition activation strategy to ensure that the risk of local overheating is effectively avoided. In addition, the current contact characteristics are compared with the user's historical usage records. If the user has shown sensitive reactions or uncomfortable behaviors under similar contact characteristics, further protection corrections will be set on the temperature control parameters, such as reducing the constant temperature maintenance time, increasing the cooling interval time, or limiting the maximum temperature platform height.

[0093] In a specific embodiment, the step of performing a multi-parameter analysis on the target area according to the contact area distribution data and the contact pressure distribution data to obtain personalized temperature control parameters may specifically include the following steps:

[0094] Performing regional characteristic detection on the target area based on the contact area distribution data and the contact pressure distribution data to obtain multi-dimensional regional characteristic data;

[0095] Performing type classification based on the multi-dimensional regional characteristic data to obtain a regional type recognition result;

[0096] querying a personalized temperature control database based on the area type identification result to obtain basic temperature control parameters;

[0097] Temperature correction is performed according to the basic temperature control parameters and the contact area distribution data to obtain personalized temperature control parameters.

[0098] Specifically, the local spatial characteristics of the target skin area are analyzed based on contact area and contact pressure distribution data. This process begins with a set of valid contact points detected by a two-dimensional electrode matrix. Within each contact area, the area boundary shape, center point location, edge smoothness, area dispersion, and local contact density are calculated to generate a morphological feature vector reflecting the geometric composition. Simultaneously, thermal map interpolation and gradient vector field extraction are performed on the contact pressure distribution to obtain mechanical characteristic dimensions such as the spatial variation trend of contact intensity, local pressure concentration, and overall pressure uniformity. All these geometric and mechanical features are then combined to form multi-dimensional regional characteristic data, encompassing at least seven core metrics: area integrity, pressure peak location, pressure center offset, edge pressure gradient, local concentration coefficient, area variance coefficient, and boundary stability. Each of these metrics corresponds to a physical quantity describing the contact area's ability to accept heat and the skin's response. Once the complete regional characteristic data is obtained, a trained regional recognition and classification model is invoked to intelligently classify the target area. The model is built using a support vector machine, multilayer perceptron, or convolutional neural network architecture. Its training set includes regional response feature annotations for various typical contact conditions, such as "high-pressure concentrated," "wide-area uniform," "edge sliding," "local drift," and "light touch instability." Each type corresponds to a specific temperature control adaptation mode. By inputting the currently detected feature vector into the model, the system outputs the target region's category label and its confidence level, forming a clear regional classification result. For example, if the pressure concentration is extremely high but the area is small, and the pressure peak point is far from the geometric center, the system identifies it as "high-pressure concentrated," indicating risks such as concentrated skin force and obstructed blood flow, requiring careful control of the temperature rise rate. Conversely, if the system identifies it as "wide-area uniform," the contact area is complete and the pressure is uniform, making a conventional temperature curve suitable for maintaining efficient heating. Based on the regional classification result, the system accesses a pre-set personalized temperature control database, which stores basic temperature control strategy parameters corresponding to different regional types under standard skin conditions. Each type of area corresponds to a set of basic temperature control parameters, including the target temperature upper limit, heating rate, insulation time interval and temperature variation tolerance. For example, for the "edge sliding type", the target temperature is limited to 38°C, the heating rate is controlled at 0.5°C / minute, and the contact stability assessment time needs to be increased as a delay before heating; for the "wide-area uniform type", the target temperature is set to 42°C, the heating rate is 1.2°C / minute, and the insulation duration is more than 10 minutes. The system directly retrieves the basic temperature control parameters of the area based on the recognition results and uses them as the first-level input variables for thermal control decisions. In order to ensure that the set temperature control strategy fully matches the current real-time contact status, a correction mechanism for the contact area distribution is introduced based on the basic temperature control parameters.This correction mechanism calculates a correction coefficient based on the proportion of the currently detected contact area to the total effective array area, the central distribution structure of the contact area, and the historical contact area change trend, thereby adjusting the target temperature or heating rate. For example, when the system finds that the current contact area conforms to the uniform contact mode but the overall proportion is low (such as only accounting for less than 30% of the total array area), it will appropriately lower the temperature limit by within 2°C and extend the heating phase to 150% of the default duration to prevent skin burning caused by concentrated heat flux; on the contrary, if the area proportion is extremely high and the contact distribution is highly central, the system will slightly increase the initial heating duty cycle to increase the overall temperature achievement speed without changing the overall temperature target. The system also combines the user's historical sensitivity level, skin type label, and temperature control feedback during the last care process to perform fine-tuning compensation, ultimately forming the personalized temperature control parameters required for the current area.

