Intelligent welding method and system for pressure steel pipe

Abstract

The invention relates to an intelligent welding method and system for a pressure steel pipe. The intelligent welding method for the pressure steel pipe comprises the following steps that an equivalent circuit model of a welding arc is established; an arc voltage instantaneous value and a welding current instantaneous value in the welding process are synchronously collected in real time; based on the equivalent circuit model and the collected instantaneous electrical parameters, the equivalent impedance and / or the change rate of the electric arc are / is calculated to serve as state evaluation indexes for reflecting the stability of the welding process and the dynamic characteristics of a molten pool; comparing the state evaluation index with a preset stability threshold range to generate a deviation signal; the deviation signal is input into a controller, and the controller is switched among different control modes according to the size and the change trend of the deviation; the controller outputs a control signal and dynamically adjusts primary control parameters of the welding power source, and the primary control parameters comprise an output current set value, an output voltage set value or a pulse waveform parameter so as to achieve closed-loop control over the arc length and the penetration state.

Description

Technical Field

[0001] This application relates to the field of pressure steel pipe welding technology, and more specifically, to an intelligent welding method and system for pressure steel pipes. Background Technology

[0002] Pressure steel pipes are widely used in water conservancy projects, water pipelines, and other fields, and their welding quality directly affects the safety and service life of the project. Traditional welding methods, such as manual electric arc welding and submerged arc welding, suffer from problems such as low welding efficiency, inaccurate heat input control, and unstable weld quality. Especially in thick plate welding, defects such as large welding deformation, high residual stress, and insufficient impact toughness are prone to occur.

[0003] In existing technologies, CO2 gas shielded welding is widely used due to its high efficiency and low cost. However, most conventional GMAW welding machines employ simple constant voltage or constant current external characteristic control, lacking in-depth perception and intelligent response to the dynamically changing physical state of the arc during welding. Adjustments to welding parameters are often open-loop or based on simple feedback from a single variable, failing to address complex conditions such as arc length fluctuations, molten pool flow, and spatter. This results in welding quality still largely depending on the welder's on-site judgment and manual intervention, making it difficult to achieve standardized, automated, and traceable high-quality welding.

[0004] Therefore, there is an urgent need for a new welding method that combines electrical models with intelligent control to improve the stability of the welding process, the consistency of weld quality, and energy utilization efficiency. Summary of the Invention

[0005] The purpose of this application is to provide an intelligent welding method and system for pressure steel pipes, which can achieve controllability and self-adaptability in the welding process and improve weld quality.

[0006] To achieve the above objectives, the first objective is to provide an intelligent welding method for pressure steel pipes, comprising the following steps: Establish an equivalent circuit model of the welding arc; Real-time synchronous acquisition of instantaneous values ​​of arc voltage and welding current during the welding process; Based on the equivalent circuit model and the collected instantaneous electrical parameters, the equivalent impedance of the arc and / or its rate of change are calculated as a state assessment index reflecting the stability of the welding process and the dynamic characteristics of the molten pool. The state evaluation index is compared with a preset stability threshold range to generate a deviation signal; The deviation signal is input to the controller, which switches between different control modes according to the magnitude and trend of the deviation. The controller outputs control signals to dynamically adjust the primary control parameters of the welding power source. These primary control parameters include output current setpoints, output voltage setpoints, or pulse waveform parameters, in order to achieve closed-loop control of the arc length and penetration state.

[0007] In an optional implementation, establishing the equivalent circuit model of the welding arc specifically includes: The arc equivalent circuit model is divided into a static operating point model and a dynamic disturbance response model. The static operating point model is used to establish a mapping relationship between arc voltage, welding current and a nominal arc resistance during the steady-state welding stage, wherein the nominal arc resistance is associated with the desired reference arc length. The dynamic disturbance response model is used to characterize the hysteresis characteristic of arc current change relative to arc voltage change by introducing an equivalent inductance when the welding process is disturbed, and to calculate dynamic impedance based on the differential relationship between instantaneous voltage and current values.

[0008] In an optional implementation, the calculation of the state assessment index includes: Calculate the first state index, which is the dynamic resistance value. The dynamic resistance value is the ratio of the average arc voltage to the average welding current within one calculation cycle. Calculate the second state index, which is the resistance change trend value. The resistance change trend value is the difference or weighted average difference between the dynamic resistance value of the current calculation period and the dynamic resistance value of the previous one or more historical calculation periods. The dynamic resistance value and the resistance change trend value are used together as state assessment indicators to comprehensively judge the instantaneous state of the electric arc.

