Intelligent welding system and welding processing technology for cooling fins

Abstract

The invention relates to the technical field of intelligent welding, and discloses an intelligent welding system for cooling fins and a welding machining process. Arranging and calibrating temperature and humidity sensors at multiple points in the welding area to obtain temperature-voltage and humidity-voltage conversion; calculating regional average temperature and humidity and reference deviation based on the calibration data; parameters such as heat conductivity coefficient, thickness, weld length and width, density and specific heat at constant pressure of the radiating fins are collected, and a one-dimensional heat resistance and equivalent heat capacity model is established; a temperature and humidity correction function is constructed, a compensation factor boundary is judged, target temperature rise and action time are set, and single-point heat energy and actual power are deduced; generating a position and power instruction, monitoring the current during execution, and performing threshold-crossing suspension or jumping; and recording the environment and parameters of each point after welding, and regularly updating the compensation model. According to the process, a closed loop from environment perception to execution of monitoring and model updating is formed, the environment influence is quantified, and tracing and reasonable distribution are achieved.

Description

Technical Field

[0001] This invention relates to the field of intelligent welding technology, specifically to an intelligent welding system and welding process for heat dissipation fins. Background Technology

[0002] Heat sink fins are widely used in electronic heat sinks, heat exchangers, and vehicle thermal management components. Their typical characteristics include thin material, large size, small heat capacity, and extreme sensitivity to heat input overshoot. Taking aluminum and aluminum alloy fins as an example, the material has high thermal conductivity and a dense natural oxide film on its surface. Even slight deviations in heat input can lead to insufficient wetting, poor soldering, warping, or localized overheating. Furthermore, the actual contact state between the fins and the substrate (contact resistance, fit, surface cleanliness) exhibits significant variability across different batches and workstations, resulting in varying welding effects for the same nominal process parameters at different times.

[0003] On existing production lines, a fixed power-fixed time (or current-time) strategy is often adopted to improve cycle time and consistency, and general disturbances are addressed through pre-selected process windows. However, the actual workshop environment's temperature and relative humidity vary significantly with the season and shift. At high temperatures, the initial temperature of materials increases and heat dissipation capacity changes; at high humidity, trace moisture absorption and surface condensation easily occur, altering the thermal-electric boundary conditions of the pre-welding interface, especially significantly affecting resistance welding or arc thermal coupling processes: contact resistance and heat dissipation paths are dynamically rewritten, causing the equivalent heat input under the same set power to deviate from the target, manifested as fluctuations in weld nugget size, increased dispersion in weld strength, or increased spatter defects. Traditional remedies include: expanding the process window, increasing preheating, increasing clamping force, or setting up protective covers (hot air / drying airflow) in local areas, but these methods either increase energy consumption and equipment complexity or introduce new uncertainties (such as overall temperature rise and deformation caused by overheating), and are difficult to replicate across production lines. Other solutions attempt to use online closed-loop sensing (melt pool vision, infrared temperature, or electrical signal feedback) to correct the process in real time. However, for highly reflective aluminum surfaces, thin-walled geometry, and high-speed cycle conditions, visual / infrared signals are easily affected by reflection, occlusion, and response lag. Data-driven methods based on complex models or training dependencies also suffer from high deployment barriers, uninterpretable parameters, and difficulties in cross-scenario migration. In factory scenarios with multiple varieties, small batches, and 24 / 7 operation, how to perform calculable, traceable, and auditable feedforward compensation for environmental temperature and humidity disturbances without significantly increasing the sensing and computing burden has become a key requirement for ensuring welding consistency.

[0004] Therefore, this case aims to propose an intelligent welding system and welding process for heat dissipation fins. It can acquire multi-point environmental temperature and humidity information in real time, combine the workpiece thermal property parameters, establish a one-dimensional thermal resistance and equivalent heat capacity model, generate dynamic compensation factors through temperature and humidity correction functions, and then generate welding commands that can be issued with single-point target thermal energy and compensation power as the core. Finally, it achieves quality closed loop by relying on current monitoring and result recording, and updates the compensation model regularly. Summary of the Invention

[0005] This invention provides an intelligent welding system and welding process for heat dissipation fins, which helps to solve the problems mentioned in the background art.

[0006] This invention provides the following technical solution: an intelligent welding process for heat dissipation fins, comprising: Multiple ambient temperature and humidity sensors were deployed at various points within the welding area, and each sensor was calibrated to obtain the temperature-voltage and humidity-voltage conversion coefficients of the sensors. Based on the calibrated sensor data, the equivalent average temperature and humidity of the area are calculated, and the temperature and humidity deviations relative to the preset benchmark are extracted. Obtain the physical parameters of a single heat sink fin, and establish a one-dimensional thermal resistance and equivalent heat capacity model accordingly. The physical parameters include the material's thermal conductivity, fin thickness, weld length, weld width, material density, and specific heat at constant pressure. Construct temperature correction functions and humidity correction functions, calculate comprehensive compensation factors based on environmental deviations, and determine the effectiveness and boundary values ​​of the compensation factors. Set the target temperature rise value and welding time, derive the target thermal energy at a single point, and calculate the actual welding power by combining the reference ambient power and compensation factor; Welding paths are generated based on the positions of each solder point on the heat sink fins, and welding instructions are constructed according to a determined power sequence. The welding execution system controls the welding to perform welding at each welding point in sequence with actual power, monitors the current in real time, and stops or adjusts the welding when the current exceeds the preset threshold or when there is a risk of skipping steps. Record the average ambient temperature and humidity when each weld point is completed, archive the welding parameters, and update the compensation model regularly based on the monitoring data; The welding parameters include the weld point location, the actual power used for the weld point, and the result code.

[0007] Optionally, the step of deploying environmental temperature and humidity sensors at multiple points within the welding area and calibrating each sensor to obtain the temperature-to-voltage and humidity-to-voltage conversion coefficients of the sensors specifically includes: Four sets of environmental sensors are installed at the four corners of the heat sink fin welding area. Each set includes one temperature sensor and one humidity sensor, and are numbered accordingly. The corresponding location has the following latitude and longitude: ;in, Number the sensors; For the first Latitude coordinates of sensor number; For the first The longitude coordinates of the sensor; Select temperature calibration point pair Let their values ​​be respectively , Record the first one respectively The corresponding voltage value of each temperature sensor , And based on this, the temperature conversion coefficient is calculated: , ;in, For low-level calibration temperature; For high-level calibration temperature; For the first A temperature sensor in The original voltage; For the first A temperature sensor in The original voltage; For the first Temperature-voltage slope of a temperature sensor; For the first Temperature-voltage intercept of a temperature sensor; If it appears If the problem persists after three consecutive measurements, stop the calculation, select a different temperature calibration point pair, and measure again. The temperature sensor was determined to be faulty; it was replaced and then calibrated. Let the humidity calibration point pair be Record the first one respectively The corresponding voltage value of each humidity sensor , Based on this, the humidity conversion factor is calculated: , ;in, The relative humidity at the first and high positions are respectively calibrated. , The first Voltage of a humidity sensor under low and high humidity calibration conditions; For the first Humidity-voltage slope of a humidity sensor; For the first Humidity-voltage intercept of a humidity sensor; If it appears If the current calculation fails, select a different humidity calibration point pair and remeasure; if the result is still the same after three consecutive measurements... The humidity sensor was determined to be faulty; the sensor was replaced and then calibrated. At system startup , collect the first Voltage value of a temperature and humidity sensor and And calculate the actual temperature and humidity values: , ;in, For a moment No. Voltage of each temperature sensor; time No. Voltage of each humidity sensor; For a moment No. Temperature measured by a temperature sensor; For a moment No. Humidity measured by a humidity sensor; Set the temperature resolution to Humidity resolution is Temperature range is With humidity range ;in, These are the lower and upper limits of the measurable temperature, respectively. These represent the lower and upper limits of measurable humidity, respectively. Obtain the resolution of the welding current measurement, denoted as The current range is denoted as . ;in, These are the lower and upper boundaries for current measurement, respectively. The output power capability range of the welding machine is obtained, denoted as . ;in, These represent the lower and upper limits of the welding machine's output power capability, respectively. Write the temperature resolution, humidity resolution, temperature range, humidity range, current measurement resolution, current range, and welding machine output power capability range into the process data table.

