Method for controlling welding of stainless steel pipe fittings and welding device

Abstract

The application is suitable for the technical field of metal material welding, and particularly relates to a stainless steel pipeline accessory welding control method and a welding device. The method comprises the following steps: based on real-time collected infrared temperature distribution data in a welding process, temperature time sequence data of a plurality of feature points of a target welding area is extracted; based on the temperature time sequence data, a cooling rate is determined; based on an absolute difference value between the cooling rate and a mean value of cooling rates of all the feature points, a cooling rate deviation degree is obtained; an abnormal feature point number exceeding a preset deviation threshold is counted, and a thermal inertia space deviation index is obtained according to the cooling rate deviation degree of each feature point, a preset position weight corresponding to the feature point, and the abnormal feature point number; and based on a threshold interval where the thermal inertia space deviation index is located, switching and execution are performed among a plurality of preset pulse parameter control strategies. The method provided by the application can solve the problem of local temperature continuous rising and lead to burning through.

Description

Technical Field

[0001] This application belongs to the field of metal material welding technology, and in particular relates to a welding control method and welding device for stainless steel pipe fittings. Background Technology

[0002] Stainless steel pipe fittings (also known as stainless steel pipe ornaments) are the core functional components of stainless steel piping systems, primarily responsible for pipe turning, diversion and convergence, pipe diameter transition, end sealing, and equipment connection. Stainless steel pipe fittings can include pipe fittings (such as tees, elbows, and reducers) and are widely used in piping systems in industries such as petrochemicals, nuclear power, and food processing.

[0003] Currently, pulse welding of stainless steel pipes mainly employs a unified control method based on average parameters. Specifically, a single sensor (such as a thermocouple or vision camera) collects the overall average temperature or average weld pool width of the welding area. This average parameter is compared with a preset target value, and the controller outputs the same pulse current, duty cycle, and other pulse parameters uniformly to the entire welding area, achieving homogenized heat input regulation. This control method implicitly assumes that the transient cooling capacity is consistent across all locations within the welding area; therefore, it uses the same set of pulse parameters to uniformly control the entire welding area.

[0004] However, at the pipe intersection, the abrupt change in wall thickness leads to significant spatial differences in transient cooling capacity across the welding area. Regions with strong transient cooling capacity (such as thin-walled areas) have low heat capacity; although their heat dissipation rate is fast, the small total heat capacity of the material makes these regions extremely sensitive to changes in heat input, with even a small amount of excess heat input causing a sharp rise in local temperature. Regions with weak transient cooling capacity (such as thick-walled areas) have high heat capacity, slow heat dissipation, and require higher heat input to reach the fusion temperature. Under homogenized control, the controller outputs a uniform pulse parameter based on the average parameter reflecting the overall average level. This pulse parameter corresponds to the average heat input requirement of the entire welding area. Because thick-walled areas have high heat capacity and require a high amount of heat input to reach the fusion temperature, the high heat input requirement in thick-walled areas raises the average parameter, causing the controller to output a higher uniform heat input level. This higher heat input level is reasonable for thick-walled areas with high heat capacity and slow heat dissipation, but it exceeds the local heat dissipation capacity of thin-walled areas with low heat capacity and fast heat dissipation. Thin-walled regions, due to their small heat capacity, cannot accommodate excess heat. The residual heat that is not completely dissipated in each excess pulse cycle gradually accumulates, causing the local temperature to rise continuously, eventually exceeding the solidus temperature of the material and resulting in burn-through defects. Summary of the Invention

[0005] This application provides a welding control method and welding device for stainless steel pipe fittings, which can solve the problem that in the traditional technology based on the uniform control method of average parameters, the high heat input demand in the thick-walled area will raise the average parameter, making the uniform heat input level output by the controller too high, resulting in the local temperature continuously rising and eventually exceeding the solidus temperature of the material, causing burn-through defects.

[0006] In a first aspect, embodiments of this application provide a welding control method for stainless steel pipe fittings, including: Based on the infrared temperature distribution data collected in real time during the welding process, temperature time-series data of multiple feature points in the target welding area are extracted; wherein, the target welding area is the molten pool and the heat-affected zone adjacent to the molten pool under the action of the welding torch arc. Based on the temperature time series data within each base period of pulse welding, the cooling rate corresponding to each feature point is determined; wherein, the cooling rate is used to reflect the transient cooling capacity of each feature point within the base period of pulse welding. The cooling rate deviation of each feature point is obtained based on the absolute difference between the cooling rate of each feature point and the average cooling rate of all feature points; wherein, the cooling rate deviation is used to reflect the magnitude of the difference between the cooling rate of the feature point and the overall average level. The number of abnormal feature points whose cooling rate deviation exceeds a preset deviation threshold is counted, and the thermal inertia spatial deviation index is obtained based on the cooling rate deviation of each feature point, the preset position weight corresponding to the feature point, and the number of abnormal feature points. Based on the threshold range of the thermal inertia spatial deviation index, the system switches between multiple preset pulse parameter control strategies to adaptively adjust the welding heat input.

[0007] The technical solutions described in this application embodiment have at least the following technical effects: The stainless steel pipe fitting welding control method provided in this application extracts temperature time-series data of multiple feature points in the target welding area based on real-time infrared temperature distribution data acquired during the welding process; determines the cooling rate corresponding to each feature point based on the temperature time-series data within each base period of pulse welding; obtains the cooling rate deviation of each feature point based on the absolute difference between the cooling rate of each feature point and the average cooling rate of all feature points; counts the number of abnormal feature points whose cooling rate deviation exceeds a preset deviation threshold, and obtains a thermal inertia spatial deviation index based on the cooling rate deviation of each feature point, the preset position weight corresponding to the feature point, and the number of abnormal feature points; and switches between multiple preset pulse parameter control strategies based on the threshold range of the thermal inertia spatial deviation index to adaptively adjust the welding heat input. This application transforms the spatial difference in cooling capacity at each location into a quantifiable spatial deviation index of thermal inertia by measuring the deviation between the cooling rate of each feature point and the average cooling rate of all feature points. This index reflects the degree of cooling non-uniformity corresponding to each feature point. Based on the threshold range of this spatial deviation index, an adaptive switching pulse parameter control strategy is used to adjust the welding heat input. When the spatial deviation index is within the threshold range, it indicates that significant cooling non-uniformity has occurred in the welding area. At this time, by switching the control strategy (such as extending the base period and reducing the duty cycle), a longer heat dissipation window can be provided for the thin-walled area with weak cooling capacity, while reducing the heat input during the peak period. This simultaneously suppresses local heat accumulation in the thin-walled area from both the direction of reducing input and increasing heat dissipation, thereby avoiding burn-through. As a result, the heat input can be differentially adjusted according to the change in the spatial non-uniformity of cooling capacity, avoiding the burn-through problem caused by the uniform heat input exceeding the local heat dissipation capacity of the area with strong transient cooling capacity under homogenized control.

[0008] In one possible implementation of the first aspect, determining the cooling rate corresponding to each feature point based on the temperature timing data within each base period of pulse welding includes: Temperature values ​​of each characteristic point were collected at the start and end times of the pulse welding baseline period, and the temperature difference of the same characteristic point within the baseline period was calculated. The cooling rate of each feature point is determined based on the ratio of the temperature difference to the duration of the baseline period.

[0009] In one possible implementation of the first aspect, the switching execution among multiple preset pulse parameter control strategies based on the threshold range of the thermal inertia spatial deviation index includes: When the thermal inertia spatial deviation index is lower than or equal to the first threshold, the standard pulse parameter strategy is executed. When the thermal inertia spatial deviation index is higher than the first threshold and lower than or equal to the second threshold, a heat dissipation enhancement strategy is executed. When the thermal inertia spatial deviation index is higher than the second threshold, a burn-through emergency strategy is executed to reduce the pulse frequency.