[0099] In a specific embodiment, the process of executing step 300 may specifically include the following steps:

[0100] Calculating PWM basic control parameters according to the personalized temperature control parameters and the negative temperature coefficient resistance characteristic parameters, wherein the PWM basic control parameters include a control frequency and a duty cycle adjustment range;

[0101] Based on the PWM basic control parameters, the duty cycles of the preheating stage, the stable heating stage and the heat preservation stage are set in sections to obtain the PWM duty cycle control sequence corresponding to each heating stage;

[0102] Establishing a nonlinear response relationship between power and temperature of the graphene electric heating film according to the negative temperature coefficient resistance characteristic parameters, and obtaining power-temperature response relationship data;

[0103] Based on the PWM duty cycle control sequence and the power-temperature response relationship data, a staged temperature output strategy analysis is performed on the graphene electric heating film to obtain a staged heating temperature output strategy.

[0104] Specifically, the basic PWM control parameters are calculated based on personalized temperature control parameters and negative temperature coefficient (NTC) resistance (NTR) characteristic parameters. These parameters are generated collaboratively by the front-end skin contact behavior recognition module, regional characteristic classification algorithm, and temperature correction module. They include information such as the target temperature, heating rate, constant temperature maintenance time, and skin sensitivity correction factor. The NTC resistance characteristic parameters of the graphene heating film include the baseline resistance value, temperature coefficient α, and response time constant τ. These parameters collectively describe the overall trend of the material's nonlinear resistance change with temperature and its dynamic response capability. The calculation of the basic PWM control parameters considers the coupling between the temperature control target and the graphene material's power response. By combining the temperature coefficient α with the baseline resistance value, the resistance change amplitude is inferred based on the target temperature range. The target power level is then estimated based on the heating film's voltage input range and mapped into the PWM control space. The PWM control frequency is selected between 1kHz and 5kHz to balance temperature control sensitivity and system response inertia, while the PWM duty cycle adjustment range covers the full heat output range from 10% to 90%. On this basis, the personalized heating rate and expected heating time are combined to define the PWM signal gradient and initial boundaries for each stage. Based on the aforementioned basic PWM control parameters, the entire heating process is segmented into a preheating phase, a stable heating phase, and a heat-holding phase. A corresponding PWM duty cycle range is set for each phase. In the preheating phase, to quickly raise the temperature from ambient to 80% of the target temperature, the duty cycle is set to a higher range, such as 70%-90%. The duration of this phase is calculated based on the set heating rate and can be dynamically adjusted. In the stable heating phase, the duty cycle is adjusted to an intermediate range of 40%-60% to slowly approach the target temperature. This phase lasts for 30 seconds to 1 minute and is linked to the resistance trend in real time. During the heat-holding phase, a constant temperature output is maintained, with the duty cycle further reduced to between 20% and 40% and dynamically adjusted to ensure that the heat output adapts to the skin's thermal diffusion effect and maintains stable temperature control. This entire process forms a staged PWM duty cycle control sequence, each corresponding to a PWM duty cycle time window structure and adjustment gradient function. While generating the control signal, a temperature-power response model is established for the graphene heating film material itself, serving as the basis for calculating thermal output. Due to graphene's negative temperature coefficient, its resistance decreases with increasing temperature. Therefore, under a fixed voltage input, its current increases, and the power output exhibits a nonlinear increasing relationship. Using the temperature coefficient and the resistance trend established by the reference resistor, combined with the system's actual voltage application parameters, the power output at various temperatures is calculated. A nonlinear power-temperature response table is then generated through continuous data fitting. To enhance the system's real-time computing capabilities, this response relationship is stored as power-temperature response data in a discrete lookup table within the temperature control system. This data is then combined with the response time constant to form a power response delay compensation model.Based on the PWM duty cycle control sequence and power-temperature response data, a phased temperature output strategy for the graphene heating film is analyzed. During each heating phase, the output power is calculated based on the current PWM duty cycle value. The current predicted temperature is mapped using a nonlinear power model and then differentially compared with the target temperature curve. If the predicted temperature is lower than the expected value, the duty cycle is appropriately increased; if it is higher than expected, the signal duty cycle is reduced. The control gradient is dynamically adjusted based on the temperature slope to ensure smooth temperature control. During the insulation phase, the temperature fluctuation amplitude is detected. If the skin temperature fluctuates beyond ±0.5°C, the duty cycle is quickly fine-tuned through a feedback mechanism to prevent temperature control from becoming unstable. During the actual output process, current, voltage, and resistance data are collected in real time and reverse-substituted into the temperature model for dynamic temperature inversion, improving the timeliness of temperature detection and response accuracy. The system outputs a phased heating temperature output strategy.

