Method for optimizing configuration of heat dissipation assembly of hair removal instrument

Abstract

The invention provides a hair removal instrument heat dissipation assembly configuration optimization method, and relates to the technical field of heat dissipation analysis, and the method comprises the steps: building a laser transmission path; determining a plurality of power modes of the target hair removal instrument; establishing a multi-mode heat distribution space network; determining each heat dissipation constraint space corresponding to each transmission stage in the laser transmission path; heat dissipation defect identification is carried out, and a heat dissipation defect assembly and defect degree are positioned; and optimizing the heat dissipation defect component based on the defect degree to generate a heat dissipation component configuration optimization result. According to the method and the device, the technical problem that local high-temperature accumulation in a laser transmission path cannot be effectively solved due to lack of accurate analysis of a heat distribution rule in a multi-power mode in the prior art can be solved, and configuration optimization of the heat dissipation assembly of the hair removal instrument is carried out based on heat distribution prediction and heat dissipation defect identification; therefore, the configuration of the heat dissipation assembly is optimized, and the technical effect of improving the heat dissipation performance of the hair removal instrument is achieved.

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 equipment market, laser hair removal devices have been widely used as an efficient and convenient hair removal tool. Laser hair removal devices act on hair follicles through the precise emission of high-energy laser beams to achieve long-term hair removal effects. However, since laser equipment generates a lot of heat during operation, this heat not only comes from the high-power energy release of the laser source, but also includes the heat dissipation requirements of optical components such as lenses and reflectors and electronic components. If the heat dissipation system is not designed properly, it may not only cause overheating and damage to the components inside the device, but also reduce the stability of the laser output and the user experience.

[0003] In the prior art, the heat dissipation design of hair removal devices usually uses traditional components such as heat sinks, fans or thermal pads, relying on preset fixed configurations for heat management. However, these designs lack accurate analysis of the heat distribution law under multiple power modes and cannot effectively solve the problem of local high temperature accumulation in 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 component 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 multi-power modes.

[0005] In view of the above problems, the present application provides a method for optimizing the configuration of a heat dissipation component of a hair removal device, comprising: 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 defective degrees; optimizing the heat dissipation defective components based on the defective degrees, 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: Analyze the generation and transmission path of the laser beam of the target hair removal device, and establish a laser transmission path; determine multiple power modes of the target hair removal device; predict heat distribution based on the multiple power modes and the laser transmission path, and establish a multi-mode heat distribution space network; determine the various heat dissipation constraint spaces corresponding to each transmission stage in the laser transmission path; 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, locate heat dissipation defective components and defect levels; optimize the heat dissipation defective components based on the defect level, and generate heat dissipation component configuration optimization results. Optimize the heat dissipation component configuration 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.

[0007] 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, it can be implemented according to the contents of the specification, and in order 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 cited 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

[0008] In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0009] Figure 1 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.

[0010] Figure 2 A schematic diagram of the process 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

[0011] This application provides a method for optimizing the configuration of the heat dissipation component of a hair removal device, thereby solving the technical problem in the prior art that the heat distribution law under multiple power modes is not accurately analyzed, and thus the local high temperature accumulation in the laser transmission path cannot be effectively solved. The configuration of the heat dissipation component of the hair removal device is optimized based on the prediction of heat distribution and the identification of heat dissipation defects, 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.

[0012] Below, the technical solutions in the present application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments of the present application. It should be understood that the present application is not limited to the example embodiments described herein. Based on the embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application. It should also be noted that, for the convenience of description, only the parts related to the present application are shown in the accompanying drawings, rather than all of them.

[0013] Please see attached Figure 1 The present application provides a method for optimizing the configuration of a heat dissipation component of a hair removal device, which specifically includes the following steps: Step 1: Analyze the generation and transmission path of the laser beam of the target hair removal device and establish the laser transmission path.

[0014] Specifically, the laser beam is a high-energy beam generated by the laser emission module in 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. Exemplarily, 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, which provides a basis for subsequent heat dissipation analysis.

[0015] Step 2: Determine multiple power modes of the target hair removal device.

[0016] Specifically, the power mode refers to the output power setting of the hair removal device in different working scenarios, which directly affects the release intensity of laser energy and the 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; in high power mode, the laser output is 15W. Thus, multiple power modes are obtained, which lays the foundation for subsequent heat distribution analysis and heat dissipation design optimization.

[0017] Step three: Predict heat distribution based on the multiple power modes and the laser transmission paths, and establish a multi-mode heat distribution spatial network.