[0010] In one possible implementation of the first aspect, after switching between multiple preset pulse parameter control strategies based on the threshold range of the thermal inertia spatial deviation index to adaptively adjust the welding heat input, the method further includes: When switching between multiple preset pulse parameter control strategies, the parameter values ​​corresponding to the previous pulse parameter control strategy and the parameter values ​​corresponding to the determined target pulse parameter control strategy are obtained. Based on the parameter values ​​corresponding to the previous pulse parameter control strategy, the parameter values ​​corresponding to the determined target pulse parameter control strategy, and the time constant, smoothing is performed to obtain the current output parameter values.

[0011] Return to the step of performing smoothing processing based on the parameter values ​​corresponding to the previous pulse parameter control strategy, the parameter values ​​corresponding to the determined target pulse parameter control strategy, and the time constant to obtain the current output parameter value, until the current output parameter value is the same as the parameter value corresponding to the determined target pulse parameter control strategy.

[0012] In one possible implementation of the first aspect, the method further includes: During the welding arc initiation and preheating stage, the temperature rise rate of multiple characteristic points was collected. Based on the relationship between the temperature rise rate of each feature point and the preset temperature rise threshold, a feedforward thermal inertia distribution map is generated; wherein, the feedforward thermal inertia distribution map is used to mark the areas on the pipe to be welded where there are differences in heat dissipation capacity. During the formal walking welding phase, based on the current position of the welding torch and the feedforward thermal inertia distribution map, the pulse parameter control strategy is pre-switched in advance.

[0013] In one possible implementation of the first aspect, generating a feedforward thermal inertia distribution map based on the relationship between the temperature rise rate of each feature point and a preset temperature rise threshold includes: Regions with a temperature rise rate lower than a preset temperature rise threshold are marked as high-risk heat dissipation areas, and regions with a temperature rise rate higher than the preset temperature rise threshold are marked as low-risk areas, in order to obtain the feedforward thermal inertia distribution map; wherein, the preset temperature rise threshold is determined in advance based on the thermophysical properties of the welding material and the preheating target temperature.

[0014] In one possible implementation of the first aspect, the pre-switching of the pulse parameter control strategy in advance during the formal walking welding phase, based on the current position of the welding torch and the feedforward thermal inertia distribution map, includes: During the formal walking welding phase, when the welding torch is located at an angle marked as a high-risk heat dissipation zone in the feedforward thermal inertia distribution map, the current pulse parameter control strategy is switched to the heat dissipation enhancement strategy in advance, regardless of whether the current real-time thermal inertia spatial deviation index triggers a strategy switch.

[0015] In one possible implementation of the first aspect, the pulse welding is a welding method in which the welding current alternates periodically between a peak current and a base current according to a preset pulse frequency; wherein, a time period corresponding to a peak current and a time period corresponding to a base current constitute a pulse cycle; the pulse cycle includes two phases: a peak period and a base period; wherein, the peak period is the time period during which the welding current is maintained at the peak current; and the base period is the time period during which the welding current switches from the peak current to the base current.

[0016] Secondly, embodiments of this application provide a stainless steel pipe fitting welding control system, applied to a welding apparatus, for implementing the stainless steel pipe fitting welding control method described in any one of the first aspects above. The stainless steel pipe fitting welding control system includes: The extraction unit is used to extract the temperature time series data of multiple feature points in the target welding area based on the infrared temperature distribution data collected in real time during the welding process; wherein, the target welding area is the molten pool under the action of the welding torch arc and the heat-affected zone adjacent to the molten pool. The determining unit is used to determine the cooling rate corresponding to each feature point based on the temperature time series data within each base period of pulse welding; wherein the cooling rate is used to reflect the transient cooling capacity of each feature point within the base period of pulse welding. The calculation unit is used to obtain the cooling rate deviation of each feature point based on the absolute difference between the cooling rate of each feature point and the average cooling rate of all feature points; wherein, the cooling rate deviation is used to reflect the magnitude of the difference between the cooling rate of the feature point and the overall average level; The analysis unit is used to count the number of abnormal feature points where the cooling rate deviation exceeds a preset deviation threshold, and to obtain the thermal inertia spatial deviation index based on the cooling rate deviation of each feature point, the preset position weight corresponding to the feature point, and the number of abnormal feature points. The control unit is used to switch between multiple preset pulse parameter control strategies based on the threshold range of the thermal inertia spatial deviation index, so as to adaptively adjust the welding heat input.

[0017] Thirdly, embodiments of this application provide a welding apparatus, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the stainless steel pipe fitting welding control method described in any one of the first aspects above.

[0018] It is understood that the beneficial effects of the second and third aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a schematic flowchart of a welding control method for stainless steel pipe fittings provided in an embodiment of this application; Figure 2 This is a schematic diagram illustrating the determination of the cooling rate corresponding to each feature point in the welding control method for stainless steel pipe fittings provided in an embodiment of this application. Figure 3 This is a schematic diagram of pulse parameters in a welding control method for stainless steel pipe fittings provided in an embodiment of this application; Figure 4 This is a schematic diagram of the difference in thermal inertia in a welding control method for stainless steel pipe fittings provided in an embodiment of this application; Figure 5 This is a schematic diagram of the stainless steel pipe fitting welding control system provided in the embodiments of this application; Figure 6 This is a schematic diagram of the structure of the control device of the welding apparatus provided in the embodiments of this application. Detailed Implementation

[0021] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0022] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0023] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0024] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if the described condition or event is detected" may be interpreted, depending on the context, as "once determined," "in response to determination," "once the described condition or event is detected," or "in response to the detection of the described condition or event."

[0025] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0026] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0027] In related technologies, in the unified control method based on mean parameters, the high heat input demand in the thick-walled region will raise the mean parameter, causing the unified heat input level output by the controller to be too high, resulting in a continuous rise in local temperature, which eventually exceeds the solidus temperature of the material and causes burn-through defects.

[0028] To address the aforementioned issues, this application provides a welding control method and welding apparatus for stainless steel pipe fittings.

[0029] In this method, the spatial difference in cooling capacity at each location is transformed into a quantifiable spatial deviation index of thermal inertia by the deviation between the cooling rate of each feature point and the average cooling rate of all feature points. This index reflects the degree of cooling non-uniformity at each feature point. Based on the threshold range of this spatial deviation index, an adaptive switching pulse parameter control strategy is used to adjust the welding heat input. This allows the heat input to be adjusted differently according to the change in the spatial non-uniformity of cooling capacity, avoiding the burn-through problem caused by the uniform heat input exceeding the local heat dissipation capacity of areas with strong transient cooling capacity under homogenized control.

[0030] The welding control method for stainless steel pipe fittings provided in this application embodiment can be applied to a welding device. In this case, the welding device is the main body for executing the welding control method for stainless steel pipe fittings provided in this application embodiment. This application embodiment does not impose any restrictions on the specific type of welding device.

[0031] For example, the welding apparatus may include a pulsed TIG welding machine for providing a controllable pulsed welding current, and with built-in or external current and voltage sensors to acquire welding electrical parameters in real time; a traveling device (e.g., a track-type or magnetic automatic traveling trolley for carrying the welding torch at a constant speed along the circumference or axial direction of the pipe, and with built-in or external position sensors to acquire the current position of the welding torch in real time); a positioning device (e.g., a roller frame or turntable for clamping and driving the pipe to be welded to rotate at a preset speed); an infrared sensing device (e.g., for acquiring temperature distribution data of the welding area in real time); and a control device, etc. For example, the output of a pulsed TIG welding machine is electrically connected to the welding torch on a traveling device. The machine outputs welding current to the torch according to preset pulse parameters. The traveling device carries the torch along the weld seam of the pipe. A positioning device (such as a roller frame) clamps the pipe to be welded and drives it to rotate at a preset low speed during the arc-starting and preheating phase. This allows an infrared sensor to collect temperature data at different angular positions along the entire circumference of the pipe. The infrared sensor is mounted on one side of the welding torch and is used to collect temperature timing data of the molten pool tail and heat-affected zone during the baseline period of pulsed welding. The control device is electrically connected to the welding device, traveling device, positioning device, and infrared sensor. The operator clamps the pipe to be welded onto the positioning device and sets the welding process parameters. Then, during the arc-starting and preheating phase, the control device controls the positioning device to drive the pipe to rotate, while simultaneously controlling the infrared sensor to collect temperature rise characteristic parameters at each angular position, generating a feedforward thermal inertia distribution map. During the formal walking welding phase, the control device controls the walking device to carry the welding torch along the weld seam, controls the welding device to output pulsed welding current, and controls the infrared sensor to collect temperature time-series data of multiple feature points during the base period of each pulse to calculate the cooling rate and thus determine the thermal inertia spatial deviation index. Finally, the control device switches the pulse parameter control strategy of the welding device according to the threshold range of the thermal inertia spatial deviation index.