[0105] In a specific embodiment, the step of establishing a nonlinear response relationship between power and temperature of the graphene electric heating film according to the negative temperature coefficient resistance characteristic parameters to obtain power-temperature response relationship data may specifically include the following steps:

[0106] Based on the reference resistance value and temperature coefficient in the negative temperature coefficient resistance characteristic parameter, the resistance change law of the graphene electric heating film in different temperature ranges is analyzed to obtain temperature range resistance change curve data;

[0107] Performing a resistance-temperature reverse mapping relationship analysis based on the resistance change curve data in the temperature range to obtain a temperature calculation model that reversely infers the temperature through the resistance value;

[0108] Perform real-time power calculation based on the temperature calculation model to obtain a power output value sequence corresponding to different temperature intervals;

[0109] Nonlinear fitting is performed based on the power output numerical sequence to obtain power-temperature response relationship data of the nonlinear response relationship between power and temperature of the graphene electric heating film.

[0110] Specifically, the research utilized data on the material's resistance-temperature response characteristics obtained during the pre-activation phase of the heating film, specifically the two key parameters: the baseline resistance value and the temperature coefficient. The baseline resistance value is the steady-state resistance value obtained by a high-precision resistance sampling module at the initial ambient temperature, before the graphene material is thermally stimulated. It represents the material's intrinsic conductivity in its unstimulated state. The temperature coefficient, on the other hand, reflects the magnitude of the material's resistance change per unit temperature change and is a key parameter determining the speed and strength of graphene's thermal response. Based on these two fundamental physical quantities, a numerical model was developed to analyze the resistance variation of the graphene heating film across different temperature ranges. Given that graphene exhibits a significant negative temperature coefficient within the skin-related temperature range of 25°C to 65°C, this range was subdivided into four sub-segments: 25°C to 35°C, 35°C to 45°C, 45°C to 55°C, and 55°C to 65°C. Resistance trends were collected within each segment, and the relationship between resistance and temperature was analyzed. Because the resistance of graphene heating films does not decrease linearly and uniformly, but rather is influenced by factors such as the microscopic arrangement of carbon atoms, carrier migration velocity, and the thermal inertia of the material, its resistance decrease exhibits a non-uniform characteristic, varying at varying rates across different temperature zones. By performing point-by-point calculation and trend smoothing of the resistance measurement data within each sub-range, a complete temperature range resistance curve is plotted, thereby constructing a raw data framework for the material's temperature response. Based on this temperature range resistance curve data, a resistance-temperature reverse mapping analysis is performed, using the resistance value as the input variable and outputting the current temperature range of the material. By establishing a data lookup table structure or employing an interpolation function, previously acquired temperature range resistance curves are mathematically processed, ensuring that each measured resistance value can be found in the response table. If the resistance value falls between two known temperature ranges, the system automatically performs linear or spline interpolation to obtain a smoother and more continuous temperature output. This forms a complete temperature calculation model, which is embedded in the main temperature control module and supports temperature inversion in the subsequent PWM closed-loop control logic. Using this temperature calculation model, the resistance data collected at any given moment can be used to quickly estimate the temperature, and real-time power calculations can be performed based on this data. Considering that the graphene heating film operates in constant voltage power supply mode, its instantaneous power output is primarily driven by changes in resistance. Due to the material's negative temperature coefficient, resistance decreases with increasing temperature, and the system can observe an asymmetric increase in power during temperature changes. To accurately capture the dynamic characteristics of power, the resistance value derived at each corresponding temperature point is input into the power estimation model along with the applied constant drive voltage, and the output power at that temperature point is calculated in real time. This process is repeated across all temperature zones, resulting in a sequence of power output values, including different temperature points and corresponding power output values, reflecting the power variation trend of the graphene heating film throughout the entire operating temperature range.A nonlinear fitting is performed on the power output numerical sequence to construct a continuous response function between the power and temperature of the graphene heating film. Polynomial fitting, exponential function fitting, or piecewise high-order curve approximation are used to reconstruct the curve of the data sequence. The optimal function expression is selected through residual evaluation and goodness-of-fit judgment. This function model must not only accurately fit the data trend but also possess a certain degree of first-order derivative continuity so that its slope can be used as a gain reference for temperature regulation in PID control or other closed-loop regulation mechanisms. The resulting fitting function constitutes the core data model of the nonlinear response relationship between the power and temperature of the graphene heating film and is encapsulated within the system as a table, function, or structure.

[0111] In a specific embodiment, the process of executing step 400 may specifically include the following steps:

[0112] Based on a multi-level temperature monitoring system, the temperature of the graphene heating film itself, the contact surface temperature of the target area and the ambient temperature are synchronously collected to obtain multi-channel temperature feedback data;

[0113] Perform multi-sensor data fusion based on the multi-channel temperature feedback data to obtain fused temperature monitoring data;

[0114] Performing PID control based on the fusion temperature monitoring data and the target temperature in the staged heating temperature output strategy to obtain temperature deviation control parameters including proportional deviation, integral deviation and differential deviation;

[0115] The PWM control parameter of the graphene electric heating film is dynamically adjusted according to the temperature deviation control parameter to obtain a stable temperature control signal.

