A stirring head temperature control method, control system, medium and product

Abstract

A stirring head temperature control method, control system, medium and product relate to the field of electrical digital data processing. In implementing this application, the control system collects the temperature data of the needle and shoulder of the stirring head in real time, and uses a temperature prediction model to predict the needle temperature and shoulder temperature within a preset time period in the future in combination with the coolant flow of the needle and shoulder. When the deviation between the predicted temperature and the target temperature exceeds the temperature threshold, the control system can calculate and adjust the coolant flow in time, thereby achieving precise dynamic control of the stirring head temperature. This predictive temperature control method can prevent processing quality problems caused by excessive temperature fluctuations of the stirring head, and improve the stability and controllability of the welding process. At the same time, the control system achieves more precise temperature regulation by separately controlling the coolant flow of the needle and shoulder, avoiding local overcooling or overheating caused by the traditional single cooling method.

Description

Technical Field

[0001] The present application relates to the field of electronic digital data processing, and in particular to a stirring head temperature control method, control system, medium and product. Background Art

[0002] Friction stir welding (FSW) is a solid-state joining technology widely used in aerospace, rail transportation, automotive manufacturing, and other fields. During the FSW process, controlling the temperature of the stir tip plays a crucial role in weld quality. Excessively high temperatures can weaken the weld, while excessively low temperatures can result in an inadequate weld. Therefore, precise control of the temperature of the stir tip is crucial.

[0003] Currently, the common method used in industrial production to control the temperature of the stirrer tip is to set the coolant flow rate according to the welding process parameters. Specifically, the flow rates of the needle coolant and the shoulder coolant are pre-set according to different welding materials, welding speed and other process parameters. The flow rate is maintained at a fixed level during the welding process to cool the stirrer tip and control the temperature.

[0004] However, fixed-flow cooling methods have certain limitations in practical applications. Due to the dynamic changes in workpiece temperature distribution during welding and fluctuations in ambient temperature, fixed-flow cooling methods struggle to respond promptly to temperature changes. During welding, the temperature of the stirring tip can easily fluctuate, leading to unstable weld quality and compromising welding results. Summary of the Invention

[0005] The present application provides a stirring head temperature control method, control system, medium and product, which are used to prevent processing quality problems caused by excessive stirring head temperature fluctuations, and improve the stability and controllability of the welding process.

[0006] In a first aspect, the present application provides a stirring head temperature control method, which is applied to a control system, the method comprising: collecting needle temperature data and shoulder temperature data of the stirring head, the needle temperature data comprising the current needle temperature and the needle temperature change rate, and the shoulder temperature data comprising the current shoulder temperature and the shoulder temperature change rate; inputting the needle temperature data, the shoulder temperature data, the needle coolant flow rate and the shoulder coolant flow rate into a temperature prediction model to obtain the needle predicted temperature and the shoulder predicted temperature within a preset time period in the future, the needle coolant flow rate refers to the coolant flow rate in the current needle cooling channel, and the shoulder coolant flow rate refers to the coolant flow rate in the current shoulder cooling channel; when the deviation between the needle predicted temperature and the preset needle target temperature exceeds a first temperature threshold and / or the deviation between the shoulder predicted temperature and the preset shoulder target temperature exceeds a second temperature threshold, calculating the needle target flow rate and / or the shoulder target flow rate; and adjusting the coolant flow rate of the needle cooling channel and / or the shoulder cooling channel to achieve the needle target flow rate and / or the shoulder target flow rate.

[0007] By adopting the above technical solution, the control system collects the temperature data of the needle and shoulder of the stirring head in real time, and uses the temperature prediction model to predict the needle temperature and shoulder temperature within a preset time period in the future, combined with the coolant flow of the needle and shoulder. When the deviation between the predicted temperature and the target temperature exceeds the temperature threshold, the control system can calculate and adjust the coolant flow in time, thereby achieving precise dynamic control of the stirring head temperature. This predictive temperature control method can prevent processing quality problems caused by excessive temperature fluctuations of the stirring head, and improve the stability and controllability of the welding process. At the same time, the control system achieves more precise temperature regulation by separately controlling the coolant flow of the needle and shoulder, avoiding local overcooling or overheating caused by the traditional single cooling method.

[0008] In combination with some embodiments of the first aspect, in some embodiments, after the step of collecting needle temperature data and shoulder temperature data of the stirring head, the needle temperature data includes the current needle temperature and the needle temperature change rate, and the shoulder temperature data includes the current shoulder temperature and the shoulder temperature change rate, the method further includes: if the needle temperature change rate and / or the shoulder temperature change rate exceeds a preset rate threshold, adjusting the coolant flow of the needle cooling channel to a preset needle maximum flow and / or adjusting the coolant flow of the shoulder cooling channel to a preset shoulder maximum flow, and reducing the rotation speed of the stirring head to a preset safety rotation speed; after a preset time, if the needle temperature change rate and / or the shoulder temperature change rate still exceeds the preset rate threshold, controlling the stirring head to shut down.

[0009] By adopting the above technical solution, when the temperature change rate of the needle and / or shoulder exceeds a preset rate threshold, the control system immediately adjusts the coolant flow to maximum and reduces the stirring head speed. This rapid response mechanism effectively prevents the stirring head from being damaged by rapid temperature changes. If the temperature change rate of the needle and / or shoulder is still too high after a preset period of time, the control system automatically shuts down for protection. This dual protection mechanism greatly improves the safety and reliability of the equipment, allowing for the timely detection and resolution of temperature anomalies, avoiding equipment damage and processing quality issues caused by temperature runaway, and ensuring the safety of the friction stir welding process.

[0010] In combination with some embodiments of the first aspect, in some embodiments, before the step of calculating the needle target flow rate and / or the shoulder target flow rate when the deviation between the needle predicted temperature and the preset needle target temperature exceeds a first temperature threshold and / or the deviation between the shoulder predicted temperature and the preset shoulder target temperature exceeds a second temperature threshold, the method further includes: obtaining operating parameters of the stirring head, the operating parameters including stirring head speed, axial pressure, and stirring depth; inputting the operating parameters into a first temperature formula and a second temperature formula, respectively, to obtain the preset needle target temperature and the preset shoulder target temperature; The first temperature formula is: Tn=T0+k1×P-k2×R+k3×D; the second temperature formula is: Ts=T0+k4×P-k5×R-k6×D; wherein, Tn is the preset needle target temperature, Ts is the preset shoulder target temperature, T0 is the preset reference temperature, P is the axial pressure, R is the stirring head speed, D is the stirring depth, k1 is the needle pressure temperature coefficient, k2 is the needle speed temperature coefficient, k3 is the needle depth temperature coefficient, k4 is the shoulder pressure temperature coefficient, k5 is the shoulder speed temperature coefficient, and k6 is the shoulder depth temperature coefficient.

[0011] By adopting the above technical solution, the control system establishes a mathematical relationship between the stirring head operating parameters (stirring head speed, axial pressure, and stirring depth) and the preset top target temperature and preset shoulder target temperature, realizing the dynamic calculation of the target temperature. The temperature formula used takes into account the different effects of stirring head speed, axial pressure, and stirring depth on the needle temperature and shoulder temperature, and reflects the contribution of each operating parameter to the temperature through different temperature coefficients. This temperature control method based on physical models makes temperature control more scientific and accurate. It can automatically adjust the target temperature according to changes in process parameters, improve the adaptability and accuracy of temperature control, and thus improve the stability of welding quality.

