A method for optimizing the configuration of heat dissipation components of a hair removal device

Abstract

The present application provides a method for optimizing the configuration of a heat dissipation component of a hair removal device, which relates to the field of heat dissipation analysis technology, including: establishing a laser transmission path; determining multiple power modes of the target hair removal device; establishing a multi-mode heat distribution space network; determining each heat dissipation constraint space corresponding to each transmission stage in the laser transmission path; performing heat dissipation defect identification, locating heat dissipation defect components and defect levels; optimizing the heat dissipation defect components based on the defect levels, and generating heat dissipation component configuration optimization results. This application can solve the technical problem in the prior art that the lack of accurate analysis of the heat distribution law under multiple power modes, and thus the inability to effectively solve the local high temperature accumulation in the laser transmission path, optimizes the configuration of the heat dissipation component of the hair removal device based on heat distribution prediction and heat dissipation defect identification, thereby optimizing the configuration of the heat dissipation component and achieving the technical effect of improving the heat dissipation performance of the hair removal device.

Description

Technical Field

[0001] The present application relates to the field of heat dissipation analysis technology, and in particular to a method for optimizing the configuration of a heat dissipation component of a hair removal device. Background Art

[0002] With the continuous development of the personal care device market, laser hair removal devices have gained widespread use as an efficient and convenient hair removal tool. Laser hair removal devices precisely emit high-energy laser beams, acting on hair follicles to achieve long-term hair removal results. However, laser devices generate a large amount of heat during operation. This heat comes not only from the high-power energy released by the laser source, but also from the heat dissipation requirements of optical components such as lenses and reflectors, as well as electronic components. If the heat dissipation system is improperly designed, it may not only cause overheating and damage to internal components of the device, but also reduce the stability of the laser output and the user experience.

[0003] Existing heat dissipation designs for hair removal devices typically employ traditional components such as heat sinks, fans, or thermal pads, relying on pre-set, fixed configurations for heat management. However, these designs lack precise analysis of heat distribution patterns under multiple power modes and are unable to effectively address the problem of localized high temperature accumulation within the laser transmission path. Summary of the Invention

[0004] The purpose of this application is to provide a method for optimizing the configuration of the heat dissipation components of a hair removal device, so as to solve the technical problem in the prior art that the local high temperature accumulation in the laser transmission path cannot be effectively solved due to the lack of accurate analysis of the heat distribution law under multiple power modes.

[0005] In view of the above problems, the present application provides a method for optimizing the configuration of the heat dissipation component of a hair removal device, including: analyzing the generation and transmission path of a laser beam of a target hair removal device, and establishing a laser transmission path; determining multiple power modes of the target hair removal device; predicting heat distribution based on the multiple power modes and the laser transmission path, and establishing a multi-mode heat distribution space network; determining each heat dissipation constraint space corresponding to each transmission stage in the laser transmission path; obtaining the heat dissipation component distribution network of the target hair removal device, and identifying heat dissipation defects in combination with the multi-mode heat distribution space network and the each heat dissipation constraint space, locating heat dissipation defective components and defect levels; optimizing the heat dissipation defective components based on the defect levels, and generating a heat dissipation component configuration optimization result.

[0006] The technical solution provided in this application has at least the following technical effects or advantages:

[0007] The target hair removal device's laser beam generation and transmission path are analyzed to establish a laser transmission path; multiple power modes of the target hair removal device are determined; heat distribution is predicted based on the multiple power modes and the laser transmission path to establish a multi-mode heat distribution space network; the respective heat dissipation constraint spaces corresponding to the respective transmission stages in the laser transmission path are determined; the heat dissipation component distribution network of the target hair removal device is obtained, and heat dissipation defects are identified in combination with the multi-mode heat distribution space network and the respective heat dissipation constraint spaces to locate heat dissipation defective components and defect levels; the heat dissipation defective components are optimized based on the defect levels to generate heat dissipation component configuration optimization results. The hair removal device's heat dissipation component configuration is optimized based on the heat distribution prediction and heat dissipation defect identification, thereby optimizing the configuration of the heat dissipation components and achieving the technical effect of improving the heat dissipation performance of the hair removal device.

