An integrated heat sink production device

Abstract

The present invention relates to the field of heat sink production, specifically an integrated heat sink production device, including: a raw material supply module, a precision forming module, a real-time temperature control module, an automatic cutting module, a quality inspection module, and a control system module. By setting up the raw material supply module, the precision forming module, the real-time temperature control module, the automatic cutting module, the quality inspection module, and the control system module, the modules cooperate with each other to form a complete fully automated production process. The close connection and information interaction between the modules achieve the continuity and high efficiency of the production process. This 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 heat sinks, and meets the requirements of high-performance electronic devices for heat dissipation components.

Description

Technical Field

[0001] The present invention relates to the field of heat sink production, and specifically 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 devices. Currently, 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 requirements of high-efficiency heat dissipation and high-precision manufacturing.

[0003] First, it is difficult to optimize the fin structure and meet the requirements of high-efficiency heat dissipation. Traditional machining methods are limited by the equipment accuracy and processing ability 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 not reaching the ideal state and being difficult to meet the requirements of high-performance electronic devices for heat dissipation performance. In addition, fin design requires a trade-off between heat dissipation performance and manufacturing cost, and the lack of effective optimization means limits the improvement of heat sink performance.

[0004] Second, it is difficult to detect microscopic defects, which affects product quality and reliability. During the production process of heat sinks, due to factors such as material defects and processing stress, internal cracks, pores, and other microscopic defects are likely to occur. These defects may lead to a decrease in the mechanical strength and heat conduction performance of the heat sink, and even failure during use. Traditional quality inspection methods mainly rely on manual visual inspection and simple dimensional measurement, and cannot effectively detect internal microscopic defects. This results in unqualified products possibly entering the market, affecting product reliability and user experience.

[0005] Third, the process parameters cannot be adaptively adjusted, and the production process lacks intelligence and flexibility. The manufacturing process of heat sinks is affected by various variables, such as material properties, environmental temperature, and equipment status. Traditional production equipment lacks advanced control systems, and process parameters (such as injection pressure, mold temperature, etc.) are usually manually set by operators based on experience, lacking the ability of real-time monitoring and adaptive adjustment. When production conditions change, the process parameters cannot be adjusted in a timely manner, resulting in fluctuations in product quality and a decrease in production efficiency. In addition, the lack of real-time analysis and feedback mechanism for production data cannot form a closed-loop control, limiting the optimization and improvement of the production process.

[0006] In addition, the lack of effective coordination and data sharing among production modules restricts the improvement of production efficiency. Traditional production lines usually consist of multiple independent modules, such as raw material supply, forming, cutting, and inspection. Due to the lack of a unified control system and communication interface, the information exchange and collaborative work among modules are limited. This results in the underutilization of data during the production process (such as material properties, process parameters, and quality inspection results), making it difficult to optimize the production process and affecting the overall production efficiency and product quality. Summary of the Invention

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

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

[0009] A raw material supply module, a precision forming module, a real-time temperature control module, an automatic cutting module, a quality inspection module, and a 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 forming module through a conveying system to ensure the stable supply and conveyance of raw materials;

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

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

[0013] The automatic cutting module precisely cuts the formed heat sink according to preset dimensions. 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 transports the cut heat sink to the quality inspection module;

[0014] The quality inspection module uses optical inspection and ultrasonic inspection technologies 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, ensuring that the product meets the quality standards;

[0015] The control system module includes a central processing unit and a human-machine interface, and is communicatively connected to the raw material supply module, the precision forming 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 operation data of the raw material supply module, the precision forming 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 the raw material supply module, the precision forming module, the real-time temperature control module, the automatic cutting module, the quality inspection module, and the control system module, each module cooperates with each other to form a complete fully automated production process. The close connection and information interaction between each module achieve the continuity and high efficiency of the production process. This 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 heat sinks, and meets the requirements of high-performance electronic devices for heat dissipation components.

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

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

[0020] S2. Calculate the optimal fin thickness according to the collected data;

[0021] S3. Automatically adjust the key dimensions of the forming die according to the calculation results;

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

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

[0024] Through steps such as data collection, parameter calculation, die adjustment, and forming control, it is possible to accurately calculate the optimal fin thickness and spacing according to the raw material characteristics and expected heat dissipation performance parameters, and automatically adjust the die dimensions. This algorithm solves the problem of difficult optimization of the fin structure of heat sinks, 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 allowable temperature;

[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 comprehensively considers key factors such as the thermal conductivity of the material, the maximum allowable temperature, the ambient temperature, the convective 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 practical applications. This precise calculation method improves the accuracy of design and production, reduces material waste and trial-and-error costs.