[0008] Optionally, the step of calculating the equivalent average temperature and humidity of the area based on the calibrated sensor data, and extracting the temperature and humidity deviation relative to a preset benchmark, specifically includes: Calculate the actual average temperature and humidity within the four-point area: , ;in, The equivalent average temperature of the region; The equivalent average humidity of the region; Set temperature reference Humidity standard ; Calculate temperature and humidity deviation: , ;in, This is due to the deviation in ambient temperature. This is due to environmental humidity deviation.

[0009] Optionally, obtaining the physical parameters of a single heat dissipation fin and establishing a one-dimensional thermal resistance and equivalent heat capacity model accordingly specifically includes: Obtain the physical parameters of the current workpiece, including: thermal conductivity of the fin material. fin thickness Single-point weld length Effective weld width Material density Specific heat at constant pressure ; The fins are regular cuboids; Calculate the transverse thermal conductivity cross-sectional area of ​​the weld. ; Calculate the one-dimensional steady-state thermal resistance along the thickness direction. ; Calculate the volume of the welded material. With equivalent heat capacity : , .

[0010] Optionally, the construction of temperature correction functions and humidity correction functions, and the calculation of a comprehensive compensation factor based on environmental deviations, while simultaneously determining the effectiveness and boundary values ​​of the compensation factor, specifically includes: Constructing a temperature correction function ; Construct a humidity correction function ; Calculate the total compensation factor ; If there exists any make or If this occurs, the welding process will be terminated, and environmental data will be output as out of bounds. like The welding process is aborted, and the compensation factor is output as invalid. Calculate the achievable range derived from the measurement range: , ;in, , These are the minimum and maximum comprehensive compensation factors derived from the measurement range, respectively. like If the data is deemed inconsistent, the welding process is stopped and an inconsistency error is output; otherwise, the process continues to the next step.

[0011] Optionally, the setting of the target temperature rise value and welding time, the derivation of the single-point target thermal energy, and the calculation of the actual welding power in combination with the reference environmental power and compensation factor specifically include: Set target temperature rise value ; Set welding action time ; Calculate the energy of a single target point ; Obtain welding power under reference conditions ; Calculate the actual compensation power ; like If the welding process is interrupted, the output power will exceed the limit.

[0012] Optionally, the step of generating a welding path based on the location of each solder point on the heat sink fins and constructing welding instructions according to a determined power sequence specifically includes: Obtain the total number of solder joints, denoted as The number is recorded as The location coordinates are ;in, The first The latitude and longitude coordinates of each weld point; For any Set the solder joint power to ;in, For the first The target power for each solder joint during execution; Constructing a welding instruction sequence .

[0013] Optionally, the controlled welding execution system performs welding at each weld point sequentially with actual power, monitors the current in real time, and stops or adjusts the welding when the current exceeds a preset threshold or when there is a risk of skipping steps. Specifically, this includes: Execute the welding path sequentially. Each solder joint will position the solder head at one of the solder joints. ; Control output power to The fixed action time is ; Set the first The start time of each solder joint is The end time is ; Let the welding current threshold be... ; like If the current exceeds the threshold, the welding of that batch will be stopped. Subsequently in the interval The instantaneous current measured internally is denoted as . Calculate the first Each solder joint is in the interval Maximum current inside ; like Record the result code ;in, For the first The result code for each solder joint has a set of values. ; like Skip to that point and record it. Then proceed to the next solder joint.

[0014] Optionally, the recording of the average ambient temperature and humidity at the completion of each weld point, archiving welding parameters, and periodically updating the compensation model based on monitoring data specifically includes: For each point, record the end time after welding. And calculate the average temperature and humidity of the area: , ;in, For the first Average temperature of the area at the moment each solder joint is completed; For the first Average humidity in the area at the moment each solder joint is completed; Calculate the mean of the global compensation factor : ; Statistical update threshold: ;in, The update threshold for the environmental compensation mean; like ,Will Updated to And archive; Otherwise, maintain the present value and archive the monitoring data. .

[0015] A system for implementing the intelligent welding process for the heat sink fins, comprising: The environmental sensing module is used to deploy and calibrate multi-point temperature and humidity sensors and collect environmental data. The parameter calculation module is used to calculate regional environmental parameters and baseline deviations; The thermal modeling module is used to determine the thermal parameters of the fins and construct models of heat capacity and thermal resistance. The compensation factor module is used to construct temperature and humidity compensation functions and perform boundary determination. The power derivation module is used to calculate the target thermal input power and the environmentally corrected power; The path planning module is used to generate multi-weld-point paths and serialize power commands; The control and execution module is used to implement welding and step-by-step protection; The data archiving module is used to store welding parameters and periodically update the compensation model.

[0016] The present invention has the following beneficial effects: 1. Multiple sets of temperature and humidity sensors are deployed in the corners of the welding area, and calibration is performed using dual-point linear mapping to ensure the comparability and consistency of temperature and humidity data output by different sensors. Compared with traditional single-point measurement or schemes without clear spatial positioning, this design establishes a reliable spatial sampling basis through spatial coverage and latitude-longitude positioning calibration, eliminating the interference of local deviations on the global environmental judgment. A systematic comparison of hardware differences between multiple sensors dynamically identifies failures and automatically triggers recalibration or replacement strategies, ensuring that online monitoring data remains reliable at all times. This improves the accuracy and stability of environmental monitoring, provides solid data support for subsequent compensation algorithms, and overcomes the problems of unstable weld formation and high rework rates caused by inaccurate environmental measurements in existing technologies.

[0017] 2. Multi-point sensor readings are fused using an arithmetic mean to form a temperature and humidity scalar representing the overall state of the welding area. Relative deviations are then extracted using a preset benchmark value. Introducing a transferable benchmark system ensures consistency in environmental parameter comparisons and compensation calculations across batches, workshops, and seasons, avoiding compensation deviations caused by inconsistent baselines. Compared to traditional methods that directly use single-point real-time readings for control, this method statistically reduces the impact of random errors and short-term fluctuations on process control, ensuring the robustness and interpretability of the compensation strategy. Furthermore, by explicitly extracting deviations and inputting them into the compensation function, the method addresses the lack of quantitative evidence regarding environmental impact and the difficulty in tracking compensation effects in existing technologies, thereby improving welding consistency and yield.