[0008] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, which can be implemented in accordance with the contents of the description, and to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are specifically listed below. It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easy to understand through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the technical solutions in this application or 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 merely exemplary, and a person of ordinary skill in the art can obtain other drawings based on the provided drawings without creative work.

[0010] Figure 1 This is a flow chart of a method for optimizing the configuration of a heat dissipation component of a hair removal device according to the present application.

[0011] Figure 2 This is a flow chart of establishing a multi-mode heat distribution space network in a method for optimizing the configuration of a heat dissipation component of a hair removal device according to the present application. DETAILED DESCRIPTION

[0012] This application provides a method for optimizing the configuration of the heat dissipation components of a hair removal device, addressing the existing technical problem of being unable to effectively address localized high temperature accumulation in the laser transmission path due to a lack of accurate analysis of heat distribution patterns in multiple power modes. Based on heat distribution prediction and heat dissipation defect identification, the heat dissipation component configuration of the hair removal device is optimized, thereby optimizing the configuration of the heat dissipation component and achieving the technical effect of improving the heat dissipation performance of the hair removal device.

[0013] Below, the technical solutions in this application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of this application, rather than all the embodiments of this application. It should be understood that this application is not limited to the example embodiments described herein. Based on the embodiments of this application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application. It should also be noted that, for the convenience of description, only the parts related to this application, rather than all of them, are shown in the accompanying drawings.

[0014] Please see the attached Figure 1 , this application provides a method for optimizing the configuration of a heat dissipation component of a hair removal device, which specifically includes the following steps:

[0015] Step 1: Analyze the generation and transmission path of the laser beam of the target hair removal device and establish the laser transmission path.

[0016] Specifically, the laser beam is a high-energy beam generated by the laser emission module inside the hair removal device. Its transmission path covers the complete process from the laser emission source to the targeted skin area. The heat characteristics in this process directly affect the heat dissipation performance of the hair removal device, so the laser transmission path needs to be modeled and quantified. The laser transmission path usually includes multiple stages, such as the laser generation stage, the laser modulation and shaping stage, the transmission of the laser beam along the reflector or optical fiber conduction path inside the hair removal device, the filtering stage, the laser focusing and output stage, etc. For example, the laser transmission path can include multiple stage nodes, laser-modulation and shaping lens-transmission reflector or optical fiber-filter and aperture-focusing lens-optical window-skin hair follicle, providing a basis for subsequent heat dissipation analysis.

[0017] Step 2: Determine multiple power modes of the target hair removal device.

[0018] Specifically, the power mode refers to the output power setting of the hair removal device in different working scenarios, which directly affects the intensity of laser energy release and heat distribution. Generally speaking, typical power modes include low power mode, medium power mode, and high power mode. For example, in low power mode, the laser output is set to 5W; in medium power mode, the laser output is 1W; and in high power mode, the laser output is 15W. The resulting multiple power modes lay the foundation for subsequent heat distribution analysis and heat dissipation design optimization.

[0019] Step 3: Predicting heat distribution based on the multiple power modes and the laser transmission path, and establishing a multi-mode heat distribution spatial network.

[0020] Specifically, by simulating the energy release and transfer patterns of lasers under different power modes, the characteristics of heat generation, diffusion, and accumulation within hair removal devices are revealed, providing quantitative data support for subsequent identification and optimization of heat dissipation defects. First, a spatial fit of heat generation is performed, combining the laser transmission path and multiple power modes. Heat generation is primarily determined by the energy absorption and conversion between the laser and internal components (such as lenses and reflectors) and the target tissue (skin). Taking the medium-power mode (10 W output) as an example, when the laser passes through the lens focal point, high energy accumulates at that point, generating significant heat. Temperature trends at different locations along the laser path are recorded to form a basic heat distribution dataset under multiple power modes. Next, the heat diffusion behavior is analyzed based on the material properties and structural characteristics of each component. The thermal conductivity of the material is a key parameter in heat diffusion analysis. A multimodal heat distribution spatial network is then established. This multimodal heat distribution spatial network can be mathematically represented as a three-dimensional grid, with each grid node corresponding to a temperature range, including the minimum and maximum temperatures achievable under various power modes. This approach enables global and refined heat distribution prediction, moving from a single mode to multiple modes.