[0035] Preferably, 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:

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

[0037] S2. Filter and amplify the collected signal;

[0038] S3. Judge the abnormal features in the signal through pattern recognition technology;

[0039] S4. Determine whether the heat sink is qualified according to the recognition result and output a detection report.

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

[0041] Use an ultrasonic sensor and pattern recognition technology to detect microscopic defects of the heat sink. This algorithm can accurately identify tiny defects inside the heat sink, solve the problem that traditional detection methods are difficult to detect tiny defects, greatly improve product quality, reduce the defective rate, and enhance product reliability.

[0042] Preferably, an abnormal feature is identified using a defect depth formula, 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 ultrasonic waves in the material;

[0046] Δt is the time difference between the transmitted and received signals.

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

[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 ultrasonic waves in the material and the time difference between the transmitted and received signals, ensuring the accuracy and reliability of the detection results. Accurate defect positioning helps to take remedial measures in a timely manner, reducing the economic losses caused by product defects.

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

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

[0051] S2. Conduct a correlation analysis on the 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, adjust the process parameters of the precision forming module in real time, such as injection pressure, mold temperature, etc.;

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

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

[0055] It realizes the organic linkage of the fin optimization algorithm and the defect detection algorithm. Through steps such as parameter collection, data analysis, process adjustment, and feedback control, this algorithm can adjust the process parameters of the precision forming module in real time according to the data of fin thickness and defect depth, such as injection pressure, mold temperature, etc. This algorithm solves the problem that the process parameters cannot be adaptively adjusted 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] Where P new is the adjusted process parameter (such as injection pressure or mold temperature);

[0059] P init is the initially set process parameter;

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

[0061] d is the detected defect depth;

[0062] t is the fin thickness.

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

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

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

[0066] Compared with the prior art, the beneficial effects of the present invention are:

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

[0068] By introducing fin optimization algorithms, defect detection algorithms, and process adaptive adjustment algorithms, the optimization of the heat sink structure, the precise detection of micro-defects, and the real-time adjustment of production process parameters are realized. 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. By comprehensively applying these algorithms, both the product qualification rate and performance indicators are significantly improved.

[0069] The present invention realizes the real-time monitoring and coordination of each production module through the control system module, and forms an intelligent production system by the organic linkage of 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 the flexibility and response speed of production, reduces production costs, and reduces resource waste, with significant economic and environmental benefits. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0071] An integrated heat sink production device includes:

[0072] Raw material supply module, precision forming 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 forming module through a conveying system to ensure the stable supply and conveyance of the raw materials;

[0074] The precision forming module processes the raw materials into a predetermined heat sink shape by using high-pressure injection molding technology. The precision forming module includes an adjustable mold and an injection system, and 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 heating / cooling elements, and monitors and adjusts the temperature in the precision forming module in real time. The real-time temperature control module is tightly coupled with the precision forming module;

[0076] The automatic cutting module precisely 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 technologies 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, ensuring that the product meets the quality standards;

[0078] The control system module includes a central processing unit and a human-machine interface, and is communicatively connected to the raw material supply module, precision forming module, real-time temperature control module, automatic cutting module and quality inspection module to coordinate the work processes of each module and collect and process the operation data of the raw material supply module, precision forming module, real-time temperature control module, automatic cutting module and quality inspection module.

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

[0080] By setting up the raw material supply module, precision forming 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 each module achieve the continuity and high efficiency of the production process. This device solves the problems of low production efficiency, unstable product quality and inability to monitor and adjust production parameters in real time in the existing technology, significantly improves the production efficiency and quality of the heat sink, and meets the requirements of high-performance electronic devices for heat dissipation components.

[0081] Preferably, the precision forming module includes a fin optimization algorithm for optimizing the fin structure of the heat sink. The fin optimization algorithm includes the following steps:

[0082] S1. Obtain the raw material properties and expected heat dissipation performance parameters;

[0083] S2. Calculate the optimal fin thickness based on the collected data;

[0084] S3. Automatically adjust the key dimensions of the forming die according to the calculation results;

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

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

[0087] Through steps such as data acquisition, parameter calculation, die adjustment, and forming control, it is possible to accurately calculate the optimal fin thickness and spacing according to the raw material properties and expected heat dissipation performance parameters, and automatically adjust the die size. This algorithm solves the problem that it is difficult to optimize the fin structure of the heat sink, improves the heat dissipation efficiency, and ensures that the performance of the heat sink meets the design requirements.

