Welding deformation optimization system for stainless steel pipe

Abstract

The invention discloses a welding deformation optimization system of a stainless steel pipe, and relates to the related technical field of welding, and the system comprises the following steps: carrying out multi-dimensional feature collection on the stainless steel pipe to obtain pipe feature information; analyzing pipe characteristic information and setting pipe welding constraints; dynamic temperature monitoring is conducted, the actual preheating temperature is obtained, and a preset welding temperature threshold value is set; the real-time welding temperature is obtained; when the real-time welding temperature does not conform to the preset welding temperature threshold value, a welding technology adjusting instruction is sent out; optimizing in the pipe welding space to obtain an optimal welding parameter strategy; and the stainless steel pipe is welded. The technical problems that according to existing stainless steel pipe welding, welding parameters are difficult to accurately set, uneven temperature distribution in the welding process is difficult to accurately control, an effective real-time monitoring and adjusting mechanism is lacked, and consequently the welding quality of the stainless steel pipe is poor are solved, effective control over welding deformation of the stainless steel pipe is achieved, and the welding quality of the stainless steel pipe is improved. The technical effect of improving the welding quality of the stainless steel pipe is achieved.

Description

Technical Field

[0001] The present application relates to the technical field related to welding, and in particular to a welding deformation optimization system for a stainless steel pipe. Background Art

[0002] With the rapid development of modern industrial technology, stainless steel pipes play a vital role in many industries such as petroleum, chemical, electric power, and pharmaceuticals. However, the welding process of stainless steel pipes is often accompanied by the challenge of welding deformation, which not only affects the overall quality of the pipeline system, but may also bring safety hazards to subsequent production operations. Although traditional welding methods can complete the connection of stainless steel pipes, due to the uneven temperature distribution during the welding process and the difference in the thermal physical properties of the materials, welding deformation is often caused, which not only affects the appearance, but more importantly, it will reduce the bearing capacity and sealing performance of the pipeline, thereby affecting the safe and stable operation of the pipeline system.

[0003] Therefore, in the current stainless steel pipe welding related technologies, there are technical problems such as difficulty in accurately setting welding parameters, accurately controlling the uneven temperature distribution during welding, and lack of effective real-time monitoring and adjustment mechanism, which in turn lead to poor stainless steel pipe welding quality. Summary of the invention

[0004] The present application provides a stainless steel pipe welding deformation optimization system, adopts technical means such as feature extraction and establishment of pipe welding space, solves the technical problems existing in the welding of existing stainless steel pipes, such as difficulty in accurately setting welding parameters, accurately controlling uneven temperature distribution during welding, and lack of effective real-time monitoring and adjustment mechanism, which in turn leads to poor welding quality of stainless steel pipes, realizes effective control of welding deformation of stainless steel pipes, and achieves the technical effect of improving the welding quality of stainless steel pipes.

[0005] The present application provides a welding deformation optimization system for a stainless steel pipe, the system comprising: a pipe feature information acquisition module, the pipe feature information acquisition module is used to collect multi-dimensional features of the stainless steel pipe to obtain pipe feature information; a pipe welding constraint setting module, the pipe welding constraint setting module is used to analyze the pipe feature information and set pipe welding constraints, the pipe welding constraints include pipe preheating temperature constraints and pipe welding parameter constraints; an actual preheating temperature acquisition module, the actual preheating temperature acquisition module is used to dynamically monitor the temperature of the stainless steel pipe under the pipe preheating temperature constraint, obtain the actual preheating temperature, and set a predetermined welding temperature threshold according to the actual preheating temperature; a real-time welding temperature acquisition module, the A real-time welding temperature acquisition module is used to weld the stainless steel pipe under the constraints of the pipe welding parameters, and dynamically monitors and obtains the real-time welding temperature; a welding process adjustment instruction issuing module, the welding process adjustment instruction issuing module is used to issue a welding process adjustment instruction when the real-time welding temperature does not meet the predetermined welding temperature threshold; an optimal welding parameter strategy acquisition module, the optimal welding parameter strategy acquisition module establishes a pipe welding space based on predetermined welding indicators, and optimizes the pipe welding space based on the welding process adjustment instruction to obtain the optimal welding parameter strategy; a stainless steel pipe welding module, the stainless steel pipe welding module is used to weld the stainless steel pipe according to the optimal welding parameter strategy.

[0006] In a possible implementation, a welding deformation optimization system for a stainless steel pipe also performs the following processing: reading a predetermined preheating factor index; extracting the pipe characteristic information based on the predetermined preheating factor index to obtain a predetermined factor parameter; using the predetermined factor parameter as input information of a preheating temperature prediction model to obtain a predicted preheating temperature; using the predicted preheating temperature as a preheating temperature constraint for the pipe; wherein the preheating temperature prediction model is an intelligent model obtained by supervised learning of a preheating training data set based on the principle of a neural network.

[0007] In a possible implementation, a stainless steel pipe welding deformation optimization system further performs the following processing: the predetermined preheating factor indicators include base material, base material thickness and welding type.