[0018] 3. Based on the acquisition of physical parameters of a single heat sink fin, this scheme maps the geometric features of the weld seam and the thermal properties of the material to the thermally conductive cross-sectional area and the steady-state thermal resistance along the thickness direction. Furthermore, it calculates the equivalent heat capacity based on the weld volume and the accumulation of the material's specific heat, thus completing the construction of the thermal model. This simplifies the two-dimensional or three-dimensional heat transfer problem into a quantifiable one-dimensional model, effectively reducing computational complexity and ensuring the physical consistency of the model. Compared with existing techniques that rely on experience or simulation software to obtain thermal parameters, this scheme directly correlates parameters through closed-form expressions, supporting rapid online calculation and dynamic updates. This model establishes a clear linear relationship between the target thermal energy and the target temperature rise, providing a quantifiable basis for power derivation and compensation strategies, thereby solving the problems of slow response to material and shape differences and insufficient precision in weld point temperature control in traditional processes.

[0019] 4. Temperature and humidity correction functions are constructed separately to convert environmental deviations into power ratios. A comprehensive compensation factor is generated through multiplicative coupling, and the validity and boundary conditions of this factor are determined. The intuitive and interpretable expression of environmental impact factors simplifies the compensation logic and makes it easy to debug. Runtime boundary checks are introduced; when environmental parameters exceed limits or compensation factors are inconsistent, the process is automatically interrupted and an error message is issued, ensuring equipment and product safety. Unlike existing technologies that simply add or subtract fixed power compensation, this solution uses independent factor coupling, avoiding inherent conflicts between compensation parameters and improving adaptability to complex environmental changes. This algorithm effectively solves the problem of unmonitored welding quality or untimely compensation under high humidity or extreme temperature conditions, improving the stability and safety of welding results.

[0020] 5. By setting target temperature rise and application time, this scheme maps the temperature rise requirement to a quantifiable target thermal energy using a heat capacity model. The actual power output is then calculated by combining the baseline environmental power and a comprehensive compensation factor. With energy as the core indicator, temperature and time are explicitly incorporated into the process design, giving power allocation clear physical meaning and traceability. Compared to existing common experience-based ratios or fixed power output methods, this method can dynamically adjust power according to different batches and environmental conditions, avoiding welding defects or equipment damage caused by overload or underload operation. This method solves the pain point of traditional processes lacking quantitative guidance on temperature control time windows, leading to uneven weld formation or high rework rates, laying the foundation for optimizing welding quality and resource utilization.

[0021] 6. The set of weld points is discretized into an ordered sequence, and a unified welding instruction triplet is constructed using position and power as core information, which is then explicitly issued to the execution system. This organically integrates spatial coordinates, power, and time windows, achieving seamless integration from process design to execution instructions. Simultaneously, at the instruction level, unambiguous commands and controllable sequence facilitate traceability and archiving. Unlike existing systems that require manual programming or intermediate tools for path planning, this solution automates the entire instruction generation process, shortening the cycle from solution design to equipment execution and reducing human error rates. This solution effectively addresses the risk of welding defects caused by disordered sequence or power mismatch in multi-weld point operations, improving production efficiency and quality consistency.

[0022] 7. During the execution phase, this solution monitors the current threshold for each weld joint and automatically stops or skips steps when abnormal current or lack of power is detected, generating a result code to record the quality status. Quality feedback is embedded in the execution closed loop, replacing subjective evaluation with hard threshold criteria, giving protective measures verifiable physical evidence. It also supports skipping steps for abnormal weld joints without interrupting the entire batch, balancing production capacity and quality. Compared to existing monitoring technologies that rely on visual or temperature feedback, this solution directly reflects the welding on / off status using current signals, resulting in faster and more stable responses. This solution effectively solves the quality risks caused by manual inspection or delayed feedback, ensuring a high yield rate even in unattended or high-speed production environments.

[0023] 8. By recording the post-weld environmental conditions and compensation factors for each weld point, the batch-average compensation factor is calculated and compared with the update threshold to determine whether to correct the compensation model. A statistical significance criterion is introduced, ensuring the model is only updated when the environmental deviation exceeds the measurement resolution, avoiding frequent adjustments caused by noise. Simultaneously, the update process is traceable and archived, providing data support for subsequent process optimization. Compared to existing simple accumulation or periodic manual calibration methods, this solution achieves true online self-adaptation, tracking environmental change trends while suppressing invalid oscillations. This solution addresses the problem of model failure or over-correction in dynamic environments, further improving the stability and consistency of long-term production. Attached Figure Description

[0024] Figure 1 This is a schematic diagram of the process of the present invention.

[0025] Figure 2 This is a schematic diagram of the welding work area of ​​the present invention.

[0026] Figure 3 This is a schematic diagram of the effective weld of the present invention.

[0027] In the diagram: 1—Welding work area; 2, 3, 4 and 5—Four corners of the welding work area; 6 and 7—Top view of the fins; 8—Effective weld. Detailed Implementation

[0028] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0029] Example, refer to Figure 1 A smart welding process for heat sink fins includes: Multiple ambient temperature and humidity sensors were deployed at various points within the welding area, and each sensor was calibrated to obtain the temperature-voltage and humidity-voltage conversion coefficients of the sensors. Based on the calibrated sensor data, the equivalent average temperature and humidity of the area are calculated, and the temperature and humidity deviations relative to the preset benchmark are extracted. Obtain the physical parameters of a single heat sink fin, and establish a one-dimensional thermal resistance and equivalent heat capacity model accordingly. The physical parameters include the material's thermal conductivity, fin thickness, weld length, weld width, material density, and specific heat at constant pressure. Construct temperature correction functions and humidity correction functions, calculate comprehensive compensation factors based on environmental deviations, and determine the effectiveness and boundary values ​​of the compensation factors. Set the target temperature rise value and welding time, derive the target thermal energy at a single point, and calculate the actual welding power by combining the reference ambient power and compensation factor; Welding paths are generated based on the positions of each solder point on the heat sink fins, and welding instructions are constructed according to a determined power sequence. The welding execution system controls the welding to perform welding at each welding point in sequence with actual power, monitors the current in real time, and stops or adjusts the welding when the current exceeds the preset threshold or when there is a risk of skipping steps. Record the average ambient temperature and humidity when each weld point is completed, archive the welding parameters, and update the compensation model regularly based on the monitoring data; The welding parameters include the weld point location, the actual power used for the weld point, and the result code.