[0116] Specifically, based on a multi-level temperature monitoring system, the temperature of the graphene heating film itself, the contact surface temperature of the target area, and the ambient temperature are collected synchronously. The architecture consists of three parts: the first is a micro temperature sensor integrated inside the graphene heating film, which is deployed on the heating film material body and is used to collect the internal thermal state of the heating source itself in real time. Its response time is less than 0.1 seconds, and the measurement accuracy is ±0.2°C. It is mainly used to determine whether the heating area is uniform, whether there is a hot spot offset or a local over-temperature trend; the second is a group of thermistor arrays arranged on the contact surface between the beauty instrument and the skin. Each thermistor element covers an area of ​​about 2cm 2The system precisely monitors the temperature distribution at different locations on the skin surface. This data reflects the actual heat flow effect felt by the user and is an important basis for adjusting comfort. Third, an independent ambient temperature sensor module, located away from heat sources, collects real-time information on current external air temperature changes. This is primarily used to perform environmental compensation on the contact surface temperature and eliminate false temperature rise or fall signals caused by external interference. These three types of sensors together constitute the system's multi-channel temperature feedback channel. During data acquisition, a synchronous sampling mechanism aligns each sensor node with the same timestamp, generating a set of time-series sampled data containing internal, surface, and ambient temperatures, resulting in multi-channel temperature feedback data. Multi-sensor data fusion is performed based on this multi-channel temperature feedback data to generate unified, fused temperature monitoring data. This fusion process utilizes a multi-sensor data fusion algorithm, including weighted averaging, time-window sliding average, Kalman filtering, outlier removal, and data fitting and reconstruction. Each temperature channel is assigned an appropriate weight. For example, the skin contact surface temperature has the highest weight, followed by the graphene membrane temperature, and the ambient temperature is mainly used for correction and has the lowest weight. A sliding time window mechanism is then used to smooth out short-term jittering data to prevent instantaneous fluctuations from interfering with control decisions. Anomaly detection logic is then used to filter out short-term jump points, duplicate points, or distorted samples, and interpolation is performed on locally missing points. Ultimately, a continuous, smooth, and reliable temperature feedback data stream is formed, namely, fused temperature monitoring data. The fused temperature data is input into the system's control strategy module and compared point by point with the target temperature in the staged heating temperature output strategy. The temperature deviation at the current moment is calculated, and the PID closed-loop control mechanism is driven accordingly. PID control is a dynamic response system constructed based on proportional, integral, and differential regulation models. It can perform feedback operations on the error between the target and the current state in three dimensions: immediate, historical, and trend. The proportional deviation reflects the real-time difference between the current temperature and the target temperature and is the most direct basis for control. The integral deviation calculates the cumulative amount of temperature difference within a certain time range and is used to correct the static error caused by long-term small deviations, thereby improving the long-term stability of temperature control. The differential deviation focuses on the trend of the temperature change rate and can respond in advance when the temperature rises or falls too quickly, preventing the control system from overshooting or oscillating. These three deviations are weighted and calculated through the set PID parameter group to form the temperature deviation control parameter, which serves as the basic quantitative instruction for the system to adjust the PWM signal. After obtaining the control parameters output by the PID, the control system directly uses them to adjust the PWM control signal of the graphene heating film, including the duty cycle size, duty cycle change step, adjustment period, and adjustment response curve.If the current temperature is lower than the target temperature, the system increases the PWM duty cycle based on the proportional deviation value to increase heat output. If the temperature overshoots and approaches the critical upper limit, the duty cycle is reduced based on the differential deviation trend to slow the heating rhythm. If the temperature is low for a long time but changes slowly, the system increases the average power output through the integral deviation to restore the temperature control curve. When the three deviations check and balance each other, the system enters a dynamic equilibrium state. At this time, the output PWM signal changes in amplitude tends to be small, fluctuating between 20% and 40% to maintain stable operation at a constant temperature. The entire adjustment cycle is 0.5 to 1 second, ensuring that the adjustment is neither too frequent nor too responsive. The final output PWM signal is the stable temperature control signal.

[0117] In a specific embodiment, the process of executing step 500 may specifically include the following steps:

[0118] Performing an end timing judgment on the temperature change trend and usage time of the target area based on the stable temperature control signal to obtain end timing judgment data;

[0119] Performing a progressive PWM duty cycle reduction control on the graphene electric heating film according to the end timing judgment data to obtain a PWM reduction control sequence;

[0120] Perform multiple safety protection status detection based on the PWM decrement control sequence to obtain safety status monitoring data including temperature overheat protection, contact abnormality protection and time limit protection;

[0121] The stop state is confirmed based on the safety state monitoring data and the condition that the temperature of the target area returns to the ambient temperature range to obtain the safety stop state of the beauty instrument.