[0008] In a possible implementation, a welding deformation optimization system for a stainless steel pipe further performs the following processing: the preheating training data set includes a first historical base material material, a first historical base material thickness, a first historical welding type, and a first historical preheating temperature in a first historical welding preheating record, wherein a first historical preheating effect index of the first historical welding preheating record is any record in the historical welding preheating record whose preheating effect index meets a predetermined preheating effect index threshold, and the first historical preheating effect index is characterized by the stress value difference before and after preheating.

[0009] In a possible implementation, a welding deformation optimization system for a stainless steel pipe further performs the following processing: extracting a base material type corresponding to the base material in the pipe feature information, wherein the base material type has an identifier of the base material thermal expansion coefficient; traversing and matching the base material thermal expansion coefficient in a welding material database to obtain an optimal welding material; wherein a deviation between the thermal expansion coefficient of the optimal welding material and the base material thermal expansion coefficient meets a predetermined deviation threshold; extracting pipe length information from the pipe feature information, and dividing the pipe length information into a plurality of welds in combination with a predetermined unit weld length; generating an optimal welding sequence of the plurality of welds based on the principle of alternating welding; the optimal welding material and the optimal welding sequence together constitute the pipe welding parameter constraint.

[0010] In a possible implementation, a welding deformation optimization system for a stainless steel pipe also performs the following processing: respectively obtaining a predetermined parameter threshold of each welding indicator in the predetermined welding indicators, and constructing the pipe welding space according to the predetermined parameter threshold of each welding indicator, wherein the predetermined welding indicators include welding voltage, welding current, welding speed, gas type and gas flow rate.

[0011] In a possible implementation, a welding deformation optimization system for a stainless steel pipe also performs the following processing: randomly extracting a first welding parameter strategy in the pipe welding space; traversing the first welding parameter strategy in historical welding records to obtain the most similar welding record, wherein the most similar welding record includes a most similar welding parameter strategy and most similar welding monitoring information; wherein the parameter strategy consistency between the most similar welding parameter strategy and the first welding parameter strategy reaches a predetermined consistency threshold; when the most similar welding monitoring temperature in the most similar welding monitoring information meets the predetermined welding temperature threshold, the first welding parameter strategy is used as the optimal welding parameter strategy.

[0012] In a possible implementation, a welding deformation optimization system for a stainless steel pipe also performs the following processing: issuing a strategy review instruction, and extracting the most similar welding monitoring stress value in the most similar welding monitoring information based on the strategy review instruction; and reviewing the first welding parameter strategy for the optimal situation according to the most similar welding monitoring stress value.

[0013] The invention proposes a welding deformation optimization system for stainless steel pipes, collects multi-dimensional features of stainless steel pipes, obtains pipe feature information; analyzes pipe feature information and sets pipe welding constraints, including pipe preheating temperature constraints and pipe welding parameter constraints; performs dynamic temperature monitoring on the stainless steel pipes under pipe preheating temperature constraints to obtain actual preheating temperature, and sets a predetermined welding temperature threshold according to the actual preheating temperature; welds stainless steel pipes under pipe welding parameter constraints, and dynamically monitors to obtain real-time welding temperature; issues welding process adjustment instructions when the real-time welding temperature does not meet the predetermined welding temperature threshold; establishes pipe welding space based on predetermined welding indicators, and optimizes the pipe welding space based on the welding process adjustment instructions to obtain the optimal welding parameter strategy; welds stainless steel pipes according to the optimal welding parameter strategy. The invention solves the technical problems of the difficulty in accurately setting welding parameters, accurately controlling the uneven temperature distribution during welding, and lacking an effective real-time monitoring and adjustment mechanism, which leads to poor welding quality of stainless steel pipes, and realizes effective control of welding deformation of stainless steel pipes, thus achieving the technical effect of improving the welding quality of stainless steel pipes. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solution of the embodiment of the present disclosure, the accompanying drawings of the embodiment of the present disclosure will be briefly introduced below. A flow chart is used in the present application to illustrate the operations performed by the system according to the embodiment of the present application. It should be understood that the preceding or following operations are not necessarily performed accurately in order. On the contrary, various steps can be processed in reverse order or simultaneously as needed. At the same time, other operations can also be added to these processes, or one or more operations can be removed from these processes.

[0015] Figure 1 A schematic diagram of the structure of a stainless steel pipe welding deformation optimization system provided in an embodiment of the present application; Figure 2 A schematic diagram of the execution process of a pipe welding constraint setting module in a welding deformation optimization system for a stainless steel pipe provided in an embodiment of the present application.

