Integral cooling fin production device

Abstract

The invention relates to the field of cooling fin production, in particular to an integral cooling fin production device which comprises a raw material supply module, a precision forming module, a real-time temperature control module, an automatic cutting module, a quality detection module and a control system module. A raw material supply module, a precision forming module, a real-time temperature control module, an automatic cutting module, a quality detection module and a control system module are arranged, and all the modules cooperate with one another to form a complete full-automatic production process. Close connection and information interaction among the modules realize continuity and high efficiency of the production process. The device solves the problems that in the prior art, production efficiency is low, product quality is unstable, and production parameters cannot be monitored and adjusted in real time, the production efficiency and quality of the cooling fins are remarkably improved, and the requirement of high-performance electronic equipment for the cooling assembly is met.

Description

Technical Field

[0001] The invention relates to the field of heat sink production, in particular to an integrated heat sink production device. Background Art

[0002] With the rapid improvement of the performance of electronic devices, the power consumption and heat generation of core components such as processors and graphics chips have increased significantly. As a key thermal management component in electronic devices, the performance of heat sinks directly affects the stability, reliability and service life of the equipment. At present, the production of heat sinks mainly relies on traditional manufacturing processes, including mechanical cutting, stamping, extrusion and welding. However, these traditional processes have many technical defects in meeting the needs of efficient heat dissipation and high-precision manufacturing.

[0003] First, the fin structure is difficult to optimize and it is difficult to meet the needs of efficient heat dissipation. Traditional mechanical processing methods are limited by equipment accuracy and processing capabilities when manufacturing complex and fine fin structures. The thickness, spacing and shape of the fins have an important impact on the heat dissipation performance, but due to the limitations of the processing technology, the optimal fin design cannot be achieved. This results in the heat dissipation efficiency of the heat sink failing to reach the ideal state and making it difficult to meet the requirements of high-performance electronic equipment for heat dissipation performance. In addition, the fin design requires a trade-off between heat dissipation performance and manufacturing cost, and the lack of effective optimization methods limits the improvement of the heat sink performance.

[0004] Secondly, microscopic defects are difficult to detect, which affects product quality and reliability. During the production process of heat sinks, microscopic defects such as internal cracks and pores are easily generated due to factors such as material defects and processing stress. These defects may lead to reduced mechanical strength and thermal conductivity of the heat sink, or even failure during use. Traditional quality inspection methods mainly rely on manual visual inspection and simple dimensional measurement, which cannot effectively detect internal microscopic defects. This results in unqualified products entering the market, affecting product reliability and user experience.

[0005] Third, the process parameters cannot be adjusted adaptively, and the production process lacks intelligence and flexibility. The manufacturing process of the heat sink is affected by many variables, such as material properties, ambient temperature, equipment status, etc. Traditional production equipment lacks advanced control systems, and process parameters (such as injection pressure, mold temperature, etc.) are usually set manually by operators based on experience, lacking the ability to monitor in real time and adaptively adjust. When production conditions change, the process parameters cannot be adjusted in time, resulting in fluctuations in product quality and reduced production efficiency. In addition, the lack of real-time analysis and feedback mechanism for production data makes it impossible to form closed-loop control, which limits the optimization and improvement of the production process.

[0006] In addition, the lack of effective collaboration and data sharing between production modules limits the improvement of production efficiency. Traditional production lines are usually composed of multiple independent modules, such as raw material supply, molding, cutting and testing. Due to the lack of a unified control system and communication interface, information exchange and collaborative work between modules are limited. This leads to the inability to fully utilize data in the production process (such as material properties, process parameters, quality inspection results), making it difficult to optimize the production process, affecting the overall production efficiency and product quality. Summary of the invention

[0007] The object of the present invention is to provide an integrated heat sink production device to solve the technical problems raised in the above background technology.