[0009] In an optional implementation, the controller includes a multimodal PID controller, the control logic of which includes: A first threshold range and a second threshold range are set, wherein the second threshold range represents a greater degree of deviation than the first threshold range; When the state evaluation index is within the first threshold range, the controller operates in fine-tuning mode. In this mode, the integral action of the controller dominates to slowly eliminate static deviations and ensure steady-state accuracy. When the state evaluation index enters the second threshold range, the controller switches to the fast response mode. In this mode, the proportional and derivative actions of the controller are enhanced, while the integral action is restricted or frozen, in order to achieve rapid suppression of arc length mutations or short-circuit risks.

[0010] In an optional implementation, feedforward-feedback composite control logic for the melt-through state is also included: Pre-determine an ideal penetration current range corresponding to the welding layer; Based on the long-term drift trend of dynamic resistance value, the change in the penetration state is judged: if the dynamic resistance value shows a continuous and slow increasing trend, it is judged that the penetration depth may be insufficient; if it shows a continuous and slow decreasing trend, it is judged that the penetration depth may be too large. When it is determined that the penetration depth may be insufficient, the control logic adds a positive feedforward compensation signal on the basis of feedback adjustment based on the state assessment index, and finely adjusts the reference setting value of the welding current towards the upper limit of the ideal penetration current range. When it is determined that the penetration depth may be too large, the control logic adds a negative feedforward compensation signal to finely adjust the reference setting value of the welding current towards the lower limit of the ideal penetration current range.

[0011] In an optional implementation, during the welding process, a high-frequency data acquisition system continuously records timestamps, arc voltage, welding current, and adjustment signals output by the controller to form a welding process database. Based on the welding process database, a welding stability index is generated for each weld. This index is calculated by statistically analyzing the frequency and magnitude of the state evaluation index exceeding the preset stability threshold during the welding process. By correlating the welding stability index with the results of subsequent non-destructive testing, a correlation model between the stability of welding electrical parameters and the internal quality of the weld was established. Based on the aforementioned correspondence model, the preset threshold range of the state evaluation index and the parameters of the multimodal PID controller are dynamically optimized.

[0012] In an optional implementation, three basic position modes—flat welding, vertical welding, and overhead welding—are preset in the welding system. Before welding begins, the operator selects the current welding position mode; The controller calls different preset parameter combinations according to the selected position mode. The parameter combinations include at least the control parameters of the multimodal PID controller, the threshold range of the state evaluation index, and the reference setting value of the welding current / voltage. Specifically, for vertical and overhead welding modes, the stability threshold range of the state evaluation index is set to be more stringent than that for flat welding, and the controller response speed is set to be faster to cope with the additional effects of gravity on the molten pool.

[0013] Secondly, the present invention provides an intelligent welding system for pressure steel pipes, used to implement the above-mentioned intelligent welding method for pressure steel pipes, including: The main body of the welding power supply is a digital inverter welding machine, which can receive external control signals and quickly adjust the output; The high-frequency data acquisition module has its signal input terminal connected to the voltage sensor and current sensor of the welding circuit, and its signal output terminal connected to the embedded main controller, with a sampling frequency of not less than 50kHz. Embedded main controller; The human-machine interface is used to display real-time electrical parameter curves, status evaluation indicators, alarm information, and allows operators to input welding parameters and modes.

[0014] In an optional implementation, the logical architecture of the embedded host controller includes: The signal processing layer is used to digitally filter and calibrate the acquired raw voltage and current signals; The model calculation layer is used to execute the equivalent circuit model in real time and calculate the state evaluation index. The decision control layer is used to run the multimodal PID control logic and generate control signals; The data management layer is used to handle the storage, retrieval, and reporting of welding process data.

[0015] This application establishes an accurate electrical equivalent model for the welding arc and designs multi-level, multi-modal intelligent control logic based on this model, enabling the welding power source to automatically, accurately, and quickly adjust according to the arc state, thereby fundamentally improving the quality, efficiency, and consistency of pressure steel pipe welding.