[0032] For example, the control device can be a PLC, tablet computer, laptop computer, ultra-mobile personal computer (UMPC), netbook, desktop computer, computing device, or computer connected to a wireless modem, laptop computer, handheld communication device, handheld computing device, etc.

[0033] To better understand the welding control method for stainless steel pipe fittings provided in the embodiments of this application, the specific implementation process of the welding control method for stainless steel pipe fittings provided in the embodiments of this application will be described by way of example below.

[0034] Figure 1 A schematic flowchart of a welding control method for stainless steel pipe fittings provided in an embodiment of this application is shown. The welding control method for stainless steel pipe fittings includes: S100 extracts the time-series temperature data of multiple feature points in the target welding area based on real-time acquired infrared temperature distribution data during the welding process. The target welding area is the molten pool and the heat-affected zone adjacent to the molten pool under the action of the welding torch arc.

[0035] It is understood that the target welding area can be the molten pool under the action of the welding torch arc and its adjacent heat-affected zone. For example, the target welding area may include the molten pool, the heat-affected zone, and part of the base material area that is not affected by heat. In the actual welding process, the temperature distribution of the welding area is not uniform, especially at the intersection of pipe fittings (such as tees, elbows, and reducers). Due to the abrupt change in wall thickness and heat dissipation cross-sectional area, the cooling capacity at different locations may vary significantly. Infrared temperature distribution data can be the surface temperature distribution information of the welding area collected by an infrared sensor. This temperature distribution information is output in the form of a sequence of temperature values ​​corresponding to each spatial location point along the scanning line direction.

[0036] For example, infrared temperature distribution data of the welding area can be obtained using an infrared sensor (such as an 808nm infrared scanning sensor) on the welding torch. The scanning line of the infrared sensor covers the tail of the molten pool and the heat-affected zone, and the scanning direction is perpendicular to the longitudinal direction of the weld. In each scanning cycle, the infrared sensor outputs a temperature distribution curve along the scanning line, with each data point on the curve corresponding to the temperature value at the location traversed by the scanning line. By analyzing the temperature distribution curves of multiple consecutive scanning cycles, infrared temperature distribution data can be obtained.

[0037] Specifically, the selection principle for feature points is to cover key locations in the welding area where the cooling capacity may change abruptly. The number of feature points can be 3, 4, or 5, depending on the geometric complexity of the welded workpiece and the degree of difference in heat dissipation conditions. The feature points selected in this step can be three points distributed along the longitudinal direction of the weld: the end point of the molten pool P1, the leading edge point of the heat-affected zone P2, and the trailing edge point of the heat-affected zone P3. P1 (the end point of the molten pool) can be a point approximately 1 mm behind the solid-liquid interface of the molten pool along the longitudinal direction of the weld. This point is located in the newly solidified weld metal region, and the cooling rate of P1 reflects the heat dissipation conditions of the weld metal after solidification. P2 (the leading edge point of the heat-affected zone) can be a point approximately 3 mm-5 mm behind the end point of the molten pool along the longitudinal direction of the weld. This point is located in the high-temperature region of the heat-affected zone, and the cooling rate of P2 reflects the heat dissipation conditions of the heat-affected zone near the weld. P3 (the trailing edge of the heat-affected zone) can be a point located approximately 8mm-12mm behind the end of the molten pool along the longitudinal direction of the weld. This point is located in the medium-low temperature region of the heat-affected zone. The cooling rate of P3 reflects the heat dissipation conditions of the heat-affected zone away from the weld and the heat conduction capacity of the base material further away. It should be noted that the spatial positions of the above three feature points can be fixed relative to the current position of the welding torch, or they can be located according to the actual temperature distribution.

[0038] For example, the methods for determining the three feature points P1, P2, and P3 are as follows: In infrared temperature distribution data, P1 can be determined by the point of maximum temperature gradient. For example, scanning along the longitudinal direction of the weld, the position where the temperature change rate (dT÷dx) reaches its maximum negative value is the end point of the molten pool, because this position is the solidification front where liquid metal transforms into solid base material, and the temperature gradient is the maximum. P2 can be determined by the temperature boundary threshold of the heat-affected zone. For example, continuing to scan from position P1 along the direction of weld advancement, when the temperature drops below the sensitization temperature of stainless steel (for example, the sensitization temperature of 304 stainless steel is about 450°C), this position is the front point of the heat-affected zone, P2. P3 can be determined symmetrically. For example, scanning from position P1 in the opposite direction of weld advancement, when the temperature drops below the aforementioned sensitization temperature threshold, this position is the rear edge point of the heat-affected zone, P3.

[0039] S200 determines the cooling rate corresponding to each feature point based on the temperature time series data within each base period of pulse welding. The cooling rate reflects the transient cooling capacity of each feature point within the base period of pulse welding.

[0040] The cooling rate can be understood as the transient cooling capacity of each feature point during the pulse welding baseline period. It characterizes the rate at which the feature point and its surrounding material lose heat through conduction, convection, and radiation under conditions without external heating source interference. A larger cooling rate value indicates a stronger transient cooling capacity of the feature point, meaning the material in that area can transfer heat to the surrounding environment or surrounding materials more quickly; a smaller cooling rate value indicates a weaker transient cooling capacity of the feature point, meaning the material in that area has a larger thermal inertia or poorer heat dissipation conditions. Pulse welding can be a welding method in which the welding current alternates periodically between the peak current and the baseline current according to a preset pulse frequency. A complete pulse cycle includes a peak period (the welding current is maintained at the peak level, e.g., 120A) and a baseline period (the welding current drops to the baseline level, e.g., 20A). During the peak period, the arc power is high, inputting a large amount of heat into the base material, causing the base material temperature to rise rapidly. During the baseline period, the arc power drops to 15% to 20% of the peak value, significantly reducing the direct heat input from the arc to the base material. At this time, the temperature change at the characteristic points is mainly dominated by the heat conduction process of the material itself and the surface heat dissipation process. The peak period can be the time when the welding current is maintained at the peak current, and the baseline period can be the time when the welding current switches from the peak current to the baseline current.

[0041] For example, the temperature of each feature point is collected at the start and end of the base period of each pulse cycle. Based on the difference between the temperature of each feature point at the start and end of the base period, and the duration of the base period, the cooling rate of each feature point is determined. For example, the cooling rate is calculated as: CRi = (Tistart - Tiend) ÷ t, where CRi is the cooling rate of the i-th feature point, Tistart is the temperature of the i-th feature point at the start of the base period, Tiend is the temperature of the i-th feature point at the end of the base period, and t is the duration of the base period.

[0042] The cooling rate calculation is performed during the baseline period of pulse welding because during this period, the direct heat input from the arc to the base material is significantly reduced due to the substantial decrease in arc power. At this time, the temperature change at the feature point is primarily driven by the following factors: (1) the heat conduction process of the point and its surrounding material, i.e., the rate of heat diffusion from the high-temperature zone to the low-temperature zone, which depends on the material's thermal conductivity and temperature gradient; (2) the convective heat transfer process between the surface of the point and the shielding gas, which depends on the flow rate and temperature of the shielding gas; and (3) the thermal radiation process of the surface of the point, which depends on the surface temperature and emissivity. Since the shielding gas flow rate and ambient temperature are essentially consistent throughout the welding area, the effects of convection and radiation conditions on each feature point can be considered approximately the same. Under these conditions, the difference in cooling rate at each feature point mainly stems from differences in the local material's heat conduction conditions (such as changes in wall thickness and changes in heat dissipation cross-sectional area due to geometric differences), i.e., differences in thermal inertia. Therefore, the baseline cooling rate can be used as a characterization of local transient cooling capacity.

