A welding apparatus and welding method for the production of anti-clogging slag discharge gate valves.

Abstract

This invention discloses a welding device and welding method for the production of anti-clogging slag discharge gate valves, belonging to the field of automated welding technology. It includes a welding base with a valve body clamping platform on its central surface. The valve body clamping platform includes floating grippers that move towards or away from each other along parallel linear guide rails. A contact temperature sensor is embedded in the inner contact surface of the floating grippers. A gantry-type moving frame is installed above the welding base. The gantry-type moving frame includes a crossbeam that moves along a first direction set by the welding base, a welding head slide mounted on the crossbeam and moving along the length of the crossbeam in a second direction, and a lifting electric cylinder vertically mounted on the welding head slide for vertical lifting. This invention ensures that the welding torch is always precisely aligned with the weld center.

Description

Technical Field

[0001] This invention relates to the field of automated welding, specifically to a welding apparatus and welding method for the production of anti-clogging slag discharge gate valves. Background Technology

[0002] Welding technology is mainly used to solve the problem of unstable welding quality in the production of anti-clogging slag discharge gate valves, which is caused by factors such as complex workpiece structure, uneven heat capacity distribution and heat-induced deformation. Traditional welding methods or simple programming automation are difficult to adapt to these complexities, resulting in uneven weld penetration and poor dimensional accuracy, which affects the performance and consistency of the product.

[0003] These problems mainly stem from a lack of dynamic, multi-dimensional welding process control, specifically:

[0004] Inaccurate initial path: Traditional methods rely on a preset welding path, but the actual workpiece may have a positional deviation after clamping, which makes it impossible for the welding path to be precisely aligned with the weld.

[0005] Energy control lag: During welding, the heat capacity characteristics vary greatly across different parts of the workpiece. Traditional methods mainly rely on static parameters or single feedback, which cannot make real-time, forward-looking energy adjustments based on weld thickness or molten pool condition. This can easily lead to insufficient penetration in thick-walled areas and burn-through in thin-walled areas.

[0006] Unpredictable and uncompensated thermal deformation: The localized high temperatures generated during welding can cause unpredictable deformation of the entire workpiece. Traditional methods lack the ability to monitor and actively compensate for this deformation trend in real time, making it difficult to guarantee the dimensional accuracy of the final product.

[0007] The information disclosed in the background section above is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0008] The purpose of this invention is to provide a welding device and welding method for the production of anti-clogging slag discharge gate valves, so as to solve the problems mentioned in the background art.

[0009] The technical solution of the present invention includes:

[0010] A welding base, wherein a valve body clamping platform is provided on the central surface of the welding base, the valve body clamping platform includes floating jaws that move toward or away from each other along parallel linear guide rails, and a contact temperature sensor is embedded in the inner contact surface of the floating jaws.

[0011] A gantry-type mobile frame is installed above the welding base. The gantry-type mobile frame includes a crossbeam that moves along a first direction set by the welding base, a welding head slide mounted on the crossbeam and moving along the length of the crossbeam in a second direction, and a lifting electric cylinder vertically mounted on the welding head slide for vertical lifting.

[0012] A welding head is connected to the telescopic end of the lifting electric cylinder. The welding head includes a welding torch, a monocular vision camera, and an arc signal acquisition device. The optical axis of the lens of the monocular vision camera forms a fixed forward angle with the axis of the welding torch to align with the area to be welded in front of the welding torch. The arc signal acquisition device is connected in parallel to the output circuit of the welding power supply.

[0013] The controller is used to control the movement of the gantry-type moving frame and to receive and process signals from the contact temperature sensor, the monocular vision camera and the arc signal acquisition device.

[0014] Preferably, each set of floating grippers on the valve body clamping platform is driven by a stepper motor via a ball screw to move in translational motion along the linear guide.

[0015] Preferably, the monocular vision camera is provided with a metal protective shell, and a splash-proof quartz glass is provided in front of its lens.

[0016] Preferably, the system also includes a cable drag chain system, which comprises a main drag chain that moves with the crossbeam and a secondary drag chain that moves with the welding head slide, for guiding and protecting the cables and conduits required for the welding head.