[0016] Other features and advantages of this application will be described in detail in the following detailed description section. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of the intelligent welding method for pressure steel pipes in this application. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0020] In the description of this application, it should be noted that the terms "inner" and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship commonly used when the product is in use. They are used only for the convenience of describing this application and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application. Furthermore, the terms "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0021] In the description of this application, it should also be noted that, unless otherwise expressly specified and limited, the terms "setup" and "connection" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0022] The core of this application lies in integrating physical models with digital control to construct a welding intelligent system capable of sensing, decision-making, and execution.

[0023] Key welding quality indicators that cannot be directly measured, such as arc stability and penetration state, are correlated with real-time measurable electrical parameters, such as arc voltage and welding current, through a relatively accurate equivalent circuit model. By analyzing changes in electrical parameters in real time, the state of the welding process is deduced in reverse, and specific and complex control logic is provided to simulate the decision-making process of an experienced welder, enabling closed-loop control of the welding power source.

[0024] See Figure 1 The intelligent welding method for pressure steel pipes in this invention mainly includes the following steps: Establish an equivalent circuit model of the welding arc; Real-time synchronous acquisition of instantaneous values ​​of arc voltage and welding current during the welding process; Based on the equivalent circuit model and the collected instantaneous electrical parameters, the equivalent impedance of the arc and / or its rate of change are calculated as a state assessment index reflecting the stability of the welding process and the dynamic characteristics of the molten pool. The state evaluation index is compared with a preset stability threshold range to generate a deviation signal; The deviation signal is input to the controller, which switches between different control modes according to the magnitude and trend of the deviation. The controller outputs control signals to dynamically adjust the primary control parameters of the welding power source. These primary control parameters include output current setpoints, output voltage setpoints, or pulse waveform parameters, in order to achieve closed-loop control of the arc length and penetration state.

[0025] The arc equivalent circuit model is specifically a continuously updated dynamic calculation process running within an embedded controller. This model consists of two parts: The static operating point model defines the appearance of the electric arc under ideal steady-state conditions. The electric arc is represented as an equivalent variable resistor R. arc-static Variable resistor R arc-static The value is positively correlated with a baseline arc length L0 that is expected to be maintained.

[0026] During system initialization, the current I set by the operator... set and voltage U set This corresponds to a desired static operating point (I). set U set ,R arc-static =U set / I set This static model is the goal pursued by the control system.

[0027] The dynamic disturbance response model is used to describe the behavior of the electric arc during actual welding. The dynamic disturbance response model is based on the static model, with an equivalent inductance L connected in series. arc Equivalent inductance L arc This represents the thermal inertial effect of the electric arc plasma and the dynamic process of welding wire melting.

[0028] In a circuit, the characteristic of an inductor is that it impedes changes in current. Therefore, when the arc length suddenly changes due to some disturbance (such as an uneven workpiece or hand tremors), the voltage will change instantaneously, but due to the presence of inductance, the change in current will lag behind.

[0029] By acquiring real-time voltage U(t) and current I(t), the model can not only calculate the instantaneous resistance R(t) = U(t) / I(t), but also perceive the dynamic characteristics of the system by analyzing the relationship between U(t) and dI(t) / dt. By monitoring the instantaneous values ​​of voltage U(t) and current I(t) and their differential relationship, the hysteresis effect of the aforementioned current changes can be captured, thus revealing the transient characteristics of the electric arc more profoundly.

[0030] In the controller's model calculation layer, the following calculation is performed once every millisecond: Instantaneous resistance calculation: R inst =U arc-filtered / I arc-filtered Among them, U arc-filtered and I arc-filtered These are the voltage and current values ​​after digital filtering to eliminate high-frequency noise.

[0031] Dynamic Resistance and Trend Calculation: Every 20 milliseconds is a calculation window, and the average resistance within this window is calculated as the dynamic resistance value R, which is used as the first state indicator. dyn At the same time, calculate R for the current window. dyn R in the previous window dyn-prev The difference is used as the resistance change trend value R, which is the second state indicator. Delta .Right now: R Delta = R dyn -R dyn-prev .

[0032] R dyn It reflects the average arc length at the current moment, that is, R dyn This reflects the average impedance of the arc within a past calculation window. Since the arc voltage is approximately proportional to the arc length, and the current is related to the melting rate of the welding wire, R... dyn It is a macroscopic indicator that is highly correlated with the average arc length, and its value is stable at R. arc-static If the arc length is nearby, it indicates that the arc length is stable.

[0033] And R Delta This reflects whether the arc length is increasing or decreasing, and the rate of change. R Delta >0: Indicates the arc is lengthening; R Delta <0: indicates that the electric arc is shortening.