[0043] It should be noted that, when collecting temperature data during the baseline period, to ensure the accuracy of the cooling rate calculation, the infrared sensor's data acquisition sequence is as follows: after the start of the baseline period, a preset stabilization time (e.g., 50ms to 100ms) is delayed before the temperature at the start of the baseline period to avoid interference from residual arc radiation during the transition from the peak period to the baseline period; and before the end of the baseline period, a preset advance time (e.g., 50ms) is used to collect the temperature at the end of the baseline period to avoid interference from arc radiation at the start of the next peak period.

[0044] In one possible implementation, S200, based on the temperature timing data within each base period of the pulse welding, determines the cooling rate corresponding to each feature point, including: S210: Collect the temperature values ​​of each characteristic point at the start and end of the pulse welding base period, and calculate the temperature difference of the same characteristic point within the base period.

[0045] Specifically, during the base value period of each pulse cycle, the temperature values ​​of each characteristic point at the start of the base value period and the temperature values ​​of each characteristic point at the end of the base value period are recorded. Then, the difference between the temperature value at the start of the base value period and the temperature value at the end of the base value period of the same characteristic point is calculated.

[0046] S220 determines the cooling rate of each feature point based on the ratio of the temperature difference to the duration of the baseline period.

[0047] For example, the cooling rate of the feature point is obtained by dividing the temperature difference by the base period duration.

[0048] S300, based on the absolute difference between the cooling rate of each feature point and the mean cooling rate of all feature points, obtains the cooling rate deviation of each feature point. The cooling rate deviation reflects the magnitude of the difference between the cooling rate of a feature point and the overall average level. As can be understood, the cooling rate deviation is used to reflect the magnitude of the difference between the cooling rate of a feature point and the overall average level. The larger the cooling rate deviation, the more the cooling rate of that feature point deviates from the average level, the greater the difference in cooling capacity between that location and the surrounding area, and the higher the probability of a local anomaly.

[0049] For example, the average cooling rate of all feature points within the current pulse cycle can be determined; then, the absolute difference between the cooling rate of each feature point and the average value can be calculated to obtain the cooling rate deviation of each feature point. For example, Di = |CRi - CR|, where Di is the cooling rate deviation of the i-th feature point, CRi is the cooling rate of the i-th feature point, and CR is the average cooling rate of all feature points. CR = (1 ÷ N) × Σ(CRi), where i ranges from 1 to N.

[0050] S400: Count the number of abnormal feature points whose cooling rate deviation exceeds the preset deviation threshold, and obtain the thermal inertia spatial deviation index based on the cooling rate deviation of each feature point, the preset position weight corresponding to the feature point, and the number of abnormal feature points.

[0051] It is understandable that the thermal inertia spatial deviation index is used to characterize the degree of spatial non-uniformity of cooling capacity within a welding area. For example, in a normal welding area with uniform heat dissipation conditions, the cooling rates of each feature point should be similar; when there are abrupt changes in thermal inertia within the welding area (such as changes in wall thickness or geometric shape), the cooling rates of feature points at different locations will show significant differences. The thermal inertia spatial deviation index is precisely a quantitative representation of this degree of difference. That is, the larger the thermal inertia spatial deviation index, the greater the difference in cooling capacity between feature points within the welding area, the more uneven the spatial distribution of cooling capacity, and the higher the probability of local overheating (burn-through) or underheating (incomplete penetration) during the welding process; the smaller the thermal inertia spatial deviation index, the more uniform the cooling capacity between feature points within the welding area, and the more stable the welding process.

[0052] A preset deviation threshold serves as a threshold value for determining whether the deviation of the cooling rate at each feature point reaches an abnormal level. When the cooling rate deviation at a feature point exceeds the preset deviation threshold, it indicates that the difference between the cooling rate at that feature point and the overall average level has exceeded the normal fluctuation range, and the feature point is marked as an abnormal feature point. The number of abnormal feature points reflects the severity of spatial non-uniformity in cooling capacity; the more abnormal feature points, the more widespread the spatial non-uniformity in cooling capacity. For example, the preset deviation threshold can be calibrated through process experiments based on the quality requirements of the welding process. For the root pass welding of 304 stainless steel pipes, the preset deviation threshold can be set to 20% of the overall average cooling rate. It should be noted that the preset deviation threshold is a dynamic threshold, adaptively adjusting with the average cooling rate of each pulse cycle, thus maintaining sensitive detection of the degree of deviation under different welding speeds, different material states, and other operating conditions.

[0053] It should be noted that the purpose of counting the number of abnormal feature points z is not only to quantify the magnitude of the deviation, but also to quantify the spatial distribution of the deviation, i.e., how many locations exhibited significant cooling condition anomalies. The thermal inertia spatial deviation index is an aggregate index that comprehensively considers both the magnitude of the cooling rate deviation and the number of abnormal feature points. Its purpose is to simultaneously take into account the depth (magnitude of deviation of a single feature point) and breadth (number of feature points exhibiting deviation), thereby providing a physically meaningful decision-making basis for switching control strategies.

[0054] For example, the thermal inertia spatial deviation index can be calculated using the formula: Thermal Inertia Spatial Deviation Index = α × Σ(Wi × Di) + β × z, where α is the deviation amplitude adjustment coefficient, β is the abnormal point number adjustment coefficient, Wi is the preset position weight of the i-th feature point, Di is the cooling rate deviation of the i-th feature point, z is the number of abnormal feature points, and Σ represents the summation over all N feature points (i.e., Σ(Wi × Di) = W1 × D1 + W2 × D2 + ... + WN × DN). The first term, α × Σ(Wi × Di), reflects the weighted amplitude of the cooling rate deviation, meaning it considers not only the absolute amplitude of the deviation but also applies differentiated importance assessments to deviations at different locations through the position weight Wi. The second term, β × z, reflects the spatial extent of the cooling condition anomalies; the more locations with significant cooling anomalies, the larger the index value. The superposition of these two terms allows the thermal inertia spatial deviation index to comprehensively reflect the spatial non-uniformity of cooling capacity within the welding area.

[0055] For example, Wi is a preset position weight, representing the degree to which the location of each feature point contributes to the burn-through risk. Position weights can be set based on the contribution of the feature point's location to the burn-through risk: in the welding process of stainless steel pipes, different locations contribute differently to the burn-through risk. The tail end point P1 of the molten pool is located at the liquid-solid interface; the cooling rate at this location directly reflects the heat accumulation at the front of the molten pool's solidification—if the cooling rate at point P1 is low (negative deviation), it indicates insufficient heat dissipation behind the molten pool, severe heat accumulation, and is a precursor to burn-through; the leading edge point P2 of the heat-affected zone is located in the high-temperature zone in front of the molten pool; the cooling rate at this location reflects the preheating state of the material in the arc's forward direction, indirectly contributing to the burn-through risk; the trailing edge point P3 of the heat-affected zone is located in the cooled area; the cooling rate at this location contributes the least to the burn-through risk of the current weld point.

[0056] For example, the position weights can be set as follows: W1=0.6 (point P1), W2=0.3 (point P2), W3=0.1 (point P3). That is, the preset position weight of the end point of the molten pool is higher than the preset position weight of the leading edge point of the heat-affected zone, and the preset position weight of the leading edge point of the heat-affected zone is higher than the preset position weight of the trailing edge point of the heat-affected zone. This weight setting makes the thermal inertia spatial deviation index most sensitive to the abnormal cooling capacity of the end point of the molten pool, and can detect the burn-through risk signal earlier.

[0057] Specifically, the location weight Wi can be calibrated by conducting independent overheating / burn-through tests at each characteristic point location in multiple welding tests of the same material and pipe fittings, and recording the critical heat input at which burn-through defects occur at each location. After normalizing the critical heat input at each location, its reciprocal is used as the initial value of the location weight, and then fine-tuned based on actual welding quality feedback.