[0008] Based on the above ideas, the present invention provides the following technical solutions: an integrated heat sink production device, comprising:

[0009] Raw material supply module, precision molding module, real-time temperature control module, automatic cutting module, quality inspection module and control system module,

[0010] The raw material supply module is used to continuously supply the metal raw materials required for production, and is connected to the precision molding module through a conveying system to ensure the stable supply and delivery of raw materials;

[0011] The precision molding module uses high-pressure injection molding technology to process the raw materials into a predetermined heat sink shape. The precision molding module includes an adjustable mold and injection system, which cooperates with the real-time temperature control module to achieve precise control of the shape and size of the heat sink;

[0012] The real-time temperature control module includes a temperature sensor and a heating / cooling element, which monitors and adjusts the temperature in the precision molding module in real time. The real-time temperature control module is tightly coupled with the precision molding module;

[0013] The automatic cutting module accurately cuts the formed heat sink according to the preset size. The automatic cutting module is connected to the output end of the precision forming module. The automatic cutting module uses numerical control technology to achieve high-precision cutting of the heat sink and transmits the cut heat sink to the quality inspection module.

[0014] The quality inspection module uses optical inspection and ultrasonic inspection technology to inspect the quality of the heat sink. The quality inspection module is connected to the automatic cutting module to obtain the size, shape and internal structure information of the heat sink in real time to ensure that the product meets the quality standards;

[0015] The control system module includes a central processing unit and a human-computer interaction interface, which is communicated and connected with the raw material supply module, the precision molding module, the real-time temperature control module, the automatic cutting module and the quality inspection module, coordinates the work processes of each module, and collects and processes the operating data of the raw material supply module, the precision molding module, the real-time temperature control module, the automatic cutting module and the quality inspection module.

[0016] The beneficial effects of this technical solution are:

[0017] By setting up raw material supply module, precision molding module, real-time temperature control module, automatic cutting module, quality inspection module and control system module, each module cooperates with each other to form a complete fully automated production process. The close connection and information interaction between the modules realize the continuity and efficiency of the production process. The device solves the problems of low production efficiency, unstable product quality and inability to monitor and adjust production parameters in real time in the prior art, significantly improves the production efficiency and quality of the heat sink, and meets the needs of high-performance electronic equipment for heat dissipation components.

[0018] Preferably, the precision molding module includes a fin optimization algorithm for optimizing the heat sink fin structure, and the fin optimization algorithm includes the following steps:

[0019] S1. Obtaining raw material characteristics and expected heat dissipation performance parameters;

[0020] S2, calculating the optimal fin thickness based on the collected data;

[0021] S3, automatically adjust the key dimensions of the molding die according to the calculation results;

[0022] S4. Monitor the forming process in real time to ensure that the fin structure meets the calculated parameters.

[0023] The beneficial effects of this technical solution are:

[0024] Through data collection, parameter calculation, mold adjustment and molding control, the optimal fin thickness and spacing can be accurately calculated according to the raw material characteristics and expected heat dissipation performance parameters, and the mold size can be automatically adjusted. This algorithm solves the problem of difficult optimization of the heat sink fin structure, improves the heat dissipation efficiency, and ensures that the performance of the heat sink meets the design requirements.

[0025] Preferably, the fin thickness calculation formula includes:

[0026]

[0027] Where t is the fin thickness;

[0028] k is the thermal conductivity of the material;

[0029] Tmax is the maximum temperature allowed;

[0030] T amb is the ambient temperature;

[0031] h is the convective heat transfer coefficient;

[0032] A is the heat dissipation area.

[0033] The beneficial effects of this technical solution are:

[0034] The fin thickness calculation formula takes into account key factors such as the thermal conductivity of the material, the maximum allowable temperature, the ambient temperature, the convection heat transfer coefficient, and the heat dissipation area. By using this formula, the optimal fin thickness can be accurately calculated to ensure that the heat sink has the best heat dissipation performance in actual applications. This precise calculation method improves the accuracy of design and production, and reduces material waste and trial and error costs.

[0035] Preferably, the quality detection module includes a defect detection algorithm for detecting microscopic defects of the heat sink, and the defect detection algorithm includes the following steps:

[0036] S1, using an ultrasonic sensor to obtain an echo signal of the internal structure of the heat sink;

[0037] S2, filtering and amplifying the collected signal;

[0038] S3, determine abnormal features in the signal through pattern recognition technology;

[0039] S4. Determine whether the heat sink is qualified based on the recognition result and output a test report.

[0040] The beneficial effects of this technical solution are:

[0041] Ultrasonic sensors and pattern recognition technology are used to detect microscopic defects in heat sinks. The algorithm can accurately identify tiny defects inside the heat sink, solving the problem that traditional detection methods are difficult to detect tiny defects, greatly improving product quality, reducing defective product rates, and enhancing product reliability.

