Vacuum electron beam high frequency pulse welding method for core components of semiconductor equipment

Abstract

The present invention relates to the technical field of electron beam welding, specifically to a vacuum electron beam high frequency pulse welding method for core parts of semiconductor equipment, comprising the following steps: based on the physical property parameters of the core parts of the semiconductor equipment, the electron beam pulse frequency and duration are set, and the applicability of the parameters is verified to obtain the initial pulse parameter setting. In the present invention, by simulating the thermal effect of electron beam welding and adjusting the parameters according to the properties of the welding material, it is helpful to identify potential welding problems at an early stage, and prediction and simulation not only improve welding accuracy, but also optimize production efficiency, reduce the trial and error cost in actual operation, and match the expected standards through cyclic simulation. The welding simulation analysis results can predictively adjust and improve the welding effect without actually investing batch resources, so that the entire welding process is highly controllable and responsive, and can adjust the operation in real time to deal with sudden quality problems.

Description

Technical Field

[0001] The invention relates to the technical field of electron beam welding, and in particular to a vacuum electron beam high-frequency pulse welding method for core components of semiconductor equipment. Background Art

[0002] Electron beam welding technology uses a high-speed electron beam as a heat source and performs welding in a vacuum environment to prevent electron beam scattering and improve welding quality. Electron beam welding can provide a concentrated and high-energy heat source, allowing the material to reach the melting point in a very short time. The main advantages include fast welding speed, small heat-affected zone and high welding accuracy, which is suitable for the processing of precision parts and high-strength materials. Electron beam welding can be automated and is widely used in aerospace, automobile manufacturing, semiconductor equipment manufacturing and other fields.

[0003] Among them, the vacuum electron beam high-frequency pulse welding method of the core components of semiconductor equipment refers to the technology of welding the key components of semiconductor equipment using high-frequency electron beam pulses in a specific vacuum environment. It can accurately control the heat input, minimize the heat-affected zone, and ensure the structural integrity and functionality of the welded part. The main purpose is to manufacture or repair key components in semiconductor manufacturing equipment, such as wafer manufacturing machinery or chip packaging equipment, to ensure that the equipment can operate stably in high-precision and high-standard production processes.

[0004] Although the existing electron beam welding technology can provide high-speed and high-energy welding solutions, when processing core components of semiconductor equipment made of delicate or special materials, conventional electron beam welding technology is difficult to ensure the optimal quality of welded parts due to the lack of flexibility in parameter adjustment. Especially in a vacuum environment, once the parameters are improperly set, excessive or low heat input will lead to uneven welds or excessive heat-affected zones, which is particularly critical in the field of precision manufacturing, resulting in unstable product performance or even failure. Existing technologies are deficient in real-time monitoring and quality adjustment of the welding process, limiting their application scope under high standards and high-precision production requirements. The lack of the ability to flexibly adjust welding parameters and the lack of real-time feedback during the welding process will lead to quality problems in the production process, and the problems will not be discovered until the product testing stage, increasing cost and time investment. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a vacuum electron beam high-frequency pulse welding method for core components of semiconductor equipment.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: a vacuum electron beam high-frequency pulse welding method for core components of semiconductor equipment, comprising the following steps:

[0007] S1: Based on the physical property parameters of the core components of the semiconductor equipment, set the electron beam pulse frequency and duration, verify the applicability of the parameters, and obtain the initial pulse parameter settings;

[0008] S2: using the initial pulse parameter setting to simulate the thermal effect in electron beam vacuum welding, adjusting the simulation parameters according to the material properties of the welding, recording the heat distribution in welding, and obtaining the heat distribution simulation result;

[0009] S3: Iteratively optimize the pulse frequency and duration based on the heat distribution simulation results, adjust the parameter values ​​to avoid the heat influence of the welding area, and obtain the optimized pulse parameters;

[0010] S4: using the optimized pulse parameters, simulating electron beam welding, analyzing the influence of parameter adjustment on the thermal effect of the welding area and the weld quality, and obtaining welding simulation analysis results by matching the expected standards through cyclic simulation;

[0011] S5: Based on the welding simulation analysis result, the power and focal length of the electron beam are adjusted, the electron beam high frequency pulse welding is calibrated and tested, the robustness of the electron beam welding is optimized, and the electron beam control adjustment result is obtained;

[0012] S6: According to the electron beam control adjustment result, the vacuum electron beam high-frequency pulse welding is monitored in real time, the weld quality and consistency are detected, and the weld quality is evaluated to obtain the welding quality detection result.

[0013] As a further scheme of the present invention, the initial pulse parameter setting includes the frequency setting value, duration setting value and initialization verification result of the parameters on the target material of the electron beam, the thermal distribution simulation result includes the temperature gradient of the welding area, the heat-affected zone and the material thermal stress distribution near the weld, the optimized pulse parameters include the adjusted pulse frequency, the adjusted duration and the effect of the parameters on the welding heat, the welding simulation analysis results include the welding quality evaluation after parameter matching, the welding stability detection and the degree of achievement of the expected standards, the electron beam control adjustment result includes the power adjustment value, the focal length adjustment value and the optimization of the robustness in welding, and the welding quality detection result includes the consistency data of the weld, the quality deviation results and the statistics of the weld pass rate in welding.