[0058] For example, the calibration of the preset deviation threshold can be carried out by conducting a stable welding test under known good welding process parameters, collecting the cooling rate deviation of each feature point within multiple pulse cycles, calculating its mean μ and standard deviation σ, and setting the preset deviation threshold to μ+2σ (or μ+3σ).

[0059] The first and second thresholds can be calibrated by recording the values ​​of the thermal inertia spatial deviation index and the corresponding welding quality state (normal / porosity present / imminent burn-through / burn-through) at each step in a stepped test with gradually increasing welding heat input. The average value of the thermal inertia spatial deviation index corresponding to the transition from normal to porosity is set as the first threshold, and the average value corresponding to the impending burn-through state is set as the second threshold.

[0060] The adjustment coefficients α and β can be calibrated using welding quality (such as weld formation quality score, burn-through rate, etc.) as the objective function. The optimal combination of α and β values ​​can be achieved through orthogonal experiments or response surface methodology to achieve the best welding quality index. Preferably, the value of α ranges from 0.6 to 0.9, and the value of β ranges from 0.1 to 0.4, with α > β.

[0061] It should be noted that in other embodiments, the specific value of the position weight can be adaptively adjusted according to factors such as the type of welding material, pipe wall thickness, and welding position (e.g., flat welding, vertical welding, overhead welding). For example, for overhead welding, due to the downward tendency of the molten pool caused by gravity, the contribution of point P2 (the leading edge of the heat-affected zone) to the risk of burn-through increases, and the value of W2 can be appropriately increased.

[0062] Specifically, the values ​​of the adjustment coefficients α and β can be calibrated through process experiments. In this embodiment, α can be set to 0.8 and β to 0.2, for example. The goal of setting α > β is that the direct impact of the deviation magnitude (depth) on defect risk is greater than the impact of the number of outliers (breadth). The ratio of α to β reflects the system's weight preference for the two different risk signals: deviation depth and deviation breadth. When the α ÷ β ratio is large, the system pays more attention to the cooling rate deviation; when the α ÷ β ratio is small, the system pays more attention to the number of abnormal feature points. The specific values ​​of α and β can be adaptively adjusted according to the actual welding materials, plate thickness, and process requirements.

[0063] The S500, based on the threshold range of the thermal inertia spatial deviation index, switches between multiple preset pulse parameter control strategies to adaptively adjust the welding heat input.

[0064] It can be understood that the threshold range includes the range where the thermal inertia spatial deviation index is lower than or equal to the first threshold, the range where the thermal inertia spatial deviation index is higher than the first threshold but lower than or equal to the second threshold, and the range where the thermal inertia spatial deviation index is higher than the second threshold. The value of the threshold can be determined based on the welding material, pipe wall thickness, and weld quality. As an example, for the root pass welding of 304 stainless steel pipes, the first threshold can be set to 2.0, and the second threshold to 5.0. The preset multiple pulse parameter control strategies can include three strategies: Strategy A, i.e., standard pulse parameter strategy (e.g., using standard pulse parameters), Strategy B, i.e., heat dissipation enhancement strategy (e.g., using long base value low duty cycle pulse parameters), and Strategy C, i.e. burn-through emergency strategy (e.g., low frequency weak pulse parameters). The three strategies correspond to different threshold ranges and different welding heat input levels, respectively.

[0065] For example, when the thermal inertia spatial deviation index is lower than or equal to a first threshold, a standard pulse parameter strategy is executed; when the thermal inertia spatial deviation index is higher than the first threshold but lower than or equal to a second threshold, a heat dissipation enhancement strategy is executed; when the thermal inertia spatial deviation index is higher than the second threshold, a burn-through emergency strategy is executed to reduce the pulse frequency.

[0066] In one possible implementation, step S500 involves switching between multiple preset pulse parameter control strategies based on the threshold range of the thermal inertia spatial deviation index, including: S510: When the thermal inertia spatial deviation index is lower than or equal to the first threshold, the standard pulse parameter strategy is executed.

[0067] It is understandable that a standard pulse parameter strategy can be to use standard pulse parameters for welding. For example, standard pulse parameters include standard peak current, standard base current, standard pulse frequency, and standard duty cycle. As an example, for the root pass welding of 304 stainless steel pipes, the standard pulse parameters can be set as follows: peak current 120A, base current 20A, pulse frequency 2Hz, and duty cycle 30% (i.e., peak period 150ms and base period 350ms).

[0068] For example, when the spatial deviation index of thermal inertia is lower than or equal to the first threshold, it indicates that the spatial non-uniformity of cooling capacity in the welding area is at a low level, the difference in cooling rate between each feature point is small, the welding process is relatively stable, and no additional intervention is required.

[0069] S520 executes a heat dissipation enhancement strategy when the thermal inertia spatial deviation index is higher than the first threshold and lower than or equal to the second threshold.

[0070] It is understandable that a heat dissipation enhancement strategy could be to use long base value and low duty cycle pulse parameters for soldering. For example, the long base value and low duty cycle pulse parameters could be set such that the peak current remains unchanged at 120A, the base current is reduced to 15A, the pulse frequency is reduced to 1.5Hz, and the duty cycle is reduced to 20% (i.e., peak period 133ms, base period 533ms).

[0071] For example, when the spatial deviation index of thermal inertia is higher than the first threshold but lower than or equal to the second threshold, it indicates that the spatial non-uniformity of cooling capacity within the welding area has reached a medium-risk level, and there is a tendency for local heat accumulation. At this point, a heat dissipation enhancement strategy should be switched to.

[0072] This configuration, by extending the duration of the base period, provides a more sufficient heat dissipation window for feature points with lower cooling rates (e.g., locations with high thermal inertia and poor heat dissipation conditions), allowing these feature points to dissipate more heat before the next peak period arrives, thereby reducing the degree of local heat accumulation. Simultaneously, by shortening the duration of the peak period, the total heat input within a single pulse cycle is reduced, suppressing heat accumulation from both the perspectives of reducing input and increasing heat dissipation.

[0073] S530: When the thermal inertia spatial deviation index is higher than the second threshold, a burn-through emergency strategy is executed to reduce the pulse frequency.

[0074] It is understandable that the emergency repair strategy for burn-through can be to use low-frequency weak pulse parameters for welding. For example, the low-frequency weak pulse parameters can be set to reduce the peak current to 90A, the base current to 10A, the pulse frequency to 1Hz, and the duty cycle unchanged.

[0075] Specifically, when the spatial deviation index of thermal inertia is higher than the second threshold, it indicates that the spatial non-uniformity of cooling capacity in the welding area has reached a high-risk level, and there is a possibility of burn-through. At this time, the burn-through emergency strategy should be switched.

[0076] This setting switches to low-frequency weak pulse parameters, further reducing peak current, minimizing heat input, and increasing heat dissipation time.

[0077] Scenario 1: When the control strategy is switched, if the welding pulse parameters (such as peak current, duty cycle, pulse frequency, etc.) change abruptly between two adjacent pulse cycles, it will cause transient thermal shock in the welding area, which may induce new welding defects (such as increased porosity, spatter, etc.). To avoid the above problems, steps S540, S550, and S560 can be used to solve them.

[0078] In one possible implementation, after switching between multiple preset pulse parameter control strategies based on the threshold range of the thermal inertia spatial deviation index in step S500 to adaptively adjust the welding heat input, the stainless steel pipe fitting welding control method further includes: S540, when switching between multiple preset pulse parameter control strategies, obtains the parameter value corresponding to the previous pulse parameter control strategy and the parameter value corresponding to the determined target pulse parameter control strategy.

[0079] It is understandable that the parameter values ​​corresponding to the previous pulse parameter control strategy could be duty cycle, peak current, etc.

[0080] Specifically, the parameter values ​​corresponding to the previous pulse parameter control strategy can be obtained by querying the system log, and the parameter values ​​corresponding to the determined target pulse parameter control strategy can be obtained through step S500.