[0012] In combination with some embodiments of the first aspect, in some embodiments, before the step of inputting the needle temperature data, the shoulder temperature data, the needle coolant flow rate and the shoulder coolant flow rate into the temperature prediction model to obtain the predicted needle temperature and the predicted shoulder temperature within a preset time period in the future, the needle coolant flow rate refers to the coolant flow rate in the current needle cooling channel, and the shoulder coolant flow rate refers to the coolant flow rate in the current shoulder cooling channel, the method further includes: obtaining the needle profile data and the shoulder profile data of the stirring head to determine wear characteristic parameters, which include the wear depth, wear area and surface roughness of the needle and the shoulder; determining the needle friction heat data and the shoulder friction heat data based on the wear characteristic parameters; calculating the needle heat dissipation and the shoulder heat dissipation per unit time based on the needle friction heat data and the shoulder friction heat data; detecting the working parameters of the needle cooling channel and the shoulder cooling channel, which include the inlet and outlet pressure difference, the coolant temperature and the channel cross-sectional area; and calculating the needle coolant flow rate and the shoulder coolant flow rate based on the needle heat dissipation, the shoulder heat dissipation and the working parameters.

[0013] By employing this technical solution, the control system acquires the needle and shoulder profile data of the stirring head and comprehensively assesses its wear status, including wear characteristic parameters such as wear depth, wear area, and surface roughness. Based on these wear characteristic parameters, the control system accurately calculates frictional heat data and heat dissipation. Combined with the operating parameters of the cooling channel (inlet and outlet pressure differential, coolant temperature, and channel cross-sectional area), it accurately calculates the coolant flow rate. This temperature control method, which considers tool wear, overcomes the drawback of traditional methods that ignore the impact of tool wear, making temperature control more consistent with actual operating conditions. Furthermore, the control system monitors the operating parameters of the cooling channel in real time, ensuring the effectiveness of the cooling system and improving the reliability and accuracy of temperature control.

[0014] In combination with some embodiments of the first aspect, in some embodiments, determining the friction heat data of the needle specifically includes: obtaining the material parameters of the needle, which include thermal conductivity, specific heat capacity and density; calculating the actual contact area between the needle and the workpiece based on the wear depth and wear area of ​​the needle, and determining the dynamic friction coefficient of the needle according to the surface roughness of the needle; substituting the material parameters, the operating parameters, the actual contact area and the dynamic friction coefficient into the needle heat dissipation calculation formula to obtain the needle heat dissipation per unit time.

[0015] By employing this technical solution, the control system comprehensively considers the needle's material properties (thermal conductivity, specific heat capacity, and density) and actual operating parameters when determining needle friction heat data, establishing a more accurate formula for calculating needle heat dissipation. This multi-parameter heat dissipation calculation method overcomes the limitations of traditional simplified calculation methods and more accurately reflects the heat generation during the actual machining process. By integrating tool wear status with heat generation mechanisms, it ensures that temperature control is more realistic and improves the accuracy of temperature prediction and control.

[0016] In combination with some embodiments of the first aspect, in some embodiments, the needle coolant flow rate and the shoulder coolant flow rate are calculated based on the needle heat dissipation, the shoulder heat dissipation and the working parameters, specifically including: calculating the coolant baseline flow rate according to the inlet and outlet pressure difference and the channel cross-sectional area; calculating the minimum cooling flow rate required for the needle based on the needle heat dissipation and the coolant temperature of the needle cooling channel; calculating the minimum cooling flow rate required for the shoulder based on the shoulder heat dissipation and the coolant temperature of the shoulder cooling channel; when the coolant baseline flow rate is less than the minimum cooling flow rate required for the needle, increasing the pump pressure of the needle cooling channel to increase the inlet and outlet inlet pressure difference; the inlet and outlet pressure difference after supercharging is substituted into the preset flow calculation formula to obtain the coolant flow of the needle; when the coolant base flow is less than the minimum cooling flow required for the shoulder, the pump pressure of the shoulder cooling channel is increased to increase the inlet and outlet pressure difference; the inlet and outlet pressure difference after supercharging is substituted into the preset flow calculation formula to obtain the coolant flow of the shoulder; when the coolant base flow is greater than the minimum cooling flow required for the needle, the minimum cooling flow required for the needle is determined as the coolant flow of the needle; when the coolant base flow is greater than the minimum cooling flow required for the shoulder, the minimum cooling flow required for the shoulder is determined as the coolant flow of the shoulder.

[0017] By adopting the above technical solution, the control system establishes a complete coolant flow calculation and regulation mechanism. First, the control system calculates the coolant baseline flow rate, then determines the minimum cooling flow rate based on the heat dissipation requirements. If the coolant baseline flow rate is insufficient, the control system increases the coolant flow rate by increasing the pump pressure. If the coolant baseline flow rate is sufficient, the control system uses the minimum required flow rate. This intelligent flow regulation solution ensures adequate cooling while avoiding excessive coolant use. It enables on-demand adjustment of the cooling system, improves energy efficiency, and ensures reliable and economical temperature control.

[0018] In combination with some embodiments of the first aspect, in some embodiments, before the step of collecting the needle temperature data and shoulder temperature data of the stirring head, the method also includes: obtaining the ambient temperature and ambient humidity; judging whether the ambient temperature and the ambient humidity meet the stir friction welding working conditions; if so, starting the stirring head; if not, adjusting the ambient temperature and ambient humidity to meet the stir friction welding working conditions.

[0019] By adopting this technical solution, the control system performs a pre-check of environmental conditions before the stir head is started, ensuring that the processing environment meets process requirements. This preventative environmental management mechanism can avoid processing quality issues caused by improper environmental conditions. By ensuring appropriate environmental conditions before processing, the stability and reliability of the process are improved, providing the necessary environmental protection for the smooth implementation of the friction stir welding process and reducing process fluctuations caused by environmental factors.

[0020] In a second aspect, an embodiment of the present application provides a control system comprising: one or more processors and a memory; the memory is coupled to the one or more processors, the memory being used to store computer program code, the computer program code comprising computer instructions, the one or more processors calling the computer instructions to enable the control system to execute the method described in the first aspect and any possible implementation of the first aspect.

[0021] In a third aspect, an embodiment of the present application provides a computer program product comprising instructions, which, when run on a control system, enables the control system to execute the method described in the first aspect and any possible implementation of the first aspect.

[0022] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium comprising instructions, which, when executed on a control system, causes the control system to execute the method described in the first aspect and any possible implementation of the first aspect.

[0023] It is understandable that the control system provided in the second aspect, the computer program product provided in the third aspect, and the computer storage medium provided in the fourth aspect are all used to execute the methods provided in the embodiments of the present application. Therefore, the beneficial effects that can be achieved can be referenced to the beneficial effects of the corresponding methods and will not be repeated here.

[0024] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0025] 1. By adopting the above technical solution, the control system collects the temperature data of the needle and shoulder of the stirring head in real time, and combines the coolant flow of the needle and shoulder to use the temperature prediction model to predict the needle temperature and shoulder temperature within a preset time in the future. When the deviation between the predicted temperature and the target temperature exceeds the temperature threshold, the control system can calculate and adjust the coolant flow in time, thereby achieving precise dynamic control of the stirring head temperature. This predictive temperature control method can prevent processing quality problems caused by excessive temperature fluctuations of the stirring head, and improve the stability and controllability of the welding process. At the same time, the control system achieves more precise temperature regulation by separately controlling the coolant flow of the needle and shoulder, avoiding local overcooling or overheating caused by the traditional single cooling method.

[0026] 2. By adopting the above technical solution, the control system establishes a mathematical relationship between the stirring head operating parameters (stirring head speed, axial pressure, and stirring depth) and the preset top target temperature and preset shoulder target temperature, realizing dynamic calculation of the target temperature. The temperature formula used considers the different effects of stirring head speed, axial pressure, and stirring depth on the needle temperature and shoulder temperature, and reflects the contribution of each operating parameter to the temperature through different temperature coefficients. This temperature control method based on physical models makes temperature control more scientific and accurate. It can automatically adjust the target temperature according to changes in process parameters, improve the adaptability and accuracy of temperature control, and thus improve the stability of welding quality.