[0014] As a further solution of the present invention, the steps of setting the electron beam pulse frequency and duration based on the physical property parameters of the core components of the semiconductor device and verifying the applicability of the parameters to obtain the initial pulse parameter settings are specifically as follows:

[0015] S101: Using the physical property parameters of the core components of the semiconductor equipment, including the thermal conductivity, melting point and resistivity of the material, the pulse frequency and duration of the electron beam are calculated according to the parameters, and the baseline of the parameters is set to obtain a pulse parameter table;

[0016] S102: Based on the pulse parameter table, vacuum electron beam welding is simulated in an experimental environment, the response performance of pulse frequency and duration on differentiated materials is recorded, the adaptability in a real-time welding scenario is evaluated, and a pulse parameter applicability record is obtained;

[0017] S103: According to the pulse parameter applicability record, the pulse frequency and duration of the electron beam are adjusted, the adjusted parameters are matched with the material characteristics, and the validity and welding effect of the adjusted parameters are verified to obtain the initial pulse parameter settings.

[0018] As a further solution of the present invention, the initial pulse parameter setting is used to simulate the thermal effect in electron beam vacuum welding, the simulation parameters are adjusted according to the material properties of the welding, the heat distribution in welding is recorded, and the steps of obtaining the heat distribution simulation result are specifically as follows:

[0019] S201: using the initial pulse parameter setting to perform an initialization thermal effect simulation of electron beam vacuum welding, setting the thermal conductivity, specific heat and thermal diffusivity of the material in the simulation, verifying the fit between the simulation environment and the real-time welding, and obtaining an initialization thermal effect simulation result;

[0020] S202: Based on the initialization thermal effect simulation result, adjusting the simulation parameters, optimizing the simulation environment according to the thermal response characteristics of the differentiated materials, and recording the thermal behavior of the differentiated materials under real-time welding conditions to obtain adjusted simulation parameters;

[0021] S203: Resimulate vacuum electron beam high-frequency pulse welding using the adjusted simulation parameters, record and analyze the thermal distribution of the welding area, including the temperature gradient, heat-affected zone, and thermal stress distribution of core component materials of semiconductor equipment, and obtain thermal distribution simulation results.

[0022] As a further solution of the present invention, the pulse frequency and duration are iteratively optimized based on the heat distribution simulation results, and the parameter values ​​are adjusted to avoid the thermal influence of the welding zone. The steps of obtaining the optimized pulse parameters are specifically as follows:

[0023] S301: Based on the heat distribution simulation result, analyzing the heat influencing factors of the welding area, including the temperature peak and the non-uniformity of the heat distribution, identifying the key intervals of the pulse frequency and duration that need to be adjusted, and obtaining the pulse parameter adjustment requirements;

[0024] S302: According to the pulse parameter adjustment requirements, a genetic algorithm is used to optimize the parameters through encoding, selection, crossover and mutation, and the pulse frequency and duration are gradually adjusted to obtain an iterative optimization record;

[0025] S303: using the iterative optimization record, determining the optimal vacuum electron beam pulse frequency and duration, checking the parameters to avoid thermal effects during welding, and verifying the welding quality and efficiency, to obtain optimized pulse parameters.

[0026] As a further solution of the present invention, the formula of the genetic algorithm is as follows:

[0027]

[0028] in, is the fitness of the target parameter, is the parameter combination of pulse frequency and duration, is the pulse shape parameter, is the initial energy distribution parameter, is the cooling rate parameter, is the weight coefficient, is the heat distribution unevenness, is the normalization coefficient.

[0029] As a further solution of the present invention, the optimized pulse parameters are used to simulate electron beam welding, and the influence of parameter adjustment on the thermal influence of the welding area and the weld quality is analyzed. The steps of obtaining the welding simulation analysis results by cyclic simulation matching the expected standards are specifically as follows:

[0030] S401: using the optimized pulse parameters to perform electron beam welding simulation, monitoring and recording the heat distribution effect after pulse adjustment, including changes in temperature distribution, heat penetration and heat affected zone, analyzing the influence of the parameters on the welding effect, and obtaining initialization welding simulation feedback;

[0031] S402: Based on the initialization welding simulation feedback, a cyclic test of the welding simulation is performed, and the simulation conditions are adjusted to match the real-time changes of the material and the preset welding quality standard, so as to obtain a welding parameter matching record;

[0032] S403: Using the welding parameter matching records and a support vector machine algorithm, the influence of the adjusted pulse parameters on the welding quality is evaluated and verified, and the welding quality is predicted to obtain welding simulation analysis results.

[0033] As a further solution of the present invention, the formula of the support vector machine algorithm is as follows:

[0034]

[0035] in, is the predicted value of welding quality, is the total number of support vectors, To traverse the index of the support vector, For real-time input of welding parameters, is the pulse frequency, is the duration, is the pulse intensity, is the cooling rate, is the coefficient of the support vector, is the target value of the training sample, is the support vector, is the kernel function, is the deviation term.

[0036] As a further solution of the present invention, based on the welding simulation analysis results, the power and focal length of the electron beam are adjusted, the electron beam high frequency pulse welding is calibrated and tested, the robustness of the electron beam welding is optimized, and the steps of obtaining the electron beam control adjustment result are specifically as follows:

[0037] S501: Based on the welding simulation analysis result, the electron beam power and focal length that need to be adjusted are identified, and adjustments are made to the uneven heat distribution and weld quality problems in the welding simulation to obtain an electron beam adjustment plan;

[0038] S502: adopting the electron beam adjustment scheme, implementing the adjustment of the electron beam power and focal length, performing a calibration test, checking whether the adjustment of the electron beam achieves the expected effect, and performing a real-time welding test to obtain an electron beam calibration test record;

[0039] S503: According to the electron beam calibration test record, the overall robustness of the electron beam welding is evaluated, the electron beam control is optimized, the consistency and stability of the electron beam welding under various materials and conditions are checked, and the electron beam control adjustment result is obtained.