[0018] Specifically, by simulating the energy release and transfer law of the laser under different power modes, the generation, diffusion and accumulation characteristics of heat inside the hair removal device are revealed, providing quantitative data support for the subsequent identification and optimization of heat dissipation defects. First, the heat generation is spatially fitted in combination with the laser transmission path and multiple power modes. The generation of heat is mainly determined by the energy absorption and conversion between the laser and internal components (such as lenses, reflectors) and the target tissue (skin). Taking the medium power mode (10 W output) as an example, when the laser passes through the focus of the lens, it will accumulate high energy at this point and generate significant heat. The temperature change trend at different positions of the laser path is recorded to form a basic data set of heat distribution under multiple power modes. Next, according to the material properties and structural characteristics of each component, the heat diffusion behavior is analyzed. The thermal conductivity of the material is the key parameter for heat diffusion analysis, and then a multi-mode heat distribution space network is established. The multi-mode heat distribution space network can be mathematically represented as a three-dimensional grid, and each grid node corresponds to a temperature value range, including the range of the lowest and highest temperatures that can be achieved under multiple power modes. In this way, the heat distribution prediction achieves a global and refined expression from a single mode to multiple modes.

[0019] Step 4: Determine each heat dissipation constraint space corresponding to each transmission stage in the laser transmission path.

[0020] Specifically, in order 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 an important part of ensuring the safe and efficient operation of the device under different power modes. The heat dissipation constraint space defines the temperature control range of each transmission stage to avoid overheating and damage to the device or cause discomfort to the user. First, a temperature sensitivity analysis is performed on each transmission stage in the laser transmission path (such as laser source, optical element, and target area) to evaluate the impact of temperature changes on device functions and material properties, determine the maximum and minimum temperature values ​​of each stage, and construct the corresponding heat dissipation constraint space. The heat dissipation constraint space is a mathematical expression used to define the temperature distribution constraints of the device under different areas and conditions. In this way, the heat dissipation constraint space provides a clear goal for subsequent heat dissipation defect identification and optimization design, so that the hair removal device can maintain stable performance in multiple power modes while ensuring user safety and device life.

[0021] 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.

[0022] Specifically, when optimizing the heat dissipation performance of the target hair removal device, it is an important step to ensure the efficiency of the thermal management of the device by obtaining the heat dissipation component distribution network and combining the multi-mode heat distribution space network and each heat dissipation constraint space to identify heat dissipation defects. First, obtain the heat dissipation component distribution network of the target hair removal device. The heat dissipation component distribution network is a model that describes the spatial position of the heat dissipation elements (such as heat sinks, fans, and thermal pads) inside the device and their thermal connection relationship with the heat source and other components. Through equipment design drawings and three-dimensional scanning technology, an accurate distribution model can be constructed. For example, in a certain model of 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 and the heat sink to form a series heat dissipation network. Subsequently, the heat dissipation component distribution network is combined with the multi-mode heat distribution space network and the heat dissipation constraint space to identify heat dissipation defects, and the multi-mode heat distribution data is loaded into the heat dissipation component distribution model to simulate the heat transfer process in actual operation. The simulation results generate a stable temperature distribution network, which reflects the temperature distribution of each part of the device in multi-power mode, and is compared with the restricted range of the heat dissipation constraint space. The area that does not meet the constraint conditions can be identified and the heat dissipation defect component is obtained. Defectiveness is usually expressed as a temperature difference, such as the difference between the stable temperature of the component corresponding to the heat dissipation defective component and the heat dissipation constraint space. This can quickly identify areas with insufficient heat dissipation, identify defective components and their impact, and provide comprehensive and accurate data support for optimizing the heat dissipation system.

[0023] Step six: Optimize the heat dissipation defect component based on the defect degree to generate a heat dissipation component configuration optimization result.

[0024] 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 into 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.

[0025] Further, as attached Figure 2 As shown, step three of this application includes: 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 in combination with the heat generation space and the material composition information of each component to establish the multi-mode heat distribution space network.