[0027] 3. By employing the above-mentioned technical solution, the control system acquires the needle and shoulder profile data of the stirring head and comprehensively assesses its wear status, including wear characteristic parameters such as wear depth, wear area, and surface roughness. Based on these wear characteristic parameters, the control system accurately calculates frictional heat data and heat dissipation. Combined with the operating parameters of the cooling channel (inlet and outlet pressure differential, coolant temperature, and channel cross-sectional area), this allows for precise calculation of coolant flow. This temperature control method, which considers tool wear, overcomes the drawback of traditional methods that ignore the impact of tool wear, making temperature control more consistent with actual operating conditions. Furthermore, the control system monitors the operating parameters of the cooling channel in real time, ensuring the effectiveness of the cooling system and improving the reliability and accuracy of temperature control. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 This is a flow chart of a method for controlling the temperature of a stirring head according to an embodiment of the present application;

[0029] Figure 2 This is another flow chart of the stirring head temperature control method in the embodiment of the present application;

[0030] Figure 3 This is a structural diagram of a stirring head in an embodiment of the present application;

[0031] Figure 4 It is a schematic diagram of the structure of a physical device of the control system in an embodiment of the present application. DETAILED DESCRIPTION

[0032] The terms used in the following examples of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the specification of the present application, the singular expressions "a", "an", "above", "the", and "this" are intended to include plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations of one or more of the listed items.

[0033] In the following, the terms "first" and "second" are used for descriptive purposes only and should not be understood to imply or suggest relative importance or implicitly indicate the number of the technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of this application, unless otherwise specified, "plurality" means two or more.

[0034] The following is a description of the process of the method provided by this implementation. Figure 1 , is a flow chart of the stirring head temperature control method in an embodiment of the present application.

[0035] S101, collecting needle temperature data and shoulder temperature data of the stirring head, the needle temperature data including the current needle temperature and the needle temperature change rate, and the shoulder temperature data including the current shoulder temperature and the shoulder temperature change rate;

[0036] Among them, the stirring head refers to the main tool used for stir friction welding, which includes two main parts: the needle and the shoulder; the needle refers to the central protruding part of the stirring head, which is used to insert the workpiece and produce a stirring effect; the shoulder refers to the flat disc-shaped structure surrounding the needle, which is used to prevent material overflow and provide additional heat; the needle temperature data and the shoulder temperature data refer to temperature-related information collected by the temperature sensor; the current needle temperature and the current shoulder temperature refer to the real-time temperature values ​​of the needle and the shoulder at a specific moment, in degrees Celsius; the needle temperature change rate and the shoulder temperature change rate are used to indicate the change in needle temperature and shoulder temperature per unit time, usually in degrees Celsius per second.

[0037] Specifically, the control system continuously collects temperature data at a preset sampling frequency (e.g., 10 Hz) using multiple temperature sensors located on the needle and shoulder. At each sampling point, the control system simultaneously records the instantaneous temperature of both the needle and shoulder. The temperature change rate is calculated by dividing the temperature difference between adjacent sampling points by the preset sampling interval.

[0038] S102: Inputting needle temperature data, shoulder temperature data, needle coolant flow rate, and shoulder coolant flow rate into a temperature prediction model to obtain predicted needle temperature and shoulder temperature within a preset future time period, wherein the needle coolant flow rate refers to the current coolant flow rate in the needle cooling channel, and the shoulder coolant flow rate refers to the current coolant flow rate in the shoulder cooling channel;

[0039] Among them, the temperature prediction model represents a mathematical model used to predict future temperature changes; the future preset time refers to the time span required for temperature prediction, which is usually several seconds; the needle cooling channel refers to the pipeline system set at the needle for passing the coolant; the shoulder cooling channel refers to the pipeline system set at the shoulder for passing the coolant; the coolant flow rate is used to represent the volume of coolant passing through the cooling channel per unit time, usually in liters / minute; the needle predicted temperature and the shoulder predicted temperature represent the needle temperature value and the shoulder temperature value at a certain moment in the future calculated by the temperature prediction model.

[0040] Specifically, the control system inputs the collected needle temperature data and the current coolant flow rate in the needle cooling channel into a pre-trained temperature prediction model (such as a deep learning-based LSTM model or a physical mechanism model). This temperature prediction model considers factors such as historical needle temperature trends, cooling effectiveness, and heat generation, and can predict needle temperature changes within the next 5-10 seconds. The prediction results include the needle temperature curve over this period, providing a basis for subsequent flow rate adjustments. The shoulder temperature data and the current coolant flow rate in the needle cooling channel are processed in a similar manner. The control system evaluates the accuracy of the prediction results in real time and fine-tunes the temperature prediction model online based on actual temperature feedback to improve prediction accuracy.

[0041] The steps to build a temperature prediction model based on deep learning are as follows:

[0042] First, the control system collects needle temperature, shoulder temperature, needle coolant flow rate, and shoulder coolant flow rate from multiple measurement points over a preset period of time (e.g., six months). The needle and shoulder temperatures represent the real-time temperature values ​​collected by the control system at each location. The needle and shoulder coolant flows represent the volume of coolant flowing through the cooling channel per second, as collected by the control system. The control system stores the collected needle temperatures and flows in data set D in chronological order, with each data entry formatted as (needle temperature, needle coolant flow rate). Similarly, the control system stores the collected shoulder temperatures and flows in data set D in chronological order, with each data entry formatted as (shoulder temperature, shoulder coolant flow rate). The current needle temperature, shoulder temperature, needle coolant flow rate, and shoulder coolant flow rate serve as input features for model training, while the future needle and shoulder temperatures serve as output features.

[0043] The control system then constructs an LSTM-based recurrent neural network consisting of an input layer, two LSTM hidden layers, a fully connected layer, and an output layer. The input layer inputs the needle temperature, shoulder temperature, needle coolant flow rate, and shoulder coolant flow rate. The hidden layer has 64 nodes, and the fully connected layer has 32 nodes. The output layer outputs the predicted needle and shoulder temperatures for a preset time period in the future.

[0044] Next, the control system uses the Adam optimizer with a learning rate of 0.001 and a training batch size of 32. These settings can be customized and are not set here. 80% of the historical data is divided into a training set and 20% into a validation set. Training is performed for 100 epochs, and the model with the highest validation set accuracy is retained. This can also be customized and is not set here. An epoch is the process by which a training dataset is fully passed through a neural network. In machine learning and deep learning, an epoch is a unit used to measure the number of times the entire training set is repeatedly learned. Specifically, an epoch is completed when the neural network completes a forward computation and backward propagation process, meaning that all data has been processed once. The control system uses binary cross entropy as the loss function and employs early stopping to prevent overfitting. When the loss function exceeds a preset threshold, model training is considered complete, resulting in a temperature prediction model. Early stopping is a technique used in deep learning and machine learning to prevent overfitting by monitoring the model's performance on the validation set to determine when to stop training.

[0045] Finally, the control system feeds the input features from the validation set into the temperature prediction model, which then generates the model's predicted output. The predicted output is then compared with the actual output features from the validation set, and performance metrics such as accuracy, precision, recall, F1 score, and mean squared error (MSE) are used to evaluate the model's performance. Based on the model's performance on the validation set, the model's parameters are adjusted, including the learning rate, model complexity (such as increasing or decreasing the number of layers or nodes in the neural network), and regularization strength. This process may require multiple iterations, with each adjustment based on the previous learning results, to optimize the temperature prediction model.