[0017] A welding method for manufacturing anti-clogging slag discharge gate valves includes:

[0018] An initial welding reference is obtained, which includes an initial spatial path point sequence generated by scanning the weld seam to be welded using the monocular vision camera, and a forward-looking heat capacity coefficient sequence calculated for the path points in the initial spatial path point sequence based on pre-stored valve body structure data.

[0019] To perform forward path correction, during the welding process, the controller continuously drives the monocular vision camera to acquire pre-welding image features of the area to be welded in front of the welding torch. The pre-welding image features include weld lateral deviation and weld gap width. The controller adjusts the movement of the gantry moving frame in real time according to the weld lateral deviation.

[0020] The controller performs a composite energy correction by acquiring the real-time arc characteristics of the arc signal acquisition device, calculating the weld depth state evaluation value through a multi-dimensional response model based on the weld gap width and the real-time arc characteristics, and generating a final welding energy correction command to adjust the welding parameters by combining the forward-looking heat capacity coefficient corresponding to the current position.

[0021] To perform thermal deformation attitude compensation, the controller collects valve body temperature distribution data from the contact temperature sensor, determines the thermal deformation trend based on the valve body temperature distribution data using a thermodynamic difference model, and generates path attitude compensation commands to adjust the height of the lifting electric cylinder or the planar movement of the gantry-type moving frame.

[0022] Preferably, the calculation of the forward thermal coefficient includes: delineating a spherical influence region centered on the path point, statistically analyzing the local material volume and heat dissipation surface area within the region, calculating the ratio of the local material volume to the heat dissipation surface area, and comparing this ratio with a preset benchmark ratio to obtain the forward thermal coefficient.

[0023] Preferably, the generation of the final welding energy correction command includes: calculating the initial adjustment amount of welding energy based on the penetration depth assessment value, and then multiplying the initial adjustment amount of welding energy by the forward-looking heat capacity coefficient.

[0024] Preferably, the determination of the thermal deformation trend includes: continuously calculating the difference value and the rate of change over time between the readings of each contact temperature sensor, and combining the total historical welding energy input as a weighting factor to comprehensively output a direction vector describing the deformation trend of the valve body.

[0025] Preferably, the multidimensional response model is established based on a database containing the correspondence between different weld gap widths, arc voltage fluctuation characteristics, and arc current and measured weld depth.

[0026] This invention provides an improved welding apparatus and welding method for the production of anti-clogging slag discharge gate valves, which has the following improvements and advantages compared with the prior art:

[0027] 1. This solution uses a monocular vision camera to scan the weld seam to be welded and generates an initial spatial path point sequence that fits the actual workpiece. This effectively overcomes the path deviation problem caused by workpiece clamping error. During the welding process, the system continuously uses the monocular vision camera to obtain the lateral deviation of the weld seam and adjusts the movement of the gantry moving frame in real time to ensure that the welding torch is always accurately aligned with the center of the weld seam. This is the key to ensuring the fusion quality.

[0028] 2. This solution addresses welding problems caused by uneven heat capacity distribution in the workpiece through an innovative composite energy correction method. When acquiring the initial welding path, the system calculates a sequence of forward-looking heat capacity coefficients for each point on the path based on pre-stored valve body structure data. This coefficient, obtained by calculating the ratio of local material volume to heat dissipation surface area, quantifies the heat accumulation capacity at different locations, thus predicting the thermophysical characteristics of each point. During welding, the system combines the weld gap width provided by a monocular vision camera and the real-time arc characteristics from the arc signal acquisition device, using a multi-dimensional response model to estimate the current weld depth. The final welding energy correction command multiplies this real-time weld depth assessment value with the forward-looking heat capacity coefficient. This allows energy adjustment to not only respond to the current molten pool state but also anticipate and adapt to changes in the material's heat capacity. For example, in thicker areas, even if the weld depth assessment value is normal, this multiplication operation will maintain or even amplify the energy increase to ensure sufficient weld depth; while in thinner areas, the energy increase is weakened to prevent burn-through.

[0029] 3. This solution continuously collects temperature data at different locations on the valve body using contact temperature sensors and uses a thermodynamic differential model to determine the thermal deformation trend of the valve body. This model calculates the difference between the readings of each sensor and its rate of change over time, and combines the total historical welding energy input as a weighting factor to output a direction vector describing the direction and degree of valve body deformation. Based on this trend, the controller generates path attitude compensation commands to fine-tune the height of the lifting electric cylinder or the planar position of the gantry moving frame, actively counteracting and suppressing the thermal deformation of the workpiece. This ensures that the entire welding process is completed in a relatively stable attitude, significantly improving the dimensional accuracy of the final product.