[0030] By establishing a complete process flow encompassing environmental perception, thermal modeling, compensation calculation, path planning, execution monitoring, and adaptive updates, intelligent closed-loop control of the entire heat sink fin welding process was achieved. Specifically, firstly, temperature and humidity sensors are deployed and calibrated at multiple points in the welding area to eliminate single-point measurement errors and obtain consistent environmental data. Then, the equivalent average temperature and humidity of the area and their deviation from a preset benchmark are calculated, quantifying the environmental impact that was previously ignored or relied upon solely on experience and inputting it into subsequent steps. Next, a one-dimensional thermal resistance and equivalent heat capacity model is constructed based on the fin material and geometric parameters, providing a physical basis for power derivation. Then, a comprehensive compensation factor is calculated using temperature and humidity correction functions to dynamically adjust the required heat input. Next, welding instructions are generated in a sequence based on position and power, and the current is monitored in real time during execution. If an over-threshold or on / off anomaly is detected, the process is immediately stopped or skipped. Finally, the environmental and welding parameters at each point are recorded, and the compensation model is updated periodically accordingly. This process solves the problems of slow response to environmental disturbances, empirical energy distribution, and lack of process traceability in traditional welding processes. It improves the consistency of weld formation, reduces the rework rate, and enables data traceability and online optimization, resulting in a dual improvement in quality and efficiency. This is significantly different from the isolated steps, manual intervention, or post-processing adjustments in existing technologies.

[0031] Reference Figure 2 The step of deploying environmental temperature and humidity sensors at multiple points within the welding area and calibrating each sensor to obtain the temperature-to-voltage and humidity-to-voltage conversion coefficients of the sensors specifically includes: Four sets of environmental sensors are installed at the four corners of the heat sink fin welding area. Each set includes one temperature sensor and one humidity sensor, and are numbered accordingly. The corresponding location has the following latitude and longitude: ;in, Number the sensors; For the first Latitude coordinates of sensor number; For the first The longitude coordinates of the sensor are determined; spatial coverage and positioning calibration of the working area are completed to ensure that the temperature / humidity data have clear spatial ownership and traceability, providing a stable and reproducible spatial sampling basis for subsequent calculation of "regional average - benchmark deviation - compensation factor", and avoiding the impact of local deviations caused by single-point measurement on global process parameters; Select temperature calibration point pair Let their values ​​be respectively , Record the first one respectively The corresponding voltage value of each temperature sensor , And based on this, the temperature conversion coefficient is calculated: , ;in, For low-level calibration temperature; For high-level calibration temperature; For the first A temperature sensor in The original voltage; For the first A temperature sensor in The original voltage; For the first Temperature-voltage slope of a temperature sensor; For the first Temperature-voltage intercept of each temperature sensor; establish a one-to-one correspondence between voltage and temperature through a two-point linear mapping, eliminate individual sensor sensitivity differences, ensure the comparability and consistency of temperature readings from different sensors, and provide a reliable metric for all subsequent temperature-related calculations (average, deviation, compensation). If it appears If the problem persists after three consecutive measurements, stop the calculation, select a different temperature calibration point pair, and measure again. The temperature sensor was determined to be faulty; it was replaced and then calibrated. Let the humidity calibration point pair be Record the first one respectively The corresponding voltage value of each humidity sensor , Based on this, the humidity conversion factor is calculated: , ;in, The relative humidity at the first and high positions are respectively calibrated. , The first Voltage of a humidity sensor under low and high humidity calibration conditions; For the first Humidity-voltage slope of a humidity sensor; For the first The humidity-voltage intercept of each humidity sensor is determined; a linear conversion between voltage and relative humidity is established to standardize humidity measurement standards, making subsequent humidity average and deviation calculations comparable, thereby enabling the humidity compensation item to... The input is accurate and reliable; If it appears If the current calculation fails, select a different humidity calibration point pair and remeasure; if the result is still the same after three consecutive measurements... The humidity sensor was determined to be faulty; the sensor was replaced and then calibrated. At system startup , collect the first Voltage value of a temperature and humidity sensor and And calculate the actual temperature and humidity values: , ;in, For a moment No. Voltage of each temperature sensor; time No. Voltage of each humidity sensor; For a moment No. Temperature measured by a temperature sensor; For a moment No. Humidity measured by a humidity sensor; on a unified time base. The temperature and humidity of each point are obtained as "calibrated" to provide an initial cross section for calculating the regional average and reference deviation; this cross section represents the actual environmental conditions before welding and is the starting point for calculating compensation parameters. Set the temperature resolution to Humidity resolution is Temperature range is With humidity range ;in, These are the lower and upper limits of the measurable temperature, respectively. These represent the lower and upper limits of measurable humidity, respectively. Temperature resolution Function: Temperature resolution is used to characterize the smallest distinguishable step size of temperature readings. In this scheme, it is first solidified as a "hard indicator" of on-site measurement capability, and then directly incorporated into the threshold construction for environmental compensation consistency and out-of-bounds judgment, determining whether the compensation value needs to be updated and whether the current data is reliable. In short, The resolution determines the granularity at which ambient temperature deviations are "visible," and also the system's sensitivity and stability to small environmental drifts. Smaller resolution makes it easier to capture subtle temperature changes and provides more sensitive compensation updates, but it also makes it easier to mistake short-term fluctuations and electrical noise for valid changes, leading to an increased update frequency. Larger resolution naturally "filters out" small disturbances, resulting in more stable updates, but it may mask small temperature differences that could affect solder joint formation, causing compensation lag. If the resolution is much smaller than the ambient noise, the practical benefits are limited; if the resolution is close to or greater than the typical temperature difference, compensation is essentially ineffective. The optimal value should be determined by a comprehensive consideration of the target temperature rise, workshop temperature control methods and seasonal fluctuations, sensor noise and stability, and the smoothing effect of averaging after four-point sampling. The key is to ensure that the "minimum resolvable temperature difference" is less than the general environmental drift that may affect solder joint formation, while not significantly lower than the noise level. Recommended values: For aluminum fin welding targeting moderate temperature rise, a resolution of no more than 0.2 Kelvin is recommended. In environments with weak temperature control and significant seasonal variations, a range of 0.1 to 0.2 Kelvin is preferable. In temperature-controlled rooms or production lines with good temperature control, 0.05 to 0.1 Kelvin is more suitable, but it must be confirmed that noise and stability can support it. Regardless of the value chosen, static and dynamic tests must be performed before going live to ensure that the resolution is less than the stable portion of short-term temperature fluctuations and does not frequently trigger meaningless compensation updates.

[0032] Humidity resolution Function: Humidity resolution defines the minimum resolvable step size for relative humidity readings. In this scheme, it is also fixed, like temperature resolution, and directly participates in compensating for consistency thresholds and effectiveness judgments. Because humidity has a significant impact on surface moisture absorption, slight condensation, and the state of contact interfaces, This determines whether the system can "detect" humidity changes that substantially affect energy demand before welding. A smaller resolution makes it easier to capture small humidity fluctuations, allowing for more precise compensation adjustments, but it's also more easily triggered by short-term disturbances such as personnel activity or access control openings. A larger resolution avoids frequent updates but may miss slow increases that affect wetting and forming. If the resolution is set too coarsely, obvious humidity changes may be mistaken for "no change"; if it's set too finely, "compensation jitter" may occur during normal production. Value selection should be based on local seasonal humidity distribution, production area ventilation and dehumidification conditions, the sensitivity of material surface treatment processes to humidity, and the sensor's response time and short-term repeatability. The key is to identify the typical magnitude of the "humidity step that affects forming" on the production line and calibrate accordingly. Recommended values: Generally, for electronics and heat exchanger workshops, a value no greater than 0.5 percentage points is recommended. For scenarios with strict relative humidity control or extreme sensitivity to condensation, a range of 0.1 to 0.3 percentage points is recommended. If the workshop humidity fluctuates significantly and there is no centralized dehumidification, 0.5 percentage points is more robust. Before going live, a corridor test needs to be conducted during typical day-night and working condition switching periods to confirm that the resolution can distinguish meaningful humidity rises without being frequently triggered by short-cycle disturbances.