[0034] |R Delta The magnitude of |R represents the rate of change; a sudden increase in |R|... Delta This often indicates a severe disturbance, such as the eve of a short circuit (R). Delta (Pulse) or risk of arc interruption (R) Delta (positive pulse).

[0035] The two status indicators mentioned above, one representing the current situation and the other representing the trend, provide a comprehensive basis for subsequent intelligent decision-making.

[0036] The core of the control logic of this invention is a multimodal PID controller with state perception capability, and its decision-making process is a typical "perception-judgment-decision-execution" loop.

[0037] The controller continuously monitors R dyn and R Delta The system presets two threshold ranges: Stable region (green area): |R dyn - R arc-static | < Th1 and |R Delta | < Th delta1 The electric arc is considered to be very stable in this region.

[0038] Warning zone (yellow area): Th1 <=|R dyn - R arc-static |< Th2 or Th delta1 <= |R Delta | <Th delta2 Within this region, the electric arc is considered to have experienced minor disturbances.

[0039] Danger zone (red area): | R dyn - R arc-static | >= Th2 or | R Delta | >= Th delta2 Within this area, it is believed that the electric arc is experiencing severe fluctuations or there is a risk of short circuit / arc breakage.

[0040] Th delta1 For R Delta At a smaller threshold in the stable region, Th delta2 For R Delta Larger thresholds in the warning and danger zones.

[0041] Th1 is around R arc-static The smaller tolerance band can be ±15% of R. arc-static ; Th2 is around R arc-static The tolerance band can be ±15% to ±40% of the R value. arc-static .

[0042] When in the stable region, initiate fine-tuning mode: Control objective: To eliminate minute static deviations and achieve the highest precision arc length control.

[0043] PID parameter settings: Use a smaller proportional gain P fine Medium integral gain I fine and the extremely small differential gain D fine The integral action can gradually reduce the steady-state error to zero, while the weakened proportional and derivative actions prevent the system from overreacting to minor noise, ensuring an extremely smooth weld formation.

[0044] When entering the warning zone, the fast response mode is activated: Control objective: Quickly suppress disturbances and prevent the situation from deteriorating further.

[0045] PID parameter settings: Immediately switch to a larger proportional gain P fast and differential gain D fast Simultaneously, the integral action is frozen. The enhanced proportional action makes the controller respond more forcefully and rapidly to deviations; the enhanced derivative action allows the controller to...Delta Anticipating future trends in deviations allows for proactive correction. Freezing the integral is to prevent the integrator from accumulating excessive energy during rapid adjustments, which could lead to system overshoot or even oscillation.

[0046] When entering the danger zone, the emergency protection mode is activated: Control logic: This mode goes beyond conventional PID control. For example, if the system detects a short-circuit risk: R dyn A sharp drop, R Delta If the value is large and negative, the controller will immediately output a command to significantly reduce the current or even apply a backpressure voltage to forcibly break the liquid bridge and reduce large particle splashing. If an arc breakage risk is detected: R dyn R increases sharply Delta If the value is large and positive, it will instantly increase the voltage and current, reigniting the electric arc.

[0047] The feedforward-feedback composite control logic for the penetration state is an advanced control strategy oriented towards welding quality (penetration depth), realizing the leap from stabilizing the arc to controlling the penetration depth.

[0048] The logical principles include: In multi-layer, multi-pass welding, the penetration depth can vary even with constant electrical parameters due to changes in the groove shape and heat accumulation. This variation in penetration depth subtly affects the arc's combustion environment and, through R... dyn The long-term drift is manifested in: Insufficient penetration: The arc may burn on an incompletely melted step, causing a slight increase in the actual arc length, resulting in R... dyn It shows a slow, continuous upward trend.

[0049] Excessive penetration: The electric arc is closer to the bottom of the molten pool, increasing the pressure of the liquid metal on the arc, which may slightly reduce the arc length, resulting in R... dyn It shows a slow downward trend.

[0050] Based on this, an ideal penetration current range, determined according to process evaluation, is preset for each layer and each weld pass, specifically [I pen-min , I pen-max ].

[0051] The controller calculates R using a long period, such as 2 seconds, as a window. dyn Moving average R dyn-MA Continuous monitoring of R dyn-MA The slope.