[0030] 4. The monocular vision camera in this solution is equipped with a metal protective shell and splash-proof quartz glass, which ensures the reliability and durability of the vision system. In addition, the cable drag chain system is used to guide and protect the moving cables and pipes, avoiding tangling and excessive bending, and ensuring that the equipment can operate without failure for a long time. Attached Figure Description

[0031] The present invention will be further explained below with reference to the accompanying drawings and embodiments:

[0032] Figure 1 This is a schematic diagram of the overall structure of the device;

[0033] Figure 2 This is a schematic diagram of the welding base structure;

[0034] Figure 3 This is a schematic diagram of the connection structure of the crossbeam and the weld joint;

[0035] Figure 4 This is a schematic diagram of the process flow of the method of the present invention;

[0036] In the diagram: 100, welding base; 110, valve body clamping platform; 120, contact temperature sensor; 200, gantry-type moving frame; 210, crossbeam; 220, welding head slide; 230, lifting electric cylinder; 300, welding head; 310, welding torch; 320, monocular vision camera; 330, arc signal acquisition device. Detailed Implementation

[0037] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments. Example 1

[0038] Please see Figure 1-3 This invention provides a welding apparatus for the production of anti-clogging slag discharge gate valves, comprising:

[0039] A welding base 100 is provided with a valve body clamping platform 110 on its central surface. The valve body clamping platform 110 includes floating grippers that move towards or away from each other along a parallel linear guide rail. A contact temperature sensor 120 is embedded in the inner contact surface of the floating grippers.

[0040] A gantry-type mobile frame 200 is installed above the welding base 100. The gantry-type mobile frame 200 includes a crossbeam 210 that moves along a first direction set by the welding base 100, a welding head slide 220 that is installed on the crossbeam 210 and moves along the length of the crossbeam 210 in a second direction, and a lifting electric cylinder 230 that is vertically installed on the welding head slide 220 for vertical lifting.

[0041] The welding head 300 is connected to the telescopic end of the lifting electric cylinder 230. The welding head 300 includes a welding torch 310, a monocular vision camera 320 and an arc signal acquisition device 330. The optical axis of the lens of the monocular vision camera 320 forms a fixed forward angle with the axis of the welding torch 310 to align with the area to be welded in front of the welding torch 310. The arc signal acquisition device 330 is connected in parallel to the output circuit of the welding power supply.

[0042] The controller is used to control the movement of the gantry moving frame 200 and to receive and process signals from the contact temperature sensor 120, the monocular vision camera 320 and the arc signal acquisition unit 330.

[0043] In one embodiment of the present invention, for workpieces with complex structures and irregular heat capacity distribution, such as anti-clogging gate valves, traditional manual welding or simple programmed welding is difficult to guarantee consistent quality. This embodiment provides a welding device for the production of anti-clogging gate valves, which addresses this problem through an integrated mechanical and sensing structure. The welding base 100 provides a stable working platform for the entire welding process, which is the foundation for achieving precision machining. The valve body clamping table 110, through its floating jaws, can adapt to the shape of valve bodies of different specifications and clamp them securely. The contact temperature sensors 120 embedded in the floating jaws, such as four PT100 platinum resistance temperature sensors, are used to acquire the temperature distribution information of the valve body during the welding process, providing data input for subsequent thermal deformation control. The gantry-type moving frame 200 drives the welding head 300 to move in three-dimensional space through the combined movement of its crossbeam 210, welding head slide 220, and lifting electric cylinder 230, so as to accurately follow the complex weld trajectory on the valve body. The welding head 300 integrates the welding torch for performing welding. 310. A monocular vision camera 320 for observing the condition of the weld seam ahead in advance, such as a Hikvision MV-CA050-11GM / GC model camera, and an arc signal acquisition device 330 for real-time monitoring of electrical signals during the welding process; a controller, such as a Siemens S7-1500 series PLC, serves as the core to coordinate the movement of the gantry-type moving frame 200 and integrate and process multi-source information from the contact temperature sensor 120, the monocular vision camera 320, and the arc signal acquisition device 330, so that the entire welding process can be dynamically adjusted according to real-time feedback, thereby improving the stability of welding quality.