[0046] S103, when the deviation between the needle predicted temperature and the preset needle target temperature exceeds a first temperature threshold and / or the deviation between the shoulder predicted temperature and the preset shoulder target temperature exceeds a second temperature threshold, calculating the needle target flow rate and / or the shoulder target flow rate;

[0047] Among them, the preset needle target temperature refers to the optimal working temperature of the needle determined according to the process requirements; the preset shoulder target temperature refers to the optimal working temperature of the shoulder determined according to the process requirements; the temperature deviation is used to indicate the difference between the predicted temperature and the target temperature; the first temperature threshold is the maximum temperature deviation allowed for the needle; the second temperature threshold refers to the maximum temperature deviation allowed for the shoulder; the needle target flow is used to indicate the ideal coolant flow required to maintain the needle temperature; the shoulder target flow indicates the ideal coolant flow required to maintain the shoulder temperature.

[0048] Specifically, the control system compares the predicted needle temperature with the preset needle target temperature, and compares the predicted shoulder temperature with the preset shoulder target temperature. When the deviation between the predicted needle temperature and the preset needle target temperature exceeds a first temperature threshold (e.g., ±15°C), or when the deviation between the predicted shoulder temperature and the preset shoulder target temperature exceeds a second temperature threshold (e.g., ±20°C), the control system initiates a flow regulation calculation program. This flow regulation calculation program, based on the heat conduction equation and the magnitude of the temperature deviation, combines this with a cooling efficiency model to calculate the coolant flow rate required to maintain the preset needle target temperature and / or preset shoulder target temperature. The calculation process takes into account the temperature change rate, heat accumulation effects, and the cooling system's response characteristics, and the optimal needle target flow rate and / or shoulder target flow rate are determined through iterative optimization. The control system employs different calculation strategies for both heating and cooling scenarios to ensure accurate and rapid regulation.

[0049] S104 , adjusting the coolant flow rate of the needle cooling channel and / or the shoulder cooling channel to achieve a needle target flow rate and / or a shoulder target flow rate.

[0050] Specifically, the control system checks the current working status of the cooling system, including parameters such as pump pressure, valve opening, and pipeline pressure. Then, the control system calculates the required adjustment amount based on the difference between the target flow and the current flow. For the needle cooling channel, the control system changes the flow by adjusting the speed of the liquid supply pump and the opening of the control valve. The adjustment process uses a PID control algorithm to achieve a smooth transition. A similar adjustment method is used for the shoulder cooling channel. The control system monitors the flow changes in real time. When the deviation between the actual flow and the target flow is less than the preset value (such as ±5%), the adjustment is completed. At the same time, the control system records the parameter changes during the adjustment process for optimizing subsequent control strategies. If the target flow is not reached within the preset time, the control system will issue a warning message and start the backup adjustment plan.

[0051] By adopting the above technical solution, the control system collects the temperature data of the needle and shoulder of the stirring head in real time, and uses the temperature prediction model to predict the needle temperature and shoulder temperature within a preset time period in the future, combined with the coolant flow of the needle and shoulder. When the deviation between the predicted temperature and the target temperature exceeds the temperature threshold, the control system can calculate and adjust the coolant flow in time, thereby achieving precise dynamic control of the stirring head temperature. This predictive temperature control method can prevent processing quality problems caused by excessive temperature fluctuations of the stirring head, and improve the stability and controllability of the welding process. At the same time, the control system achieves more precise temperature regulation by separately controlling the coolant flow of the needle and shoulder, avoiding local overcooling or overheating caused by the traditional single cooling method.

[0052] The following is a more detailed description of the process of the method provided by this implementation. Figure 2 , is another flow chart of the stirring head temperature control method in the embodiment of the present application.

[0053] S201. Obtaining ambient temperature and ambient humidity; determining whether the ambient temperature and ambient humidity meet friction stir welding working conditions.

[0054] Among them, ambient temperature refers to the air temperature in the friction stir welding processing area, and the unit is degrees Celsius; ambient humidity refers to the moisture content in the air in the friction stir welding processing area, usually expressed as a percentage of relative humidity; friction stir welding working conditions are used to indicate the range of environmental parameters required for the normal operation of the equipment.

[0055] Specifically, the control system uses multiple temperature and humidity sensors distributed throughout the processing area to simultaneously collect temperature and humidity data from multiple measurement points. The control system averages the collected data to eliminate the effects of local fluctuations. The temperature judgment standard is typically 15-35°C, and the humidity judgment standard is typically 30%-70% relative humidity. The control system also considers the changing trends of temperature and humidity. If a rapid change is detected, it may determine that the friction stir welding operating conditions are not met, even if the current value is within the range.

[0056] S202: If satisfied, start the stirring head.

[0057] Specifically, the control system first performs a self-check to confirm the normal operation of all components. It then gradually increases the speed of the agitator head according to a preset startup curve, typically using a staged acceleration method. For example, the system first accelerates to 50% of the rated speed and maintains steady operation for 10 seconds before continuing to accelerate to the operating speed. During the startup process, the control system monitors parameters such as motor current, bearing temperature, and vibration in real time, and immediately interrupts the startup process if any abnormalities are detected.

[0058] S203. If not, adjust the ambient temperature and humidity to meet the friction stir welding working conditions.

[0059] Specifically, the control system analyzes the type and degree of deviation in environmental parameters, such as excessive temperature or humidity. Based on the type and degree of deviation, the control system formulates an adjustment strategy, such as activating the refrigeration system to reduce the temperature or turning on the dehumidifier to lower the humidity. If the control system detects that the environmental parameters are approaching the operating conditions of friction stir welding, it reduces the adjustment intensity to avoid overshoot.

[0060] S204 , collecting needle temperature data and shoulder temperature data of the stirring head, where the needle temperature data includes the current needle temperature and the needle temperature change rate, and the shoulder temperature data includes the current shoulder temperature and the shoulder temperature change rate.

[0061] For details, please refer to step S101, which will not be described again here.

[0062] S205. If the needle temperature change rate and / or the shoulder temperature change rate exceeds the preset rate threshold, the coolant flow rate of the needle cooling channel is adjusted to the preset needle maximum flow rate and / or the coolant flow rate of the shoulder cooling channel is adjusted to the preset shoulder maximum flow rate, and the rotation speed of the stirring head is reduced to the preset safety rotation speed.

[0063] Among them, the preset rate threshold is used to indicate the safe upper limit of the needle temperature change rate and the shoulder temperature change rate, usually in degrees Celsius per second; the preset needle maximum flow rate refers to the maximum coolant flow rate that the needle cooling channel can withstand; the preset shoulder maximum flow rate refers to the maximum coolant flow rate that the shoulder cooling channel can withstand; the preset safety speed refers to the target speed at which the stirring head slows down when an abnormality occurs.

[0064] Specifically, the control system rapidly assesses the needle and shoulder temperature change rates. If the needle temperature change rate exceeds a preset threshold (e.g., 2°C / second) or the shoulder temperature change rate exceeds a preset threshold (e.g., 1.5°C / second), the emergency procedure is immediately initiated. The control system simultaneously performs three actions: rapidly increasing the flow rate in the needle cooling channel to a maximum value (e.g., 20 L / minute), increasing the flow rate in the shoulder cooling channel to a maximum value (e.g., 25 L / minute), and reducing the stirring head speed to a preset safety speed (e.g., 60% of the rated speed). The control system employs a rapid response control strategy to ensure that all parameter adjustments are completed within 0.5 seconds.

[0065] S206 : After the preset time period, if the needle temperature change rate and / or the shoulder temperature change rate still exceeds the preset rate threshold, the stirring head is controlled to stop.