[0016] Explanation of the reference numerals: pipe characteristic information obtaining module 10 , pipe welding constraint setting module 20 , actual preheating temperature obtaining module 30 , real-time welding temperature obtaining module 40 , welding process adjustment instruction issuing module 50 , optimal welding parameter strategy obtaining module 60 , stainless steel pipe welding module 70 . DETAILED DESCRIPTION

[0017] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0018] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0019] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict, and the terms "first\second" involved are merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "including" and "having" and any variations are intended to cover non-exclusive inclusions, for example, a process, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by technicians in the technical field of this application. The terms used herein are for the purpose of describing the embodiments of the present application only.

[0020] The present application embodiment provides a stainless steel pipe welding deformation optimization system, such as Figure 1 As shown, the system comprises: The tube characteristic information acquisition module 10 is used to collect multi-dimensional characteristics of the stainless steel tube to obtain tube characteristic information. Collecting multi-dimensional characteristics of the stainless steel tube specifically refers to collecting and analyzing information such as the characteristics, performance and application scenarios of the stainless steel tube from multiple dimensions to obtain tube characteristic information, which may include but is not limited to material and alloy elements, classification and manufacturing process, performance characteristics, application scenarios, etc. Specifically, the main materials of stainless steel include iron, chromium, nickel and other elements. Among them, chromium is the main alloying element of stainless steel, which can form a dense chromium oxide film to prevent further corrosion of the steel; seamless stainless steel tubes are manufactured through hot rolling, cold rolling or cold drawing processes, with smooth inner and outer surfaces and precise dimensions, suitable for high temperature and high pressure working environments; welded stainless steel tubes are connected to stainless steel plates or strips through welding processes, and the manufacturing process is relatively simple, the cost is low, and it is widely used Used in construction, furniture, decoration and other fields, precision stainless steel pipe manufacturing process requirements are higher, dimensional accuracy and internal and external surface finish are higher, suitable for electronics, instrumentation, medical equipment and other high-precision fields; the corrosion resistance of stainless steel pipes can be used stably for a long time in corrosive media such as acids, alkalis, and salts, and the high-temperature oxidation resistance can maintain good structural stability in high temperature environments. It is not easy to oxidize and deform. The high strength can withstand greater pressure and impact. The beauty and decorativeness have a smooth surface and metallic luster, and are suitable for architectural decoration, landscape design and outdoor facilities; stainless steel pipes can be used in industrial pipelines such as petroleum, chemical, medical, and food, mechanical structure components and parts manufacturing, as well as architectural decoration, landscape design, outdoor facilities and other fields.

[0021] The pipe welding constraint setting module 20 is used to analyze the pipe feature information and set pipe welding constraints, wherein the pipe welding constraints include pipe preheating temperature constraints and pipe welding parameter constraints. After analyzing the characteristic information of the stainless steel pipe, the pipe welding constraint is set. The pipe welding constraint refers to a series of restrictive conditions set to ensure the welding quality and reduce welding deformation when welding the stainless steel pipe. It is to ensure that the welding process can be carried out according to the predetermined standards and requirements to minimize welding deformation and improve welding quality. The pipe welding constraint mainly includes pipe preheating temperature constraint and pipe welding parameter constraint. Specifically, the pipe preheating temperature constraint refers to preheating the stainless steel pipe before welding to reach a certain temperature range to reduce the deformation caused by temperature difference during welding. The setting of pipe preheating temperature is usually based on material and wall thickness, ambient temperature, preheating temperature range, etc. Stainless steel pipes of different materials and wall thicknesses have different preheating temperature requirements. For example, for thicker pipeline steel, the preheating temperature may need to be higher to ensure uniform temperature in the welding area; the ambient temperature will also affect the selection of preheating temperature. At lower ambient temperatures, the preheating temperature may need to be increased to compensate for heat loss; generally speaking, the range of preheating temperature may vary depending on the specific situation, but it is usually required to be preheated within a certain temperature range, such as 150℃-200℃. Pipe welding parameter constraints refer to the setting and control of key parameters in the welding process to ensure welding quality and reduce deformation. Welding parameters mainly include welding current, arc voltage, welding speed, segmented program control of welding parameters, etc. Specifically, the size of the welding current directly affects the welding speed and the quality of the weld. For stainless steel pipes of different materials and thicknesses, it is necessary to select a suitable welding current; arc voltage is another important parameter in the welding process, which determines the length and stability of the arc. The selection of arc voltage should be based on welding current and welding speed; welding speed determines welding efficiency and quality. Too fast or too slow welding speed may cause welding defects or deformation; for some complex welding tasks, it may be necessary to use segmented program control to control welding parameters to ensure stability and quality during the welding process.