[0042] Preferably, a defect depth formula is used to identify abnormal features, and the defect depth formula includes:

[0043]

[0044] Where d is the depth of the defect from the sensor;

[0045] v is the propagation speed of ultrasound in the material;

[0046] Δt is the time difference between transmitting and receiving signals.

[0047] The beneficial effects of this technical solution are:

[0048] The defect depth formula can accurately calculate the depth of the defect from the sensor. This formula is based on the propagation speed of ultrasound in the material and the time difference between the transmitted and received signals, ensuring the accuracy and reliability of the test results. Accurate defect location helps to take remedial measures in a timely manner and reduce economic losses caused by product defects.

[0049] Preferably, it also includes a process adaptive adjustment algorithm, and the process adaptive adjustment algorithm includes:

[0050] S1, obtaining the fin thickness t calculated in the fin optimization algorithm and the defect depth d detected in the defect detection algorithm;

[0051] S2, performing correlation analysis on fin thickness and defect depth data to identify the relationship between parameter settings and defect generation during the production process;

[0052] S3. According to the analysis results, the process parameters of the precision molding module, such as injection pressure, mold temperature, etc., are adjusted in real time;

[0053] S4. Feedback the adjusted process parameters to the precision molding module and quality inspection module to form a closed-loop control and continuously optimize the production process.

[0054] The beneficial effects of this technical solution are:

[0055] The fin optimization algorithm and defect detection algorithm are organically linked. Through parameter collection, data analysis, process adjustment and feedback control, the algorithm can adjust the process parameters of the precision molding module, such as injection pressure and mold temperature, in real time according to the data of fin thickness and defect depth. The algorithm solves the problem that the process parameters cannot be adjusted adaptively during the production process, forms a closed-loop control of the production process, significantly improves the production quality and efficiency of the heat sink, and reduces the production cost.

[0056] Preferably, the process adaptive adjustment algorithm includes a parameter adjustment formula, and the parameter adjustment formula includes:

[0057]

[0058] Among them, P new is the adjusted process parameter (such as injection pressure or mold temperature);

[0059] P init Initially set process parameters;

[0060] k depends on the material properties and equipment characteristics;

[0061] d is the detected defect depth;

[0062] t is the thickness of the fin.

[0063] The beneficial effects of this technical solution are:

[0064] According to the ratio of defect depth to fin thickness, process parameters are adjusted dynamically. By using this formula, key process parameters such as injection pressure and mold temperature can be accurately adjusted, reducing the generation of defects and ensuring the stability and consistency of heat sink quality. This precise process adjustment method improves the flexibility and adaptability of the production process, further improving production efficiency and product quality.

[0065] Preferably, the process parameters include injection pressure or mold temperature.

[0066] Compared with the prior art, the present invention has the following beneficial effects:

[0067] The integrated heat sink production device of the present invention realizes full automation and continuity of the production process by integrating modules such as raw material supply, precision molding, real-time temperature control, automatic cutting and quality inspection. The close collaboration and information exchange between the modules greatly improves production efficiency and reduces manual intervention and downtime. Compared with traditional production methods, the production cycle is shortened and the production capacity is significantly improved, meeting the market's large-scale demand for high-performance heat sinks.

[0068] By introducing the fin optimization algorithm, defect detection algorithm and process adaptive adjustment algorithm, the optimization of the heat sink structure, the accurate detection of microscopic defects and the real-time adjustment of production process parameters are achieved. The fin optimization algorithm ensures that the heat sink has the best heat dissipation performance, the defect detection algorithm improves the reliability and consistency of the product, and the process adaptive adjustment algorithm forms a closed-loop control of the production process, further stabilizing the product quality. The comprehensive application of these algorithms has significantly improved the product qualification rate and performance indicators.