[0033] Temperature range Function: The temperature range defines the legal range of the measurement system and is directly used for environmental data validity verification and the derivation of the achievable compensation range. It determines the environment in which the system can continue welding and the theoretical upper and lower bounds of comprehensive compensation. The range also reflects the compliance and safety boundaries of the equipment, serving as the first line of defense against abnormal data, faulty sensors, and extreme environments. A range that is too narrow can lead to frequent production stoppages during normal seasonal fluctuations or when local heat sources are present; a range that is too wide makes it easier for abnormal observations to "mix" into the legal domain and also excessively widens the theoretical range of comprehensive compensation, reducing the interception capability of consistency verification. An excessively high upper limit may also mask the risk warnings from local overheating; an excessively low lower limit may cause the risk of low-temperature condensation to be overlooked. Basis for value selection: It should refer to the factory's air conditioning and fresh air capacity, the diurnal and seasonal temperature distribution in historical records, the superposition of heat dissipation from equipment near the workstation, and the tolerance of the product and fixture to ambient temperature. A safety margin for actual fluctuations and occasional disturbances should be reserved, while extreme values ​​should not be allowed to enter the compensation calculation. Recommended values: Generally set within the Kelvin range corresponding to 5 to 45 degrees Celsius, satisfying most operating conditions in both northern and southern regions; if a temperature-controlled room is available, the range can be further narrowed to 20 to 30 degrees Celsius; for large open-plan factories with significant summer heat, the upper limit can be increased, but it is recommended to add management of condensation and personnel heat sources. Once the range is determined, the upper and lower limits of the comprehensive compensation should be derived from this range, and it should be verified during the first batch of deployments that normal environmental fluctuations will not cause the limits to be falsely triggered.

[0034] Humidity range Function: The humidity range is used to determine the validity of humidity data and participates in the derivation of the achievable range of comprehensive compensation. Together with the temperature range, it determines whether continued operation is permissible before welding and the maximum and minimum boundaries of the compensation multiplier, thus preventing blindly applying power under unsuitable air humidity conditions. A range that is too narrow will frequently trigger shutdowns during the rainy season, humid weather, or rainy / snowy weather; a range that is too wide may fail to detect slight condensation or extreme dryness, leading to compensation distortion or even quality issues. An excessively high upper limit weakens the identification of condensation risks; an excessively low lower limit may ignore the impact of static electricity and surface cracking on the contact interface. Value selection should be based on local climate, factory dehumidification and ventilation capabilities, historical humidity distribution, product humidity sensitivity, and pre-processing cleaning and storage conditions. The key is to clearly define the boundary between "producible" and "requiring shutdown," and ensure that this boundary matches the quality risk. Recommended values: Generally, a range of 10 to 90 percentage points is recommended. If centralized dehumidification and constant temperature and humidity conditions are available, this range can be narrowed to 30 to 70 percentage points. In southern regions during the rainy season, coastal areas, or areas with high humidity, the upper limit can be slightly higher, but corresponding measures for material drying, temporary storage, and feeding cycle should be implemented simultaneously. After determining the value, the frequency of shutdowns should be reviewed during the first month of operation to prevent the range setting from being too lenient, reducing interception capacity, or too stringent, affecting production capacity.

[0035] Obtain the resolution of the welding current measurement, denoted as The current range is denoted as . ;in, These are the lower and upper boundaries for current measurement, respectively. The output power capability range of the welding machine is obtained, denoted as . ;in, These represent the lower and upper limits of the welding machine's output power capability, respectively. Write the temperature resolution, humidity resolution, temperature range, humidity range, current measurement resolution, current range, and welding machine output power capability range into the process data table; It provides "hard constraints and measurement limits" for subsequent boundary determination and threshold derivation; used to filter out out-of-bounds data, verify the reachability range of compensation factors, determine whether the power falls within the equipment capacity range, define on / off thresholds, and calculate statistical update thresholds.

[0036] This paper details the steps for deploying environmental sensors at the four corners of the welding area and performing dual-point linear calibration. Through systematic spatial coverage and precise calibration, high reliability of environmental data is achieved. Specific steps include equidistant deployment at the four corners, a combination of dual temperature and humidity sensors at each location, and voltage measurement using two sets of standard points (low and high) to construct a linear mapping relationship and eliminate failed sensors. This method solves the spatial deviation and sensor sensitivity differences caused by existing single-point or unstructured deployments, ensuring all readings have clear coordinate assignments and comparability, thus providing a reliable basis for subsequent calculations. Furthermore, automatic recalibration or replacement is triggered when calibration fails or exceeds tolerances, ensuring stable system operation. This design reduces welding energy deviation caused by environmental measurement errors, allowing the compensation algorithm and power derivation to be based on reliable environmental quantification. Compared to traditional techniques relying on experience or single sensor readings, it has higher accuracy and robustness, which is of great significance for improving welding yield and production safety.

[0037] The calculation of the equivalent average temperature and humidity of the area based on the calibrated sensor data, and the extraction of the temperature and humidity deviation relative to a preset benchmark, specifically includes: Calculate the actual average temperature and humidity within the four-point area: , ;in, The equivalent average temperature of the region; The equivalent average humidity of the region is obtained by merging the readings of the four corner points in an equal weighted manner to reduce the influence of single-point random errors and small spatial gradients, thus obtaining a scalar temperature / humidity that represents the overall state of the welding area, laying a statistical foundation for unified deviation calculation. Set temperature reference Humidity standard It provides a zero-point reference for process deviations, enabling environmental conditions under different batches, workshops, or seasons to be compared and quantified on a unified benchmark, thereby ensuring the consistency and transferability of compensation logic. Calculate temperature and humidity deviation: , ;in, This is due to the deviation in ambient temperature. For environmental humidity deviation, the absolute value is converted into a relative deviation, which is then used as the direct input of the compensation function to avoid the influence of "normal offset" of different workstations on the consistency of power setting.

[0038] By arithmetically averaging the readings from four environmental sensors and comparing them with a preset benchmark, temperature and humidity deviations are extracted, providing a consistent quantification input for the compensation function. This solves the problem of compensation failure caused by inconsistent baselines across different batches and operating conditions in existing technologies. The specific steps involve first fusing spatial readings, then setting a process deviation benchmark, and finally converting it into a relative deviation. This deviation directly drives the compensation function, avoiding reference confusion caused by absolute value differences. In any workshop and any season, a transferable compensation strategy can be obtained by using the same benchmark, ensuring consistent welding quality across batches and production lines. Unlike traditional methods that simply substitute real-time readings into the control without benchmarking, this method enhances process replicability and comparability, improving production process stability and the transferability of process parameters.