[0052] If the system detects R dyn-MA If a positive slope (continuously rising) is maintained for multiple consecutive cycles (e.g., 3 cycles, i.e., 6 seconds), it is judged that there is a tendency for insufficient melting depth in this area.

[0053] At this point, the controller adds a positive feedforward compensation signal to the existing feedback control loop. This signal is not instantaneous, but rather gradually and incrementally (e.g., increasing by 1A each time) the global setpoint I of the welding current. set Adjust upwards until R dyn-MA The trend returns to stability, or the current reaches I. pen-max .

[0054] Conversely, if R is detected dyn-MA If the decline continues, a negative feedforward signal is added, and I is lowered. set But not lower than I pen-min .

[0055] The feedforward-feedback composite control logic mechanism enables the system to have predictive and adaptive capabilities, and can actively compensate for the penetration deviation caused by slow-changing factors such as bevel changes and heat accumulation, thus realizing intelligent control of the internal quality of welding.

[0056] This invention fully digitizes the welding process and uses data-driven continuous improvement.

[0057] The welding process database, a high-frequency data acquisition system records the following data streams at a rate of not less than 50kHz: Timestamp: accurate to milliseconds.

[0058] Instantaneous values ​​of arc voltage and current.

[0059] Calculated state assessment index (R dyn , R Delta ).

[0060] Controller mode switching event.

[0061] PID controller output and feedforward compensation.

[0062] All of this data is linked to information such as weld ID, welder number, time and date to form a complete welding process database.

[0063] Welding stability index (WSI): After each weld is completed, the system automatically analyzes its process data and calculates a welding stability index (WSI).

[0064] WSI = 100% * (1 - (T off-limit / T total )) Wherein: T total This represents the total welding time for the weld.

[0065] T off-limit The cumulative time during which the state assessment index exceeds the preset stability threshold (first threshold range).

[0066] The higher the WSI (closer to 100%), the more stable the welding process of that weld.

[0067] Association analysis and self-optimization: The system performs big data correlation analysis on the WSI of each weld and its subsequent nondestructive testing (UT, RT) results and mechanical property test results. For example: Welds with a WSI of less than 95% were found to have a significantly higher probability of showing point defects in UT inspection.

[0068] Discover a specific type of R Delta There is a strong correlation between the high-frequency jitter mode and the dispersion of the impact power value.

[0069] Based on these analyses, the system can: Optimize thresholds: Automatically adjust the boundaries of the first and second threshold ranges to better match actual quality requirements.

[0070] Optimize controller parameters: Automatically fine-tune P, I, and D parameters under different modes to achieve higher WSI and better quality performance.

[0071] This forms a closed loop from "process control" to "quality inspection" and then to "model optimization," enabling the welding process to continuously evolve.

[0072] To address the need for all-position welding of pressure steel pipes, the system incorporates position adaptive logic.

[0073] Preset modes: The system library contains three basic position modes: "flat welding", "vertical welding", and "overhead welding".

[0074] Parameter Request: Before welding, the operator selects the current mode. The controller then retrieves the complete set of preset parameters corresponding to that mode, including: R arc-static The baseline value may need to be fine-tuned for the arc length control target of vertical and overhead welding due to the influence of gravity.

[0075] For multimodal PID control parameters, the proportional and derivative actions for vertical and overhead welding need to be stronger and the response needs to be faster.

[0076] The threshold ranges for condition assessment indicators are set narrower and the requirements are stricter for vertical and overhead welding.

[0077] Intelligent Adaptation: Gravity has a significant impact on the molten pool during vertical and overhead welding. Faster response speed and more stringent stability criteria ensure that the system can quickly counteract the tendency of the molten pool to flow downwards or sag, guaranteeing the forming quality of all-position welding.

[0078] The present invention also provides an intelligent welding system for pressure steel pipes that implements the above method, comprising: Welding power supply body: Utilizes an NB500T or equivalent digital inverter GMAW welding machine. Its core consists of an IGBT / MOSFET inverter module with high-speed PWM control capability and a DSP digital signal processor, capable of receiving external analog voltage signals or digital communication commands, such as Modbus TCP / IP and EtherCAT, and completing output adjustment within one millisecond.

[0079] High-frequency data acquisition module: Voltage sensor: A high-precision, high-isolation Hall voltage sensor is used, with the measurement point between the welding torch and the workpiece, and the signal bandwidth is not less than 1MHz.

[0080] Current sensor: Also uses a high-frequency Hall current sensor, which is sleeved on the welding cable.