[0022] The actual preheating temperature acquisition module 30 is used to dynamically monitor the temperature of the stainless steel pipe under the pipe preheating temperature constraint, obtain the actual preheating temperature, and set a predetermined welding temperature threshold according to the actual preheating temperature. In the process of welding preheating of stainless steel pipes according to the set pipe preheating temperature constraint, temperature monitoring equipment (such as thermocouples, infrared thermometers, etc.) is used to perform dynamic temperature monitoring of stainless steel pipes. Specifically, these temperature monitoring equipment can record the temperature changes on the surface of stainless steel pipe materials in real time to ensure that the preheating temperature reaches and is maintained within a predetermined range. Through dynamic temperature monitoring, the actual preheating temperature of the stainless steel pipe can be obtained. This temperature is measured in real time during the preheating process and reflects the actual temperature state of the pipe surface. Due to factors such as the material, thickness, preheating time and ambient temperature of the pipe, the actual preheating temperature may deviate from the set preheating temperature range. When the preheating does not reach the pipe preheating temperature constraint, the welding temperature needs to be appropriately lowered, and then a predetermined welding temperature threshold is set according to the measured actual preheating temperature. The role of the predetermined welding temperature threshold is to ensure that during the welding process, the temperature of the pipe can be maintained within a suitable range, neither too high nor too low, so as to ensure welding quality and reduce deformation. For example, if the actual preheating temperature is 180°C, the operator may set a welding temperature threshold of 170°C~190°C. Welding within this range can ensure that the temperature of the pipe is well controlled.

[0023] The real-time welding temperature acquisition module 40 is used to weld the stainless steel pipe under the constraints of the pipe welding parameters, and dynamically monitor and obtain the real-time welding temperature. The stainless steel pipe is welded under the constraints of the pipe welding parameters. For example, for a stainless steel pipe of a certain material and thickness, the welding current is set to 150-200A, the arc voltage is 20-25V, and the welding speed is 5-10cm / min. After setting the welding parameter constraints, the stainless steel pipe is welded in a predetermined welding sequence and direction. During the welding process, the stability and consistency of the welding parameters are ensured to avoid excessive fluctuations in the parameters that affect the welding quality. The temperature monitoring equipment (such as thermocouples, infrared thermometers, etc.) is used to dynamically monitor the temperature of the welding area, and the temperature changes of the welding area are recorded in real time to obtain the real-time welding temperature. By observing the changes in the real-time welding temperature, the heat input and welding effect of the welding process can be understood.

[0024] The welding process adjustment instruction issuing module 50 is used to issue a welding process adjustment instruction when the real-time welding temperature does not meet the predetermined welding temperature threshold. When the real-time welding temperature does not meet the preset welding temperature threshold, a welding process adjustment instruction is issued. Specifically, during the welding process, the real-time welding temperature is dynamically monitored and compared with the preset welding temperature threshold. If the monitored real-time welding temperature exceeds the preset threshold range (i.e., the temperature is too high or too low), an adjustment instruction is automatically issued according to the preset control strategy to adjust the welding process parameters to ensure the stability of the welding process and the welding quality. Specifically, this welding process adjustment instruction may include welding current adjustment. If the real-time welding temperature is too high, the welding current may need to be reduced to reduce the heat input. On the contrary, if the temperature is too low, the welding current may need to be increased; arc voltage adjustment. The change of arc voltage will also affect the welding heat input. By adjusting the arc voltage, the temperature of the welding area can be controlled; welding speed adjustment. The speed of welding directly affects the welding heat input and the cooling speed of the weld. If the real-time welding temperature is too high, the welding speed can be appropriately increased. On the contrary, if the temperature is too low, the welding speed can be reduced; other parameter adjustments. Depending on the specific welding process and equipment, other parameters may also need to be adjusted, such as the flow rate of the shielding gas and the feeding speed of the welding wire.

[0025] The optimal welding parameter strategy acquisition module 60 establishes a pipe welding space based on a predetermined welding index, and obtains an optimal welding parameter strategy in the pipe welding space based on the welding process adjustment instruction. Establishing the pipe welding space refers to defining the predetermined welding indicators and formulating the welding parameter range. First, according to the material, specification, welding requirements, etc. of the stainless steel pipe, a series of predetermined welding indicators are set, such as weld quality, welding efficiency, deformation control, etc. Then, based on the welding process and equipment capabilities, the reasonable range of each welding parameter (such as welding current, arc voltage, welding speed, etc.) is determined, and finally the pipe welding space is formed; according to the determined welding process adjustment instructions, the optimization is carried out in the pipe welding space. Specifically, the optimization goals are clarified, such as improving welding quality, reducing welding deformation or improving welding efficiency, etc., and then a variety of optimization methods such as experimental optimization method and mathematical model optimization method are used to find the optimal welding parameter combination in the pipe welding space. For example, the orthogonal test method can design an orthogonal table, combine the changes of multiple process parameters for a series of tests, find out the factors that have the greatest impact on welding quality, and select the best process parameter combination. According to the feedback of the adjustment instructions and the optimization method, the welding parameters are continuously optimized iteratively until the optimal parameter strategy that meets the predetermined welding indicators is found.