[0040] As a further solution of the present invention, according to the electron beam control adjustment result, the vacuum electron beam high frequency pulse welding is monitored in real time, the weld quality and consistency are detected, and the weld quality is evaluated. The specific steps of obtaining the welding quality detection result are:

[0041] S601: Based on the electron beam control adjustment result, key data in vacuum electron beam high-frequency pulse welding is captured in real time, including weld temperature, speed and pulse response, and the continuity and consistency of welding parameters are checked to obtain real-time welding monitoring records;

[0042] S602: using the real-time welding monitoring record, evaluating the weld quality, detecting the uniformity, straightness and penetration of the weld, and performing problem diagnosis and quality evaluation to obtain a weld quality evaluation record;

[0043] S603: According to the weld quality evaluation record, the consistency and overall quality of the weld are evaluated, the welding effect is iteratively optimized by adjusting the monitoring and control parameters, and the welding quality is checked to meet the set standards to obtain the welding quality test results.

[0044] Compared with the prior art, the advantages and positive effects of the present invention are:

[0045] In the present invention, by accurately setting the pulse frequency and duration of the electron beam, it is ensured that the heat input can be finely controlled in the early stage of welding, and the precise initial parameter setting effectively reduces the heat-affected zone and ensures the structural integrity of the welding area. Simulating the thermal effect of electron beam welding and adjusting the parameters according to the properties of the welding material helps to identify potential welding problems in the early stage. Prediction and simulation not only improve welding accuracy, but also optimize production efficiency and reduce the trial and error cost in actual operation. Iterative optimization of pulse parameters, adjustment according to simulation results, further refine the control during welding, and the iterative process makes welding parameters more accurate and can effectively adapt to complex welding requirements. By cyclic simulation matching the expected standards, the welding simulation analysis results can predictively adjust and improve the welding effect without actually investing batch resources. Control adjustment not only improves the robustness of electron beam welding, but also ensures the consistency and reliability of welding operations. Real-time monitoring of vacuum electron beam welding and detection of weld quality make the entire welding process highly controllable and fast in response, and can adjust operations in real time to deal with sudden quality problems. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 It is a schematic diagram of the main steps of the present invention;

[0047] Figure 2 It is a schematic diagram of the refinement of S1 of the present invention;

[0048] Figure 3 It is a schematic diagram of the refinement of S2 of the present invention;

[0049] Figure 4 It is a schematic diagram of the refinement of S3 of the present invention;

[0050] Figure 5 It is a schematic diagram of the refinement of S4 of the present invention;

[0051] Figure 6 It is a detailed schematic diagram of S5 of the present invention;

[0052] Figure 7 It is a detailed schematic diagram of S6 of the present invention. DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0054] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0055] See also Figure 1 The present invention provides a technical solution for a vacuum electron beam high frequency pulse welding method for core components of semiconductor equipment, comprising the following steps:

[0056] S1: Based on the physical property parameters of the core components of semiconductor equipment, including thermal conductivity, specific heat capacity and density, set the electron beam pulse frequency and duration, verify the applicability of the parameters, make setting adjustments, and obtain the initial pulse parameter settings;

[0057] S2: Use the initial pulse parameter setting to simulate the thermal effect in electron beam vacuum welding, adjust the simulation parameters according to the material properties of the welding, record the heat distribution in welding, and obtain the heat distribution simulation results;

[0058] S3: Based on the heat distribution simulation results, the pulse frequency and duration are iteratively optimized, the parameter values ​​are adjusted to avoid the thermal influence of the welding area, and the parameter settings of each iteration are recorded to obtain the optimized pulse parameters;

[0059] S4: Use the optimized pulse parameters to simulate vacuum electron beam high-frequency pulse welding, analyze the effect of parameter adjustment on the thermal effect of the welding area and the quality of the weld, check that the welding quality meets the expected standards through cyclic simulation, and obtain the welding simulation analysis results;

[0060] S5: Based on the welding simulation analysis results, the power and focal length of the electron beam are adjusted, the electron beam high-frequency pulse welding is calibrated and tested, the robustness of the electron beam welding is optimized, and the electron beam control adjustment results are obtained;

[0061] S6: According to the electron beam control adjustment result, the vacuum electron beam high frequency pulse welding is monitored in real time, the weld quality and consistency are detected, and the weld quality is evaluated to obtain the welding quality detection result.

[0062] The initial pulse parameter setting includes the frequency setting value, duration setting value and initialization verification results of the electron beam on the target material. The thermal distribution simulation results include the temperature gradient in the welding area, the heat-affected zone and the material thermal stress distribution near the weld. The optimized pulse parameters include the adjusted pulse frequency, the adjusted duration and the effect of the parameters on the thermal influence of welding. The welding simulation analysis results include the welding quality evaluation after parameter matching, the welding stability detection and the degree of achievement of the expected standards. The electron beam control adjustment results include the power adjustment value, the focal length adjustment value and the optimization of the robustness in welding. The welding quality detection results include the consistency data of the weld, the quality deviation results and the statistics of the weld pass rate in welding.