[0026] Specifically, in order 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 the material composition information of each component of the device. The composition of the material directly determines its thermal conductivity, heat capacity and heat dissipation characteristics. For example, the commonly used materials for hair removal devices include high thermal conductivity aluminum alloy, low thermal conductivity engineering plastics and quartz glass with optical properties. Based on the multiple power modes that have been obtained, heat generation fitting is performed 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. Therefore, it is necessary to collect heat generation data in different modes through experiments. For example, in high power mode (15W output), the temperature of multiple key nodes on the laser path is monitored by thermal sensors. It is found that the temperature of the laser focus area reaches 85°C, while the temperature of the front and rear positions is 60°C and 40°C respectively. Through these 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 in the space reflects the law 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 ultimately a multi-mode heat distribution space network can be established, in which each node records the temperature value under different power modes, showing the heat distribution characteristics of the hair removal device under different modes, and providing detailed basic data support for the subsequent identification of heat dissipation defects and optimization of heat dissipation components.

[0027] Furthermore, the present application also includes the following steps: Taking 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 with the multiple heat generation monitoring data sets to generate the heat generation space.

[0028] Specifically, in the process of optimizing the heat dissipation performance of the hair removal device, the core step of constructing the heat distribution model is to collect the heat generation monitoring data of the laser transmission path through multiple power mode constraints, and to fit the heat range of each part of the device to generate the heat generation space. This method ensures the accurate simulation of the heat characteristics of the hair removal device under actual working conditions. First, with multiple power modes as constraints, the experiment is designed to collect heat data. For example, in low power mode, medium power mode and high power mode, monitoring points are set along the laser transmission path, including the laser source, focusing lens, reflector and target area. High-precision thermal sensors (such as thermocouples or infrared thermometers) are used to collect temperature data at these points, and a heat generation monitoring data set is generated. Next, according to multiple heat generation monitoring data sets, the heat generation range of each part of the target hair removal device is fitted. In simple terms, it is to determine the comprehensive temperature range of the same position under multiple power modes, thereby obtaining the temperature ranges corresponding to multiple positions, and generating the heat generation space. The generated heat generation space truly reflects the heat load characteristics of the hair removal device under multiple power modes, laying a reliable foundation for subsequent heat dissipation optimization design and thermal stability analysis.

[0029] Furthermore, the present application also includes the following steps: A heat transfer coefficient network is established 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.

[0030] 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 properties of the material with the thermodynamic behavior inside 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). Through experiments, the thermal conductivity of each material was tested using a laser heating source. For example, the temperature difference of the aluminum heat sink when the heat flux density was 50W / m² was measured by the steady-state method to be 0.24℃, verifying its thermal conductivity efficiency. These test results were input into the mathematical model to construct a heat transfer coefficient network represented by nodes and edges, where the nodes represent each material unit and the weight of the edge represents the thermal conductivity. Subsequently, based on the heat generation space, the heat diffusion analysis was carried out in combination with the heat transfer coefficient network. The heat diffusion analysis is to simulate the distribution behavior of heat flow in multiple materials. The finite element analysis software can be used to embed the heat transfer coefficient network into a three-dimensional space model to simulate the dynamic process of heat flow diffusing from high-temperature areas (such as focal points, 80℃) to low-temperature areas (such as shells, 30℃). The analysis results show that aluminum heat sinks can quickly reduce the temperature gradient in high-temperature areas, while plastic shells may cause local heat accumulation due to poor thermal conductivity. Through this series of analyses, a multi-mode heat distribution space network was generated. This network is a multi-level three-dimensional thermal distribution map that presents in detail the dynamic distribution of heat in the device under different power modes. For example, in high-power mode, the temperature distribution in the focused area of ​​the laser path is 70°C-90°C, while the temperature in the area away from the path is 30°C-50°C; in low-power mode, the temperature range is reduced overall and the distribution is more uniform. This network provides a direct reference for optimizing heat dissipation components, such as prompting the design team to add high thermal conductivity materials in areas with high heat accumulation, or adjust the structure in areas with low heat dissipation efficiency to improve thermal fluidity.

[0031] 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.

[0032] Further, step 4 of this application includes: 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.

[0033] Specifically, in the process of optimizing the heat dissipation performance of the hair removal device, it is an important step to establish the thermal management system of the device by analyzing the temperature sensitivity of each transmission stage of the laser transmission path, determining the maximum and minimum temperature values ​​of each stage, and constructing the heat dissipation constraint space based on this. First, a temperature sensitivity analysis is performed to evaluate the impact of temperature changes on device functions, material properties, and safety by combining experiments and simulations. For example, for the laser source stage, a thermocouple is used in the experiment to measure the operating temperature under different power modes, and the stability of the laser output is recorded in combination with the beam quality monitoring tool. When the laser source temperature exceeds 85°C, the experimental data shows that its power fluctuation amplitude increases by 12%, indicating a significant impact of high temperature on the performance of the laser. Similarly, for the focusing lens stage, by simulating the refractive index changes of optical components at different temperatures, it is found that when the temperature is higher than 70°C, the focusing ability of the laser is weakened by 8%, thereby reducing the hair removal efficiency. Based on these analysis results, the temperature range of each transmission stage is determined. For example, the temperature constraint range of the laser source is 20°C to 50°C, and for the optical lens, the temperature range is generally 25°C to 65°C to avoid optical performance degradation. Based on the above temperature range, the heat dissipation constraint space of each transmission stage is constructed. The heat dissipation constraint space is a set of mathematical constraints that defines the allowable range of temperature changes in each stage. The heat dissipation constraint space corresponding to each transmission stage is obtained, which provides a clear thermal management target and lays the foundation for the subsequent optimization design of heat dissipation components and the rapid identification of heat dissipation defects.