[0066] The preset time duration indicates the waiting time for observing the temperature change trend, which is usually several seconds; shutdown means that the stirring head is completely stopped according to the safety procedure.

[0067] Specifically, after adjusting the parameters, the control system continuously monitors the temperature changes within a preset time (usually 10-15 seconds). If the needle temperature change rate and / or the shoulder temperature change rate still exceeds the preset rate threshold during this period, it means that the cooling measures are not effective, and the control system will start the shutdown procedure. The shutdown process is divided into three stages: first, the stirring head speed is reduced to the minimum (such as 100rpm) and maintained for 5 seconds, then the spindle power is cut off but the cooling system is kept running at full power, and finally, the cooling system is gradually shut down after confirming that the temperature has begun to drop. The entire shutdown process lasts about 30 seconds, and the control system will record the parameter changes throughout the process.

[0068] S207 , obtaining the needle profile data and the shoulder profile data of the stirring head to determine wear characteristic parameters, wherein the wear characteristic parameters include the wear depth, wear area and surface roughness of the needle and shoulder.

[0069] Among them, the needle profile data is used to represent the digital information of the needle's external dimensions and surface shape, including geometric parameters such as height and diameter; the shoulder profile data is used to represent the digital information of the shoulder's external dimensions and surface shape, including parameters such as diameter and inclination; the wear depth is used to represent the loss depth of the tool surface relative to the original state, in millimeters; the wear area is used to represent the plane projection area of ​​the damaged part of the tool surface, in square millimeters; the surface roughness refers to the statistical characteristic value of the surface micro-geometry, usually expressed by the Ra value.

[0070] Specifically, the control system uses a high-precision laser scanning system to perform contour scanning when the mixing head is stationary. The scanning process adopts a multi-point measurement method, with 36 measurement points set at 10-degree intervals in the needle area and 72 measurement points set at 5-degree intervals in the shoulder area. The raw data collected by the control system is processed for noise reduction and compared with the standard CAD model to calculate the wear depth distribution map. For the wear area, the control system uses an image processing algorithm to identify the boundary of the wear area and calculate the area value. The surface roughness is obtained by micro-profilometer measurement, and multiple sampling points are selected in the main stress-bearing area for measurement. All measurement data are digitally filtered and verified for validity to ensure data accuracy.

[0071] S208 : Determine the needle friction heat data and the shoulder friction heat data based on the wear characteristic parameters.

[0072] Among them, friction heat data refers to the heat information generated during the contact between the stirring head and the workpiece.

[0073] Specifically, the control system corrects the friction coefficient based on the wear characteristic parameters. For every 0.1mm increase in wear depth, the friction coefficient is adjusted by 0.02; for every 1μm increase in surface roughness, the friction coefficient is adjusted by 0.01. The control system then combines the process parameters (speed, pressure) and the corrected friction coefficient to calculate the friction heat of the needle and shoulder using a heat generation model. The calculation process takes into account the impact of different wear levels on the contact area and adjusts the heat distribution coefficient according to the wear morphology. The control system uses a partition calculation method to divide the needle and shoulder into multiple calculation units to obtain a more accurate heat distribution. The calculation results include the heat flux density and total heat generation rate of each area.

[0074] The following is a specific calculation example to illustrate this process. Assume that the initial conditions are the standard friction coefficient μ0 = 0.3, the process parameters are: speed = 1000 rpm, axial pressure = 10 kN, initial needle diameter = 8 mm, initial shoulder diameter = 24 mm, and when the following wear characteristic parameters are detected:

[0075] 1. Needle wear:

[0076] Wear depth = 0.3 mm (increase friction coefficient 0.06);

[0077] Surface roughness Ra = 3 μm (increase friction coefficient by 0.03);

[0078] Corrected needle friction coefficient = 0.3 + 0.06 + 0.03 = 0.39;

[0079] 2. Shoulder wear:

[0080] Wear depth = 0.2 mm (increase friction coefficient 0.04);

[0081] Surface roughness Ra = 2μm (increase friction coefficient by 0.02);

[0082] Corrected shoulder friction coefficient = 0.3 + 0.04 + 0.02 = 0.36;

[0083] Calorie calculation example:

[0084] 1. Needle heat calculation (divided into 3 areas):

[0085] (1) Central area (0-3mm radius):

[0086] Contact pressure = 12kN (considering pressure concentration after wear);

[0087] Heat flux density = 0.39 × 12 kN × 1000 rpm × 0.1047 = 489.996 W / cm²;

[0088] Heat distribution coefficient = 0.6 (60% of the heat enters the tool);

[0089] Regional heat = 489.996 × π × 0.3² × 0.6 = 83.09W;

[0090] (2) Middle area (3-6mm radius):

[0091] Contact pressure = 10 kN;

[0092] Heat flux density = 0.39 × 10 kN × 1000 rpm × 0.1047 = 408.33 W / cm²;

[0093] Heat distribution coefficient = 0.55;

[0094] Regional heat = 408.33 × π × (0.6² 0.3²) × 0.55 = 127.39W;

[0095] (3) Peripheral area (6-8mm radius):

[0096] Contact pressure = 8kN;

[0097] Heat flux density = 0.39 × 8 kN × 1000 rpm × 0.1047 = 326.664 W / cm²;

[0098] Heat distribution coefficient = 0.5;

[0099] Regional heat = 326.664 × π × (0.8² 0.6²) × 0.5 = 102.73W;

[0100] Total heat of the needle = 83.09 + 127.39 + 102.73 = 313.21W;

[0101] 2. Shoulder heat calculation (divided into 2 areas):

[0102] (1) Inner ring area (8-16mm radius):

[0103] Contact pressure = 9kN;

[0104] Heat flux density = 0.36 × 9 kN × 1000 rpm × 0.1047 = 339.228 W / cm²;

[0105] Heat distribution coefficient = 0.45;

[0106] Regional heat = 339.228 × π × (1.6² 0.8²) × 0.45 = 543.93W;

[0107] (2) Outer ring area (16-24mm radius):

[0108] Contact pressure = 7kN;

[0109] Heat flux density = 0.36 × 7 kN × 1000 rpm × 0.1047 = 263.844 W / cm²;

[0110] Heat distribution coefficient = 0.4;

[0111] Regional heat = 263.844 × π × (2.4² + 1.6²) × 0.4 = 633.85W;

[0112] Total heat of shoulder = 543.93 + 633.85 = 1177.78W.

[0113] Optionally, under normal circumstances, the friction heat data of the needle can be determined by the following methods, which are not limited here: obtaining the material parameters of the needle, which include thermal conductivity, specific heat capacity and density; calculating the actual contact area between the needle and the workpiece based on the wear depth and wear area of ​​the needle, and determining the dynamic friction coefficient of the needle according to the surface roughness of the needle; substituting the material parameters, operating parameters, actual contact area and dynamic friction coefficient into the needle heat dissipation calculation formula to obtain the needle heat dissipation per unit time.

[0114] The following example illustrates the calculation process of the needle friction heat data, assuming the following initial conditions:

[0115] Needle material parameters (taking H13 steel as an example): thermal conductivity (λ) = 28W / (m·K), specific heat capacity (c) = 460J / (kg·K), density (ρ) = 7800kg / m³;

[0116] Initial parameters of the needle: initial diameter = 8 mm, initial length = 6 mm, standard dynamic friction coefficient (μ0) = 0.3;

[0117] Needle operating parameters: speed (n) = 1200 rpm, axial pressure (F) = 12 kN, linear velocity (v) = πdn / 60 = π × 0.008 × 1200 / 60 = 0.503 m / s;

[0118] Detected wear parameters: wear depth (h) = 0.25 mm, wear area (S) = 38 mm², surface roughness Ra = 2.5 μm.