[0026] The stainless steel pipe welding module 70 is used to weld the stainless steel pipe according to the optimal welding parameter strategy. Welding the stainless steel pipe according to the optimal welding parameter strategy means that after determining the optimal welding parameter combination, these parameters are set on the welding equipment, and the actual welding operation of the stainless steel pipe is performed according to these parameters. Specifically, the optimal welding parameter strategy (such as welding current, arc voltage, welding speed, etc.) obtained by optimization is input into the control system of the welding equipment, the welding equipment is started, and the welding operation is performed according to the set optimal welding parameter strategy. During the welding process, the conditions in the welding area, such as weld formation, molten pool state, etc., are closely monitored to ensure the welding quality. The quality of the welded stainless steel pipe is inspected, including the integrity of the weld, surface quality, dimensional accuracy, etc., to realize the automation and intelligence of the welding process, ensure that the welding quality meets the predetermined indicators, ensure the stability of the welding process and the welding quality, improve welding efficiency and reduce production costs.

[0027] A stainless steel pipe welding deformation optimization system according to an embodiment of the present invention is used to solve the technical problems of the difficulty in accurately setting welding parameters, accurately controlling the uneven temperature distribution during welding, and lacking an effective real-time monitoring and adjustment mechanism in the existing stainless steel pipe welding, which leads to poor welding quality of the stainless steel pipe, and realizes effective control of the welding deformation of the stainless steel pipe, thereby achieving the technical effect of improving the welding quality of the stainless steel pipe. A stainless steel pipe welding deformation optimization system includes: a pipe feature information acquisition module 10, a pipe welding constraint setting module 20, an actual preheating temperature acquisition module 30, a real-time welding temperature acquisition module 40, a welding process adjustment instruction issuing module 50, an optimal welding parameter strategy acquisition module 60, and a stainless steel pipe welding module 70.

[0028] Next, the specific configuration of the pipe welding constraint setting module 20 will be described in detail. Figure 2As shown, the pipe welding constraint setting module 20 may further include: reading a predetermined preheating factor index. Reading a factor index related to preheating from a data source (such as a stainless steel pipe welding database, a welding file, etc.), these factor indexes may include the material, thickness, ambient temperature, humidity, etc. of the stainless steel pipe, which are important factors affecting the preheating temperature. It also includes extracting the pipe feature information based on the predetermined preheating factor index to obtain a predetermined factor parameter. According to the read preheating factor index, the corresponding feature value is extracted from the feature information of the stainless steel pipe. For example, if the preheating factor index includes the thickness of the stainless steel pipe, then the thickness is extracted from the data of the stainless steel pipe, and the thickness is one of the predetermined factor parameters. It also includes using the predetermined factor parameter as input information of the preheating temperature prediction model to obtain a predicted preheating temperature. The extracted predetermined factor parameter will be input into a preheating temperature prediction model, which is constructed based on the principle of a neural network. By learning a large number of preheating training data sets, the relationship between the input factor and the preheating temperature is established. When the preheating temperature prediction model receives a new input parameter, it can predict the corresponding preheating temperature according to the learned law to obtain the predicted preheating temperature.

[0029] The pipe welding constraint setting module 20 also includes: using the predicted preheating temperature as the pipe preheating temperature constraint. The predicted preheating temperature is used as a temperature constraint in the preheating process of the stainless steel pipe, which means that when the preheating operation is performed, the temperature needs to be controlled near the predicted value to ensure that the preheating effect is optimal. It also includes that the preheating temperature prediction model is an intelligent model obtained by supervised learning of the preheating training data set based on the neural network principle. The preheating temperature prediction model is an intelligent model based on a neural network. The neural network is an algorithm model that simulates the connection mode of human brain neurons. It can predict and classify by learning the laws in the data of a large number of preheating training data sets. The preheating training data set is a data set for training the preheating temperature prediction model, which contains historical relevant information about welding preheating. Specifically, the temperature prediction model is constructed based on the neural network, and the data in the preheating training data set are supervised to learn, and the complex relationship between the input data (such as the material, thickness, ambient temperature, humidity, etc. of the stainless steel pipe) and the output data (preheating temperature) is established. During the model training process, the preheating temperature prediction results are continuously compared with the actual results, so as to adjust its own parameters to improve the accuracy of the preheating temperature prediction, and finally obtain the preheating temperature prediction model.

[0030] The specific configuration of the pipe welding constraint setting module 20 will be described in detail below. The pipe welding constraint setting module 20 may further include: the predetermined preheating factor index includes the base material, base material thickness and welding type. The parent material refers to the material of the base material to be welded, such as stainless steel, carbon steel, alloy steel, etc. Different materials have different physical and chemical properties such as thermal conductivity, thermal expansion coefficient, melting point and phase change temperature, which will directly affect the heat input and temperature distribution during welding; the parent material thickness refers to the thickness of the base material to be welded. Different thicknesses require different heat inputs during welding. Thicker parent materials require more heat to ensure complete penetration and fusion of the weld, while thinner parent materials may be more susceptible to thermal stress and deformation in the heat-affected zone; the welding type refers to the welding process method used, such as tungsten inert gas welding, metal inert gas shielded welding, active gas shielded welding, submerged arc welding, etc. Different welding types have different heat input characteristics, welding speeds and welding efficiencies. For example, tungsten inert gas welding usually has lower heat input and slower welding speeds, while submerged arc welding has higher heat input and faster welding speeds. These differences will affect the temperature distribution and welding quality during welding.