[0044] Each set of floating grippers on the valve body clamping stage 110 is driven by a stepper motor via a ball screw to move along a linear guide.

[0045] The floating grippers on the valve body clamping stage 110 employ stepper motors, or, for example, the MOONSAM24HS series from MOONS, ball screw drives. This design aims to achieve precise control of the clamping process; the stepper motor receives pulse signals from the controller and rotates at precise angles, while the ball screw efficiently converts the rotational motion into linear motion. This combination allows the movement distance of the floating grippers and the applied clamping force to be quantified and repeated, ensuring that valve bodies from different batches can be welded under the same clamping conditions, thus providing a prerequisite for ensuring consistent welding paths.

[0046] The monocular vision camera 320 is equipped with a metal protective shell, and its lens is protected by a splash-proof quartz glass.

[0047] The monocular vision camera 320 operates in an environment with high temperatures, electric arc light, and metal spatter. To ensure its long-term stable operation, the monocular vision camera 320's external metal protective shell is typically made of aluminum alloy and equipped with heat sinks to effectively dissipate the heat generated during camera operation and radiant heat from the environment. The anti-splash quartz glass in front of the lens utilizes the excellent light transmittance and physical properties of quartz glass, such as high temperature resistance and thermal shock resistance, to effectively prevent molten metal spatter generated during welding from directly damaging the lens without affecting image quality, thus ensuring the reliability and durability of the vision system.

[0048] It also includes a cable drag chain system, which includes a main drag chain that moves with the crossbeam 210 and a secondary drag chain that moves with the welding head slide 220, for guiding and protecting the cables and conduits required for the welding head 300.

[0049] The welding head 300 requires multiple cables during operation, such as camera data cables, sensor signal cables, welding torch cables, and conduits, including protective gas tubing, which move accordingly. The cable drag chain system, through the structural design of the main drag chain and auxiliary drag chains, accommodates the movement of the crossbeam 210 in the first direction and the welding head slide 220 in the second direction, respectively. This system houses all cables and conduits within a defined bending radius, preventing entanglement, excessive bending, or interference with other equipment components during three-dimensional movement. This ensures the continuity and stability of signal and energy transmission, providing essential support for the equipment to operate trouble-free for extended periods. Example 2

[0050] Please see Figure 4 A welding method for manufacturing anti-clogging slag discharge gate valves, comprising:

[0051] The initial welding reference is obtained, which includes an initial spatial path point sequence generated by scanning the weld seam to be welded by a monocular vision camera 320, and a forward-looking heat capacity coefficient sequence calculated for the path points in the initial spatial path point sequence based on the pre-stored valve body structure data.

[0052] To perform forward-looking path correction, during the welding process, the controller continuously drives the monocular vision camera 320 to acquire pre-welding image features of the area to be welded in front of the welding torch 310. The pre-welding image features include the weld lateral deviation and the weld gap width. The controller adjusts the movement of the gantry moving frame 200 in real time according to the weld lateral deviation.

[0053] The controller performs composite energy correction by acquiring the real-time arc characteristics of the arc signal acquisition device 330. Based on the weld gap width and the real-time arc characteristics, it calculates the weld depth state evaluation value through a multi-dimensional response model and combines it with the forward-looking heat capacity coefficient corresponding to the current position to generate the final welding energy correction command to adjust the welding parameters.

[0054] To perform thermal deformation attitude compensation, the controller collects valve body temperature distribution data from the contact temperature sensor 120, determines the thermal deformation trend based on the valve body temperature distribution data through a thermodynamic difference model, and generates path attitude compensation commands to adjust the height of the lifting electric cylinder 230 or the planar movement of the gantry moving frame 200.

[0055] The purpose of this model is to determine the thermal deformation trend of the valve body due to uneven heating by analyzing real-time temperature data during the welding process, and to quantify it into a command that can be used for attitude compensation. The model characterizes the physical causal relationship between heat input leading to uneven temperature distribution, which in turn causes thermal expansion and contraction of materials. It receives real-time temperature readings from multiple contact temperature sensors 120 and continuously calculates the difference values ​​and time change rates between them. It combines the total historical welding energy input as a weighting factor and outputs a direction vector describing the deformation trend of the valve body.