[0039] Reference Figure 3 The process of obtaining the physical parameters of a single heat sink fin and establishing a one-dimensional thermal resistance and equivalent heat capacity model based on these parameters specifically includes: Obtain the physical parameters of the current workpiece, including: thermal conductivity of the fin material. fin thickness Single-point weld length Effective weld width Material density Specific heat at constant pressure ; The fins are regular cuboids; Calculate the transverse thermal conductivity cross-sectional area of ​​the weld. Map the weld geometry to a heat transfer section, for The area term is provided, which indirectly reflects the influence of weld shape and size on the heat conduction path; Calculate the one-dimensional steady-state thermal resistance along the thickness direction. It provides the equivalent impedance for steady-state thermal conductivity in the thick direction, which can be used for thermal design verification and extreme boundary analysis (such as excessively thick / thin, low / high thermal conductivity materials); it does not directly participate in the main energy calculation, but can be used to review the achievability of the target temperature rise and the risk of heat leakage. Calculate the volume of the welded material. With equivalent heat capacity : , The equivalent heat capacity is calculated using volume and material thermophysical properties. This establishes a linear relationship between the target energy and the target temperature rise, ensuring that the dimensions of the power calculation are strictly consistent with its physical meaning.

[0040] By acquiring parameters such as the thermal conductivity, geometric dimensions, and weld width of the fin material, a one-dimensional thermal resistance and equivalent heat capacity model is established. This simplifies the complex multidimensional heat transfer problem into a physical quantity that can be calculated online, solving the problems of long calculation cycles and insufficient accuracy caused by existing technologies relying on simulation software or empirical coefficients. First, the weld geometry is mapped to the thermally conductive cross-sectional area. Then, the thickness-dependent steady-state thermal resistance is calculated. Finally, the equivalent heat capacity is obtained based on the weld volume and the material's specific heat. This model can quickly derive the linear relationship between energy and temperature rise, providing an intuitive and traceable physical basis for power calculation. It reduces computational complexity, shortens response time, and enables the system to complete power demand assessment in real time. Simultaneously, it improves the accuracy of power calculation, avoiding errors in traditional empirical formulas due to material differences or variations in fin thickness, ensuring that different types of fins receive appropriate heat input.

[0041] The process involves constructing temperature and humidity correction functions, calculating a comprehensive compensation factor based on environmental deviations, and determining the effectiveness and boundary values ​​of the compensation factor. Specifically, this includes: Constructing a temperature correction function Linear measurement of the impact of ambient temperature on heat input demand: above the baseline ( Increase the power appropriately, below the reference value ( The corresponding reduction enables direct and explainable compensation for environmental temperature differences; Construct a humidity correction function The humidity deviation is converted into a power ratio to reflect the impact of high humidity on welding energy (such as the impact of surface moisture absorption and trace condensation on heat transfer and weld formation), and the calculation is made in a linear form to ensure that the calculation is simple and traceable. Calculate the total compensation factor The two independent environmental factors of temperature and humidity are coupled by multiplication to obtain a comprehensive compensation ratio, which is used to correct the reference power in one go, reducing the complexity of parameter coupling and repeated adjustment. If there exists any make or If the welding process is interrupted, the environmental data will be output as out of bounds; distorted or abnormal hardware data will be eliminated at the source to prevent incorrect observations from entering the power calculation link and causing unsafe or unpredictable energy output. like The welding process is aborted, and the compensation factor is output as invalid. Calculate the achievable range derived from the measurement range: , ;in, , These are the minimum and maximum comprehensive compensation factors derived from the measurement range, respectively. like If the data is determined to be inconsistent, the welding process is stopped and an inconsistency error is output; otherwise, the next step is continued. Ensure that the compensation ratio is positive and within the theoretically achievable range, and avoid negative ratios or non-physical values ​​under extreme deviations or abnormal data, thereby ensuring the physical rationality and safety boundaries of subsequent power settings.

[0042] A temperature and humidity correction function is constructed to convert environmental deviations into power ratios. A comprehensive compensation factor is generated through multiplicative coupling, and the effectiveness and boundaries are dynamically assessed, achieving quantitative compensation and safety interception for environmental impacts. Specific steps include establishing linear temperature and humidity correction functions separately, synthesizing the factor, and verifying boundary anomalies. If any exceedances are detected, the process is terminated and an alarm is triggered. This design solves the problems of existing technologies that simply add or subtract fixed power compensation, which cannot adapt to complex environmental changes and lack anomaly protection. It makes the compensation logic interpretable and debuggable, and boundary judgments ensure equipment and product safety. Simultaneously, comprehensive coupling avoids repeated adjustments, improves computational efficiency and the stability of the compensation effect, and ensures accurate compensation of welding energy even under high humidity or extreme temperature conditions.

[0043] The process involves setting a target temperature rise value and welding time, deriving the target thermal energy at a single point, and calculating the actual welding power by combining the baseline environmental power and compensation factors. Specifically, this includes: Set target temperature rise value ; Set welding action time ; By defining the target temperature rise and fixed heating time, the process objectives and time window of the solder joint are clearly defined, so that the allocation of energy and power has clear design indicators, which facilitates consistent execution across batches; Calculate the energy of a single target point Mapping temperature rise demand to equivalent thermal energy demand directly connects material and geometric properties, forming a "quantifiable and traceable" basis for energy setting. Obtain welding power under reference conditions ; In a baseline environment, energy is evenly distributed across a time window to obtain a reference power, which serves as the "neutral point" for determining whether environmental correction is needed; Calculate the actual compensation power The environmental impact is integrated into the power output in one go, generating a target power value that can be directly issued, providing core process parameters for the path command sequence; like If the power output exceeds the limit, the welding process will be stopped; the equipment capacity will be used as a hard constraint to prevent overload or underload operation and ensure safety and consistency.

[0044] Using target temperature rise and application time as inputs, this method derives the energy demand at a single point and calculates the actual welding power by combining the baseline environmental power and comprehensive compensation factors, forming a complete mapping process from temperature rise to power. This solves the problems of disconnect between energy demand and time window, and lack of physical basis for power setting in existing technologies. The specific steps first clarify the process target, then obtain the baseline power, and finally obtain the allotted power value in one go, automatically stopping when the power exceeds the limit. This gives the power setting a clear and traceable physical meaning, improving the accuracy of power allocation; at the same time, it hard-constrains equipment capabilities to prevent overload or underload operation, ensuring production safety and consistency. Compared with traditional power setting methods based on experience or preset values, this solution is more flexible and reliable.