[0088] During actual use:

[0089] S1. Install material property sensors, such as thermocouples and thermal conductivity measuring instruments, in the raw material supply module to detect the thermal conductivity k and other physical properties of the metal raw material in real time. The expected heat dissipation performance parameters (such as the maximum allowable temperature T max , ambient temperature T amb , convective heat transfer coefficient h, and heat dissipation area A) are input through the human-machine 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 the material properties and expected heat dissipation performance parameters, runs the built-in calculation program, and calculates the optimal fin thickness t using the formula.

[0091] S3. The die of the precision forming module is equipped with an electric servo mechanism, including a high-precision stepping motor and a lead screw drive device. The central processing unit sends the calculated optimal fin thickness t and fin spacing data to the die control system, driving the servo mechanism to adjust the key dimensions of the die.

[0092] The die adjustment mechanism is equipped with displacement sensors (such as grating scales or encoders) to monitor the position of the die components in real time, ensuring that the adjustment accuracy reaches the micron level. A closed-loop control system is adopted to correct the adjustment instructions according to the feedback displacement signal to ensure that the die size accurately reaches the calculated value.

[0093] S4. Install a laser distance sensor or a high-precision displacement sensor in the forming cavity to monitor the actual thickness and spacing of the fins in real time. The sensor transmits the measured data to the central processor in real time. Compare the actual measured values with the calculated optimal parameters. If there is a deviation, the control system adjusts process parameters such as injection pressure and speed, or finely tunes the mold position to ensure the forming 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 allowable temperature;

[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 comprehensively considers key factors such as the thermal conductivity of the material, the maximum allowable temperature, the ambient temperature, the convective 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 practical applications. This precise calculation method improves the accuracy of design and production, reducing material waste and trial-and-error costs.

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

[0105] Preferably, 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:

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

[0107] S2. Filter and amplify the collected signal;

[0108] S3. Judge the abnormal features in the signal through pattern recognition technology;

[0109] S4. Determine whether the heat sink is qualified according to the recognition result and output a detection report.

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

[0111] By using ultrasonic sensors and pattern recognition technology, the heat sink is detected for microscopic defects. This algorithm can accurately identify the tiny defects inside the heat sink, solve the problem that it is difficult to detect tiny defects with traditional detection methods, greatly improve the product quality, reduce the defective rate, and enhance the reliability of the product.

[0112] During actual use:

[0113] S1. Configure an ultrasonic detection system in the quality inspection 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] Use a two-dimensional or three-dimensional mechanical motion platform to control the ultrasonic probe to move according to the set path and speed to achieve full coverage scanning of the heat sink. The transmitter emits ultrasonic pulses that penetrate the heat sink. When encountering discontinuities (such as cracks, pores) inside the material, part of the waves are reflected, and the receiver receives the reflected signal.

[0115] S2. Transmit the received original signal to the signal processing unit through a high-speed data acquisition card, and use digital filters (such as band-pass filters, low-pass filters) to preprocess the signal to eliminate noise and interference. Use an adjustable gain amplifier to enhance weak signals and improve the signal-to-noise ratio. Convert the analog signal into a digital signal through an analog-to-digital converter (ADC) for subsequent digital processing.

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

[0117] S4. Record the identified defect information (such as location, size) in the database and display it through a human-machine interface. Automatically determine whether the heat sink is qualified according to the preset quality standards (such as the maximum allowable defect size, location range). For unqualified products, the system issues an instruction to start the mechanical device to remove them from the production line or mark them for further inspection.

[0118] Preferably, an abnormal feature is identified using a defect depth formula, 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 ultrasonic waves in the material;

[0122] Δt is the time difference between the transmitted and received signals.

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

[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 ultrasonic waves in the material and the time difference between the transmitted and received signals, ensuring the accuracy and reliability of the detection results. Accurate defect location helps to take remedial measures in a timely manner, reducing economic losses caused by product defects.

[0125] Principle of this formula: According to the propagation speed v of ultrasonic waves in the material and the time difference Δt between the ultrasonic wave transmission and reception, calculate the depth d of the reflection point (i.e., the defect) from the probe.

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

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

[0128] S2. Conduct a correlation analysis on the 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, adjust the process parameters of the precision forming module in real time, such as injection pressure, mold temperature, etc.;

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

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

[0132] It realizes the organic linkage between the fin optimization algorithm and the defect detection algorithm. Through steps such as parameter collection, data analysis, process adjustment, and feedback control, this algorithm can adjust the process parameters of the precision forming module in real time, such as injection pressure, mold temperature, etc., according to the data of fin thickness and defect depth. This algorithm solves the problem that the process parameters cannot be adaptively adjusted 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] During actual use:

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

[0135] S2. Run the 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 fins. By analyzing historical data, identify the influence trends of process parameters (such as injection pressure and mold temperature) on defect generation.

