A PID-based intelligent throttle control method and device

Abstract

The present application relates to the technical field of PID control, and particularly relates to a PID-based intelligent gas-saving control method and device. The method comprises the following steps: loading a welding current-target flow rate relationship model and initializing PID parameters; then collecting welding current in real time and calculating corresponding target flow rate; then comparing the target flow rate with the actual flow rate to obtain an error signal and generating a control output by PID control; then converting the control output into an electrically-controlled proportional valve opening degree adjustment signal to realize dynamic adjustment of the protective gas flow rate; finally, cyclically executing current input, target generation, error calculation and valve regulation to realize real-time closed-loop gas-saving control of the welding process. The present application realizes fine real-time intelligent control of the protective gas through welding condition identification, target flow rate modeling and PID closed-loop adaptive regulation, not only improving welding stability and weld quality, but also significantly reducing gas consumption and enhancing the responsiveness and reliability of device operation.

Description

Technical Field

[0001] This invention relates to the field of PID control technology, and in particular to a PID-based intelligent fuel-saving control method and device. Background Technology

[0002] In gas-shielded welding processes (including MIG / MAG welding, TIG welding, pulsed welding, and their derivative processes), shielding gases such as argon, carbon dioxide, or mixed gases play a crucial role in isolating the weld from air, preventing oxidation, stabilizing the arc, and improving weld formation. An appropriate shielding gas flow rate can not only effectively cover the molten pool area and prevent the intrusion of impurities such as oxygen and nitrogen, but also reduce the incidence of welding defects such as porosity, cracks, and slag inclusions, thereby improving weld quality and welding stability.

[0003] However, in existing technologies, most welding equipment uses a fixed-flow gas control method, where the operator presets the shielding gas flow rate based on experience before welding, and the flow rate remains constant during the welding process. This method is simple in structure and low in cost, but it cannot be adjusted according to real-time changes in welding conditions such as welding current, heat input, and arc morphology. When the welding current is low or in the non-welding standby stage, the gas flow rate still maintains a high output, resulting in a large waste of shielding gas; while in the state of high current or strong arc fluctuation, the fixed gas flow often has insufficient shielding capacity, easily causing gas turbulence or air entrainment, thus leading to weld protection failure. Summary of the Invention

[0004] Therefore, it is necessary to provide a PID-based intelligent fuel-saving control method and device to solve at least one of the above-mentioned technical problems.

[0005] To achieve the above objectives, a PID-based intelligent fuel-saving control method is provided, the method comprising the following steps:

[0006] Step S1: Load the preset welding current-target flow rate relationship model and initialize the proportional coefficient, integral coefficient, and derivative coefficient of the PID controller;

[0007] Step S2: Obtain the real-time welding current value and input the welding current value into the welding current-target flow rate relationship model to calculate the target shielding gas flow rate value;

[0008] Step S3: By comparing the target protective gas flow rate with the actual protective gas flow rate, confirm the flow rate error signal; input the flow rate error signal into the initialized PID controller to obtain the protective gas control output;

[0009] Step S4: Convert the protective gas control output into an adjustment signal to drive the opening of the electronically controlled proportional valve, and continuously control the opening of the electronically controlled proportional valve based on the adjustment signal, so that the actual flow rate of the protective gas approaches the target protective gas flow rate.

[0010] Step S5: Repeat steps S2-S4 to perform a real-time closed-loop gas control process driven by welding current.

[0011] The present invention has the following beneficial effects:

[0012] I. By introducing a welding current-target flow rate relationship model and a PID closed-loop control mechanism, real-time dynamic adjustment of the shielding gas flow rate is achieved, enabling the shielding gas flow rate to accurately match the current requirements at different welding stages. Compared with traditional fixed flow rate or stepped flow adjustment methods, this solution can significantly improve the accuracy of shielding gas control, making the actual gas flow response more timely, continuous, and stable, reducing weld defects caused by fluctuations in the molten pool atmosphere, and effectively improving the consistency and quality of the welding process.

[0013] II. By analyzing the effectiveness of welding current signals and identifying welding conditions, differentiated and more adaptive target flow rate control strategies can be generated in different stages, such as non-welding standby, transient arc ignition, and steady-state welding. In the non-welding state, this method can intelligently determine whether a low-amplitude gas curtain needs to be maintained to prevent gas backflow or moisture absorption and oxidation, thereby avoiding unnecessary gas waste. In the arc ignition stage, this scheme calculates the shielding gas compensation requirement in advance based on the current change characteristics, which can prevent weld oxidation caused by insufficient gas at the moment of arc ignition. In the steady-state stage, the model output and PID regulation work together to achieve dynamic balance in the gas control process, further improving control stability and flexible response capability.

[0014] Third, by employing a continuous valve control and iterative adjustment signal update mechanism, a real-time adaptive gas regulation capability is established, enabling the device to maintain a flow rate close to the target value even under the influence of disturbances, sensing errors, and response delays. Simultaneously, due to the optimizable and automatically correctable PID controller parameters, this solution possesses long-term operational stability, environmental adaptability, and hardware compatibility. This not only reduces the cost of protective gas usage but also extends the service life of actuators such as the electronically controlled proportional valve, demonstrating significant industrial application value and high energy efficiency. Attached Figure Description

[0015] Figure 1 This is a flowchart illustrating the steps of a PID-based intelligent fuel-saving control method.