[0045] The process of generating welding paths based on the positions of each solder joint on the heat sink fins and constructing welding instructions according to a determined power sequence specifically includes: Obtain the total number of solder joints, denoted as The number is recorded as The location coordinates are ;in, The first The latitude and longitude coordinates of each weld point are determined; the discretized object and spatial location of the welding task are clearly defined, providing a definite set of instruction targets for subsequent power assignment and sequential execution; For any Set the solder joint power to ;in, For the first The target power for each solder joint is used; the same power setting is used for each solder joint to ensure process consistency under the assumptions of the same material, thickness and geometry, and to reduce batch dispersion; if subsequent partitioning differentiation is required, the value can be reassigned by block within this equation framework. Constructing a welding instruction sequence Construct an ordered triplet sequence of "position-power" as the unique execution list of the control system to avoid password ambiguity and sequence errors, and facilitate traceability and compliant archiving.

[0046] By discretizing the set of solder joints into an ordered sequence and generating structured instruction triples based on position and power, a seamless connection between process design and equipment execution is achieved, solving the problems of sequence disorder and information loss caused by manual programming or intermediate manual conversion in existing technologies. Specific steps include obtaining the coordinates of all solder joints, assigning unified power values, constructing a "position-power" sequence, and issuing it to the control system. Execution instructions can be automatically generated, reducing human intervention and the chance of errors; at the same time, the structured instructions facilitate traceability and archiving, meeting production compliance requirements and improving production efficiency and quality consistency.

[0047] The controlled welding execution system performs welding sequentially at each weld point with actual power, monitors the current in real time, and stops or adjusts the welding when the current exceeds a preset threshold or when there is a risk of skipping steps. Specifically, it includes: Execute the welding path sequentially. Each solder joint will position the solder head at one of the solder joints. Ensure the execution path is consistent with... Consistency is maintained to avoid skipping points, missing points, or disordered sequence, ensuring a clear spatial orientation for power release; Control output power to The fixed action time is ; Set the first The start time of each solder joint is The end time is ; Power and time are bound to a defined process action window, and a time boundary is given for the current criterion to ensure that the recording window and the energy release window are completely consistent. Let the welding current threshold be... ; like If the current exceeds the threshold, the welding of that batch will be stopped. Subsequently in the interval The instantaneous current measured internally is denoted as . Calculate the first Each solder joint is in the interval Maximum current inside ; like Record the result code ;in, For the first The result code for each solder joint has a set of values. ; like Skip to that point and record it. And proceed to the next solder joint; Hard threshold on / off discrimination is used to record quality compliance and skip steps, ensuring that points that have not actually had effective power / current flow can be eliminated even without feedback, thus guaranteeing the consistency between batch data and finished products.

[0048] During execution, the system monitors the current in real time and uses hard thresholds to determine the on / off state, implementing skip-step protection and batch termination logic. This solves the quality problems caused by the lag in existing reliance on visual or temperature feedback. The specific steps sequentially position the welding head, output power, and bind the time window, measuring the current in real time and comparing it with the threshold. If an anomaly is detected, the process skips or terminates, and the result code is recorded. The current signal directly reflects the welding current flow status, offering fast response and high stability. Skip-step protection ensures production capacity while preventing unwelded areas from entering the batch's acceptable range, improving data consistency and the controllability of weld quality.

[0049] The process involves recording the average ambient temperature and humidity at the completion of each weld joint, archiving welding parameters, and periodically updating the compensation model based on monitoring data. Specifically, this includes: For each point, record the end time after welding. And calculate the average temperature and humidity of the area: , ;in, For the first Average temperature of the area at the moment each solder joint is completed; For the first Average humidity in the area at the moment each solder joint is completed; Calculate the mean of the global compensation factor : ; The environmental conditions of the entire batch of solder joints are synthesized to obtain the average compensation factor representing this batch. This factor can smooth out random disturbances and reflect the systematic shifts in seasons / operating conditions, which can be used for the prior settings of subsequent batches. Statistical update threshold: ;in, The update threshold for the environmental compensation mean is constructed using the measurement resolution to suppress spurious updates. The compensation benchmark is only corrected when statistically significant differences occur, ensuring that the cross-batch settings can slowly follow environmental drift without frequent fluctuations due to measurement noise. like ,Will Updated to And archive; Otherwise, maintain the present value and archive the monitoring data. .

[0050] By recording the post-weld environmental state and compensation factor at each point, calculating the batch average and comparing it with the update threshold, the system determines whether to update the compensation model, thus achieving statistical significance-driven online adaptive modeling. Specific steps include post-weld data acquisition, mean calculation, threshold determination, and model updating. This method solves the problems of frequent invalid oscillations or excessive lag in existing technologies; it only updates when the environmental deviation exceeds the statistical significance level of the measurement resolution, thus tracking environmental trends while suppressing meaningless fluctuations, improving the stability and consistency of long-term production.

[0051] This embodiment also provides a system for intelligent welding processing of heat sink fins, including: The environmental sensing module is used to deploy and calibrate multi-point temperature and humidity sensors and collect environmental data. The parameter calculation module is used to calculate regional environmental parameters and baseline deviations; The thermal modeling module is used to determine the thermal parameters of the fins and construct models of heat capacity and thermal resistance. The compensation factor module is used to construct temperature and humidity compensation functions and perform boundary determination. The power derivation module is used to calculate the target thermal input power and the environmentally corrected power; The path planning module is used to generate multi-weld-point paths and serialize power commands; The control and execution module is used to implement welding and step-by-step protection; The data archiving module is used to store welding parameters and periodically update the compensation model.

[0052] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0053] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A heat dissipation fin intelligent welding processing technology, characterized in that, The method comprises the following steps: Multiple environmental temperature and humidity sensors are arranged in the welding area, and each sensor is calibrated to obtain the temperature-voltage and humidity-voltage conversion coefficients of the sensor; Based on the calibrated sensor data, the equivalent average temperature and humidity of the area environment are calculated, and the temperature and humidity deviation relative to the preset reference is extracted; The physical parameters of the single-piece heat dissipation fin are obtained, and a one-dimensional thermal resistance and equivalent heat capacity model is established accordingly; The physical parameters include material thermal conductivity, fin thickness, weld length, weld width, material density, and constant-pressure specific heat; Temperature correction function and humidity correction function are constructed, and comprehensive compensation factor is calculated according to environmental deviation, while the validity and boundary value of the compensation factor are determined; The target temperature rise value and welding action time are set, the single-point target heat energy is derived, and the actual welding power is calculated combined with the reference environmental power and the compensation factor; Based on the positions of the welding points of the heat dissipation fin, a welding path is generated, and a welding instruction is constructed according to the determined power sequence; The welding execution system is controlled to weld at each welding point with actual power in sequence, and the current is monitored in real time, and the welding is stopped or adjusted when the preset threshold is exceeded or the risk of step skipping occurs; The average temperature and humidity of the environment when each welding point is completed are recorded, the welding parameters are archived, and the compensation model is updated regularly according to the monitoring data; The welding parameters include the position of the welding point, the actual power used by the welding point, and the result code.