[0031] The specific configuration of the pipe welding constraint setting module 20 will be described in detail below. The pipe welding constraint setting module 20 may further include: the preheating training data set includes a first historical base material, a first historical base material thickness, a first historical welding type, and a first historical preheating temperature in a first historical welding preheating record, wherein a first historical preheating effect index of the first historical welding preheating record is any record in the historical welding preheating record whose preheating effect index meets a predetermined preheating effect index threshold, and the first historical preheating effect index is characterized by a stress value difference before and after preheating. The first historical parent material is the parent material corresponding to each record in the historical welding preheating record. For example, the data set may contain records of various parent materials such as stainless steel, carbon steel, and alloy steel; the first historical parent material thickness is the parent material thickness corresponding to each record in the historical welding preheating record; the first historical welding type is the welding type used in each record in the historical welding preheating record; the first historical preheating temperature is the preheating temperature corresponding to each record in the historical welding preheating record, which is the preheating temperature used in the actual welding process to reduce stress and deformation in the welding process; the first historical welding preheating record is a collection of all historical welding preheating records. The preheating effect index is selected from the records. Specifically, only the records whose preheating effect index meets the preset preheating effect index threshold value will be selected. The preheating effect index is characterized by the stress value difference before and after preheating. In the welding process, preheating can reduce the stress and deformation of the welding area, thereby improving the welding quality. Therefore, the quality of the preheating effect can be measured by the stress value difference of the welding area before and after preheating. For example, the stress value of the welding area before preheating is measured, and then the welding area is preheated, and the stress value after preheating is measured again, and the difference in stress values ​​before and after preheating is calculated. This stress difference is the preheating effect index.

[0032] The specific configuration of the pipe welding constraint setting module 20 will be described in detail below. The pipe welding constraint setting module 20 may further include: extracting the base material type corresponding to the base material in the pipe feature information, and the base material type has an identification of the base material thermal expansion coefficient. Extracting the base material from the pipe feature information, this material information is usually related to the physical properties such as the thermal expansion coefficient of the base material, and the base material type refers to a specific material type, such as carbon steel, stainless steel, alloy steel, etc. Each material has its own specific thermal expansion coefficient and is identified. It also includes traversing and matching the base material thermal expansion coefficient in the welding material database to obtain the optimal welding material; wherein the deviation between the thermal expansion coefficient of the optimal welding material and the base material thermal expansion coefficient meets the predetermined deviation threshold. After obtaining the base material with the thermal expansion coefficient identification, traversing and matching in the welding material database to find a welding material whose thermal expansion coefficient has the smallest deviation from the thermal expansion coefficient of the base material, and this deviation meets the predetermined deviation threshold, to ensure that the thermal expansion behavior of the welding material and the base material is similar during welding, and to reduce welding stress and deformation.

[0033] The pipe welding constraint setting module 20 also includes extracting the pipe length information in the pipe feature information, and dividing the pipe length information into a plurality of welds in combination with a predetermined unit weld length. In combination with a predetermined unit weld length (for example, a weld is set every 10 cm), the pipe length information is divided into a plurality of welds, and the continuous welding process is discretized to facilitate management and optimization of the welding sequence. It also includes generating the optimal welding sequence of the plurality of welds based on the principle of alternating welding. Based on the principle of alternating welding, the optimal welding sequence of these welds is generated, wherein the alternating welding principle is a welding strategy that reduces welding stress and deformation by alternately welding different welds during the welding process, and finally determines an optimal welding sequence to minimize stress and deformation during the welding process. It also includes that the optimal welding material and the optimal welding sequence together constitute the pipe welding parameter constraint. The matched optimal welding material and the generated optimal welding sequence are combined together to form a pipe welding parameter constraint, which is used to guide the actual stainless steel pipe welding, ensuring the welding quality while optimizing the welding efficiency.