[0021] Step 4: Determine each heat dissipation constraint space corresponding to each transmission stage in the laser transmission path.

[0022] Specifically, to optimize the heat dissipation performance of the hair removal device, determining the heat dissipation constraint space corresponding to each transmission stage in the laser transmission path is a key step in ensuring the safe and efficient operation of the device in different power modes. The heat dissipation constraint space defines the temperature control range for each transmission stage to avoid overheating that may damage the device or cause user discomfort. First, a temperature sensitivity analysis is conducted on each transmission stage in the laser transmission path (such as the laser source, optical elements, and target area) to evaluate the impact of temperature changes on device functions and material properties. The maximum and minimum temperature values ​​for each stage are determined, and the corresponding heat dissipation constraint space is constructed. The heat dissipation constraint space is a mathematical expression used to define the temperature distribution constraints of the device in different areas and conditions. In this way, the heat dissipation constraint space provides a clear target for subsequent heat dissipation defect identification and optimization design, enabling the hair removal device to maintain stable performance in multiple power modes while ensuring user safety and device life.

[0023] Step 5: Obtain the heat dissipation component distribution network of the target hair removal device, and identify heat dissipation defects in combination with the multi-mode heat distribution space network and the various heat dissipation constraint spaces to locate heat dissipation defective components and defect degrees.

[0024] Specifically, when optimizing the heat dissipation performance of a target hair removal device, identifying heat dissipation defects by obtaining a heat dissipation component distribution network and combining it with a multi-mode heat distribution spatial network and various heat dissipation constraint spaces is a crucial step in ensuring efficient device thermal management. First, the heat dissipation component distribution network of the target hair removal device is obtained. This model describes the spatial location of internal heat dissipation components (such as heat sinks, fans, and thermal pads) and their thermal connections to heat sources and other components. Using device design drawings and 3D scanning technology, an accurate distribution model can be constructed. For example, in a certain hair removal device, the heat sink covers the laser source area, the fan is located at the rear of the device, and the thermal pad connects the laser source to the heat sink, forming a series heat dissipation network. Subsequently, the heat dissipation component distribution network is combined with the multi-mode heat distribution spatial network and the heat dissipation constraint spaces to identify heat dissipation defects. The multi-mode heat distribution data is loaded into the heat dissipation component distribution model to simulate the heat transfer process during actual operation. The simulation results generate a stable temperature distribution network that reflects the temperature distribution of various device components under multiple power modes. This network is then compared with the limits of the heat dissipation constraint space to identify areas that do not meet the constraints and identify components with heat dissipation defects. Defectivity is typically expressed as a temperature difference, such as the difference between the stable temperature of a component with a heat dissipation defect and the heat dissipation constraint space. This allows for rapid identification of areas of insufficient heat dissipation, pinpointing defective components and their impact, and providing comprehensive and accurate data support for optimizing the cooling system.

[0025] Step six: Optimize the heat dissipation defect component based on the defect degree to generate a heat dissipation component configuration optimization result.

[0026] Specifically, based on the defectivity calculated in the previous analysis, the preset heat dissipation component optimization library is used to select suitable candidate components. Subsequently, the defective components are replaced based on the candidate components, and the optimization effect is verified through heat dissipation simulation analysis. For example, after replacing the new heat sink in the device, the temperature distribution in high-power mode is re-simulated, and the updated stable temperature distribution network is recorded. After multiple optimization and verification iterations, the target heat dissipation component that meets the heat dissipation constraints is finally determined, and the optimized heat dissipation component configuration scheme is generated as the heat dissipation component configuration optimization result. For example, the optimization results may include selecting a heat sink with a higher thermal conductivity, increasing the thickness of the thermal pad, or upgrading the heat dissipation capacity of the fan, thereby improving the heat dissipation performance of the hair removal device.