[0137] S3. According to the data analysis results, calculate new process parameters using the formula.

[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 defects are still not improved after adjustment, the system prompts the operator, and 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] Where P new is the adjusted process parameter (such as injection pressure or mold temperature);

[0142] P init is the initially set process parameter;

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

[0144] d is the detected defect depth;

[0145] t is the fin thickness.

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

[0147] Dynamically adjust process parameters according to the ratio of defect depth to fin thickness. 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 the heat sink quality. This precise process adjustment method improves the flexibility and adaptability of the production process, and further enhances production efficiency and product quality.

[0148] By adjusting process parameters, change the fluidity and solidification characteristics of the material during the forming process, thereby affecting the formation of defects. k is determined based on experiments or experience, reflecting the sensitivity of process parameters to defects, and ensuring an appropriate adjustment range. The calculated P newSent to the control units of the precision forming 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, 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 integral heat sink production device, characterized in that, Including: a raw material supply module, a precision forming module, a real-time temperature control module, an automatic cutting module, a quality inspection module, and a 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 forming module through a conveying system to ensure the stable supply and conveyance of the raw materials; the precision forming module processes the raw materials into a predetermined heat sink shape using high-pressure injection molding technology. The precision forming module includes an adjustable mold and an injection system, and 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 heating / cooling elements, and monitors and adjusts the temperature inside the precision forming module in real time. The real-time temperature control module is tightly coupled with the precision forming module; the automatic cutting module precisely cuts the formed heat sink according to preset dimensions. 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 technologies 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, ensuring that the product meets the quality standards; the control system module includes a central processing unit and a human-machine interface, and is communicatively connected to the raw material supply module, the precision forming module, the real-time temperature control module, the automatic cutting module, and the quality inspection module to coordinate the work processes of each module, and collect and process the operation data of the raw material supply module, the precision forming module, the real-time temperature control module, the automatic cutting module, and the quality inspection module; the precision forming module includes a fin optimization algorithm for optimizing the fin structure of the heat sink. The fin optimization algorithm includes the following steps: S1. Obtain the raw material characteristics and expected heat dissipation performance parameters; S2. Calculate the optimal fin thickness according to the collected data; S3. Automatically adjust the key dimensions of the forming mold according to the calculation results; S4. Monitor the forming process in real time to ensure that the fin structure conforms to the calculated parameters; 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 allowable temperature; T amb is the ambient temperature; h is the convective heat transfer coefficient; A is the heat dissipation area.

2. The integrated heat sink production device according to claim 1, wherein, the quality inspection module includes a defect detection algorithm for detecting microscopic defects of the heat sink. The defect detection algorithm includes the following steps: S1. Use an ultrasonic sensor to obtain the echo signal of the internal structure of the heat sink; S2. Filter and amplify the collected signal; S3. Judge the abnormal features in the signal through pattern recognition technology; S4. Determine whether the heat sink is qualified according to the recognition result and output a detection report.

3. The integrated heat sink production device according to claim 2, characterized in that, Use the defect depth formula to identify abnormal features. The defect depth formula includes: where d is the depth of the defect from the sensor; v is the propagation speed of ultrasonic waves in the material; Δt is the time difference between the transmitted and received signals.

4. An integrated heat sink production device according to claim 3, characterized in that, It also includes a process adaptive adjustment algorithm, and the process adaptive adjustment algorithm includes: S1. Obtain the fin thickness t calculated in the fin optimization algorithm and the defect depth d detected in the defect detection algorithm; S2. Conduct a correlation analysis on the 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, adjust the process parameters of the precision forming module in real time, such as injection pressure, mold temperature, etc.; S4. Feed back the adjusted process parameters to the precision forming module and the quality inspection module to form a closed-loop control and continuously optimize the production process.

5. An integrated heat sink production device according to claim 4, characterized in that, The process adaptive adjustment algorithm includes a parameter adjustment formula, and the parameter adjustment formula includes: where P new is the adjusted process parameter (such as injection pressure or mold temperature); P init Initially set process parameters; k depends on material characteristics and equipment characteristics; d is the detected defect depth; t is the fin thickness.

6. The integrated heat sink production device according to claim 5, wherein the process parameters include injection pressure or mold temperature.

Images