[0081] S550 performs smoothing processing based on the parameter values ​​corresponding to the previous pulse parameter control strategy, the parameter values ​​corresponding to the determined target pulse parameter control strategy, and the time constant to obtain the current output parameter value.

[0082] It is understandable that the time constant τ is used to reflect the speed of parameter transition. The larger the value of τ, the slower and smoother the parameter transition; the smaller the value of τ, the faster the parameter transition.

[0083] Specifically, the parameter difference between the parameter value corresponding to the determined target pulse parameter control strategy and the parameter value corresponding to the previous pulse parameter control strategy can be calculated. The current output parameter value is then calculated based on the parameter difference, the time constant, and the parameter value corresponding to the previous pulse parameter control strategy. For example, the current output parameter value (e.g., duty cycle or peak current) = Y(n-1) + (1 ÷ τ) × [XY(n-1)], where Y(n-1) is the parameter value corresponding to the previous pulse parameter control strategy, and τ is the time constant (e.g., 1 ÷ τ = ...). X(n) represents the parameter value corresponding to the determined target pulse parameter control strategy.

[0084] S560, return to the step of smoothing the output parameter value based on the parameter value corresponding to the previous pulse parameter control strategy, the parameter value corresponding to the determined target pulse parameter control strategy, and the time constant, until the current output parameter value is the same as the parameter value corresponding to the determined target pulse parameter control strategy.

[0085] It is understandable that after calculating the current output parameter value, it is determined whether the current output parameter value is the same as the parameter value corresponding to the determined target pulse parameter control strategy. If they are not the same, the process can return to the step of smoothing the output parameter value based on the parameter value corresponding to the previous pulse parameter control strategy, the parameter value corresponding to the determined target pulse parameter control strategy, and the time constant; otherwise, it stops.

[0086] For example, suppose the welding process switches from a standard pulse parameter strategy to a heat dissipation enhancement strategy. The peak current of the standard pulse parameter strategy is 120A, the peak current of the heat dissipation enhancement strategy is 120A, the duty cycle of the standard pulse parameter strategy is 30%, and the duty cycle of the heat dissipation enhancement strategy is 20%. In the first pulse cycle after the switching occurs, the output duty cycle is 30% + (2 ÷ 3) × (20% - 30%) = 23.3%; in the second cycle, it is 23.3% + (2 ÷ 3) × (20% - 23.3%) = 21.1%; in the third cycle, it is 21.1% + (2 ÷ 3) × (20% - 21.1%) = 20.4%; in the fourth cycle, it is 20.4% + (2 ÷ 3) × (20% - 20.4%) = 20.1%; and in the fifth cycle, it is 20.1% + (2 ÷ 3) × (20% - 20.1%) = 20%. That is, the difference between the current output duty cycle of 20% and the output duty cycle of 20% corresponding to the determined target pulse parameter control strategy is less than the preset convergence threshold.

[0087] For example, suppose the welding process switches from a heat dissipation enhancement strategy to a burn-through emergency repair strategy. The peak current of the heat dissipation enhancement strategy is 120A, and the peak current of the burn-through emergency repair strategy is 90A. In the first pulse cycle after the switch, the peak current = 120 + (2 ÷ 3) × (90 - 120) = 100A; in the second cycle, the peak current = 100 + (2 ÷ 3) × (90 - 100) = 93A; in the third cycle, the peak current = 93 + (2 ÷ 3) × (90 - 93) = 91A; and in the fourth cycle, the peak current = 91 + (2 ÷ 3) × (90 - 91) = 90A. That is, the difference between the current peak current of 90A and the peak current of 90A corresponding to the determined target pulse parameter control strategy is less than the preset convergence threshold.

[0088] It should be noted that after the welding is completed with the current output parameter value, if the current output parameter value is different from the parameter value corresponding to the determined target pulse parameter control strategy, the process returns to the step of smoothing based on the parameter value corresponding to the previous pulse parameter control strategy, the parameter value corresponding to the determined target pulse parameter control strategy, and the time constant to obtain the current output parameter value. At this time, the current output parameter value calculated last time becomes the parameter value corresponding to the previous pulse parameter control strategy.

[0089] In one possible implementation, the welding control method for stainless steel pipe fittings also includes: The S600 collects the temperature rise rate at multiple feature points during the welding arc initiation and preheating stage.

[0090] It is understandable that the welding arc ignition and preheating stage is suitable for the period after the welding arc has ignited but before the welding torch has begun to move along the weld seam. During this stage, the welding torch remains stationary at the welding start position, the welding power source maintains the arc combustion at preset low power parameters, and the pipe rotates slowly at a preset low speed (e.g., 1 to 3 degrees per second) driven by a positioning device, allowing the pipe wall to sequentially pass through the arc's action area. During this process, the arc inputs heat to the pipe wall, and the wall temperature at each circumferential angle position gradually increases. Since the welding torch does not move, the arc heat input conditions are the same at each angle position; therefore, the difference in the rate of temperature rise at each position depends only on its own thermophysical properties and heat dissipation conditions. Areas with low thermal inertia rise faster, while areas with high thermal inertia rise slower. This stage is used to pre-determine the spatial distribution of thermal inertia throughout the pipe circumference by utilizing the difference in temperature rise rates at each position before formal welding, providing a basis for feedforward control in the subsequent formal welding stage.

[0091] Specifically, during the arc initiation and preheating stage of welding, infrared sensors are used to continuously collect temperature data of characteristic points at different angles along the entire circumference of the pipeline.

[0092] For example, the method for calculating the temperature rise rate can be as follows: at each circumferential angular position of the pipe, take temperature data at several sampling times (such as 10 to 20 sampling points) after the electric arc is applied to that position, perform linear fitting on the temperature-time curve, and the slope of the fitted line is the temperature rise rate at that position.

[0093] S700 generates a feedforward thermal inertia distribution map based on the relationship between the temperature rise rate of each feature point and a preset temperature rise threshold. This feedforward thermal inertia distribution map is used to mark areas on the pipe to be welded where there are differences in heat dissipation capacity.

[0094] It is understandable that the preset temperature rise threshold is a threshold value used to distinguish between high-risk and low-risk heat dissipation zones. The preset temperature rise threshold can be pre-calibrated and determined based on the thermophysical properties of the welding material and the target preheating temperature. The feedforward thermal inertia distribution diagram is a segmented marked diagram that varies with the circumferential angle θ (0°≤θ<360°) of the pipe. A temperature rise rate lower than the preset temperature rise threshold indicates that the thermal inertia is greater than the standard value, meaning that the material in that area is more difficult to heat.

[0095] For example, for the root pass welding of 304 stainless steel pipes, when the target preheating temperature during the arc initiation and preheating stage is set to 150°C, the temperature rise threshold can be set to 5°C / s. Areas with a temperature rise rate below 5°C / s are marked as high-risk heat dissipation zones, while areas with a temperature rise rate above 5°C / s are marked as low-risk zones. In the feedforward thermal inertia distribution diagram of the entire pipe circumference, each angular position is marked according to its corresponding risk level, forming a risk level curve distributed along the circumference of the pipe, i.e., the feedforward thermal inertia distribution diagram.

[0096] It should be noted that in this application, areas with a temperature rise rate lower than a preset temperature rise threshold are marked as high-risk heat dissipation zones. The physical meaning of this is as follows: a low temperature rise rate indicates a large thermal inertia in this area. During the actual welding process, when the arc moves from an adjacent thin-walled area to this thick-walled area, the cooling conditions change drastically due to the sudden change in wall thickness. This results in a significant difference in the cooling rates of the feature points on both sides, easily triggering a sudden increase in the spatial deviation index of thermal inertia, thereby triggering frequent switching of the control strategy. Therefore, a high-risk heat dissipation zone can be a risky area in the wall thickness transition region where the control system frequently responds due to sudden changes in cooling conditions. The purpose of switching to a heat dissipation enhancement strategy in advance in this area is to provide a soft transition of heat input for sudden changes in cooling conditions, reducing the probability of temperature anomalies caused by control lag.