[0122] Specifically, based on the temperature plateau maintained by a stable temperature control signal, the system continuously monitors the temperature trend of the target area's skin surface and the cumulative duration of the current session. These two dimensions together form the core reference parameters for determining the end timing. The temperature trend refers to the slope characteristic of the integrated temperature data within a specific time window. If the skin contact surface temperature remains within a ±0.5°C fluctuation range for 5 consecutive minutes, with no signs of continued increase or abnormal decrease, the temperature plateau is considered to have reached a stable state. The system also calculates the total usage time from the start of the heating phase to the current time. If the cumulative usage time has reached the optimal skincare heat load range of 15 to 20 minutes without triggering any alarm events, the current treatment process is considered to be nearing completion. Based on the intersection of these two conditions, the system generates the end timing judgment data, indicating the end of the current heating phase and the transition to the heat reduction phase. After generating the end judgment data, the system gradually adjusts the PWM control signal of the graphene heating film to officially start the cooling control mode. At this point, the system uses the current duty cycle value as a starting point and, combined with the set cooling rate and cooling time window, gradually generates a duty cycle reduction sequence. This sequence continuously adjusts by 5% or a constant decrease every 30 seconds until the duty cycle reaches the minimum maintenance range of 10% to 15%. If the user's ambient temperature is higher or their skin is less sensitive to heat, the system extends the reduction time, targeting a cooling rate of 1°C / minute. This linear or exponential control of the PWM signal's ramp-down curve prevents thermal discomfort or skin stress caused by sudden power reductions. During this ramp-down process, the control module maintains real-time sampling of current, voltage, and membrane resistance to ensure that each change in the PWM signal generates a corresponding thermal output feedback, resulting in a continuous, smooth, and gentle cooling process. Furthermore, multiple safety protection mechanisms are activated during the cooling phase. By comprehensively monitoring key safety aspects of the operating state, a comprehensive safety status monitoring model is established, covering temperature limits, electrical anomalies, and time limits. The first is temperature overheat protection, which continuously monitors all skin contact surface sensor points and graphene film temperature points. If any monitoring point still shows an abnormal temperature above 50°C during the cooling process, all PWM signals will be immediately interrupted, the event will be recorded, and the device will be forced to enter protection mode. The second is contact abnormality protection, which continuously determines whether the user's skin is still in effective contact with the beauty instrument head during the heating process through multi-point capacitance sensing electrodes. If a sharp drop in contact area, loss of pressure or abnormal capacitance fluctuation is detected, the system will determine that the user is loose or displaced, and immediately cut off the power output and lock the feedback channel. Finally, there is time limit protection. If the cumulative running time of the system since startup has exceeded the set upper limit (such as 20 minutes), regardless of whether it is currently on the temperature control platform, the heating process will be forcibly terminated to prevent long-term heat load from causing micro-burn damage to the skin or epidermal dehydration.The three types of protection logic described above are integrated into an independent safety status monitoring module, which continuously performs status assessments and outputs monitoring results to form complete safety status monitoring data. In the later stages of the coordinated operation of PWM decrement control and safety status monitoring, the actual skin cooling effect is determined based on the ambient temperature difference, and a final decision is made as to whether to execute the shutdown operation. The temperature data of the fused skin contact surface is compared with the ambient temperature baseline. If the average skin temperature measured continuously for more than three minutes is within 2°C below the ambient temperature upper limit, and the temperature curve flattens or even begins to decline, the cooling process is considered to be essentially complete. At the same time, the system requires that these conditions be verified synchronously with the safety status monitoring data to ensure that no temperature control exceeds the limit, contact interruption, or other device anomalies occur during the cooling period. If all judgment conditions are normal, a final stop status confirmation signal is generated, and a shutdown command is output to the main control unit.

[0123] In a specific embodiment, the step of performing a progressive PWM duty cycle reduction control on the graphene electric heating film according to the end timing judgment data to obtain a PWM reduction control sequence may specifically include the following steps:

[0124] Determining an initial PWM duty cycle based on the temperature stability evaluation index in the end timing judgment data to obtain an initial PWM duty cycle value and a target cooling rate parameter for progressive cooling;

[0125] Calculating the decreasing interval time and decreasing amplitude according to the initial PWM duty cycle value and the target cooling rate parameter to obtain a PWM decreasing control strategy including a time interval and a decreasing percentage;

[0126] Generating a duty cycle decreasing timing sequence based on the PWM decreasing control strategy to obtain PWM timing decreasing data that gradually reduces the duty cycle value according to a preset time interval;

[0127] The total duration of the cooling process and the termination condition are set according to the PWM timing decrement data to obtain a PWM decrement control sequence.