[0119] The calculation process is as follows:

[0120] (1) Corrected dynamic friction coefficient:

[0121] Wear depth influence: 0.25mm / 0.1mm×0.02=0.05;

[0122] Surface roughness influence: 2.5μm×0.01=0.025;

[0123] Corrected dynamic friction coefficient (μ) = 0.3 + 0.05 + 0.025 = 0.375;

[0124] (2) Calculate the actual contact area:

[0125] Initial contact area = π × (8mm)² / 4 = 50.27mm²;

[0126] The actual contact area after wear (A) = 50.27 + 38 = 88.27 mm² = 8.827 × 10⁻ 5 m²;

[0127] (3) The calculation formula for needle heat dissipation is: Q = μ × F × v × k × A;

[0128] Where Q is the heat dissipation (W), μ is the corrected dynamic friction coefficient, F is the axial pressure (N), v is the linear velocity (m / s), k is the heat distribution coefficient (assumed to be 0.6, indicating that 60% of the heat enters the tool), and A is the actual contact area coefficient (actual contact area / initial contact area).

[0129] Substitute the numerical value into the calculation: Q = 0.375 × 12000 × 0.503 × 0.6 × (88.27 / 50.27) = 2249.8W;

[0130] Therefore, the heat dissipation of the needle per unit time is about 2250W.

[0131] S209 , calculating the heat dissipation of the needle and the heat dissipation of the shoulder per unit time based on the frictional heat data of the needle and the frictional heat data of the shoulder.

[0132] The heat dissipation of the needle refers to the amount of heat that the needle needs to dissipate per unit time, and its unit is joules per second; the heat dissipation of the shoulder refers to the amount of heat that the shoulder needs to dissipate per unit time, and its unit is joules per second.

[0133] Specifically, the control system uses a multi-layer heat conduction model to calculate the heat dissipation, taking into account the thermal conductivity, geometric structure and cooling channel distribution of the tool material. For the needle part, the control system divides it into a core area and a peripheral area, and calculates the heat transfer path separately; for the shoulder, the control system adopts a radial partitioning method to consider the heat dissipation conditions at different radial positions. The heat conduction equations are introduced in the calculation process, considering both steady-state and transient working conditions. The control system also takes into account the changes in the thermal physical properties of the material with temperature, such as adjusting the thermal conductivity by 5% for every 100°C increase in temperature. The final heat dissipation data includes the distribution value and total amount of each area, with an accuracy of ±3%.

[0134] S210 , detecting operating parameters of the needle cooling channel and the shoulder cooling channel, the operating parameters including inlet and outlet pressure difference, coolant temperature, and channel cross-sectional area.

[0135] Among them, the inlet and outlet pressure difference refers to the pressure difference between the inlet and outlet of the cooling channel, and the unit is kilopascals; the coolant temperature refers to the temperature of the cooling medium in the cooling channel, and the unit is degrees Celsius; the channel cross-sectional area is used to indicate the effective area for the coolant to circulate, and the unit is square millimeters.

[0136] Specifically, the control system uses a network of sensors placed at key locations throughout the cooling channels to synchronously collect operating parameters. High-precision pressure sensors are installed at the inlet and outlet, with a sampling frequency of 100Hz and a measurement accuracy of 0.1kPa. Temperature sensors are evenly spaced throughout the channels (no fewer than three per channel) to monitor the coolant temperature distribution in real time. Ultrasonic sensors are used to regularly monitor the channel cross-sectional area to determine whether there is any deposit or deformation. All sensor data undergoes real-time calibration and digital filtering to ensure 99.9% data reliability.

[0137] S211. Calculate the needle coolant flow rate and the shoulder coolant flow rate based on the needle heat dissipation, the shoulder heat dissipation, and the operating parameters.

[0138] Specifically, the control system establishes a coupled thermal-fluid calculation model, integrating heat dissipation requirements with channel characteristics. The calculation process is divided into three stages: The first stage calculates the theoretical required flow rate based on heat dissipation, taking into account the coolant's specific heat capacity and allowable temperature rise. The second stage establishes a flow resistance equation based on channel characteristics (pressure differential, cross-sectional area) to determine the practically feasible flow rate range. The third stage uses iterative calculations to find the optimal flow rate that meets the heat dissipation requirements while minimizing system pressure loss. The control system employs a dynamic correction mechanism, updating the correction factor every 30 minutes based on actual operating results. The control system also compares the calculated results with equipment limits to ensure operation within a safe range.

[0139] Optionally, under normal circumstances, based on the heat dissipation of the needle, the heat dissipation of the shoulder and the working parameters, the calculation of the coolant flow rate of the needle and the coolant flow rate of the shoulder can be achieved by the following methods, which are not limited here: according to the inlet and outlet pressure difference and the cross-sectional area of ​​the channel, the coolant baseline flow rate is calculated; based on the heat dissipation of the needle and the coolant temperature of the needle cooling channel, the minimum cooling flow rate required for the needle is calculated; based on the heat dissipation of the shoulder and the coolant temperature of the shoulder cooling channel, the minimum cooling flow rate required for the shoulder is calculated; when the coolant baseline flow rate is less than the minimum cooling flow rate required for the needle, the pump pressure of the needle cooling channel is increased to increase the inlet pressure. outlet pressure difference; substitute the inlet and outlet pressure difference after pressurization into the preset flow calculation formula to obtain the needle coolant flow; when the coolant base flow is less than the minimum cooling flow required for the shoulder, increase the pump pressure of the shoulder cooling channel to increase the inlet and outlet pressure difference; substitute the inlet and outlet pressure difference after pressurization into the preset flow calculation formula to obtain the shoulder coolant flow; when the coolant base flow is greater than the minimum cooling flow required for the needle, the minimum cooling flow required for the needle is determined as the needle coolant flow; when the coolant base flow is greater than the minimum cooling flow required for the shoulder, the minimum cooling flow required for the shoulder is determined as the shoulder coolant flow.

[0140] The following is a specific example to illustrate the calculation process of coolant flow:

[0141] Initial conditions:

[0142] 1. Heat dissipation data:

[0143] Needle heat dissipation = 2250W;

[0144] Heat dissipation at shoulder = 3800W;

[0145] 2. Coolant physical parameters (taking water-based coolant as an example):

[0146] Specific heat capacity (c) = 4200 J / (kg·K);

[0147] Density (ρ) = 998 kg / m³;

[0148] Allowable temperature rise (ΔT) = 15°C;

[0149] 3. Channel parameters:

[0150] Needle channel cross-sectional area (A1) = 28.3 mm² (φ6 mm);

[0151] Cross-sectional area of ​​shoulder channel (A2) = 50.3 mm² (φ8 mm);

[0152] Initial inlet and outlet pressure difference (ΔP) = 0.2 MPa;

[0153] Maximum allowable pressure difference = 0.8MPa.