[0081] A / D converter: 16-bit or higher precision, sampling rate synchronously not less than 50kHz / channel.

[0082] Embedded main controller: This is the brain of the system. It can be a high-performance ARM Cortex-A series or an equivalent industrial-grade MPU. Its software logic architecture is divided into four layers: Signal processing layer: responsible for receiving raw data and performing preprocessing such as filtering and calibration.

[0083] Model calculation layer: Runs the arc equivalent circuit model in real time and calculates RA. dyn and R Delta .

[0084] Decision control layer: Executes multimodal PID control logic, feedforward-feedback composite logic, and position adaptive logic to generate control commands.

[0085] Data Management Layer: Responsible for storing, compressing, and packaging welding process data, as well as communicating with the human-machine interface.

[0086] Human-Computer Interface (HMI): Typically a high-resolution touchscreen. It displays in real time: Real-time waveforms of current and voltage.

[0087] R dyn and R Delta The trend chart.

[0088] The current controller mode is displayed as "Fine-tuning in progress".

[0089] Alarm messages, such as "arc length fluctuation exceeds limit".

[0090] Operators can use the HMI to set all welding parameters, select welding modes, call up process programs, and view historical reports.

[0091] In one specific embodiment, a circumferential weld of a Q355C steel pipe with a thickness of 22mm is taken as an example.

[0092] Before welding: Select the “Pressure steel pipe - flat welding” mode. The system will automatically call the reference parameters (I=190A, U=21V) for a 22mm thick plate.

[0093] Root pass welding: After arc ignition, the system quickly enters the fine-tuning mode, resulting in uniform back-side bonding. During the process, a 1mm local misalignment was encountered. dyn The system switched to fast response mode within 15ms due to the sudden increase in current, which pulled the arc length back and prevented a defect from forming.

[0094] Filler soldering: When the third layer is reached, the system detects R dyn The current slowly increased by 2% over 10 seconds, triggering the feedforward-feedback composite control, which gradually increased the current from 188A to 193A. Subsequent UT tests showed that the fusion of this segment was good.

[0095] Cover weld: The system is always kept in a fine-tuning mode, the weld appearance is beautiful, and the reinforcement height is controlled within 2.5±0.3mm.

[0096] Post-weld: The WSI index of the weld is 98.7%. RT and UT tests were passed, and all mechanical properties met the standards. All process data was recorded and can be used for archiving and traceability.

[0097] This invention systematically integrates advanced technologies such as arc physics models, multimodal intelligent control, and data-driven optimization into the welding process, creatively solving core challenges in pressure steel pipe welding, including quality consistency, process stability, and efficiency and cost. As a paradigm shift from experience-driven to model- and data-driven welding, it provides a solid technical guarantee for the safety and reliability of major engineering structures.

[0098] It should be noted that, where there is no conflict, the features in the embodiments of this application can be combined with each other.

[0099] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for intelligent welding of pressure steel pipes, characterized in that, Includes the following steps: Establish an equivalent circuit model of the welding arc; Real-time synchronous acquisition of instantaneous values ​​of arc voltage and welding current during the welding process; Based on the equivalent circuit model and the collected instantaneous electrical parameters, the equivalent impedance of the arc and / or its rate of change are calculated as a state assessment index reflecting the stability of the welding process and the dynamic characteristics of the molten pool. The state evaluation index is compared with a preset stability threshold range to generate a deviation signal; The deviation signal is input to the controller, which switches between different control modes according to the magnitude and trend of the deviation. The controller outputs control signals to dynamically adjust the primary control parameters of the welding power source. These primary control parameters include output current setpoints, output voltage setpoints, or pulse waveform parameters, in order to achieve closed-loop control of the arc length and penetration state.

2. The welding method according to claim 1, characterized in that, The establishment of the equivalent circuit model for the welding arc specifically includes: The arc equivalent circuit model is divided into a static operating point model and a dynamic disturbance response model. The static operating point model is used to establish a mapping relationship between arc voltage, welding current and a nominal arc resistance during the steady-state welding stage, wherein the nominal arc resistance is associated with the desired reference arc length. The dynamic disturbance response model is used to characterize the hysteresis characteristic of arc current change relative to arc voltage change by introducing an equivalent inductance when the welding process is disturbed, and to calculate dynamic impedance based on the differential relationship between instantaneous voltage and current values.