[0069] The present invention realizes real-time monitoring and coordination of each production module through the control system module, and forms an intelligent production system by organically linking multiple algorithms. The production process can automatically adjust process parameters according to real-time data to adapt to different raw material characteristics and production requirements. This intelligent and adaptive production method improves production flexibility and response speed, reduces production costs, reduces resource waste, and has significant economic and environmental benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Figure 1 The figure is a schematic diagram of the module relationship of an integrated heat sink production device of the present invention. DETAILED DESCRIPTION

[0071] An integrated heat sink production device, comprising:

[0072] Raw material supply module, precision molding module, real-time temperature control module, automatic cutting module, quality inspection module and control system module,

[0073] The raw material supply module is used to continuously supply the metal raw materials required for production, and is connected to the precision molding module through a conveying system to ensure the stable supply and delivery of raw materials;

[0074] The precision molding module uses high-pressure injection molding technology to process the raw materials into a predetermined heat sink shape. The precision molding module includes an adjustable mold and injection system, which cooperates with the real-time temperature control module to achieve precise control of the shape and size of the heat sink;

[0075] The real-time temperature control module includes a temperature sensor and a heating / cooling element, which monitors and adjusts the temperature in the precision molding module in real time. The real-time temperature control module is tightly coupled with the precision molding module;

[0076] The automatic cutting module accurately cuts the formed heat sink according to the preset size. The automatic cutting module is connected to the output end of the precision forming module. The automatic cutting module uses numerical control technology to achieve high-precision cutting of the heat sink and transmits the cut heat sink to the quality inspection module.

[0077] The quality inspection module uses optical inspection and ultrasonic inspection technology to inspect the quality of the heat sink. The quality inspection module is connected to the automatic cutting module to obtain the size, shape and internal structure information of the heat sink in real time to ensure that the product meets the quality standards;

[0078] The control system module includes a central processing unit and a human-computer interaction interface, which is communicated and connected with the raw material supply module, the precision molding module, the real-time temperature control module, the automatic cutting module and the quality inspection module, coordinates the work processes of each module, and collects and processes the operating data of the raw material supply module, the precision molding module, the real-time temperature control module, the automatic cutting module and the quality inspection module.

[0079] The beneficial effects of this technical solution are:

[0080] By setting up raw material supply module, precision molding module, real-time temperature control module, automatic cutting module, quality inspection module and control system module, each module cooperates with each other to form a complete fully automated production process. The close connection and information interaction between the modules realize the continuity and efficiency of the production process. The device solves the problems of low production efficiency, unstable product quality and inability to monitor and adjust production parameters in real time in the prior art, significantly improves the production efficiency and quality of the heat sink, and meets the needs of high-performance electronic equipment for heat dissipation components.

[0081] Preferably, the precision molding module includes a fin optimization algorithm for optimizing the heat sink fin structure, and the fin optimization algorithm includes the following steps:

[0082] S1. Obtaining raw material characteristics and expected heat dissipation performance parameters;

[0083] S2, calculating the optimal fin thickness based on the collected data;

[0084] S3, automatically adjust the key dimensions of the molding die according to the calculation results;

[0085] S4. Monitor the forming process in real time to ensure that the fin structure meets the calculated parameters.

[0086] The beneficial effects of this technical solution are:

[0087] Through data collection, parameter calculation, mold adjustment and molding control, the optimal fin thickness and spacing can be accurately calculated according to the raw material characteristics and expected heat dissipation performance parameters, and the mold size can be automatically adjusted. This algorithm solves the problem of difficult optimization of the heat sink fin structure, improves the heat dissipation efficiency, and ensures that the performance of the heat sink meets the design requirements.

[0088] In actual use:

[0089] S1. Install material property sensors, such as thermocouples, thermal conductivity meters, etc., in the raw material supply module to detect the thermal conductivity k and other physical properties of the metal raw materials in real time. Expected heat dissipation performance parameters (such as the maximum allowable temperature T max 、Ambient temperature T amb , convection heat transfer coefficient h, and heat dissipation area A) are input through the human-computer interaction interface of the control system module or read from the product design database.

[0090] S2. The central processing unit (CPU) or industrial computer in the control system module receives material properties and expected heat dissipation performance parameters, runs a built-in calculation program, and calculates the optimal fin thickness t using a formula.

[0091] S3, the mold of the precision molding module is equipped with an electric servo mechanism, including a high-precision stepper motor and a lead screw transmission device. The central processor sends the calculated optimal fin thickness t and fin spacing data to the mold control system to drive the servo mechanism to adjust the key dimensions of the mold.