[0034] The specific configuration of the optimal welding parameter strategy acquisition module 60 will be described in detail below. The optimal welding parameter strategy acquisition module 60 may further include: respectively acquiring predetermined parameter thresholds of each welding indicator in the predetermined welding indicators, and constructing the pipe welding space according to the predetermined parameter thresholds of each welding indicator, wherein the predetermined welding indicators include welding voltage, welding current, welding speed, gas type and gas flow rate. Constructing the pipe welding space based on the predetermined parameter thresholds of multiple predetermined welding indicators, The predetermined welding indicators are key parameters that need to be controlled during the welding process, which directly affect the quality and efficiency of welding, including welding voltage, welding current, welding speed, gas type and gas flow rate. Specifically, welding voltage is the voltage applied between the electrode and the workpiece during welding, which determines the length and energy density of the welding arc. The predetermined parameter threshold refers to the appropriate range of welding voltage according to different welding materials and welding processes. Exceeding or falling below this range will affect the quality and efficiency of welding. For example, for tungsten inert gas arc welding of certain stainless steel materials, the predetermined parameter threshold of welding voltage may be set to 10-15V; welding current is the current passing between the electrode and the workpiece during welding, which determines the heat input of the welding arc. The predetermined parameter threshold refers to the size of the welding current, which directly affects the penetration depth and width of the weld. The appropriate range set is that too small current may result in incomplete penetration of the weld, while too large current may cause burn-through or produce too much welding spatter; welding speed is the speed at which the electrode moves along the weld during welding. The speed of the seam movement determines the time of the welding process and the distribution of the heat input. The preset parameter threshold means that the selection of the welding speed should take into account factors such as the melting point and thermal conductivity of the welding material. A welding speed that is too fast may result in the weld not being fused, while a speed that is too slow may cause overheating and deformation. In gas shielded welding, the type of gas used has an important influence on the welding quality. Different gas types have different protective effects and stabilities. The preset parameter threshold actually refers to which type of gas is selected, rather than a specific numerical range. For example, for tungsten inert gas welding, commonly used shielding gases are argon (Ar) or a mixture of argon and a small amount of oxygen (Ar+O2). Gas flow refers to the flow rate of the shielding gas during the welding process, which determines the quality of the protection. The preset parameter threshold means that the setting of the gas flow should be determined based on factors such as the welding current, welding speed and gas type. Too small a flow may result in poor protection, while too large a flow may waste gas and increase costs.

[0035] The specific configuration of the optimal welding parameter strategy acquisition module 60 will be described in detail below. The optimal welding parameter strategy acquisition module 60 may further include: randomly extracting the first welding parameter strategy in the pipe welding space. Randomly selecting a welding parameter strategy from the predefined pipe welding space as a starting point, including a combination of parameters such as welding voltage, welding current, welding speed, gas type and gas flow rate. It also includes traversing the first welding parameter strategy in the historical welding records to obtain the most similar welding record, and the most similar welding record includes the most similar welding parameter strategy and the most similar welding monitoring information. Use the extracted first welding parameter strategy to traverse and search in the historical welding database to find similar welding records, that is, find the welding record most similar to the first welding parameter strategy, including the most similar welding parameter strategy and the most similar welding monitoring information. Specifically, the most similar welding parameter strategy refers to the parameter combination closest to the current first welding parameter strategy in the historical record, and the most similar welding monitoring information refers to the data monitored in real time during the welding process, such as welding temperature, weld width, gas concentration, etc.

[0036] The optimal welding parameter strategy acquisition module 60 also includes, wherein the parameter strategy consistency of the most similar welding parameter strategy and the first welding parameter strategy reaches a predetermined consistency threshold. In order to ensure that the most similar welding parameter strategy found is sufficiently similar to the first welding parameter strategy, it is necessary to calculate the consistency between them, that is, to achieve it by comparing the differences between the various parameters. If this difference (or distance) is less than the predetermined threshold, the two parameter strategies are considered to be consistent. It also includes, when the most similar welding monitoring temperature in the most similar welding monitoring information meets the predetermined welding temperature threshold, the first welding parameter strategy is used as the optimal welding parameter strategy. Compare whether the most similar welding monitoring temperature in the most similar welding monitoring information meets the predetermined welding temperature threshold. If the welding monitoring temperature in the most similar welding monitoring information meets the predetermined welding temperature threshold, it means that the welding process is successfully completed under similar parameters and the welding quality is guaranteed. The first welding parameter strategy can be regarded as the optimal welding parameter strategy under current conditions.

[0037] The specific configuration of the optimal welding parameter strategy acquisition module 60 will be described in detail below. The optimal welding parameter strategy acquisition module 60 may further include: issuing a strategy review instruction, and extracting the most similar welding monitoring stress value in the most similar welding monitoring information based on the strategy review instruction. After determining the most similar welding record, in order to ensure that the selected first welding parameter strategy can achieve the expected effect in actual application, it is necessary to review it, that is, by issuing a strategy review instruction to trigger the verification process. During the review process, the most similar welding monitoring stress value is extracted from the most similar welding monitoring information as the basis for the review, because the welding stress is the internal stress generated during the welding process. If the stress is too large, it may cause quality problems such as deformation and cracking of the welded parts. It also includes reviewing the first welding parameter strategy for the optimal situation according to the most similar welding monitoring stress value. The first welding parameter strategy is re-tested for the best case using the extracted most similar welding monitoring stress value. Specifically, it is evaluated whether the most similar welding monitoring stress value is within an acceptable range. If the most similar welding monitoring stress value is within the acceptable range, it is considered that the first welding parameter strategy is effective under similar conditions and is an optimal welding parameter strategy; if the most similar welding monitoring stress value exceeds the acceptable range, it is necessary to adjust the first welding parameter strategy and re-test it until a suitable welding parameter strategy is found. By using similar situations in historical welding records, the currently selected welding parameter strategy is verified and adjusted to ensure that it can achieve the expected welding effect and quality in actual applications, thereby improving the controllability and quality stability of the welding process.