[0063] See also Figure 2 , based on the physical property parameters of the core components of semiconductor equipment, the electron beam pulse frequency and duration are set, and the applicability of the parameters is verified. The steps for obtaining the initial pulse parameter setting are as follows:

[0064] S101: Using the physical property parameters of the core components of the semiconductor device, including the thermal conductivity, melting point and resistivity of the material, the pulse frequency and duration of the electron beam are calculated according to the parameters, and the baseline of the parameters is set to obtain the pulse parameter table. The execution process is as follows;

[0065] The physical property parameters of the core components of semiconductor equipment, including the thermal conductivity, melting point and resistivity of the material, are used to calculate the pulse frequency and duration required during the electron beam welding process. The calculation takes into account the thermal response characteristics and resistance characteristics of the material to ensure that the energy output of the electron beam matches the melting point of the material to prevent overheating or underheating. The calculation is to reverse the required electron beam pulse frequency and duration by setting the thermal energy required for the material to reach the melting point. The initial pulse parameters are set using relevant physical formulas. The parameters will be verified and adjusted in subsequent experiments to ensure optimal performance in actual welding applications. The pulse parameter table is obtained using the formula:

[0066]

[0067] in, represents the initial pulse parameters, represents the thermal conductivity of the material, Represents the melting point of the material, Represents the resistivity of the material.

[0068] S102: Based on the pulse parameter table, vacuum electron beam welding is simulated in an experimental environment, the response performance of pulse frequency and duration on differentiated materials is recorded, and the adaptability in real-time welding scenarios is evaluated. The execution process of obtaining the pulse parameter applicability record is as follows;

[0069] Based on the pulse parameter table, vacuum electron beam welding simulation is carried out in an experimental environment. The simulation test includes a variety of differentiated materials, and the response performance of each material under different pulse frequencies and durations is recorded. The purpose is to evaluate the adaptability and effect of the initial pulse parameters in a real welding environment. Through experiments, detailed data can be collected to show how different materials respond to the set electron beam parameters, and then evaluate the applicability of the parameters in actual welding scenarios. The collection and analysis of data will provide a scientific basis for the next step of parameter optimization, and obtain the pulse parameter applicability record, using the formula:

[0070]

[0071] in, represents the adaptive record of pulse parameters, represents the pulse frequency recorded in the experiment, Indicates duration.

[0072] S103: According to the pulse parameter applicability record, the pulse frequency and duration of the electron beam are adjusted, the adjusted parameters are matched with the material characteristics, and the validity and welding effect of the adjusted parameters are verified. The execution process of the initial pulse parameter setting is as follows;

[0073] According to the pulse parameter applicability record, the electron beam pulse frequency and duration are adjusted. The adjustment is made according to the specific response of various materials, with the purpose of making the electron beam parameters better match the material characteristics and optimize the welding effect. The effectiveness of the adjusted parameters is verified through experiments to ensure that the adjusted parameters can provide better performance in actual welding operations. The adjustment process includes repeatedly testing the effects of different parameter combinations, judging the parameter combination that is most suitable for a specific material through actual welding results, and obtaining the initial pulse parameter setting, using the formula:

[0074]

[0075] in, Indicates the initial pulse parameter setting after adjustment, represents the adjusted pulse frequency, Represents duration.

[0076] See also Figure 3, use the initial pulse parameter setting to simulate the thermal effect in electron beam vacuum welding, adjust the simulation parameters according to the material properties of the welding, record the heat distribution in welding, and obtain the heat distribution simulation results in the following steps:

[0077] S201: using the initial pulse parameter setting, performing the initial thermal effect simulation of electron beam vacuum welding, setting the thermal conductivity, specific heat and thermal diffusivity of the material in the simulation, verifying the fit between the simulation environment and the real-time welding, and obtaining the initial thermal effect simulation result. The execution process is as follows;

[0078] The initial pulse parameter setting is used to perform the initial thermal effect simulation of electron beam vacuum welding. The thermal conductivity, specific heat and thermal diffusivity of the material are set during the simulation. Parameters are crucial to ensure the accuracy of the simulation because they directly affect the transfer and distribution of heat energy in the material, verify the fit between the simulation environment and real-time welding, ensure that the simulation can accurately reflect the thermal effects of the actual welding process, predict the thermal-related problems encountered by the material in actual welding, such as overheating or uneven heating, make appropriate parameter adjustments, and obtain the initial thermal effect simulation results. The formula used is:

[0079]

[0080] in, represents the initialization thermal effect simulation results, is the thermal conductivity of the material, is the specific heat, is the thermal diffusivity.

[0081] S202: Based on the initialization thermal effect simulation result, the simulation parameters are adjusted, the simulation environment is optimized according to the thermal response characteristics of the differentiated materials, and the thermal behavior of the differentiated materials under real-time welding conditions is recorded, and the execution process of the adjusted simulation parameters is obtained as follows;

[0082] Based on the initialization thermal effect simulation results, the simulation parameters are adjusted to take into account the thermal response characteristics of different materials, such as thermal conductivity, specific heat and thermal diffusivity, to optimize the simulation environment. By adjusting the parameters, not only can the accuracy of the simulation be improved, but also a better understanding of the thermal behavior of different materials under real-time welding conditions can be achieved. Recording the response of the material helps to further optimize the welding process to ensure that the requirements of efficiency and quality are met. The adjusted simulation parameters are obtained using the formula:

[0083]

[0084] in, represents the adjusted simulation parameters, is the adjusted thermal conductivity, is the specific heat, is the thermal diffusivity.