[0154] Calculation process:

[0155] 1. Calculate the coolant base flow rate: Use the Bernoulli equation: Q = Cd × A × √ (2 × ΔP / ρ), where Cd is the flow coefficient (take 0.85);

[0156] Needle reference flow rate: Q1=0.85×28.3×10⁻ 6 ×√(2×0.2×10 6 / 998) = 4.82 L / min;

[0157] Shoulder reference flow: Q2=0.85×50.3×10⁻ 6 ×√(2×0.2×10 6 / 998) = 8.57 L / min;

[0158] 2. Calculate the minimum required cooling flow: Qmin = Qcooling / (ρ×c×ΔT);

[0159] Minimum needle flow rate: Q1 minimum = 2250 / (998×4200×15)×60000=6.43L / min;

[0160] Minimum flow rate at the shoulder: Q2 minimum = 3800 / (998×4200×15)×60000=10.85L / min;

[0161] 3. Flow regulation calculation:

[0162] Needle cooling channel: The base flow rate (4.82 L / min) is less than the required minimum flow rate (6.43 L / min), so the pressure differential needs to be increased;

[0163] New pressure difference calculation: ΔP1new = (6.43 / 4.82)²×0.2=0.357MPa, final needle flow rate = 6.43L / min;

[0164] Shoulder cooling channel: The baseline flow rate (8.57L / min) is less than the required minimum flow rate (10.85L / min), and the pressure difference needs to be increased;

[0165] New pressure difference calculation: ΔP2new = (10.85 / 8.57)²×0.2 = 0.320MPa, final shoulder flow = 10.85L / min;

[0166] 4. Verification and adjustment:

[0167] Check whether the new pressure difference is within the allowable range:

[0168] The new pressure difference of the needle is 0.357MPa < the maximum allowable pressure difference is 0.8MPa (satisfied);

[0169] New pressure difference at shoulder 0.320MPa < maximum allowable pressure difference 0.8MPa (satisfied);

[0170] System correction: Check the actual cooling effect after 30 minutes. If the temperature control effect is not ideal, adjust the correction factor. Assuming the cooling effect is slightly lower, the correction factor is 1.1. The corrected flow rate is: needle: 6.43×1.1=7.07L / min, shoulder: 10.85×1.1=11.94L / min;

[0171] 5. Final output parameters:

[0172] 1. Needle cooling channel: flow rate: 7.07L / min, working pressure difference: 0.432MPa;

[0173] 2. Shoulder cooling channel: flow rate: 11.94L / min, working pressure difference: 0.387MPa.

[0174] S212. Input the needle temperature data, shoulder temperature data, needle coolant flow rate, and shoulder coolant flow rate into a temperature prediction model to obtain a predicted needle temperature and a predicted shoulder temperature within a preset time period in the future. The needle coolant flow rate refers to the coolant flow rate in the current needle cooling channel, and the shoulder coolant flow rate refers to the coolant flow rate in the current shoulder cooling channel.

[0175] For details, please refer to step S102, which will not be described again here.

[0176] S213. Obtain operating parameters of the stirring head, including stirring head rotation speed, axial pressure, and stirring depth.

[0177] Among them, the operating parameters represent the key process variables that describe the working status of the stirring head; the stirring head speed refers to the angular velocity of the tool rotating around its own axis, and the unit is revolutions per minute; the axial pressure is used to indicate the pressure applied by the stirring head in the vertical direction, and the unit is kilonewton; the stirring depth indicates the distance the stirring head needle is inserted into the workpiece, and the unit is millimeters.

[0178] Specifically, the control system collects operating parameters in real time through multiple collaborative sensor systems: Agitator head speed is measured by a high-precision Hall effect sensor with a sampling frequency of 1000Hz and an accuracy of ±1rpm; axial pressure is measured by a strain gauge pressure sensor with a sampling frequency of 500Hz and an accuracy of ±0.1kN; and stirring depth is measured by a displacement sensor with a sampling frequency of 100Hz and an accuracy of ±0.01mm. The control system filters and averages the collected data in real time to eliminate the effects of transient fluctuations. The control system also records parameter trends to assess process stability.

[0179] S214 , inputting the operating parameters into the first temperature formula and the second temperature formula respectively to obtain a preset needle target temperature and a preset shoulder target temperature.

[0180] The first temperature formula represents the mathematical equation for calculating the preset needle target temperature; the second temperature formula represents the mathematical equation for calculating the preset shoulder target temperature. The preset needle target temperature represents the ideal operating temperature of the needle; the preset shoulder target temperature represents the ideal operating temperature of the shoulder. The first temperature formula is: Tn = T0 + k1 × P - k2 × R + k3 × D; the second temperature formula is: Ts = T0 + k4 × P - k5 × R - k6 × D; where Tn is the preset needle target temperature, Ts is the preset shoulder target temperature, T0 is the preset reference temperature, P is the axial pressure, R is the stirring head speed, D is the stirring depth, k1 is the needle pressure temperature coefficient, k2 is the needle speed temperature coefficient, k3 is the needle depth temperature coefficient, k4 is the shoulder pressure temperature coefficient, k5 is the shoulder speed temperature coefficient, and k6 is the shoulder depth temperature coefficient.

[0181] Specifically, the control system substitutes the collected operating parameters into the first and second temperature formulas. The reference temperature, T0, is typically set at ambient temperature plus 100°C. The temperature coefficients are calibrated through extensive testing: k1 (needle pressure temperature coefficient) ≈ 0.5°C / kN, k2 (needle speed temperature coefficient) ≈ 0.02°C / rpm, k3 (needle depth temperature coefficient) ≈ 2°C / mm, k4 (shoulder pressure temperature coefficient) ≈ 0.3°C / kN, k5 (shoulder speed temperature coefficient) ≈ 0.015°C / rpm, and k6 (shoulder depth temperature coefficient) ≈ 1°C / mm. The control system updates the calculation results every 0.1 seconds and compares the calculated target temperature with the process's allowable range to ensure the setpoint temperature is within a safe range.

[0182] S215 . When the deviation between the needle predicted temperature and the preset needle target temperature exceeds a first temperature threshold and / or the deviation between the shoulder predicted temperature and the preset shoulder target temperature exceeds a second temperature threshold, calculate the needle target flow rate and / or the shoulder target flow rate.

[0183] For details, please refer to step S103, which will not be described again here.

[0184] S216 , adjusting the coolant flow rate of the needle cooling channel and / or the shoulder cooling channel to achieve the needle target flow rate and / or the shoulder target flow rate.

[0185] For details, please refer to step S104, which will not be described again here.

[0186] The stirring head in the embodiment of this application is described below. Figure 3 , which is a structural schematic diagram of the stirring head in an embodiment of the present application.

[0187] The following describes the control system in the embodiment of the present invention from the perspective of hardware processing. Figure 4 , which is a schematic diagram of the structure of a physical device of the control system in an embodiment of the present application.

[0188] It should be noted that Figure 4 The structure of the control system shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0189] like Figure 4As shown, the control system includes a CPU 401, which can perform various appropriate actions and processes according to programs stored in a read-only memory ROM 402 or programs loaded from a storage unit 408 into a random access memory RAM 403, such as executing the methods described in the above embodiments. Various programs and data required for system operation are also stored in RAM 403. CPU 401, ROM 402, and RAM 403 are interconnected via a bus 404. An I / O interface 405 is also connected to bus 404.

[0190] The following components are connected to the I / O interface 405: an input section 406 including an audio input device, push button switches, and the like; an output section 407 including a liquid crystal display (LCD), an audio output device, indicator lights, and the like; a storage section 408 including a hard disk and the like; and a communication section 409 including a network interface card such as a LAN (Local Area Network) card or a modem. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the I / O interface 405 as needed. Removable media 411, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, is installed in the drive 410 as needed, so that computer programs read from the removable media can be installed in the storage section 408 as needed.

[0191] In particular, according to an embodiment of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, an embodiment of the present invention includes a computer program product comprising a computer program carried on a computer-readable medium, the computer program including a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 409 and / or installed from a removable medium 411. When the computer program is executed by the CPU 401, the various functions defined in the present invention are performed.

[0192] It should be noted that specific examples of computer-readable storage media may include, but are not limited to, an electrical connection having one or more conductors, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0193] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. Each box in the flowchart or block diagram can represent a module, program segment, or part of the code, and the above-mentioned module, program segment, or part of the code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings.