[0038] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0039] The above specific implementations do not constitute a limitation on the protection scope of this application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of this application should be included in the protection scope of this application.

Claims

1. A stainless steel pipe welding deformation optimization system, characterized in that: include: A tube characteristic information acquisition module, which is used to collect multi-dimensional characteristics of the stainless steel tube to obtain tube characteristic information; A tube welding constraint setting module, the tube welding constraint setting module is used to analyze the tube feature information and set tube welding constraints, the tube welding constraints include tube preheating temperature constraints and tube welding parameter constraints; An actual preheating temperature acquisition module, the actual preheating temperature acquisition module is used to perform dynamic temperature monitoring on the stainless steel pipe under the pipe preheating temperature constraint, obtain the actual preheating temperature, and set a predetermined welding temperature threshold according to the actual preheating temperature; A real-time welding temperature acquisition module, wherein the real-time welding temperature acquisition module is used to weld the stainless steel pipe under the constraints of the pipe welding parameters and dynamically monitor and obtain the real-time welding temperature; A welding process adjustment instruction issuing module, wherein the welding process adjustment instruction issuing module is used to issue a welding process adjustment instruction when the real-time welding temperature does not meet the predetermined welding temperature threshold; An optimal welding parameter strategy acquisition module, wherein the optimal welding parameter strategy acquisition module establishes a pipe welding space based on a predetermined welding index, and seeks an optimal welding parameter strategy in the pipe welding space based on the welding process adjustment instruction; A stainless steel pipe welding module, wherein the stainless steel pipe welding module is used to weld the stainless steel pipe according to the optimal welding parameter strategy.

2. According to the welding deformation optimization system of a stainless steel pipe according to claim 1, it is characterized in that: include: Read the predetermined warm-up factor indicator; Extracting the tube characteristic information based on the predetermined preheating factor index to obtain a predetermined factor parameter; Using the predetermined factor parameters as input information of a preheating temperature prediction model to obtain a predicted preheating temperature; using the predicted preheating temperature as the tube preheating temperature constraint; Among them, the preheating temperature prediction model is an intelligent model obtained by supervised learning of the preheating training data set based on the neural network principle.

3. According to the welding deformation optimization system of a stainless steel pipe according to claim 2, it is characterized in that: The predetermined preheating factor indicators include base material material, base material thickness and welding type.

4. A stainless steel pipe welding deformation optimization system according to claim 3, characterized in that: The preheating training data set includes a first historical base material material, a first historical base material thickness, a first historical welding type and a first historical preheating temperature in a first historical welding preheating record, wherein a first historical preheating effect index of the first historical welding preheating record is any record in the historical welding preheating record whose preheating effect index meets a predetermined preheating effect index threshold, and the first historical preheating effect index is characterized by a stress value difference before and after preheating.

5. The stainless steel pipe welding deformation optimization system according to claim 3, characterized in that: include: Extracting a base material type corresponding to the base material in the tube characteristic information, wherein the base material type has an identifier of a base material thermal expansion coefficient; Traversing and matching the thermal expansion coefficient of the base material in a welding material database to obtain an optimal welding material; wherein the deviation between the thermal expansion coefficient of the optimal welding material and the thermal expansion coefficient of the base material meets a predetermined deviation threshold; Extracting tube length information from the tube feature information, and dividing the tube length information into a plurality of welding points in combination with a predetermined unit welding point length; Generating an optimal welding sequence of the plurality of welding points based on the principle of alternating welding; The optimal welding material and the optimal welding sequence together constitute the pipe welding parameter constraints.

6. The stainless steel pipe welding deformation optimization system according to claim 1, characterized in that: The predetermined parameter threshold of each welding indicator in the predetermined welding indicators is obtained respectively, and the pipe welding space is constructed according to the predetermined parameter threshold of each welding indicator, wherein the predetermined welding indicators include welding voltage, welding current, welding speed, gas type and gas flow rate.

7. The stainless steel pipe welding deformation optimization system according to claim 1, characterized in that: include: randomly extracting a first welding parameter strategy in the tube welding space; Traversing the first welding parameter strategy in historical welding records to obtain the most similar welding record, wherein the most similar welding record includes the most similar welding parameter strategy and the most similar welding monitoring information; Wherein, the parameter strategy consistency between the most similar welding parameter strategy and the first welding parameter strategy reaches a predetermined consistency threshold; When the most similar welding monitoring temperature in the most similar welding monitoring information meets the predetermined welding temperature threshold, the first welding parameter strategy is used as the optimal welding parameter strategy.

8. A stainless steel pipe welding deformation optimization system according to claim 7, characterized in that: include: issuing a strategy review instruction, and extracting the most similar welding monitoring stress value in the most similar welding monitoring information based on the strategy review instruction; The first welding parameter strategy is re-checked for optimal situation according to the most similar welding monitoring stress value.

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