[0085] S203: Use the adjusted simulation parameters to re-simulate vacuum electron beam high-frequency pulse welding, record and analyze the thermal distribution of the welding area, including the temperature gradient, heat-affected zone, and thermal stress distribution of the core component materials of the semiconductor device, and obtain the execution process of the thermal distribution simulation results as follows;

[0086] Using the adjusted simulation parameters, the vacuum electron beam high frequency pulse welding simulation was performed again. The simulation mainly recorded and analyzed the thermal distribution of the welding area, including the temperature gradient, heat affected zone and thermal stress distribution of the material, which is crucial for understanding the impact of electron beam welding on the core components of semiconductor equipment. The optimization direction of the welding process was evaluated, and the welding parameters were adjusted to ensure the structural integrity of the material and the performance of the equipment, and the thermal distribution simulation results were obtained using the formula:

[0087]

[0088] in, represents the thermal distribution simulation results, is the temperature gradient, is the heat affected zone, is the thermal stress distribution.

[0089] See also Figure 4 , through the heat distribution simulation results, the pulse frequency and duration are iteratively optimized, and the parameter values ​​are adjusted to avoid the thermal influence of the welding area. The steps to obtain the optimized pulse parameters are as follows:

[0090] S301: Based on the heat distribution simulation results, the heat influencing factors of the welding area are analyzed, including the temperature peak and the non-uniformity of the heat distribution, and the key intervals of the pulse frequency and duration that need to be adjusted are identified. The execution process of obtaining the pulse parameter adjustment requirements is as follows;

[0091] Based on the results of thermal distribution simulation, the thermal influencing factors of the welding area are analyzed, with special attention paid to the temperature peak and the unevenness of the heat distribution. By analyzing the thermal effect parameters in detail, the key intervals that affect the welding quality can be identified. The intervals indicate that the pulse frequency and duration need to be adjusted. In order to ensure that the welding process can achieve the best welding effect while controlling thermal stress and thermal deformation. After identifying the key intervals, the pulse parameters are adjusted in a targeted manner to adapt to the characteristics of the material and the requirements of welding, and the pulse parameter adjustment requirements are obtained. The formula used is:

[0092]

[0093] in, Indicates the need for pulse parameter adjustment. is the peak temperature, It is the unevenness of heat distribution.

[0094] S302: According to the pulse parameter adjustment requirements, a genetic algorithm is used to optimize the parameters through encoding, selection, crossover and mutation, and the pulse frequency and duration are gradually adjusted to obtain the execution process of the iterative optimization record as follows;

[0095] According to the pulse parameter adjustment requirements, genetic algorithms are used to optimize parameters, including the adjustment process of pulse frequency and duration. Genetic algorithms are an iterative process, including encoding, selection, crossover and mutation. Genetic algorithms continuously optimize parameters to find the pulse settings that best suit welding conditions by simulating the process of natural selection. Each generation of optimization is selected and adjusted based on the evaluation of welding effects, gradually approaching the optimal solution and obtaining iterative optimization records.

[0096] The formula of genetic algorithm is as follows:

[0097]

[0098] in, is the fitness of the target parameter, is the parameter combination of pulse frequency and duration, is the pulse shape parameter, is the initial energy distribution parameter, is the cooling rate parameter, is the weight coefficient, is the heat distribution unevenness, is the normalization coefficient.

[0099] The execution flow is as follows:

[0100] Setting pulse parameters And introduce new parameters , calculate the influence of each parameter and the corresponding weight coefficient The weights are determined by the operating range and expected effect of the parameters, and are Calibrate to ensure that the actual impact of each parameter is effectively reflected, combine all parameters and weights, and calculate the fitness , ensuring that the value can comprehensively reflect the thermal effect after pulse parameter adjustment and the overall performance of parameter optimization. The calculation is used to adjust the relative importance of different parameters to ensure that the parameter settings can achieve the best heat distribution uniformity.

[0101] S303: using the iterative optimization record, determining the optimal vacuum electron beam pulse frequency and duration, checking the parameters to avoid heat effects during welding, and verifying the welding quality and efficiency, the execution process of obtaining the optimized pulse parameters is as follows;

[0102] Iterative optimization records are used to determine the optimal vacuum electron beam pulse frequency and duration, including checking the effectiveness of parameters in avoiding thermal effects during welding and verifying welding quality and efficiency. Through meticulous experiments and data analysis, the impact of each set of parameters on welding results is evaluated to ensure that the selected parameters can optimize production efficiency and reduce costs while ensuring welding quality. The optimized pulse parameters are obtained using the formula:

[0103]

[0104] in, represents the optimized pulse parameters, is the optimal pulse frequency, is the optimal duration.

[0105] See also Figure 4 , use the optimized pulse parameters to simulate electron beam welding, analyze the effect of parameter adjustment on the thermal effect of the welding area and the quality of the weld, and match the expected standards through cyclic simulation to obtain the welding simulation analysis results. The specific steps are as follows:

[0106] S401: Use the optimized pulse parameters to perform electron beam welding simulation, monitor and record the heat distribution effect after pulse adjustment, including temperature distribution, heat penetration and changes in heat affected zone, analyze the influence of parameters on welding effect, and obtain the execution process of initializing welding simulation feedback as follows;

[0107] The optimized pulse parameters are used to simulate electron beam welding. The simulation aims to monitor and record the heat distribution effect after pulse adjustment, with special attention to temperature distribution, heat penetration and changes in the heat-affected zone. By monitoring the data, it is possible to deeply analyze how the adjusted parameters affect thermal management during welding. It is crucial to verify the effectiveness of welding parameters because it is directly related to the quality and strength of the welded joint. The data obtained provides real-time feedback to help further optimize the welding process and ensure that the welding effect meets the expected standards. Initialized welding simulation feedback is obtained using the formula:

[0108]

[0109] in, Indicates initialization of welding simulation feedback. represents the temperature distribution, Indicates the degree of heat penetration. Indicates the heat affected zone.