[0097] In one possible implementation, S700 generates a feedforward thermal inertia distribution map based on the relationship between the temperature rise rate of each feature point and a preset temperature rise threshold, including: Regions with a temperature rise rate below a preset temperature rise threshold are marked as high-risk heat dissipation areas, while regions with a temperature rise rate above the preset temperature rise threshold are marked as low-risk areas, thus obtaining a feedforward thermal inertia distribution map. The preset temperature rise threshold is determined in advance based on the thermophysical properties of the welding material and the target preheating temperature.

[0098] It is understandable that the temperature rise rate is compared with the preset temperature rise threshold. Areas with a temperature rise rate lower than the preset temperature rise threshold are marked as high-risk heat dissipation areas, and areas with a temperature rise rate higher than the preset temperature rise threshold are marked as low-risk areas. Each angular position is marked according to its risk level to obtain the feedforward thermal inertia distribution map.

[0099] During the formal walking welding phase, the S800 triggers a pre-switching of the pulse parameter control strategy in advance based on the current position of the welding torch and the feedforward thermal inertia distribution map.

[0100] It is understandable that during the actual welding process, when the welding torch travels to the angle position marked as a high-risk heat dissipation zone in the feedforward thermal inertia distribution map, even if the thermal inertia spatial deviation index calculated in real time during the current pulse cycle has not exceeded the standard, the control strategy is switched from the standard pulse parameters to the heat dissipation enhancement strategy in advance to achieve the effect of early prevention.

[0101] Specifically, the real-time position information of the welding torch can be obtained through an angle encoder mounted on the pipe rotation mechanism. By outputting the rotation angle of the pipe in real time through the angle encoder, and combining it with the fixed position of the welding torch, the angular position of the current welding point in the circumferential direction of the pipe can be determined.

[0102] For example, during circumferential welding of a pipe, when the electric arc moves from the thin-walled region (low thermal inertia) to the transition region of the thick-walled region (high thermal inertia), the cooling rate deviation increases sharply due to the significant difference in cooling rates on both sides, leading to a sudden increase in the thermal inertia spatial deviation index. If strategy switching relies solely on feedback from the real-time thermal inertia spatial deviation index, the control system response is lag-dependent. For instance, there is at least a delay of one pulse cycle between the thermal inertia spatial deviation index exceeding the limit and the actual effectiveness of the strategy parameters. During this delay, the thin-walled side may experience temperature exceeding the safety threshold due to heat accumulation. By pre-triggering the pulse parameter control strategy switch in advance, the degree of local heat accumulation can be reduced, providing a soft transition of heat input to the transition region with abrupt changes in cooling capacity, thus avoiding local temperature anomalies caused by control lag.

[0103] It should be noted that if the system is already in heat dissipation enhancement strategy or burn-through emergency strategy (triggered by real-time thermal inertia spatial deviation index feedback) when the welding torch enters the high-risk heat dissipation zone, the feedforward pre-switching will not be executed, and the current control strategy will remain unchanged to avoid a reduction in strategy level. If the welding torch leaves the high-risk heat dissipation zone and enters the low-risk zone, and the real-time thermal inertia spatial deviation index has fallen below the first threshold and remained below it for more than 3 pulse cycles, the system will automatically revert from the heat dissipation enhancement strategy to the standard pulse parameter strategy, restoring normal heat input and ensuring that the low-risk zone receives sufficient welding heat.

[0104] In one possible implementation, S800, during the formal walking welding phase, triggers a pre-switching of the pulse parameter control strategy based on the current position of the welding torch and the feedforward thermal inertia distribution map, including: During the formal walking welding phase, when the welding torch is located at an angle marked as a high-risk heat dissipation zone in the feedforward thermal inertia distribution map, the current pulse parameter control strategy is switched to the heat dissipation enhancement strategy in advance, regardless of whether the current real-time thermal inertia spatial deviation index triggers a strategy switch.

[0105] Specifically, during the formal welding process, when the welding torch travels to the angle position marked as a high-risk heat dissipation zone in the feedforward thermal inertia distribution map, even if the thermal inertia spatial deviation index calculated in real time during the current pulse cycle has not exceeded the standard, the control strategy is switched from the standard pulse parameters to the heat dissipation enhancement strategy in advance.

[0106] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0107] Corresponding to the stainless steel pipe fitting welding control method described in the above embodiments, this application also provides a stainless steel pipe fitting welding control system, in which each unit can realize each step of the stainless steel pipe fitting welding control method. Figure 5 A structural block diagram of the stainless steel pipe fitting welding control system provided in the embodiments of this application is shown. For ease of explanation, only the parts related to the embodiments of this application are shown.

[0108] Reference Figure 5 The stainless steel pipe fitting welding control system includes: The extraction unit is used to extract the time-series temperature data of multiple feature points in the target welding area based on the infrared temperature distribution data acquired in real time during the welding process. The target welding area is the molten pool and the heat-affected zone adjacent to the molten pool under the action of the welding torch arc.

[0109] The determination unit is used to determine the cooling rate corresponding to each feature point based on the temperature time series data within each base period of pulse welding. The cooling rate reflects the transient cooling capacity of each feature point within the base period of pulse welding.

[0110] The calculation unit is used to obtain the cooling rate deviation of each feature point based on the absolute difference between the cooling rate of each feature point and the average cooling rate of all feature points. The cooling rate deviation reflects the magnitude of the difference between the cooling rate of a feature point and the overall average level.

[0111] The analysis unit is used to count the number of abnormal feature points whose cooling rate deviation exceeds a preset deviation threshold, and to obtain the thermal inertia spatial deviation index based on the cooling rate deviation of each feature point, the preset position weight of the feature point, and the number of abnormal feature points.

[0112] The control unit is used to switch between multiple preset pulse parameter control strategies based on the threshold range of the thermal inertia spatial deviation index, so as to adaptively adjust the welding heat input.

[0113] It should be noted that the information interaction and execution process between the above systems / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0114] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units is merely an example. In practical applications, the above functions can be assigned to different functional units as needed, that is, the internal structure of the system can be divided into different functional units to complete all or part of the functions described above. The functional units in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0115] This application also provides a welding apparatus. Figure 6 This is a schematic diagram of the control device of a welding apparatus provided in one embodiment of this application. Figure 6 As shown, the control device 6 in this embodiment includes: at least one processor 60 ( Figure 6 Only one is shown in the image), at least one memory 61 ( Figure 6 (Only one is shown in the image) and a computer program 62 stored in the at least one memory 61 and executable on the at least one processor 60, wherein when the processor 60 executes the computer program 62, it causes the control device 6 to perform the steps in any of the above embodiments of the stainless steel pipe fitting welding control method, or causes the control device 6 to perform the functions of each unit in the above embodiments of the system.

[0116] For example, the computer program 62 may be divided into one or more units, which are stored in the memory 61 and executed by the processor 60 to complete this application. The one or more units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program 62 in the control device 6.

[0117] The welding apparatus may include a pulsed TIG welding machine for providing a controllable pulsed welding current, and with built-in or external current and voltage sensors to acquire welding electrical parameters in real time; a traveling device (e.g., a track-type or magnetically attached automatic traveling trolley for carrying the welding torch at a constant speed along the circumference or axial direction of the pipe, and with built-in or external position sensors to acquire the current position of the welding torch in real time); a positioning device (e.g., a roller frame or turntable for clamping and driving the pipe to be welded to rotate at a preset speed); an infrared sensing device (e.g., for acquiring temperature distribution data of the welding area in real time); and a control device 6, etc. The control device 6 may include, but is not limited to, a processor 60 and a memory 61. Those skilled in the art will understand that… Figure 6 This is merely an example of control device 6 and does not constitute a limitation on control device 6. It may include more or fewer components than shown, or combine certain components, or different components, such as input / output devices, network access devices, buses, etc.