[0034] Further, step five of this application includes: Perform 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; compare the stable temperature distribution network with the various heat dissipation constraint spaces, identify defective parts that do not meet the heat dissipation constraint spaces, and the heat dissipation components corresponding to the defective parts, and generate the heat dissipation defective components; compare the stable temperature distribution of the defective parts with the corresponding heat dissipation constraint spaces, and generate the defect degree according to the degree of difference.

[0035] Specifically, first, the heat dissipation component distribution network and the multi-mode heat distribution space network are used to perform heat dissipation simulation analysis. The heat dissipation simulation uses existing digital simulation technology to simulate the temperature distribution behavior and heat dissipation behavior of the hair removal device under different power modes. For example, in high-power mode, the heat generated by the laser source is transferred to the heat sink through the thermal pad, and then the residual heat is taken away by the fan. The finite element simulation tool is used to simulate the laser path and the heat dissipation component area multiple times in the three-dimensional space model, and a stable temperature distribution network is generated. The simulation results provide the temperature distribution data of each key component inside the device during stable operation, forming a stable temperature distribution network. Then, the generated stable temperature distribution network is compared with the heat dissipation constraint space of each transmission stage. The constraint space defines the allowable temperature range of each component of the device. During the comparison process, the area that does not meet the heat dissipation constraint conditions is identified as a defective part, and the corresponding heat dissipation component is located as a heat dissipation defective component, and then the defect degree of each defective part is calculated. The defect degree is 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 inside the device, helping to accurately locate the heat dissipation problem area and its cause. Ultimately, the generated defective components and defect degree list provides a detailed technical basis for the subsequent optimized design of heat dissipation components, and helps to improve the thermal management performance and user experience of the hair removal device.

[0036] Furthermore, the present application also includes the following steps: 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 centralized trend analysis is performed on the temperature data at the same point, and the stable temperature distribution network is established using the temperature centralized value.

[0037] Specifically, in the process of heat dissipation optimization of the hair removal device, the temperature monitoring data set of the target device is recorded through heat dissipation simulation analysis, and the temperature at the same point is analyzed based on these data. The core method of evaluating the stability of the device's heat dissipation performance is to establish a stable temperature distribution network with the temperature concentration value. First, the 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 are simulated through existing simulation tools (such as ANSYS or COMSOL). The laser path, the physical parameters of the heat dissipation components (such as thermal conductivity, specific heat capacity) and the external environmental conditions (such as 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 shell surface). A typical data set may include the instantaneous temperature of each point. Next, the temperature monitoring data at the same point is subjected to a central trend analysis. The central trend analysis aims to calculate the representative value of the 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 trend analysis, a stable temperature distribution network is established with the temperature concentration value. The stable temperature distribution network is a three-dimensional temperature field model. The nodes represent different locations of the device (such as laser source, heat sink, etc.), and the node values ​​are the temperature concentration 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, and also provides a reliable data basis for identifying heat dissipation defects and optimizing heat dissipation design, which helps to improve the heat dissipation performance of the device and the user experience.

[0038] Furthermore, step six of this application includes: Based on the defect degree, a set of candidate heat dissipation components whose heat dissipation range constraints match the defect degree are screened in a preset heat dissipation component optimization library; wherein the preset heat dissipation component optimization library includes a variety of historical heat dissipation components, and the various 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.