[0110] S402: Based on the initialization welding simulation feedback, a cyclic test of the welding simulation is performed, and the simulation conditions are adjusted to match the real-time changes of the material and the preset welding quality standard, and the execution process of obtaining the welding parameter matching record is as follows;

[0111] Based on the initial welding simulation feedback, a cyclic test of the welding simulation is performed to adjust the simulation conditions to match the real-time changes of the material and the preset welding quality standards. By continuously adjusting and testing different simulation parameters, such as temperature control and heat penetration adjustment, the actual welding environment can be simulated more accurately. The purpose of the cyclic test is to ensure that the welding parameters can provide consistent quality results under various conditions, meet the high requirements for accuracy and reliability in the manufacturing process, and obtain a welding parameter matching record, using the formula:

[0112]

[0113] in, Indicates welding parameter matching record, represents the temperature control of the analog adjustment, Indicates heat penetration adjustment.

[0114] S403: Using the welding parameter matching records and the support vector machine algorithm, the influence of the adjusted pulse parameters on the welding quality is evaluated and verified, and the welding quality is predicted. The execution process of obtaining the welding simulation analysis results is as follows;

[0115] Using the welding parameter matching records, the support vector machine (SVM) algorithm is used to evaluate and verify the influence of the adjusted pulse parameters on the welding quality, and to predict the welding quality. The SVM algorithm can build a model based on the existing data to predict the welding results under different pulse parameter combinations. The process includes training and testing the algorithm to identify the best parameter settings in order to maximize the efficiency and quality of the welding process. The actual effect of the pulse parameter adjustment can be evaluated, and accurate predictions can be made for future welding operations to obtain welding simulation analysis results.

[0116] The formula of the support vector machine algorithm is as follows:

[0117]

[0118] in, is the predicted value of welding quality, is the total number of support vectors, To traverse the index of the support vector, For real-time input of welding parameters, is the pulse frequency, is the duration, is the pulse intensity, is the cooling rate, is the coefficient of the support vector, is the target value of the training sample, is the support vector, is the kernel function, is the deviation term.

[0119] The execution flow is as follows:

[0120] Select the pulse frequency , Duration , Pulse intensity and cooling rate As a new parameter, combined with the currently input welding parameters , using the kernel function Calculate the similarity between the input parameters and each support vector, consider the multidimensional influence of welding parameters, and determine each support vector through training data and the corresponding target value ,coefficient and the deviation term , all values ​​are added together to predict the welding quality. Through the calibration and optimization of the weighting coefficients, it is ensured that the weight of each newly added parameter appropriately reflects the actual impact on the welding quality, ensuring that the prediction results can accurately match the expected standards.

[0121] See also Figure 6 Based on the welding simulation analysis results, the power and focal length of the electron beam are adjusted, the electron beam high-frequency pulse welding is calibrated and tested, and the robustness of the electron beam welding is optimized. The specific steps for obtaining the electron beam control adjustment results are as follows:

[0122] S501: Based on the welding simulation analysis results, the electron beam power and focal length that need to be adjusted are identified, and adjustments are made to the uneven heat distribution and weld quality problems in the welding simulation. The execution process of the electron beam adjustment scheme is as follows;

[0123] Based on the welding simulation analysis results, the electron beam power and focal length that need to be adjusted are identified. The main problems to be adjusted are the uneven heat distribution and weld quality problems found in the simulation. By precisely controlling the power and focal length of the electron beam, the distribution of heat input can be optimized and the thermal effect management during welding can be improved. The purpose is to achieve better welding quality, reduce thermal deformation and weld defects, and ensure the uniformity and integrity of the weld by adjusting the power and focal length. The electron beam adjustment plan is obtained using the formula:

[0124]

[0125] in, represents the electron beam adjustment scheme, Indicates the electron beam power adjustment, Indicates focus adjustment.

[0126] S502: adopt the electron beam adjustment scheme, implement the adjustment of the electron beam power and focal length, perform the calibration test, check whether the adjustment of the electron beam achieves the expected effect, and perform the real-time welding test. The execution process of obtaining the electron beam calibration test record is as follows;

[0127] The electron beam adjustment scheme is adopted to implement the adjustment of electron beam power and focal length, and the calibration test is performed to ensure that the adjustment achieves the expected effect. The calibration test includes the precise measurement and adjustment of the electron beam parameters to ensure the consistency and accuracy of the parameters for each welding. After the calibration is completed, a real-time welding test is performed to test and verify the performance of the adjusted parameters in the actual welding operation to ensure the stability of the welding process and the high quality of the weld. The electron beam calibration test record is obtained, and the formula used is:

[0128]

[0129] in, Indicates the electron beam calibration test record, represents the adjusted electron beam power, Indicates the adjusted focal length.

[0130] S503: According to the electron beam calibration test record, the overall robustness of the electron beam welding is evaluated, the electron beam control is optimized, the consistency and stability of the electron beam welding under various materials and conditions are checked, and the execution process of obtaining the electron beam control adjustment result is as follows;

[0131] Based on the electron beam calibration test records, the overall robustness of electron beam welding is evaluated, including further optimization of electron beam control to ensure the consistency and stability of the welding process under a variety of materials and different conditions. Through the careful adjustment of electron beam parameters, the flexibility and reliability of welding operations can be improved, ensuring that the welding quality can be maintained at a high standard regardless of the material type or operating conditions. The results of electron beam control adjustment are obtained.