[0027] Further, as attached Figure 2 As shown, step three of this application includes:

[0028] Obtain material composition information of each component of the target hair removal device; perform heat generation fitting on the target hair removal device based on the multiple power modes to establish a heat generation space corresponding to the laser transmission path; perform heat diffusion analysis based on the heat generation space and the material composition information of each component to establish the multi-mode heat distribution space network.

[0029] Specifically, to comprehensively analyze the heat distribution of the target hair removal device and establish a multi-mode heat distribution space network, it is first necessary to obtain information on the material composition of each device component. The material composition directly determines its thermal conductivity, heat capacity, and heat dissipation characteristics. For example, commonly used materials for hair removal devices include high-thermal conductivity aluminum alloys, low-thermal conductivity engineering plastics, and quartz glass with optical properties. Based on the multiple power modes obtained, heat generation is fitted to construct the heat generation space of the laser transmission path. The power mode determines the energy density of the laser at different transmission nodes, so it is necessary to experimentally collect heat generation data under different modes. For example, in high-power mode (15W output), thermal sensors are used to monitor the temperature of multiple key nodes along the laser path. It is found that the temperature in the laser focus area reaches 85°C, while the temperatures before and after it are 60°C and 40°C, respectively. Using this data, the heat distribution curve of the laser transmission path can be fitted and a three-dimensional heat generation space can be generated. The temperature distribution within the space reflects the laws of heat accumulation and dissipation. After combining the heat generation space with the material composition information of each component, further heat diffusion analysis can be performed, and finally a multi-mode heat distribution space network can be established, in which each node records the temperature value in different power modes, showing the heat distribution characteristics of the hair removal device in different modes, and providing detailed basic data support for the subsequent identification of heat dissipation defects and optimization of heat dissipation components.

[0030] Furthermore, the present application further comprises the following steps:

[0031] With the multiple power modes as constraints, multiple heat generation monitoring data sets corresponding to the laser transmission path are collected; the heat generation range of each part of the target hair removal device is fitted using the multiple heat generation monitoring data sets to generate the heat generation space.

[0032] Specifically, during the process of optimizing the heat dissipation performance of a hair removal device, heat generation monitoring data from the laser transmission path is collected under various power mode constraints. Heat range fitting is then performed for each device component to generate a heat generation volume. This is a key step in constructing a thermal distribution model. This method ensures an accurate simulation of the hair removal device's thermal characteristics under actual operating conditions. First, experiments are designed to collect heat data using various power modes as constraints. For example, monitoring points are set along the laser transmission path, including the laser source, focusing lens, reflector, and target area, in low, medium, and high power modes. Temperature data is collected at these points using high-precision thermal sensors (such as thermocouples or infrared thermometers), generating a heat generation monitoring dataset. Next, based on these multiple heat generation monitoring datasets, heat generation range fitting is performed for each component of the target hair removal device. Simply put, the combined temperature range for the same location under various power modes is determined. This results in temperature ranges corresponding to multiple locations, generating the heat generation volume. The generated heat generation volume accurately reflects the heat load characteristics of the hair removal device under various power modes, laying a solid foundation for subsequent heat dissipation optimization design and thermal stability analysis.

[0033] Furthermore, the present application further comprises the following steps:

[0034] A heat transfer coefficient network is established based on the material composition information of each component; and heat diffusion analysis is performed based on the heat transfer coefficient network on the basis of the heat generation space to generate the multi-mode heat distribution space network.