[0092] The mold adjustment mechanism is equipped with a displacement sensor (such as a grating ruler or encoder) to monitor the position of the mold components in real time to ensure that the adjustment accuracy reaches the micron level. A closed-loop control system is used to correct the adjustment instructions based on the feedback displacement signal to ensure that the mold size accurately reaches the calculated value.

[0093] S4. Install a laser distance sensor or a high-precision displacement sensor in the molding cavity to monitor the actual thickness and spacing of the fins in real time. The sensor transmits the measurement data to the central processor in real time. The actual measurement value is compared with the calculated optimal parameters. If there is a deviation, the control system adjusts the injection pressure, speed and other process parameters, or fine-tunes the mold position to ensure molding quality.

[0094] Preferably, the fin thickness calculation formula includes:

[0095]

[0096] Where t is the fin thickness;

[0097] k is the thermal conductivity of the material;

[0098] T max is the maximum temperature allowed;

[0099] T amb is the ambient temperature;

[0100] h is the convective heat transfer coefficient;

[0101] A is the heat dissipation area.

[0102] The beneficial effects of this technical solution are:

[0103] The fin thickness calculation formula takes into account key factors such as the thermal conductivity of the material, the maximum allowable temperature, the ambient temperature, the convection heat transfer coefficient, and the heat dissipation area. By using this formula, the optimal fin thickness can be accurately calculated to ensure that the heat sink has the best heat dissipation performance in actual applications. This precise calculation method improves the accuracy of design and production, and reduces material waste and trial and error costs.

[0104] This formula is based on the steady-state heat conduction equation and the convection heat transfer formula. It solves the optimal fin thickness by balancing the heat conduction inside the fin and the heat dissipation on the surface.

[0105] Preferably, the quality detection module includes a defect detection algorithm for detecting microscopic defects of the heat sink, and the defect detection algorithm includes the following steps:

[0106] S1, using an ultrasonic sensor to obtain an echo signal of the internal structure of the heat sink;

[0107] S2, filtering and amplifying the collected signal;

[0108] S3, determine abnormal features in the signal through pattern recognition technology;

[0109] S4. Determine whether the heat sink is qualified based on the recognition result and output a test report.

[0110] The beneficial effects of this technical solution are:

[0111] Ultrasonic sensors and pattern recognition technology are used to detect microscopic defects in heat sinks. The algorithm can accurately identify tiny defects inside the heat sink, solving the problem that traditional detection methods are difficult to detect tiny defects, greatly improving product quality, reducing defective product rates, and enhancing product reliability.

[0112] In actual use:

[0113] S1. Configure an ultrasonic detection system in the quality detection module, including an ultrasonic transmitter and a receiver. Place the heat sink on the detection table and scan the heat sink with an ultrasonic probe.

[0114] Using a two-dimensional or three-dimensional mechanical motion platform, the ultrasonic probe is controlled to move along the set path and speed to achieve full coverage scanning of the heat sink. The transmitter emits an ultrasonic pulse that penetrates the heat sink. When encountering discontinuities (such as cracks and pores) inside the material, part of the wave is reflected and the receiver receives the reflected signal.

[0115] S2. The received original signal is transmitted to the signal processing unit through a high-speed data acquisition card, and the signal is pre-processed using a digital filter (such as a bandpass filter, a low-pass filter) to eliminate noise and interference. An adjustable gain amplifier is used to enhance weak signals and improve the signal-to-noise ratio. The analog signal is converted into a digital signal through an analog-to-digital converter (ADC) for subsequent digital processing.

[0116] S3. Run defect recognition software on a central processing unit or a dedicated digital signal processor (DSP), use pattern recognition technology (such as support vector machine, convolutional neural network) to analyze the processed signals and identify abnormal features.

[0117] S4. The identified defect information (such as location and size) is recorded in the database and displayed through the human-computer interaction interface. According to the preset quality standards (such as the maximum allowable defect size and location range), the heat sink is automatically determined to be qualified. For unqualified products, the system issues instructions to start the mechanical device to remove them from the production line or mark them for further inspection.

[0118] Preferably, a defect depth formula is used to identify abnormal features, and the defect depth formula includes:

[0119]

[0120] Where d is the depth of the defect from the sensor;

[0121] v is the propagation speed of ultrasound in the material;

[0122] Δt is the time difference between transmitting and receiving signals.