[0128] Specifically, the initial PWM duty cycle is determined based on the temperature stability evaluation metric in the end-of-time judgment data. This temperature stability metric includes the maximum fluctuation value, average fluctuation slope, and change offset within a five-minute segment of the skin contact area temperature change within multiple continuous time windows. Through mathematical processing of these differential change data, it is determined whether the current temperature control platform has reached a stable period, has a potential warming trend, or is about to enter a natural re-warming period. If the temperature stability is good, with a fluctuation range within ±0.5°C and a temperature slope close to zero or slowly decreasing, the cooling logic is triggered. Based on this, the last set of PWM duty cycle data used to maintain the constant temperature state is used as the initial cooling point. The system also retrieves the user's skin type, contact surface thermal response category, and care mode label from the personalized temperature control database. Combined with a preset human comfort cooling rate standard (e.g., a temperature drop of 1°C per minute), this is used to generate a target cooling rate parameter, thereby determining the cooling rate boundary and initial power state. Based on these initial PWM duty cycle values ​​and target cooling rate parameters, the decrement strategy calculation module derives the optimal decrement interval and single decrement amplitude. This calculation process requires comprehensive consideration of three key factors: first, the graphene material's heat capacity and conduction delay, i.e., the actual thermal decay lag caused by the reduction in electrical power per unit time; second, the skin-sensed thermal buffer response model, which prevents users from experiencing discomfort caused by a sudden "loss of heat" during the cooling process; and third, the degree of compatibility between the device's heat dissipation mechanism and the ambient heat exchange rate. Therefore, the initial duty cycle reduction is divided into multiple discrete time windows for gradual decay. The time interval is set to 30 seconds, and the decrement amplitude is set to 5%, or dynamically adjusted to a floating range of 3% to 7% based on the target rate. A decrement control strategy with a "decrement by y% every x seconds" structure is constructed, forming a combined regulation map in both the time domain and the duty cycle amplitude domain. Within the decrement control strategy, a timing generation operation is explicitly executed. Based on the aforementioned time interval and amplitude configuration, complete PWM decrement timing data is constructed. This data consists of multiple sets of PWM signals, each of which records the target duty cycle value after a decrement and the duration of the decrement. This data is used as a basis to drive the PWM output module for precise duty cycle control. Taking an initial duty cycle of 40%, a decreasing amplitude of 5%, and an interval of 30 seconds as an example, the system generates PWM values ​​of multiple stages such as 35%, 30%, 25%, 20%, and 15% in sequence, and transmits them to the control channel through a timing scheduling mechanism. In this way, the input power of the graphene heating film is gradually attenuated at the physical level, and the heat release rhythm is slowed down. The skin-perceived temperature will also drop slowly, steadily, and linearly close to the natural temperature, thereby avoiding skin irritation, rapid contraction of blood vessels, or capillary congestion caused by sudden power drop or forced thermal shutdown, and ensuring the mildness and physiological safety of the fever-reducing process.During stable cooling, the total duration and termination conditions of the entire cooling process are dynamically set. The boundary conditions for the entire cooling process are constructed using PWM timing decrement data. The initial total duration is determined by inversely calculating the minimum power maintenance time and the target temperature drop rate, maintaining it between 3 and 5 minutes. This ensures complete temperature drop without overutilizing device resources due to slow cooling. A temperature termination condition is also set: cooling is considered complete if the skin contact surface temperature drops to within ±2°C of the ambient temperature at any point and remains within this range for more than one minute. If this condition is met simultaneously with the decrement sequence being completed, the system determines the cooling process is complete and outputs a final PWM decrement control sequence completion signal. At this point, the system automatically disconnects the heating element power supply, shuts down all heating-related modules, and records key information such as the duty cycle evolution curve, duration, thermal response characteristics, and skin temperature recovery trend of the cooling process. This provides useful data for initializing temperature control parameters and self-learning user models during the next use.

[0129] The above describes the control method of the beauty instrument using the graphene electrothermal effect in the embodiment of the present invention. The following describes the beauty instrument using the graphene electrothermal effect in the embodiment of the present invention. Figure 2 In one embodiment of the present invention, a beauty instrument using the graphene electrothermal effect includes:

[0130] A pre-activation module 11 is used to pre-activate the graphene electric heating film to obtain negative temperature coefficient resistance characteristic parameters;

[0131] The contact state detection module 12 is used to perform contact state detection and multi-parameter analysis on the target area to obtain personalized temperature control parameters;

[0132] A power control module 13 is configured to perform PWM segmented power control on the graphene heating film based on the personalized temperature control parameter and the negative temperature coefficient resistance characteristic parameter to obtain a staged heating temperature output strategy;

[0133] A real-time feedback adjustment module 14 is configured to perform real-time feedback adjustment based on the staged heating temperature output strategy to obtain a stable temperature control signal;

[0134] The cooling power adjustment module 15 is used to gradually adjust the cooling power of the graphene electric heating film according to the stable temperature control signal, and at the same time confirm the safe stop state of the beauty instrument.