[0035] Specifically, in optimizing the heat dissipation performance of the hair removal device, establishing a heat transfer coefficient network based on the material composition information of each component and performing heat diffusion analysis based on the heat generation space are key steps in accurately constructing a multi-mode heat distribution space network. This process combines the thermal physical properties of the material with the internal thermodynamic behavior of the device, providing a scientific basis for a comprehensive understanding of the flow path and distribution of heat. First, based on the material composition information of each component of the hair removal device, a heat transfer coefficient network is constructed. The heat transfer coefficient describes the conduction efficiency of heat flow between different materials, and its value is closely related to the thermal conductivity, contact area and interface conditions of the material. For example, the thermal conductivity of common components such as aluminum heat sinks is 205W / (m·K), the thermal conductivity of plastic housings is 0.2W / (m·K), and that of quartz glass lenses is 1.38W / (m·K). Experimental tests were conducted using a laser heating source to measure the thermal conductivity of each material. For example, a steady-state method determined that the temperature difference of an aluminum heat sink at a heat flux density of 50 W / m² was 0.24°C, verifying its thermal conductivity. These test results were then input into a mathematical model to construct a heat transfer coefficient network represented by nodes and edges, where nodes represent individual material units and edge weights represent thermal conductivity. Subsequently, a heat diffusion analysis was conducted based on the heat generation space and combined with the heat transfer coefficient network. This analysis simulates the distribution of heat flow in multiple materials. Using finite element analysis software, the heat transfer coefficient network was embedded in a three-dimensional spatial model to simulate the dynamic process of heat flow from high-temperature areas (e.g., the focal point, 80°C) to low-temperature areas (e.g., the outer casing, 30°C). The analysis results showed that the aluminum heat sink rapidly reduced the temperature gradient in the high-temperature area, while the plastic casing, due to its poor thermal conductivity, could lead to localized heat accumulation. This series of analyses generated a multimodal heat distribution spatial network. This network is a multi-layered three-dimensional thermal map that details the dynamic distribution of heat within the device under different power modes. For example, in high-power mode, the temperature distribution in the focused area of ​​the laser path ranges from 70°C to 90°C, while the temperature in areas away from the path ranges from 30°C to 50°C. In low-power mode, the overall temperature range decreases and the distribution becomes more uniform. This network provides direct insights for optimizing heat dissipation components, such as suggesting that the design team add high-thermal conductivity materials in areas of high heat accumulation or adjust the structure to improve thermal flow in areas of low heat dissipation efficiency.

[0036] Ultimately, the heat transfer coefficient network and heat diffusion analysis work together to construct a multi-mode heat distribution space network that accurately reflects the thermodynamic behavior of the hair removal device, laying a scientific data foundation for heat dissipation defect identification and optimization strategy design.

[0037] Furthermore, step 4 of this application includes:

[0038] A temperature sensitivity analysis is performed on each transmission stage to determine the maximum temperature value and the minimum temperature value corresponding to each transmission stage; and each heat dissipation constraint space is constructed based on the maximum temperature value and the minimum temperature value corresponding to each transmission stage.

[0039] Specifically, optimizing the heat dissipation performance of a hair removal device involves conducting a temperature sensitivity analysis of each stage of the laser transmission path, determining the maximum and minimum temperatures for each stage, and constructing a heat dissipation constraint based on this analysis. This is a crucial step in establishing a device's thermal management system. First, a temperature sensitivity analysis is conducted, combining experiments and simulations to assess the impact of temperature variations on device functionality, material properties, and safety. For example, for the laser source stage, experiments used thermocouples to measure operating temperatures at different power modes, and combined with beam quality monitoring tools to record the stability of the laser output. Experimental data showed that when the laser source temperature exceeded 85°C, its power fluctuation increased by 12%, indicating a significant impact of high temperatures on laser performance. Similarly, for the focusing lens stage, simulations of the refractive index changes of optical components at different temperatures revealed that when the temperature exceeded 70°C, the laser's focusing ability decreased by 8%, thereby reducing hair removal efficiency. Based on these analysis results, a temperature range was determined for each transmission stage. For example, the temperature constraint for the laser source was 20°C to 50°C, while for the optical lens, the temperature range was generally 25°C to 65°C to prevent optical performance degradation. Based on these temperature ranges, a heat dissipation constraint was constructed for each transmission stage. The thermal constraint space is a set of mathematical constraints that defines the permissible temperature range for each stage. This provides a clear thermal management target for each transmission stage, laying the foundation for optimizing the design of subsequent cooling components and quickly identifying thermal defects.