[0132] See also Figure 7 According to the electron beam control adjustment result, the vacuum electron beam high frequency pulse welding is monitored in real time, the weld quality and consistency are detected, and the weld quality is evaluated. The specific steps for obtaining the welding quality detection result are as follows:

[0133] S601: Based on the electron beam control adjustment result, the key data in vacuum electron beam high frequency pulse welding, including weld temperature, speed and pulse response, are captured in real time, and the continuity and consistency of welding parameters are checked to obtain the execution process of real-time welding monitoring records as follows;

[0134] Based on the electron beam control adjustment results, the key data in vacuum electron beam high-frequency pulse welding, including weld temperature, speed and pulse response, are captured in real time. The data monitoring is to ensure the continuity and consistency of welding parameters throughout the process. Real-time monitoring allows timely detection of deviations from preset parameters and necessary adjustments. Monitoring is a key part of ensuring that welding quality meets standards, helping to maintain the accuracy and reliability of operations, and obtaining real-time welding monitoring records. The formula used is:

[0135]

[0136] in, Indicates real-time welding monitoring records, Indicates the weld temperature, Indicates welding speed, represents the impulse response.

[0137] S602: Use the real-time welding monitoring record to evaluate the weld quality, detect the uniformity, straightness and penetration of the weld, and perform problem diagnosis and quality evaluation. The execution process of obtaining the weld quality evaluation record is as follows;

[0138] Real-time welding monitoring records are used to evaluate the quality of welds. The uniformity, straightness and penetration of welds are all important indicators for evaluating welding quality. Through detailed analysis of data, problem diagnosis can be performed and the quality of the welding process can be evaluated. The evaluation process helps to identify problems in welding operations and provides a basis for improving welding technology. The weld quality evaluation record is obtained using the formula:

[0139]

[0140] in, Indicates weld quality evaluation record, Indicates the uniformity of the weld. Indicates the straightness of the weld. Indicates the degree of penetration of the weld.

[0141] S603: According to the weld quality evaluation record, evaluate the consistency and overall quality of the weld, iteratively optimize the welding effect by adjusting the monitoring and control parameters, check that the welding quality meets the set standards, and obtain the welding quality test results. The execution process is as follows;

[0142] According to the weld quality evaluation records, the consistency and overall quality of the weld are evaluated, and the welding effect is iteratively optimized by adjusting the monitoring and control parameters to ensure that the welding quality meets the set standards. The process involves subtle adjustments to the welding parameters to improve the welding quality and ensure consistency and stability under a variety of materials and conditions. The optimization strategy is the key to ensuring product quality and process reliability, and obtaining welding quality inspection results.

[0143] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A vacuum electron beam high frequency pulse welding method for core parts of semiconductor equipment, characterized in that: The following steps are involved: Based on the physical property parameters of the core components of semiconductor equipment, set the electron beam pulse frequency and duration, verify the applicability of the parameters, and obtain the initial pulse parameter settings; The initial pulse parameter setting is used to simulate the thermal effect in electron beam vacuum welding, the simulation parameters are adjusted according to the material properties of the welding, the heat distribution in welding is recorded, and the heat distribution simulation result is obtained; The pulse frequency and duration are iteratively optimized based on the heat distribution simulation results, and the parameter values ​​are adjusted to avoid the heat influence of the welding zone to obtain the optimized pulse parameters; Using the optimized pulse parameters, simulating electron beam welding, analyzing the effect of parameter adjustment on the thermal effect of the welding area and the quality of the weld, and obtaining welding simulation analysis results by matching the expected standards through cyclic simulation; Based on the welding simulation analysis results, the power and focal length of the electron beam are adjusted, the electron beam high frequency pulse welding is calibrated and tested, the robustness of the electron beam welding is optimized, and the electron beam control adjustment result is obtained; According to the electron beam control adjustment result, the vacuum electron beam high frequency pulse welding is monitored in real time, the weld quality and consistency are detected, and the weld quality is evaluated to obtain the welding quality detection result; Based on the physical property parameters of the core components of semiconductor equipment, the electron beam pulse frequency and duration are set, and the applicability of the parameters is verified. The steps to obtain the initial pulse parameter setting are as follows: Using the physical property parameters of the core components of semiconductor equipment, including the thermal conductivity, melting point and resistivity of the material, the pulse frequency and duration of the electron beam are calculated based on the parameters, and the baseline of the parameters is set to obtain a pulse parameter table; Based on the pulse parameter table, vacuum electron beam welding is simulated in an experimental environment, the response performance of pulse frequency and duration on differentiated materials is recorded, the adaptability in real-time welding scenarios is evaluated, and a pulse parameter applicability record is obtained; According to the pulse parameter applicability record, the pulse frequency and duration of the electron beam are adjusted, the adjusted parameters are matched with the material characteristics, and the validity and welding effect of the adjusted parameters are verified to obtain the initial pulse parameter setting; The steps of using the initial pulse parameter setting to simulate the thermal effect in electron beam vacuum welding, adjusting the simulation parameters according to the material properties of the welding, recording the heat distribution in welding, and obtaining the heat distribution simulation results are as follows: The initial pulse parameter setting is adopted to perform the initialization thermal effect simulation of electron beam vacuum welding, the thermal conductivity, specific heat and thermal diffusivity of the material are set in the simulation, the fit between the simulation environment and the real-time welding is verified, and the initialization thermal effect simulation result is obtained; Based on the initialization thermal effect simulation result, the simulation parameters are adjusted, the simulation environment is optimized according to the thermal response characteristics of the differentiated materials, and the thermal behavior of the differentiated materials under real-time welding conditions is recorded to obtain the adjusted simulation parameters; Using the adjusted simulation parameters, resimulating vacuum electron beam high frequency pulse welding, recording and analyzing the thermal distribution of the welding area, including the temperature gradient, the heat affected zone, and the thermal stress distribution of the core component materials of the semiconductor device, to obtain the thermal distribution simulation results; The optimized pulse parameters are used to simulate electron beam welding, and the influence of parameter adjustment on the thermal effect of the welding area and the weld quality is analyzed. The specific steps of obtaining the welding simulation analysis results by matching the expected standards through cyclic simulation are as follows: Using the optimized pulse parameters, electron beam welding simulation is performed, the heat distribution effect after pulse adjustment is monitored and recorded, including changes in temperature distribution, heat penetration and heat-affected zone, the influence of the parameters on the welding effect is analyzed, and initialization welding simulation feedback is obtained; Based on the initialization welding simulation feedback, a cyclic test of the welding simulation is performed, and the simulation conditions are adjusted to match the real-time changes of the material and the preset welding quality standards to obtain a welding parameter matching record; Using the welding parameter matching records and a support vector machine algorithm, the influence of the adjusted pulse parameters on the welding quality is evaluated and verified, and the welding quality is predicted to obtain a welding simulation analysis result; Based on the welding simulation analysis results, the power and focal length of the electron beam are adjusted, the electron beam high frequency pulse welding is calibrated and tested, the robustness of the electron beam welding is optimized, and the steps of obtaining the electron beam control adjustment result are specifically as follows: Based on the welding simulation analysis results, the electron beam power and focal length that need to be adjusted are identified, and adjustments are made to the uneven heat distribution and weld quality problems in the welding simulation to obtain an electron beam adjustment plan; Adopting the electron beam adjustment scheme, implementing the adjustment of electron beam power and focal length, performing calibration test, checking that the adjustment of the electron beam achieves the expected effect, and performing real-time welding test to obtain electron beam calibration test record; According to the electron beam calibration test record, the overall robustness of electron beam welding is evaluated, the electron beam control is optimized, the consistency and stability of electron beam welding under various materials and conditions are checked, and the electron beam control adjustment results are obtained; According to the electron beam control adjustment result, the vacuum electron beam high frequency pulse welding is monitored in real time, the weld quality and consistency are detected, and the weld quality is evaluated. The specific steps of obtaining the welding quality detection result are: Based on the electron beam control adjustment result, key data in vacuum electron beam high frequency pulse welding, including weld temperature, speed and pulse response, are captured in real time, the continuity and consistency of welding parameters are checked, and real-time welding monitoring records are obtained; Using the real-time welding monitoring record, the weld quality is evaluated, the uniformity, straightness and penetration of the weld are tested, and problem diagnosis and quality evaluation are performed to obtain a weld quality evaluation record; According to the weld quality evaluation record, the consistency and overall quality of the weld are evaluated, the welding effect is iteratively optimized by adjusting the monitoring and control parameters, the welding quality is checked to meet the set standards, and the welding quality test results are obtained.