[0118] The processor 60 can be a Central Processing Unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0119] In some embodiments, the memory 61 may be an internal storage unit of the control device 6, such as a hard disk or memory of the control device 6. In other embodiments, the memory 61 may be an external storage device of the control device 6, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the control device 6. Furthermore, the memory 61 may include both internal storage units and external storage devices of the control device 6. The memory 61 is used to store operating systems, applications, bootloaders, data, and other programs, such as the program code of computer programs. The memory 61 can also be used to temporarily store data that has been output or will be output.

[0120] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in any of the above method embodiments.

[0121] This application provides a computer program product that, when run on a welding apparatus, causes the welding apparatus to perform the steps in any of the above-described method embodiments.

[0122] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying the computer program code to the welding apparatus, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, such as a USB flash drive, a portable hard drive, a magnetic disk, or an optical disk.

[0123] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0124] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0125] In the embodiments provided in this application, it should be understood that the disclosed welding apparatus / stainless steel pipe fitting welding control system and stainless steel pipe fitting welding control method can be implemented in other ways. For example, the welding apparatus / stainless steel pipe fitting welding control system embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling or direct coupling or communication connection may be through some interfaces, indirect coupling or communication connection of devices or units, and may be electrical, mechanical, or other forms.

[0126] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0127] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A welding control method for stainless steel pipe fittings, characterized in that, The method includes: Based on the infrared temperature distribution data collected in real time during the welding process, temperature time-series data of multiple feature points in the target welding area are extracted; wherein, the target welding area is the molten pool and the heat-affected zone adjacent to the molten pool under the action of the welding torch arc. Based on the temperature time series data within each base period of pulse welding, the cooling rate corresponding to each feature point is determined; wherein, the cooling rate is used to reflect the transient cooling capacity of each feature point within the base period of pulse welding. The cooling rate deviation of each feature point is obtained based on the absolute difference between the cooling rate of each feature point and the average cooling rate of all feature points; wherein, the cooling rate deviation is used to reflect the magnitude of the difference between the cooling rate of the feature point and the overall average level. The number of abnormal feature points whose cooling rate deviation exceeds a preset deviation threshold is counted, and the thermal inertia spatial deviation index is obtained based on the cooling rate deviation of each feature point, the preset position weight corresponding to the feature point, and the number of abnormal feature points. Based on the threshold range of the thermal inertia spatial deviation index, the system switches between multiple preset pulse parameter control strategies to adaptively adjust the welding heat input.

2. The welding control method for stainless steel pipe fittings as described in claim 1, characterized in that, The determination of the cooling rate corresponding to each feature point based on the temperature time series data within each base period of pulse welding includes: Temperature values ​​of each characteristic point were collected at the start and end times of the pulse welding baseline period, and the temperature difference of the same characteristic point within the baseline period was calculated. The cooling rate of each feature point is determined based on the ratio of the temperature difference to the duration of the baseline period.

3. The welding control method for stainless steel pipe fittings as described in claim 1, characterized in that, The step of switching between multiple preset pulse parameter control strategies based on the threshold range of the thermal inertia spatial deviation index includes: When the thermal inertia spatial deviation index is lower than or equal to the first threshold, the standard pulse parameter strategy is executed. When the thermal inertia spatial deviation index is higher than the first threshold and lower than or equal to the second threshold, a heat dissipation enhancement strategy is executed. When the thermal inertia spatial deviation index is higher than the second threshold, a burn-through emergency strategy is executed to reduce the pulse frequency.

4. The welding control method for stainless steel pipe fittings as described in claim 1, characterized in that, After switching between multiple preset pulse parameter control strategies within the threshold range based on the thermal inertia spatial deviation index to adaptively adjust the welding heat input, the method further includes: When switching between multiple preset pulse parameter control strategies, the parameter values ​​corresponding to the previous pulse parameter control strategy and the parameter values ​​corresponding to the determined target pulse parameter control strategy are obtained. Based on the parameter values ​​corresponding to the previous pulse parameter control strategy, the parameter values ​​corresponding to the determined target pulse parameter control strategy, and the time constant, smoothing is performed to obtain the current output parameter values; Return to the step of performing smoothing processing based on the parameter values ​​corresponding to the previous pulse parameter control strategy, the parameter values ​​corresponding to the determined target pulse parameter control strategy, and the time constant to obtain the current output parameter value, until the current output parameter value is the same as the parameter value corresponding to the determined target pulse parameter control strategy.

5. The welding control method for stainless steel pipe fittings as described in claim 1, characterized in that, The method further includes: During the welding arc initiation and preheating stage, the temperature rise rate of multiple characteristic points was collected. Based on the relationship between the temperature rise rate of each feature point and the preset temperature rise threshold, a feedforward thermal inertia distribution map is generated; wherein, the feedforward thermal inertia distribution map is used to mark the areas on the pipe to be welded where there are differences in heat dissipation capacity. During the formal walking welding phase, based on the current position of the welding torch and the feedforward thermal inertia distribution map, the pulse parameter control strategy is pre-switched in advance.

6. The welding control method for stainless steel pipe fittings as described in claim 5, characterized in that, The relationship between the temperature rise rate of each feature point and the preset temperature rise threshold is used to generate a feedforward thermal inertia distribution map, including: Regions with a temperature rise rate lower than a preset temperature rise threshold are marked as high-risk heat dissipation areas, and regions with a temperature rise rate higher than the preset temperature rise threshold are marked as low-risk areas, in order to obtain the feedforward thermal inertia distribution map; wherein, the preset temperature rise threshold is determined in advance based on the thermophysical properties of the welding material and the preheating target temperature.

7. The welding control method for stainless steel pipe fittings as described in claim 6, characterized in that, During the formal walking welding phase, based on the current position of the welding torch and the feedforward thermal inertia distribution map, the pre-switching of the pulse parameter control strategy is triggered in advance, including: During the formal walking welding phase, when the welding torch is located at an angle marked as a high-risk heat dissipation zone in the feedforward thermal inertia distribution map, the current pulse parameter control strategy is switched to the heat dissipation enhancement strategy in advance, regardless of whether the current real-time thermal inertia spatial deviation index triggers a strategy switch.

8. The welding control method for stainless steel pipe fittings as described in claim 1, characterized in that, The pulse welding is a welding method in which the welding current alternates periodically between the peak current and the base current according to a preset pulse frequency; wherein, a pulse cycle consists of a time period corresponding to a peak current and a time period corresponding to a base current; the pulse cycle includes two stages: a peak period and a base period; wherein, the peak period is the time period during which the welding current is maintained at the peak current; the base period is the time period during which the welding current switches from the peak current to the base current.

9. A welding control system for stainless steel pipe fittings, characterized in that, An application to a welding apparatus for implementing the stainless steel pipe fitting welding control method as described in any one of claims 1 to 8, wherein the stainless steel pipe fitting welding control system comprises: The extraction unit is used to extract the temperature time series data of multiple feature points in the target welding area based on the infrared temperature distribution data collected in real time during the welding process; wherein, the target welding area is the molten pool under the action of the welding torch arc and the heat-affected zone adjacent to the molten pool. The determining unit is used to determine the cooling rate corresponding to each feature point based on the temperature time series data within each base period of pulse welding; wherein the cooling rate is used to reflect the transient cooling capacity of each feature point within the base period of pulse welding. The calculation unit is used to obtain the cooling rate deviation of each feature point based on the absolute difference between the cooling rate of each feature point and the average cooling rate of all feature points; wherein, the cooling rate deviation is used to reflect the magnitude of the difference between the cooling rate of the feature point and the overall average level; The analysis unit is used to count the number of abnormal feature points where the cooling rate deviation exceeds a preset deviation threshold, and to obtain the thermal inertia spatial deviation index based on the cooling rate deviation of each feature point, the preset position weight corresponding to the feature point, and the number of abnormal feature points. The control unit is used to switch between multiple preset pulse parameter control strategies based on the threshold range of the thermal inertia spatial deviation index, so as to adaptively adjust the welding heat input.

10. A welding apparatus, characterized in that, The method includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the method as claimed in any one of claims 1 to 8.

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