[0040] Furthermore, step five of this application includes:

[0041] A heat dissipation simulation analysis is performed using the heat dissipation component distribution network and the multi-mode heat distribution space network to generate simulation results, wherein the simulation results include a stable temperature distribution network of the target hair removal device; the stable temperature distribution network is compared with the various heat dissipation constraint spaces to identify defective parts that do not meet the heat dissipation constraint spaces, as well as the heat dissipation components corresponding to the defective parts, to generate the heat dissipation defective components; the stable temperature distribution of the defective parts is compared with the corresponding heat dissipation constraint spaces to generate the defect degree according to the degree of difference.

[0042] Specifically, a heat dissipation simulation analysis was first performed using a heat dissipation component distribution network and a multi-mode heat distribution space network. This heat dissipation simulation employed existing digital simulation technology to simulate the temperature distribution and heat dissipation behavior of the hair removal device under different power modes. For example, in high-power mode, heat generated by the laser source is transferred to the heat sink via a thermal pad, with the excess heat then removed by a fan. Finite element simulation tools were used to perform multiple simulations of the laser path and heat dissipation component area within a three-dimensional spatial model, generating a stable temperature distribution network. The simulation results provided temperature distribution data for key components within the device during stable operation, forming a stable temperature distribution network. The generated stable temperature distribution network was then compared with the heat dissipation constraint space for each transmission stage. The constraint space defines the allowable temperature range for each device component. During this comparison, areas that did not meet the heat dissipation constraints were identified as defective locations, and the corresponding heat dissipation components were located as defective heat dissipation components. The defectivity of each defective location was then calculated. The defectivity was quantified by the degree of difference between the stable temperature distribution and the corresponding heat dissipation constraint space. This analysis process clearly demonstrates the heat transfer and accumulation behavior within the device, helping to accurately locate the heat dissipation problem areas and their causes. Ultimately, the generated list of defective components and defect levels provides a detailed technical basis for the subsequent optimized design of heat dissipation components, and helps improve the thermal management performance and user experience of the hair removal device.

[0043] Furthermore, the present application further comprises the following steps:

[0044] Heat dissipation simulation is performed using the heat dissipation component distribution network and the multi-mode heat distribution space network, and the temperature monitoring data set of the target hair removal device is recorded after each heat dissipation simulation; based on the temperature monitoring data set, a central trend analysis is performed on the temperature data at the same point, and the stable temperature distribution network is established using the temperature concentration value.

[0045] Specifically, during the heat dissipation optimization process of the hair removal device, the temperature monitoring data set of the target device is recorded through heat dissipation simulation analysis, and based on this data, the temperature at the same point is analyzed for a centralized trend. A stable temperature distribution network is established with the temperature concentration value, which is the core method for evaluating the stability of the device's heat dissipation performance. First, a heat dissipation simulation is performed using the heat dissipation component distribution network and the multi-mode heat distribution space network. The heat transfer and heat dissipation behavior of the hair removal device in multiple power modes is simulated using existing simulation tools (such as ANSYS or COMSOL). The laser path, the physical parameters of the heat dissipation components (such as thermal conductivity and specific heat capacity), and the external environmental conditions (such as the air convection coefficient) are set in the simulation. After each simulation, the temperature monitoring data set is recorded at key locations of the device (such as the laser source, lens, heat sink, and housing surface). A typical data set may include the instantaneous temperature of each point. Next, a central tendency analysis was performed on the temperature monitoring data at the same point. Central tendency analysis aims to calculate representative values ​​of temperature data through statistical methods to eliminate the influence of random errors on the results. Common methods include calculating the mean, median, or mode. Based on the results of the central tendency analysis, a stable temperature distribution network is established with the concentrated temperature values. The stable temperature distribution network is a three-dimensional temperature field model. The nodes represent different locations of the device (such as the laser source, heat sink, etc.), and the node values ​​are the concentrated temperature values ​​of the corresponding points. Ultimately, the stable temperature distribution network reflects the characteristics of the internal heat distribution of the hair removal device after heat dissipation. It also provides a reliable data foundation for identifying heat dissipation defects and optimizing heat dissipation design, helping to improve the device's heat dissipation performance and user experience.