[0135] Through the collaborative efforts of the aforementioned components, the present invention establishes the negative temperature coefficient resistance characteristic parameters of the graphene heating film. Utilizing the unique property of graphene materials—their resistance decreases as temperature rises—this method achieves precise temperature control by real-time monitoring of resistance changes and inferring temperature. This method offers higher temperature control accuracy and response speed than traditional linear resistor materials. The use of a multi-point distributed capacitance sensing electrode array enables simultaneous detection of multi-dimensional information such as contact area, pressure distribution, and contact angle. Compared to existing single-point contact detection technologies, this significantly improves the accuracy and comprehensiveness of contact state identification, providing a reliable data foundation for subsequent personalized control. By performing multi-parameter analysis of the target area and establishing a personalized temperature control database based on contact characteristics, temperature parameters can be automatically adjusted according to different skin types and characteristics, achieving a technological leap from traditional fixed temperature control to intelligent personalized control. Pulse width modulation technology is used to implement segmented power control of the graphene heating film. Through refined management of the preheating phase, steady-state heating phase, and heat-holding phase, the advantages of graphene materials for rapid heating and precise temperature control are fully utilized, achieving higher energy efficiency and control accuracy than traditional linear voltage regulation methods. A multi-level temperature monitoring system, utilizing multi-sensor data fusion and PID control algorithms, enables real-time monitoring and dynamic adjustment of the temperature control process, effectively avoiding the temperature fluctuations associated with traditional on-off control modes and ensuring temperature stability during the treatment process. Intelligent end-of-life timing determination and PWM duty cycle reduction control enable a smooth transition from treatment temperature to ambient temperature, avoiding the discomfort caused by the sudden cessation of heating in traditional devices. Multiple integrated safety protection mechanisms significantly enhance safety and comfort during use.

[0136] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0137] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for enabling an electronic device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0138] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that the technical solutions described in the above embodiments can still be modified, or some of the technical features thereof can be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for controlling a beauty instrument using the graphene electrothermal effect, characterized in that: include: Pre-activate the graphene electric heating film to obtain the negative temperature coefficient resistance characteristic parameters; Conduct contact status detection and multi-parameter analysis on the target area to obtain personalized temperature control parameters; Based on the personalized temperature control parameters and the negative temperature coefficient resistance characteristic parameters, PWM segmented power control is performed on the graphene electric heating film to obtain a staged heating temperature output strategy; Specifically, it includes: calculating PWM basic control parameters according to the personalized temperature control parameters and the negative temperature coefficient resistance characteristic parameters, the PWM basic control parameters including the control frequency and duty cycle adjustment range; setting the duty cycles of the preheating stage, the stable heating stage and the insulation stage in sections based on the PWM basic control parameters, and obtaining the PWM duty cycle control sequence corresponding to each heating stage; establishing the nonlinear response relationship between the power and temperature of the graphene electric heating film according to the negative temperature coefficient resistance characteristic parameters, and obtaining power-temperature response relationship data; performing a staged temperature output strategy analysis on the graphene electric heating film based on the PWM duty cycle control sequence and the power-temperature response relationship data, and obtaining a staged heating temperature output strategy; Perform real-time feedback adjustment based on the staged heating temperature output strategy to obtain a stable temperature control signal; The graphene electric heating film is gradually cooled and the power is adjusted according to the stable temperature control signal, and the safe stop state of the beauty instrument is confirmed at the same time.

2. The method for controlling a beauty instrument using the graphene electrothermal effect according to claim 1, wherein: The graphene electric heating film is pre-activated to obtain negative temperature coefficient resistance characteristic parameters, including: Applying an excitation voltage pulse signal within a preset voltage range to the graphene electric heating film and collecting stable conductivity state data; Performing real-time resistance change monitoring on the stable conductivity state data to obtain a dynamic resistance value sequence of the graphene heating film during the pre-activation process; Performing resistance temperature characteristic curve modeling based on the dynamic resistance value sequence and corresponding temperature data to obtain a negative temperature coefficient resistance model; Parameters are extracted based on the negative temperature coefficient resistor model to obtain negative temperature coefficient resistor characteristic parameters including a reference resistance value, a temperature coefficient, and a response time constant.

3. The method for controlling a beauty instrument using the graphene electrothermal effect according to claim 1, wherein: The contact state detection and multi-parameter analysis of the target area are performed to obtain personalized temperature control parameters, including: Based on the capacitance change of each sensing electrode in the multi-point capacitive sensing electrode array, the target area is monitored in real time to obtain the capacitance change data of each sensing electrode; Performing effective contact determination based on the capacitance change data of each sensing electrode and a preset capacitance threshold to obtain effective contact electrode distribution information; Calculating contact parameters based on capacitance differences between different sensing electrodes in the effective contact electrode distribution information to obtain contact area distribution data and contact pressure distribution data; A multi-parameter analysis is performed on the target area according to the contact area distribution data and the contact pressure distribution data to obtain personalized temperature control parameters.