[0056] This value is a dynamic quantitative indicator used to assess in real time whether the depth of the weld pool has reached the expected fusion requirements. It establishes a correlation between externally measurable signals, such as weld gap width and real-time arc characteristics, and the internally difficult-to-measure melt depth state, providing a core basis for real-time adjustment of welding energy.

[0057] The method provided in this embodiment aims to solve multiple problems caused by workpiece differences, geometric complexity, and thermal deformation in valve body welding. It obtains an initial welding reference step by scanning the actual weld seam using a monocular vision camera 320, generating an initial spatial path point sequence that fits the current workpiece's actual state. This overcomes path deviations caused by workpiece clamping errors. Simultaneously, a forward-looking heat capacity coefficient sequence calculated based on pre-stored valve body structure data marks each point on the path with its heat absorption and dissipation characteristics, enabling welding control to predict material physical properties. The forward-looking path correction step involves observing the path ahead in advance using the monocular vision camera 320 during welding to obtain the weld seam's lateral deviation and gap width. The controller fine-tunes the movement of the gantry-type moving frame 200 in real time based on the lateral deviation, ensuring that the welding torch 310 is always precisely aligned with the weld seam center, which is fundamental to guaranteeing fusion quality. The composite energy correction step combines geometric information such as the weld gap width from the monocular vision camera 320 and physical process information such as the real-time arc characteristics from the arc signal acquisition device 330. The controller calculates the weld depth assessment value through a multi-dimensional response model and then generates the final welding energy correction command by combining the forward-looking heat capacity coefficient of the current point. The purpose of this is to ensure that the adjustment of welding energy not only responds to the current molten pool state but also anticipates the heat capacity characteristics of the material itself, thereby increasing energy in thick-walled areas to ensure weld depth and reducing energy in thin-walled areas to prevent burn-through. The thermal deformation posture compensation step is then executed. Using the valve body temperature distribution data collected by the contact temperature sensor 120, the controller uses a thermodynamic difference model to determine the overall deformation trend of the valve body caused by uneven heating. Based on this trend, the controller generates a path posture compensation command to fine-tune the height of the lifting electric cylinder 230 or the planar position of the gantry moving frame 200. The purpose is to actively counteract and suppress the thermal deformation of the workpiece, ensuring that the entire welding process is completed in a relatively stable posture, thereby improving the dimensional accuracy of the final product.

[0058] The calculation of the forward thermal coefficient includes: delineating a spherical influence region centered on the path point, statistically analyzing the local material volume and heat dissipation surface area within the region, calculating the ratio of the local material volume to the heat dissipation surface area, and comparing this ratio with a preset benchmark ratio to obtain the forward thermal coefficient.

[0059] This coefficient is a quantitative predictive indicator used to characterize the heat accumulation and dissipation characteristics at various points along the weld path during welding. It is derived by comparing and converting the ratio of the local material volume to the heat dissipation surface area at a specific location with a pre-calculated baseline ratio. This baseline ratio represents ideal and uniform heat capacity characteristics. As a basis for feedforward control, this coefficient allows the adjustment of welding parameters to anticipate changes in material properties in advance.

[0060] The purpose of calculating the forward-looking thermal capacity coefficient is to quantify the thermophysical properties of each point along the weld path in a simplified way. For a given point on the path, the controller delineates a fixed spherical influence region centered on that point in the pre-stored 3D structural data of the valve body. In the example, the radius of the spherical influence region can be set to 2 to 5 times the average wall thickness of the area to be welded, balancing calculation accuracy and efficiency when calculating local thermal capacity characteristics. The controller then calculates the total volume of material contained within this spherical region, as well as the surface area of ​​these materials in contact with the outside. The ratio of the local material volume to the heat dissipation surface area intuitively reflects the heat accumulation capacity at that location: a large ratio means that there is more material volume per unit heat dissipation area, and heat is not easily dissipated, such as in thick-walled areas; conversely, heat is easily dissipated, such as in thin-walled flanges. This ratio is compared and converted with the benchmark ratio calculated from the standard wall thickness area of ​​the valve body, ultimately yielding a standardized forward-looking thermal capacity coefficient, providing a quantitative and physically meaningful adjustment basis for subsequent energy correction.