2. The finned heat sink intelligent welding process of claim 1, wherein, The multiple environmental temperature and humidity sensors are arranged in the welding area, and each sensor is calibrated to obtain the temperature-voltage and humidity-voltage conversion coefficients of the sensor, which specifically comprises: Four groups of environmental sensors are arranged at four corners of the fin welding work area, each group of sensors including one temperature sensor and one humidity sensor, numbered as , respectively ; wherein, is the sensor number; is the latitude coordinate of the th sensor; is the longitude coordinate of the th sensor; Selecting temperature calibration points , set their values respectively , , record the corresponding voltage values of the first temperature sensor , , and calculate the temperature conversion coefficient accordingly , ; wherein, is a low calibration temperature; is a high calibration temperature; is an original voltage of the th temperature sensor at ; is an original voltage of the th temperature sensor at ; is a temperature-voltage slope of the th temperature sensor; is a temperature-voltage intercept of the th temperature sensor; If , stop the calculation, reselect a different pair of temperature calibration points and remeasure; if continues for three times, determine that the temperature sensor is invalid, replace the sensor and then calibrate again. Let humidity calibration point pairs be , record the corresponding voltage values of the first humidity sensor , , and calculate the humidity conversion coefficient accordingly. , ;in, The relative humidity at the first and high positions are respectively calibrated. , The first Voltage of a humidity sensor under low and high humidity calibration conditions; For the first Humidity-voltage slope of a humidity sensor; For the first Humidity-voltage intercept of a humidity sensor; If , stop the current calculation, reselect different humidity calibration point pairs and re-measure; if still exists for three times, determine that the humidity sensor is invalid, replace the sensor and then calibrate again. At the system starting moment , the voltage value of the first humidity sensor is collected and , and the actual temperature and humidity value is calculated , ; wherein, is a time the temperature sensor voltage; is a time the humidity sensor voltage; is a temperature measured by the temperature sensor at time is a humidity measured by the humidity sensor at time The temperature resolution is set to , the humidity resolution is set to , the temperature range is set to and the humidity range is set to ; wherein are the lower and upper temperature measurable limits, respectively; are the lower and upper humidity measurable limits, respectively. The acquisition of the welding current measurement resolution is denoted by ; the acquisition of the current range is denoted by ; wherein are the lower and upper current measurement bounds, respectively. An output power capability interval of the welding machine is obtained, denoted as ; wherein, are lower and upper bounds of the output power capability of the welding machine, respectively. The temperature resolution, humidity resolution, temperature range, humidity range, current measurement resolution, current range, and welding machine output power capability interval are written into the process data table.

3. The finned heat sink intelligent welding process of claim 2, wherein, Based on the calibrated sensor data, the equivalent average temperature and humidity of the area environment are calculated, and the temperature and humidity deviation relative to the preset reference is extracted, which specifically comprises: The actual environmental average temperature and humidity in the four-point area are calculated: , ; wherein, is the zone equivalent average temperature; is the zone equivalent average humidity; Set temperature reference , humidity reference ; Computing the temperature and humidity deviation: , ; wherein, is the ambient temperature deviation; is the ambient humidity deviation.

4. The finned heat sink intelligent welding process of claim 3, wherein, The physical parameters of the single-piece heat dissipation fin are obtained, and a one-dimensional thermal resistance and equivalent heat capacity model is established accordingly, which specifically comprises: Obtaining physical parameters of the current workpiece, including: fin material thermal conductivity , fin thickness , single spot weld length , effective weld width , material density , specific heat at constant pressure ; The fin is a regular cuboid; Computing the transverse heat conduction cross-sectional area of a weld ; Computing one-dimensional steady-state thermal resistance along thickness ; Computing heated weld volume With equivalent heat capacity : ， 。 5. The finned heat sink intelligent welding process of claim 4, wherein, Temperature correction function and humidity correction function are constructed, and comprehensive compensation factor is calculated according to environmental deviation, while the validity and boundary value of the compensation factor are determined, which specifically comprises: Constructing a temperature correction function ; Constructing a humidity correction function ; calculating a total compensation factor ; If there is any Make Or Then, the welding process is suspended, and the environmental data is output out of bounds; If , the welding process is aborted and the compensation factor is output as invalid; The reachable range derived from the range is calculated: , ; wherein, , are the minimum and maximum overall compensation factors derived from the range, respectively; If , it is determined that the data is inconsistent, the welding process is suspended, and a consistency exception is output; otherwise, the next step is continued.

6. The finned heat sink intelligent welding process of claim 5, wherein, The target temperature rise value and welding action time are set, the single-point target heat energy is derived, and the actual welding power is calculated combined with the reference environmental power and the compensation factor, which specifically comprises: Setting target temperature value ; Setting the welding action time ; Computing single point target energy ; Acquiring welding power in a reference environment ; Calculating actual compensation power ; If then the welding process is aborted and the power out-of-bounds is output.

7. The finned heat sink intelligent welding process of claim 6, wherein, Based on the positions of the welding points of the heat dissipation fin, a welding path is generated, and a welding instruction is constructed according to the determined power sequence, which specifically comprises: The total number of welding points is obtained, denoted as , the number is denoted as , and the position coordinates are denoted as ; wherein, the latitude and longitude coordinates of the i th welding point, respectively. For any , the solder joint power is set to ; wherein is the target power for the th solder joint Constructing a sequence of welding instructions .

8. The finned heat sink intelligent welding process of claim 7, wherein, The welding execution system is controlled to weld at each welding point with actual power in sequence, and the current is monitored in real time, and the welding is stopped or adjusted when the preset threshold is exceeded or the risk of step skipping occurs, which specifically comprises: Execute the welding path sequentially. Each solder joint will position the solder head at one of the solder joints. ; The control output power is , the fixed action time is ; The start time of the first solder joint is , and the end time is ; Setting a welding current threshold value as ; If then abort the batch of welds and output current threshold crossed; The instantaneous current is then measured in the interval , denoted by , and the maximum current of the th solder joint in the interval is calculated; If , record the result code ; wherein, is the result code of the th welding spot, and the value set is ; If , skip the point, record , and go to the next point.

9. The finned heat sink intelligent welding process of claim 8, wherein, The average temperature and humidity of the environment when each welding point is completed are recorded, the welding parameters are archived, and the compensation model is updated regularly according to the monitoring data, which specifically comprises: For each point, record the time at the end of the weld and calculate the area average temperature and humidity: , ; wherein, is the area average temperature at the completion time of the th weld; is the area average humidity at the completion time of the th weld; calculating a global compensation factor mean : ； Statistical update threshold: ; wherein, is an update threshold for the environmental compensation mean; If , the update is , and archived; Otherwise keep present value and archive monitoring data .

10. A system for intelligent welding of heat sink fins using the process of claim 9, wherein, The method comprises the following steps: An environmental perception module is used to arrange and calibrate multiple temperature and humidity sensors and collect environmental data; A parameter calculation module is used to calculate the environmental parameters of the area and the reference deviation; a thermal modeling module for determining fin thermal parameters and constructing thermal capacitance and resistance models; a compensation factor module for constructing temperature and humidity compensation functions and performing boundary determinations; a power derivation module for calculating target thermal input power and environmental correction power; a path planning module for generating multi-spot paths and serializing power instructions; a control execution module for implementing welding and step skipping protection; a data archiving module for storing welding parameters and periodically updating compensation models.

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