[0123] The beneficial effects of this technical solution are:

[0124] The defect depth formula can accurately calculate the depth of the defect from the sensor. This formula is based on the propagation speed of ultrasound in the material and the time difference between the transmitted and received signals, ensuring the accuracy and reliability of the test results. Accurate defect location helps to take remedial measures in a timely manner and reduce economic losses caused by product defects.

[0125] The principle of this formula: According to the propagation speed v of ultrasound in the material and the time difference Δt between ultrasound emission and reception, the depth d of the reflection point (i.e. the defect) from the probe is calculated.

[0126] Preferably, it also includes a process adaptive adjustment algorithm, and the process adaptive adjustment algorithm includes:

[0127] S1, obtaining the fin thickness t calculated in the fin optimization algorithm and the defect depth d detected in the defect detection algorithm;

[0128] S2, performing correlation analysis on fin thickness and defect depth data to identify the relationship between parameter settings and defect generation during the production process;

[0129] S3. According to the analysis results, the process parameters of the precision molding module, such as injection pressure, mold temperature, etc., are adjusted in real time;

[0130] S4. Feedback the adjusted process parameters to the precision molding module and quality inspection module to form a closed-loop control and continuously optimize the production process.

[0131] The beneficial effects of this technical solution are:

[0132] The fin optimization algorithm and defect detection algorithm are organically linked. Through parameter collection, data analysis, process adjustment and feedback control, the algorithm can adjust the process parameters of the precision molding module, such as injection pressure and mold temperature, in real time according to the data of fin thickness and defect depth. The algorithm solves the problem that the process parameters cannot be adjusted adaptively during the production process, forms a closed-loop control of the production process, significantly improves the production quality and efficiency of the heat sink, and reduces the production cost.

[0133] In actual use:

[0134] S1. The central processor obtains the current fin thickness t from the fin optimization algorithm and the defect depth d and defect rate data from the defect detection algorithm through the internal communication network. The collected data is stored in the database in chronological order or batches for subsequent analysis.

[0135] S2. Run data analysis software on the central processing unit and use statistical analysis and machine learning algorithms (such as linear regression and decision tree) to analyze the relationship between fin thickness, defect depth and process parameters.

[0136] Calculate the ratio of fin thickness t to defect depth d to evaluate the relative severity of defects in the fin. Identify the influence trend of process parameters (such as injection pressure and mold temperature) on defect generation by analyzing historical data.

[0137] S3. Based on the data analysis results, use the formula to calculate new process parameters.

[0138] S4. Continuously monitor the process effect after adjustment, collect new fin thickness and defect data, and repeat the data analysis and process adjustment process. Form an adaptive closed-loop control system to automatically optimize process parameters and maintain the stability of the production process. If the defect is still not improved after adjustment, the system prompts the operator that it may be necessary to check the equipment status or replace the raw materials.

[0139] Preferably, the process adaptive adjustment algorithm includes a parameter adjustment formula, and the parameter adjustment formula includes:

[0140]

[0141] Among them, P new is the adjusted process parameter (such as injection pressure or mold temperature);

[0142] P init Initially set process parameters;

[0143] k depends on the material properties and equipment characteristics;

[0144] d is the detected defect depth;

[0145] t is the thickness of the fin.

[0146] The beneficial effects of this technical solution are:

[0147] According to the ratio of defect depth to fin thickness, process parameters are adjusted dynamically. By using this formula, key process parameters such as injection pressure and mold temperature can be accurately adjusted, reducing the generation of defects and ensuring the stability and consistency of heat sink quality. This precise process adjustment method improves the flexibility and adaptability of the production process, further improving production efficiency and product quality.

[0148] By adjusting the process parameters, the fluidity and solidification characteristics of the material during the molding process are changed, thereby affecting the formation of defects. k is determined based on experiments or experience, reflecting the sensitivity of the process parameters to defects and ensuring that the adjustment range is appropriate. newThe data is sent to the control unit of the precision molding module and the real-time temperature control module. The control unit adjusts the corresponding equipment (such as the pressure controller of the injection molding machine and the mold temperature controller) to make the process parameters reach the new set values.

[0149] The process parameters include injection pressure or mold temperature.