[0061] The generation of the final welding energy correction command includes: calculating the initial adjustment amount of welding energy based on the penetration depth assessment value, and then multiplying the initial adjustment amount of welding energy by the forward thermal coefficient.

[0062] The final welding energy correction command generation process embodies a control concept combining real-time feedback and feedforward prediction. The controller calculates the initial welding energy adjustment based on the weld penetration assessment value derived from the multi-dimensional response model. This is a reactive adjustment based on the current welding state. For example, if the assessment value indicates a shallow weld penetration, the initial adjustment is positive. The controller multiplies this initial adjustment by the forward-looking heat capacity coefficient corresponding to the current position of the welding head 300. The purpose of this multiplication is to adjust the reactive adjustment using the pre-calculated heat capacity coefficient. When the welding head 300 reaches a thin-walled region with a heat capacity coefficient less than 1, even if the weld penetration is shallow, the energy increase will be weakened, thus avoiding burn-through due to overheating. Conversely, in a thick-walled region with a heat capacity coefficient greater than 1, the energy increase will be maintained or even amplified to ensure sufficient weld penetration.

[0063] The determination of thermal deformation trend includes: continuously calculating the difference and rate of change over time between the 120°C readings of each contact temperature sensor, and combining the total historical welding energy input as a weighting factor to comprehensively output a direction vector describing the deformation trend of the valve body.

[0064] The determination of thermal deformation trends is not based on complex finite element analysis, but rather on the analysis of real-time temperature data. The controller continuously collects readings from multiple contact temperature sensors 120 and calculates the differences between them and the rate of change of these differences over time. For example, if the temperature of the sensor on the left side of the valve body is consistently higher than that on the right side, and the temperature difference continues to increase, the model determines that there is a tendency for bending to the right. At the same time, the total historical welding energy input is used as a weighting factor. This is significant because as welding progresses, the overall temperature of the workpiece rises, and even small local temperature unevenness can lead to more significant deformation. The controller integrates this information and outputs a vector that describes the current main deformation direction and degree of the valve body, providing a clear command direction for subsequent attitude compensation.

[0065] In this example, the direction vector can be calculated using the following exemplary formula:

[0066]

[0067] in:

[0068] It is a feature vector describing the thermal deformation trend of the valve body. Its direction indicates the main trend of deformation, and its modulus characterizes the rate and intensity of the thermal deformation trend. The controller generates the final physical position compensation command based on this vector.

[0069] It is a weighting factor that is positively correlated with the total historical welding energy input;

[0070] It is the first Current reading of contact temperature sensor 120;

[0071] It is a reference temperature, such as the ambient temperature before welding or the average temperature of all sensors;

[0072] It is the first Rate of change of sensor readings over time;

[0073] and It is preset, and the first The unit direction vector related to the physical location of each sensor is used to represent the direction of the contribution of temperature difference and temperature change rate to the overall deformation trend.

[0074] This is the total number of contact temperature sensors 120;

[0075] It is a unit with a reciprocal time, for example, Scale factor;

[0076] The multidimensional response model is based on a database that includes different weld gap widths, arc voltage fluctuation characteristics, and the correspondence between arc current and measured weld penetration.

[0077] The multidimensional response model is an empirical model built upon a large amount of experimental data. Its purpose is to infer the internal state, which is difficult to measure directly, and the weld penetration depth through directly measurable external features such as weld gap and arc signal. In preliminary experiments, researchers systematically changed the weld gap width and welding parameters, such as current and voltage, recording the corresponding arc voltage fluctuation characteristics and arc current. After welding, they accurately measured the actual weld penetration depth using metallographic analysis and other methods. By performing correlation analysis on these data (input: gap width, voltage fluctuation, current; output: weld penetration depth), a large database of correspondences was established. During actual welding, the controller matches or interpolates the real-time input information in this database to obtain a reliable weld penetration state assessment value, making it possible to monitor the weld pool state. The multidimensional response model can be an empirical formula obtained through multivariate nonlinear regression analysis of the database, or a feedforward neural network model trained on the database, which can map the input parameters to the weld penetration state assessment value.