[0046] Furthermore, step six of this application includes:

[0047] Based on the defect degree, a set of candidate heat dissipation components whose heat dissipation range constraints match the defect degree is screened in a preset heat dissipation component optimization library; wherein, the preset heat dissipation component optimization library includes a plurality of historical heat dissipation components, and the plurality of historical heat dissipation components have heat dissipation range constraint tags; based on the candidate heat dissipation component set, a heat dissipation simulation analysis is performed on the heat dissipation defective components after replacement, and a target heat dissipation component with an updated stable temperature distribution network that satisfies the corresponding heat dissipation constraint space is generated; and the heat dissipation component configuration optimization result is generated using the target heat dissipation component.

[0048] Specifically, when optimizing the heat dissipation performance of the hair removal device, the core step of the optimization design is to screen the candidate heat dissipation components in the preset heat dissipation component optimization library based on the defectivity, select the target heat dissipation components that meet the heat dissipation constraint space through simulation analysis, and finally generate the heat dissipation component configuration optimization result. First, the optimization requirements are determined based on the defectivity. The preset heat dissipation component optimization library contains a variety of historical heat dissipation components, and their heat dissipation range constraints (such as thermal conductivity, maximum heat dissipation capacity) are marked. For the current problem, the optimization scheme of the heat sink can be screened, such as: aluminum heat sink, improved heat sink with increased fin area, enhanced air-cooled heat sink, etc. By screening with the defectivity matching principle, a set of candidate heat dissipation components whose heat dissipation range constraints meet the defectivity are selected. For example, the enhanced air-cooled heat sink mentioned above is suitable for high-temperature areas because its heat dissipation capacity is significantly improved and can be used as a candidate component. Next, defective components were replaced based on candidate heat sinks and simulation analysis was performed. Within the finite element simulation tool, heat sink parameters were updated and the heat transfer process was re-simulated. Using an enhanced air-cooled heat sink as an example, simulation results showed that the laser source temperature in high-power mode dropped from 70°C to 50°C, satisfying the heat dissipation constraints (laser source temperature ≤ 600°C). Through iterative optimization of the simulation analysis, an updated stable temperature distribution network was ultimately generated, and a target heat sink component that met all constraints was identified. For example, an enhanced air-cooled heat sink was ultimately selected as an alternative for the laser source region, while the thickness of the thermal pad was adjusted to further improve heat transfer efficiency. Finally, a complete heat sink configuration optimization result was generated based on the target heat sink and sent to the arch pendulum staff. Ultimately, the optimized heat sink configuration improved the device's heat dissipation performance.

[0049] In summary, the method for optimizing the configuration of the heat dissipation component of a hair removal device provided by this application has the following technical effects:

[0050] The target hair removal device's laser beam generation and transmission path are analyzed to establish a laser transmission path; multiple power modes of the target hair removal device are determined; heat distribution is predicted based on the multiple power modes and the laser transmission path to establish a multi-mode heat distribution space network; the respective heat dissipation constraint spaces corresponding to the respective transmission stages in the laser transmission path are determined; the heat dissipation component distribution network of the target hair removal device is obtained, and heat dissipation defects are identified in combination with the multi-mode heat distribution space network and the respective heat dissipation constraint spaces to locate heat dissipation defective components and defect levels; the heat dissipation defective components are optimized based on the defect levels to generate heat dissipation component configuration optimization results. The hair removal device's heat dissipation component configuration is optimized based on the heat distribution prediction and heat dissipation defect identification, thereby optimizing the configuration of the heat dissipation components and achieving the technical effect of improving the heat dissipation performance of the hair removal device.

[0051] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present application. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application is not limited to the embodiments shown herein, but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

[0052] Obviously, those skilled in the art may make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application is intended to include these modifications and variations.