3. The welding method according to claim 2, characterized in that, The calculation of the status assessment index includes: Calculate the first state index, which is the dynamic resistance value. The dynamic resistance value is the ratio of the average arc voltage to the average welding current within one calculation cycle. Calculate the second state index, which is the resistance change trend value. The resistance change trend value is the difference or weighted average difference between the dynamic resistance value of the current calculation period and the dynamic resistance value of the previous one or more historical calculation periods. The dynamic resistance value and the resistance change trend value are used together as state assessment indicators to comprehensively judge the instantaneous state of the electric arc.

4. The welding method according to claim 3, characterized in that, The controller includes a multimodal PID controller, and the control logic of the multimodal PID controller includes: A first threshold range and a second threshold range are set, wherein the second threshold range represents a greater degree of deviation than the first threshold range; When the state evaluation index is within the first threshold range, the controller operates in fine-tuning mode. In this mode, the integral action of the controller dominates to slowly eliminate static deviations and ensure steady-state accuracy. When the state evaluation index enters the second threshold range, the controller switches to the fast response mode. In this mode, the proportional and derivative actions of the controller are enhanced, while the integral action is restricted or frozen, in order to achieve rapid suppression of arc length mutations or short-circuit risks.

5. The welding method according to claim 4, characterized in that, It also includes feedforward-feedback composite control logic for the melt-through state: Pre-determine an ideal penetration current range corresponding to the welding layer; Based on the long-term drift trend of dynamic resistance value, the change in the penetration state is judged: if the dynamic resistance value shows a continuous and slow increasing trend, it is judged that the penetration depth may be insufficient; if it shows a continuous and slow decreasing trend, it is judged that the penetration depth may be too large. When it is determined that the penetration depth may be insufficient, the control logic adds a positive feedforward compensation signal on the basis of feedback adjustment based on the state assessment index, and finely adjusts the reference setting value of the welding current towards the upper limit of the ideal penetration current range. When it is determined that the penetration depth may be too large, the control logic adds a negative feedforward compensation signal to finely adjust the reference setting value of the welding current towards the lower limit of the ideal penetration current range.

6. The welding method according to claim 1, characterized in that, During the welding process, a high-frequency data acquisition system continuously records timestamps, arc voltage, welding current, and adjustment signals output by the controller to form a welding process database. Based on the welding process database, a welding stability index is generated for each weld. This index is calculated by statistically analyzing the frequency and magnitude of the state evaluation index exceeding the preset stability threshold during the welding process. By correlating the welding stability index with the results of subsequent non-destructive testing, a correlation model between the stability of welding electrical parameters and the internal quality of the weld was established. Based on the aforementioned correspondence model, the preset threshold range of the state evaluation index and the parameters of the multimodal PID controller are dynamically optimized.

7. The welding method according to claim 1, characterized in that, The welding system is pre-set with three basic position modes: flat welding, vertical welding, and overhead welding. Before welding begins, the operator selects the current welding position mode; The controller calls different preset parameter combinations according to the selected position mode. The parameter combinations include at least the control parameters of the multimodal PID controller, the threshold range of the state evaluation index, and the reference setting value of the welding current / voltage. Specifically, for vertical and overhead welding modes, the stability threshold range of the state evaluation index is set to be more stringent than that for flat welding, and the controller response speed is set to be faster to cope with the additional effects of gravity on the molten pool.

8. A smart welding system for pressure steel pipes, used to implement the smart welding method for pressure steel pipes according to any one of claims 1-7, characterized in that, include: The main body of the welding power supply is a digital inverter welding machine, which can receive external control signals and quickly adjust the output; The high-frequency data acquisition module has its signal input terminal connected to the voltage sensor and current sensor of the welding circuit, and its signal output terminal connected to the embedded main controller, with a sampling frequency of not less than 50kHz. Embedded main controller; The human-machine interface is used to display real-time electrical parameter curves, status evaluation indicators, alarm information, and allows operators to input welding parameters and modes.

9. The welding system according to claim 8, characterized in that, The logical architecture of the embedded host controller includes: The signal processing layer is used to digitally filter and calibrate the acquired raw voltage and current signals; The model calculation layer is used to execute the equivalent circuit model in real time and calculate the state evaluation index. The decision control layer is used to run multimodal PID control logic and generate control signals; The data management layer is used to handle the storage, retrieval, and reporting of welding process data.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the intelligent welding method for pressure steel pipes as described in any one of claims 1-7.

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