[0194] Specifically, the control system of this embodiment includes a processor and a memory. The memory stores a computer program. When the computer program is executed by the processor, the stirring head temperature control method provided in the above embodiment is implemented.

[0195] As another aspect, the present invention further provides a computer-readable storage medium, which may be included in the control system described in the above embodiments, or may exist independently and not be incorporated into the control system. The storage medium carries one or more computer programs, and when executed by a processor of the control system, the control system implements the stirring head temperature control method provided in the above embodiments.

[0196] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0197] Those skilled in the art will appreciate that all or part of the process steps in the above-described method embodiments can be implemented by a computer program instructing the relevant hardware. The program can be stored in a computer-readable storage medium, and when executed, the program can include the process steps in the above-described method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A method for controlling the temperature of a stirring head, characterized in that: Applied to a control system, the method includes: collecting needle temperature data and shoulder temperature data of a stirring head, the needle temperature data including a current needle temperature and a needle temperature change rate, and the shoulder temperature data including a current shoulder temperature and a shoulder temperature change rate; inputting the needle temperature data, the shoulder temperature data, the needle coolant flow rate, and the shoulder coolant flow rate into a temperature prediction model to obtain a predicted needle temperature and a predicted shoulder temperature within a preset time period in the future, the needle coolant flow rate referring to the coolant flow rate in the current needle cooling channel, and the shoulder coolant flow rate referring to the coolant flow rate in the current shoulder cooling channel; calculating a needle target flow rate and / or a shoulder target flow rate when a deviation between the predicted needle temperature and a preset needle target temperature exceeds a first temperature threshold and / or a deviation between the predicted shoulder temperature and a preset shoulder target temperature exceeds a second temperature threshold; and adjusting the coolant flow rates of the needle cooling channel and / or the shoulder cooling channel to achieve the needle target flow rate and / or the shoulder target flow rate; Before the step of inputting the needle temperature data, the shoulder temperature data, the needle coolant flow rate and the shoulder coolant flow rate into the temperature prediction model to obtain the predicted needle temperature and the predicted shoulder temperature within a preset time period in the future, the needle coolant flow rate refers to the coolant flow rate in the current needle cooling channel, and the shoulder coolant flow rate refers to the coolant flow rate in the current shoulder cooling channel, the method further includes: obtaining the needle profile data and the shoulder profile data of the stirring head to determine wear characteristic parameters, the wear characteristic parameters including the wear depth, wear area and surface roughness of the needle and the shoulder; determining the needle friction heat data and the shoulder friction heat data based on the wear characteristic parameters; calculating the needle heat dissipation and the shoulder heat dissipation per unit time based on the needle friction heat data and the shoulder friction heat data; detecting the operating parameters of the needle cooling channel and the shoulder cooling channel, the operating parameters including the inlet and outlet pressure difference, the coolant temperature and the channel cross-sectional area; and calculating the needle coolant flow rate and the shoulder coolant flow rate based on the needle heat dissipation, the shoulder heat dissipation and the operating parameters.

2. The method according to claim 1, characterized in that After the step of collecting needle temperature data and shoulder temperature data of the stirring head, wherein the needle temperature data includes the current needle temperature and the needle temperature change rate, and the shoulder temperature data includes the current shoulder temperature and the shoulder temperature change rate, the method further includes: if the needle temperature change rate and / or the shoulder temperature change rate exceeds a preset rate threshold, adjusting the coolant flow of the needle cooling channel to a preset needle maximum flow and / or adjusting the coolant flow of the shoulder cooling channel to a preset shoulder maximum flow, and reducing the rotation speed of the stirring head to a preset safety rotation speed; after a preset time period, if the needle temperature change rate and / or the shoulder temperature change rate still exceeds the preset rate threshold, controlling the stirring head to shut down.

3. The method according to claim 1, characterized in that Before the step of calculating the needle target flow rate and / or the shoulder target flow rate when the deviation between the needle predicted temperature and the preset needle target temperature exceeds a first temperature threshold and / or the deviation between the shoulder predicted temperature and the preset shoulder target temperature exceeds a second temperature threshold, the method further comprises: obtaining operating parameters of the stirring head, the operating parameters including stirring head speed, axial pressure and stirring depth; inputting the operating parameters into a first temperature formula and a second temperature formula respectively to obtain the preset needle target temperature and the preset shoulder target temperature; the first temperature formula is : Tn=T0+k1×P-k2×R+k3×D; the second temperature formula is: Ts=T0+k4×P-k5×R-k6×D; wherein, Tn is the preset needle target temperature, Ts is the preset shoulder target temperature, T0 is the preset reference temperature, P is the axial pressure, R is the stirring head speed, D is the stirring depth, k1 is the needle pressure temperature coefficient, k2 is the needle speed temperature coefficient, k3 is the needle depth temperature coefficient, k4 is the shoulder pressure temperature coefficient, k5 is the shoulder speed temperature coefficient, and k6 is the shoulder depth temperature coefficient.

4. The method according to claim 1, wherein Determining the needle friction heat data specifically includes: obtaining material parameters of the needle, the material parameters including thermal conductivity, specific heat capacity, and density; calculating the actual contact area between the needle and the workpiece based on the wear depth and wear area of ​​the needle, and determining the dynamic friction coefficient of the needle according to the surface roughness of the needle; substituting the material parameters, operating parameters, the actual contact area, and the dynamic friction coefficient into a needle heat dissipation calculation formula to obtain the needle heat dissipation per unit time.

5. The method according to claim 1, wherein The calculation of the needle coolant flow rate and the shoulder coolant flow rate based on the needle heat dissipation, the shoulder heat dissipation and the operating parameters specifically includes: calculating the coolant base flow rate according to the inlet and outlet pressure difference and the channel cross-sectional area; calculating the minimum cooling flow rate required for the needle based on the needle heat dissipation and the coolant temperature of the needle cooling channel; calculating the minimum cooling flow rate required for the shoulder based on the shoulder heat dissipation and the coolant temperature of the shoulder cooling channel; when the coolant base flow rate is less than the minimum cooling flow rate required for the needle, increasing the pump pressure of the needle cooling channel to increase the inlet and outlet pressure difference; and increasing the pressurized inlet pressure to the needle. The outlet pressure difference is substituted into the preset flow calculation formula to obtain the needle coolant flow; when the coolant base flow is less than the minimum cooling flow required for the shoulder, the pump pressure of the shoulder cooling channel is increased to increase the inlet and outlet pressure difference; the pressurized inlet and outlet pressure difference is substituted into the preset flow calculation formula to obtain the shoulder coolant flow; when the coolant base flow is greater than the minimum cooling flow required for the needle, the minimum cooling flow required for the needle is determined as the needle coolant flow; when the coolant base flow is greater than the minimum cooling flow required for the shoulder, the minimum cooling flow required for the shoulder is determined as the shoulder coolant flow.

6. The method according to claim 1, characterized in that Before the step of collecting the needle temperature data and shoulder temperature data of the stirring head, the method also includes: obtaining the ambient temperature and ambient humidity; judging whether the ambient temperature and the ambient humidity meet the stir friction welding working conditions; if so, starting the stirring head; if not, adjusting the ambient temperature and ambient humidity to meet the stir friction welding working conditions.

7. A control system, characterized in that: The control system includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the control system to execute the method as described in any one of claims 1 to 6.

8. A computer-readable storage medium comprising instructions, characterized in that: When the instructions are executed on a control system, the control system is caused to execute the method according to any one of claims 1 to 6.

9. A computer program product, characterized in that When the computer program product is run on a control system, the control system is caused to execute the method according to any one of claims 1 to 6.

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