Claims

1. A method for optimizing the configuration of a heat dissipation component of a hair removal device, characterized in that: include: Analyze the generation and transmission path of the laser beam of the target hair removal device and establish the laser transmission path; determining multiple power modes of the target hair removal device; Performing heat distribution prediction based on the multiple power modes and the laser transmission paths, and establishing a multi-mode heat distribution spatial network; Determining each heat dissipation constraint space corresponding to each transmission stage in the laser transmission path; Obtaining the heat dissipation component distribution network of the target hair removal device, and identifying heat dissipation defects in combination with the multi-mode heat distribution space network and the various heat dissipation constraint spaces, and locating heat dissipation defective components and defect levels; Optimizing the heat dissipation defect component based on the defect degree to generate a heat dissipation component configuration optimization result; The heat distribution prediction is performed based on the multiple power modes and the laser transmission path, and a multi-mode heat distribution spatial network is established, including: Obtaining material composition information of each component of the target hair removal device; Performing heat generation fitting on the target hair removal device based on the multiple power modes to establish a heat generation space corresponding to the laser transmission path; Conducting heat diffusion analysis based on the heat generation space and the material composition information of each component to establish the multi-mode heat distribution space network; The heat diffusion analysis is performed in combination with the material composition information of the heat generating space and the various components to establish the multi-mode heat distribution space network, including: establishing a heat transfer coefficient network based on the material composition information of each component; Based on the heat generation space, heat diffusion analysis is performed according to the heat transfer coefficient network to generate the multi-mode heat distribution space network; Determining each heat dissipation constraint space corresponding to each transmission stage in the laser transmission path includes: Performing temperature sensitivity analysis on each transmission stage to determine the maximum temperature value and the minimum temperature value corresponding to each transmission stage; Constructing each heat dissipation constraint space according to the maximum temperature value and the minimum temperature value corresponding to each transmission stage; The heat dissipation component distribution network of the target hair removal device is obtained, and heat dissipation defects are identified by combining the multi-mode heat distribution space network and the various heat dissipation constraint spaces to locate heat dissipation defective components and defect levels, including: Performing heat dissipation simulation analysis on the heat dissipation component distribution network and the multi-mode heat distribution space network to generate simulation results, wherein the simulation results include a stable temperature distribution network of the target hair removal device; Comparing the stable temperature distribution network with the respective heat dissipation constraint spaces, identifying defective parts that do not satisfy the heat dissipation constraint spaces, and heat dissipation components corresponding to the defective parts, and generating the heat dissipation defective components; The stable temperature distribution of the defective part is compared with the corresponding heat dissipation constraint space, and the defect degree is generated according to the degree of difference.

2. A method for optimizing the configuration of a heat dissipation component of a hair removal device according to claim 1, characterized in that: Performing heat generation fitting on the target hair removal device based on the multiple power modes to establish a heat generation space corresponding to the laser transmission path includes: collecting a plurality of heat generation monitoring data sets corresponding to the laser transmission path with the plurality of power modes as constraints; The heat generation range of each part of the target hair removal device is fitted using the multiple heat generation monitoring data sets to generate the heat generation space.

3. A method for optimizing the configuration of a heat dissipation component of a hair removal device according to claim 1, characterized in that: Performing heat dissipation simulation analysis on the heat dissipation component distribution network and the multi-mode heat distribution spatial network to generate simulation results includes: Performing heat dissipation simulation using the heat dissipation component distribution network and the multi-mode heat distribution spatial network, and recording a temperature monitoring data set of the target hair removal device after each heat dissipation simulation; Based on the temperature monitoring data set, a central trend analysis is performed on the temperature data at the same point, and the stable temperature distribution network is established based on the temperature concentration value.

4. A method for optimizing the configuration of a heat dissipation component of a hair removal device according to claim 1, characterized in that: Optimizing the heat dissipation defect component based on the defect degree to generate a heat dissipation component configuration optimization result, including: Based on the defectivity, screening a set of candidate heat dissipation components whose heat dissipation range constraints match the defectivity in a preset heat dissipation component optimization library; The preset heat dissipation component optimization library includes a plurality of historical heat dissipation components, and the plurality of historical heat dissipation components have heat dissipation range constraint marks; Performing a heat dissipation simulation analysis on the defective heat dissipation component after replacement based on the candidate heat dissipation component set to generate a target heat dissipation component with an updated stable temperature distribution network that satisfies the corresponding heat dissipation constraint space; The heat dissipation component configuration optimization result is generated using the target heat dissipation component.

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