2. The vacuum electron beam high frequency pulse welding method for core parts of semiconductor equipment according to claim 1, characterized in that: The initial pulse parameter setting includes the frequency setting value, duration setting value and initialization verification result of the parameters on the target material of the electron beam; the thermal distribution simulation result includes the temperature gradient of the welding area, the heat-affected zone and the material thermal stress distribution near the weld; the optimized pulse parameters include the adjusted pulse frequency, the adjusted duration and the effect of the parameters on the welding heat; the welding simulation analysis results include the welding quality evaluation after parameter matching, the welding stability detection and the degree of achievement of the expected standards; the electron beam control adjustment result includes the power adjustment value, the focal length adjustment value and the optimization of the robustness in welding; the welding quality detection result includes the consistency data of the weld, the quality deviation result and the statistics of the weld pass rate in welding.

3. The vacuum electron beam high frequency pulse welding method for core parts of semiconductor equipment according to claim 1, characterized in that: The pulse frequency and duration are iteratively optimized based on the heat distribution simulation results, and the parameter values ​​are adjusted to avoid the thermal influence of the welding area. The steps of obtaining the optimized pulse parameters are as follows: Based on the heat distribution simulation results, the heat influencing factors of the welding area are analyzed, including the temperature peak and the non-uniformity of the heat distribution, the key intervals of the pulse frequency and duration that need to be adjusted are identified, and the pulse parameter adjustment requirements are obtained; According to the pulse parameter adjustment requirements, a genetic algorithm is used to optimize the parameters through encoding, selection, crossover and mutation, and the pulse frequency and duration are gradually adjusted to obtain an iterative optimization record; The iterative optimization records are used to determine the optimal vacuum electron beam pulse frequency and duration, check the parameters to avoid thermal effects during welding, and verify the welding quality and efficiency to obtain optimized pulse parameters.

4. The vacuum electron beam high frequency pulse welding method for core parts of semiconductor equipment according to claim 3, characterized in that: The formula of the genetic algorithm is as follows: in, is the fitness of the target parameter, is the parameter combination of pulse frequency and duration, is the pulse shape parameter, is the initial energy distribution parameter, is the cooling rate parameter, is the weight coefficient, is the heat distribution unevenness, is the normalization coefficient.

5. The vacuum electron beam high frequency pulse welding method for core parts of semiconductor equipment according to claim 1, characterized in that: The formula of the support vector machine algorithm is as follows: in, is the predicted value of welding quality, is the total number of support vectors, To traverse the index of the support vector, For real-time input of welding parameters, is the pulse frequency, is the duration, is the pulse intensity, is the cooling rate, is the coefficient of the support vector, is the target value of the training sample, is the support vector, is the kernel function, is the deviation term.

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