[0078] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A welding method for the production of a non-clogging de-slagging gate valve, characterized by, The application is applied to a welding device for producing anti-blocking slag discharge gate valve, and the welding device comprises: a welding base (100), a valve body clamping table (110) is arranged on the center surface of the welding base (100), the valve body clamping table (110) comprises floating clamping jaws moving towards or away from each other along parallel linear guide rails, and a contact temperature sensor (120) is embedded in the inner side contact surface of the floating clamping jaws; a gantry movable frame (200) is installed above the welding base (100), the gantry movable frame (200) comprises a cross beam (210) moving in a first direction arranged on the welding base (100), a welding head sliding base (220) installed on the cross beam (210) and moving in a second direction along the length direction of the cross beam (210), and a lifting electric cylinder (230) vertically installed on the welding head sliding base (220) for realizing vertical lifting; a welding head (300) is connected to the telescopic end of the lifting electric cylinder (230), the welding head (300) comprises a welding torch (310), a monocular vision camera (320) and an electric arc signal collector (330), the lens optical axis of the monocular vision camera (320) forms a fixed front included angle with the axis of the welding torch (310) to align the to-be-welded area in front of the welding torch (310), and the electric arc signal collector (330) is connected in parallel to the output loop of a welding power supply; a controller is used for controlling the movement of the gantry movable frame (200) and receiving and processing signals from the contact temperature sensor (120), the monocular vision camera (320) and the electric arc signal collector (330); the welding method comprises the following steps: obtaining an initial welding reference, the initial welding reference comprises an initial spatial path point sequence generated by scanning a to-be-welded weld seam through the monocular vision camera (320), and a corresponding prospective heat capacity coefficient sequence is calculated and generated for the path points in the initial spatial path point sequence according to pre-stored valve body structure data; performing prospective path correction, the controller continuously drives the monocular vision camera (320) to obtain the pre-welding image features of the to-be-welded area in front of the welding torch (310) during the welding process, the pre-welding image features comprise a weld seam transverse deviation and a weld seam gap width, and the controller adjusts the movement of the gantry movable frame (200) in real time according to the weld seam transverse deviation; performing composite energy correction, the controller collects real-time electric arc features of the electric arc signal collector (330), calculates a molten depth state evaluation value through a multi-dimensional response model according to the weld seam gap width and the real-time electric arc features, and generates a final welding energy correction instruction to adjust the welding parameters in combination with the prospective heat capacity coefficient corresponding to the current position. The controller collects valve body temperature distribution data of the contact temperature sensor (120), determines a thermal deformation trend by a thermodynamic difference model according to the valve body temperature distribution data, and generates a path posture compensation instruction to adjust the height of the lifting cylinder (230) or the planar motion of the gantry type moving frame (200); The calculation of the prospective thermal capacity coefficient includes: defining a spherical influence area centered on the path point, counting the local material volume and heat dissipation surface area in the area, and calculating the ratio of the local material volume to the heat dissipation surface area; comparing the ratio with a preset reference ratio to obtain the prospective thermal capacity coefficient; The generation of the final welding energy correction instruction includes: calculating a welding energy preliminary adjustment amount according to the penetration state evaluation value, and multiplying the welding energy preliminary adjustment amount by the prospective thermal capacity coefficient. The determination of the thermal deformation trend includes: continuously calculating the difference value and the time change rate between the readings of each contact temperature sensor (120), and combining the historical total welding energy input as a weighting factor to comprehensively output a direction vector describing the valve body deformation trend.

2. A welding method for producing a de-choking slag discharge gate valve according to claim 1, characterized by, Each set of floating clamping jaws on the valve body clamping table (110) is driven by a stepping motor through a ball screw to move along the linear guide rail.

3. A welding method for producing a de-clogging sluice valve according to claim 1, characterized in that, The monocular vision camera (320) is externally provided with a metal protective shell, and a splash-proof quartz glass is arranged in front of the lens.

4. A welding method for producing a de-clogging sluice valve according to claim 1, characterized in that, A cable drag chain system is further included, which includes a main drag chain moving with the cross beam (210) and a secondary drag chain moving with the welding head sliding seat (220), for guiding and protecting the cables and pipelines required by the welding head (300).

5. A welding method for producing a de-clogging sluice valve according to claim 1, characterized in that, The multi-dimensional response model is established based on a database containing the corresponding relationship between different weld gap widths, arc voltage fluctuation characteristics, arc current and measured penetration.

Images