[0039] Specifically, when optimizing the heat dissipation performance of the hair removal device, the candidate heat dissipation components in the preset heat dissipation component optimization library are screened based on the defect degree, and the target heat dissipation components that meet the heat dissipation constraint space are selected through simulation analysis. Finally, the heat dissipation component configuration optimization result is generated, which is the core link of the optimization design. First, the optimization requirements are determined according to the defect degree. 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 defect degree matching principle, a set of candidate heat dissipation components whose heat dissipation range constraints meet the defect degree are selected. For example, the above-mentioned enhanced air-cooled heat sink is suitable for high-temperature areas, and can be used as a candidate component because its heat dissipation capacity is significantly improved. Next, the defective components were replaced based on the candidate heat dissipation components and simulation analysis was performed. In the finite element simulation tool, the heat dissipation component parameters were updated and the heat transfer process was re-simulated. Taking the enhanced air-cooled heat sink as an example, the simulation results showed that the laser source temperature dropped from 70°C to 50°C in high-power mode, satisfying the heat dissipation constraint space (laser source temperature ≤ 600°C). Through iterative optimization of simulation analysis, an updated stable temperature distribution network was finally generated, and the target heat dissipation component that met all constraints was determined. For example, the enhanced air-cooled heat sink was finally selected as an alternative to the laser source area, and the thickness of the thermal pad was adjusted to further improve the heat transfer efficiency. Finally, the complete heat dissipation component configuration optimization results were generated with the target heat dissipation component and sent to the arch pendulum staff. In the end, the optimized heat dissipation component configuration improved the heat dissipation performance of the equipment.

[0040] In summary, the method for optimizing the configuration of the heat dissipation component of a hair removal device provided in this application has the following technical effects: Analyze the generation and transmission path of the laser beam of the target hair removal device, and establish a laser transmission path; determine multiple power modes of the target hair removal device; predict heat distribution based on the multiple power modes and the laser transmission path, and establish a multi-mode heat distribution space network; determine the various heat dissipation constraint spaces corresponding to each transmission stage in the laser transmission path; 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, locate heat dissipation defective components and defect levels; optimize the heat dissipation defective components based on the defect level, and generate heat dissipation component configuration optimization results. Optimize the heat dissipation component configuration 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.

[0041] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those 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 will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

[0042] Obviously, those skilled in the art can 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 belong to the scope of the present application and its equivalent technology, the present application is also 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; Predicting heat distribution based on the multiple power modes and the laser transmission paths, and establishing a multi-mode heat distribution spatial network; Determine 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 each heat dissipation constraint space, and locating heat dissipation defective components and defective degrees; The heat dissipation defective component is optimized based on the defect degree to generate a heat dissipation component configuration optimization result.

2. A method for optimizing the configuration of a heat dissipation component of a hair removal device as claimed in claim 1, characterized in that: Heat distribution prediction is performed based on the multiple power modes and the laser transmission paths, and a multi-mode heat distribution spatial network is established, including: Obtaining 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; 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.

3. A method for optimizing the configuration of a heat dissipation component of a hair removal device as claimed in claim 2, 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.

4. A method for optimizing the configuration of a heat dissipation component of a hair removal device as claimed in claim 2, characterized in that: Combining the heat generation space and the material composition information of each component to perform heat diffusion analysis and 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.

5. A method for optimizing the configuration of a heat dissipation component of a hair removal device as claimed in claim 1, characterized in that: 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; The respective heat dissipation constraint spaces are constructed with the highest temperature value and the lowest temperature value corresponding to the respective transmission stages.

6. A method for optimizing the configuration of a heat dissipation component of a hair removal device as claimed in claim 1, characterized in that: 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 defective degrees, including: Performing heat dissipation simulation analysis 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; 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 and the corresponding heat dissipation constraint space are compared, and the defect degree is generated according to the degree of difference.

7. A method for optimizing the configuration of a heat dissipation component of a hair removal device as claimed in claim 6, characterized in that: Performing heat dissipation simulation analysis on the heat dissipation component distribution network and the multi-mode heat distribution space network to generate simulation results includes: Performing heat dissipation simulation using the heat dissipation component distribution network and the multi-mode heat distribution space 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 with the temperature central value.

8. A method for optimizing the configuration of a heat dissipation component of a hair removal device as claimed in claim 6, characterized in that: The heat dissipation defective component is optimized based on the defect degree to generate a heat dissipation component configuration optimization result, including: Based on the defect degree, screening a set of candidate heat dissipation components whose heat dissipation range constraints match the defect degree 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 marks; Based on the candidate heat dissipation component set, a heat dissipation simulation analysis is performed on the heat dissipation defective component after replacement, to generate a target heat dissipation component that updates a stable temperature distribution network to satisfy a corresponding heat dissipation constraint space; The heat dissipation component configuration optimization result is generated using the target heat dissipation component.

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