Claims

1. An integrated heat sink production device, characterized in that: include: Raw material supply module, precision molding module, real-time temperature control module, automatic cutting module, quality inspection module and control system module, The raw material supply module is used to continuously supply the metal raw materials required for production, and is connected to the precision molding module through a conveying system to ensure the stable supply and delivery of raw materials; The precision molding module uses high-pressure injection molding technology to process the raw materials into a predetermined heat sink shape. The precision molding module includes an adjustable mold and injection system, which cooperates with the real-time temperature control module to achieve precise control of the shape and size of the heat sink; The real-time temperature control module includes a temperature sensor and a heating / cooling element, which monitors and adjusts the temperature in the precision molding module in real time. The real-time temperature control module is tightly coupled with the precision molding module; The automatic cutting module accurately cuts the formed heat sink according to the preset size. The automatic cutting module is connected to the output end of the precision forming module. The automatic cutting module uses numerical control technology to achieve high-precision cutting of the heat sink and transmits the cut heat sink to the quality inspection module. The quality inspection module uses optical inspection and ultrasonic inspection technology to inspect the quality of the heat sink. The quality inspection module is connected to the automatic cutting module to obtain the size, shape and internal structure information of the heat sink in real time to ensure that the product meets the quality standards; The control system module includes a central processing unit and a human-computer interaction interface, which is communicated and connected with the raw material supply module, the precision molding module, the real-time temperature control module, the automatic cutting module and the quality inspection module, coordinates the work processes of each module, and collects and processes the operating data of the raw material supply module, the precision molding module, the real-time temperature control module, the automatic cutting module and the quality inspection module.

2. The integrated heat sink production device according to claim 1, characterized in that: The precision molding module includes a fin optimization algorithm for optimizing the heat sink fin structure, and the fin optimization algorithm includes the following steps: S1. Obtaining raw material characteristics and expected heat dissipation performance parameters; S2, calculating the optimal fin thickness based on the collected data; S3, automatically adjust the key dimensions of the molding die according to the calculation results; S4. Monitor the forming process in real time to ensure that the fin structure meets the calculated parameters.

3. The integrated heat sink production device according to claim 2, characterized in that: The fin thickness calculation formula includes: Where t is the fin thickness; k is the thermal conductivity of the material; T max is the maximum temperature allowed; T amb is the ambient temperature; h is the convective heat transfer coefficient; A is the heat dissipation area.

4. The integrated heat sink production device according to claim 3, characterized in that: The quality inspection module includes a defect detection algorithm for detecting microscopic defects of the heat sink, and the defect detection algorithm includes the following steps: S1, using an ultrasonic sensor to obtain an echo signal of the internal structure of the heat sink; S2, filtering and amplifying the collected signal; S3, determine abnormal features in the signal through pattern recognition technology; S4. Determine whether the heat sink is qualified based on the recognition result and output a test report.

5. The integrated heat sink production device according to claim 5, characterized in that: The defect depth formula is used to identify abnormal features, and the defect depth formula includes: Where d is the depth of the defect from the sensor; v is the propagation speed of ultrasound in the material; Δt is the time difference between transmitting and receiving the signal.

6. The integrated heat sink production device according to claim 5, characterized in that: It also includes a process adaptive adjustment algorithm, which includes: S1, obtaining the fin thickness t calculated in the fin optimization algorithm and the defect depth d detected in the defect detection algorithm; S2, performing correlation analysis on fin thickness and defect depth data to identify the relationship between parameter settings and defect generation during the production process; S3. According to the analysis results, the process parameters of the precision molding module, such as injection pressure, mold temperature, etc., are adjusted in real time; S4. Feedback the adjusted process parameters to the precision molding module and quality inspection module to form a closed-loop control and continuously optimize the production process.

7. The integrated heat sink production device according to claim 6, characterized in that: The process adaptive adjustment algorithm includes a parameter adjustment formula, and the parameter adjustment formula includes: Among them, P new is the adjusted process parameter (such as injection pressure or mold temperature); P init Initially set process parameters; k depends on the material properties and the device characteristics; d is the detected defect depth; t is the thickness of the fin.

8. The integrated heat sink production device according to claim 7, characterized in that: The process parameters include injection pressure or mold temperature.

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