4. The method for controlling a beauty instrument using the graphene electrothermal effect according to claim 3, wherein: The performing multi-parameter analysis on the target area according to the contact area distribution data and the contact pressure distribution data to obtain personalized temperature control parameters includes: Performing regional characteristic detection on the target area based on the contact area distribution data and the contact pressure distribution data to obtain multi-dimensional regional characteristic data; Performing type classification based on the multi-dimensional regional characteristic data to obtain a regional type recognition result; querying a personalized temperature control database based on the area type identification result to obtain basic temperature control parameters; Temperature correction is performed according to the basic temperature control parameters and the contact area distribution data to obtain personalized temperature control parameters.

5. The method for controlling a beauty instrument using the graphene electrothermal effect according to claim 1, wherein: The method of establishing a nonlinear response relationship between power and temperature of the graphene electric heating film according to the negative temperature coefficient resistance characteristic parameters to obtain power-temperature response relationship data includes: Based on the reference resistance value and temperature coefficient in the negative temperature coefficient resistance characteristic parameter, the resistance change law of the graphene electric heating film in different temperature ranges is analyzed to obtain temperature range resistance change curve data; Performing a resistance-temperature reverse mapping relationship analysis based on the resistance change curve data in the temperature range to obtain a temperature calculation model that reversely infers the temperature through the resistance value; Perform real-time power calculation based on the temperature calculation model to obtain a power output value sequence corresponding to different temperature intervals; Nonlinear fitting is performed based on the power output numerical sequence to obtain power-temperature response relationship data of the nonlinear response relationship between power and temperature of the graphene electric heating film.

6. The method for controlling a beauty instrument using the graphene electrothermal effect according to claim 1, wherein: The real-time feedback adjustment based on the staged heating temperature output strategy to obtain a stable temperature control signal includes: Based on a multi-level temperature monitoring system, the temperature of the graphene heating film itself, the contact surface temperature of the target area and the ambient temperature are synchronously collected to obtain multi-channel temperature feedback data; Perform multi-sensor data fusion based on the multi-channel temperature feedback data to obtain fused temperature monitoring data; Performing PID control based on the fusion temperature monitoring data and the target temperature in the staged heating temperature output strategy to obtain temperature deviation control parameters including proportional deviation, integral deviation and differential deviation; The PWM control parameter of the graphene electric heating film is dynamically adjusted according to the temperature deviation control parameter to obtain a stable temperature control signal.

7. The method for controlling a beauty instrument using the graphene electrothermal effect according to claim 1, wherein: The step of gradually adjusting the temperature of the graphene electric heating film according to the stable temperature control signal and confirming the safe stop state of the beauty instrument comprises: Performing an end timing judgment on the temperature change trend and usage time of the target area based on the stable temperature control signal to obtain end timing judgment data; Performing a progressive PWM duty cycle reduction control on the graphene electric heating film according to the end timing judgment data to obtain a PWM reduction control sequence; Perform multiple safety protection status detection based on the PWM decrement control sequence to obtain safety status monitoring data including temperature overheat protection, contact abnormality protection and time limit protection; The stop state is confirmed based on the safety state monitoring data and the condition that the temperature of the target area returns to the ambient temperature range to obtain the safety stop state of the beauty instrument.

8. The method for controlling a beauty instrument using the graphene electrothermal effect according to claim 7, wherein: The step of performing progressive PWM duty cycle reduction control on the graphene electric heating film according to the end timing judgment data to obtain a PWM reduction control sequence includes: Determining an initial PWM duty cycle based on the temperature stability evaluation index in the end timing judgment data to obtain an initial PWM duty cycle value and a target cooling rate parameter for progressive cooling; Calculating the decreasing interval time and decreasing amplitude according to the initial PWM duty cycle value and the target cooling rate parameter to obtain a PWM decreasing control strategy including a time interval and a decreasing percentage; Generating a duty cycle decreasing timing sequence based on the PWM decreasing control strategy to obtain PWM timing decreasing data that gradually reduces the duty cycle value according to a preset time interval; The total duration of the cooling process and the termination condition are set according to the PWM timing decrement data to obtain a PWM decrement control sequence.

9. A beauty instrument using the graphene electrothermal effect, characterized in that: A method for controlling a beauty device using the graphene electrothermal effect according to any one of claims 1 to 8, comprising: A pre-activation module is used to pre-activate the graphene electric heating film to obtain negative temperature coefficient resistance characteristic parameters; The contact state detection module is used to perform contact state detection and multi-parameter analysis on the target area to obtain personalized temperature control parameters; A power control module, configured to perform PWM segmented power control on the graphene electric heating film based on the personalized temperature control parameter and the negative temperature coefficient resistance characteristic parameter, to obtain a staged heating temperature output strategy; A real-time feedback adjustment module is used to perform real-time feedback adjustment based on the staged heating temperature output strategy to obtain a stable temperature control signal; The cooling power adjustment module is used to gradually adjust the cooling power of the graphene electric heating film according to the stable temperature control signal, and at the same time confirm the safe stop state of the beauty instrument.

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