[0016] Figure 2 for Figure 1 A detailed flowchart illustrating the implementation steps of step S4.

[0017] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0018] The technical method of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0019] Furthermore, the accompanying drawings are merely illustrative of the invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor methods and / or microcontroller methods.

[0020] It should be understood that although the terms "first," "second," etc., may be used herein to describe various units, these units should not be limited by these terms. These terms are used merely to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, a first unit may be referred to as a second unit, and similarly, a second unit may be referred to as a first unit. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0021] To achieve the above objectives, please refer to Figures 1 to 2 A PID-based intelligent fuel-saving control method, the method comprising the following steps:

[0022] Step S1: Load the preset welding current-target flow rate relationship model and initialize the proportional coefficient, integral coefficient, and derivative coefficient of the PID controller;

[0023] In this embodiment of the invention, to achieve an adaptive response of the shielding gas flow rate to changes in welding current, a preset welding current-target flow rate relationship model is first loaded into the control module. This relationship model is derived from data obtained during the equipment production phase based on multiple batches of welding tests, including welding current, arc stability, penetration depth, and porosity probability, and is stored in the non-volatile storage area of ​​the control chip. The model records the target shielding gas flow rate required for the corresponding current range in the form of piecewise curves or lookup tables, and is automatically retrieved by the control module after the device is started.

[0024] After loading is complete, the PID control logic initialization phase begins. The control module calls the corresponding parameter template based on the welding process type (including carbon steel welding, stainless steel welding, and aluminum welding, etc.) and initializes the proportional control coefficient, integral control coefficient, and derivative control coefficient respectively. The proportional coefficient is used to quickly respond to changes in welding current, the integral coefficient is used to correct small long-term deviations during the welding process, and the derivative coefficient is used to suppress transient misadjustments caused by rapid changes.

[0025] After initialization, the control module executes an internal parameter verification program to confirm that the PID parameters are not out of bounds, have abnormal data formats, or are missing. Based on the initial welding current value collected by the sensor, the module generates the first target flow value through the model, which serves as the initial expected output of the PID controller.

[0026] In a preferred embodiment, to avoid unstable arc ignition during the first run due to large flow rate adjustments, the control module adopts a soft-start initialization strategy. That is, before the PID control is officially run, the protective gas flow rate is gradually increased in a step-by-step manner, and the arc shape change trend caused by the flow rate change is recorded in real time to ensure stable protective gas output.

[0027] Step S2: Obtain the real-time welding current value and input the welding current value into the welding current-target flow rate relationship model to calculate the target shielding gas flow rate value;

[0028] In this embodiment of the invention, after executing step S1, the real-time welding current acquisition stage begins. The control module periodically calls the current acquisition unit, which uses a Hall sensor or sampling resistor as the detection element to measure the instantaneous current in the welding circuit at a fixed sampling period (e.g., 5ms to 20ms). To avoid the influence of welding arc fluctuations on a single sampling, a multi-point sampling strategy is adopted in the acquisition process, that is, at least 3 to 5 sets of current data are continuously acquired within a single sampling period, and the average value of the multiple sets of sampled data is processed to obtain the real-time welding current value at the current moment.

[0029] After obtaining the real-time welding current value, the control module inputs this current value into a preset welding current-target flow rate relationship model for lookup or interpolation calculation to obtain the corresponding target shielding gas flow rate value. When the model is a discrete interval lookup table type, the control module directly calls the standard target flow rate parameter for the corresponding current segment; when the model is a continuous curve type, the control module calls the interpolation algorithm based on the interval where the current value is located to generate a more accurate target shielding gas flow rate value, thereby ensuring continuous and smooth flow rate adjustment.

[0030] In another embodiment, to reduce the interference of instantaneous current fluctuations caused by welding arc jitter or spatter on flow rate adjustment, a fluctuation suppression strategy is implemented before calculating the target flow rate value. This strategy includes historical data sliding window filtering, threshold fluctuation ignoring, and current stability determination. If the real-time current fluctuation range is within the set tolerance, the existing target flow rate value is kept unchanged; if the current change exceeds the tolerance threshold, the target flow rate value is adjusted according to the current change trend to ensure timely control action and avoid misadjustment.

[0031] In a preferred embodiment, after the target gas flow rate value is generated, the control module compares the value with the target flow rate generated in the previous cycle and executes a change restriction strategy to ensure that the change in the target flow rate does not exceed the set maximum allowable step range, thereby avoiding sudden changes in the protective gas flow rate that could affect the weld formation quality.

[0032] Step S3: By comparing the target protective gas flow rate with the actual protective gas flow rate, confirm the flow rate error signal; input the flow rate error signal into the initialized PID controller to obtain the protective gas control output;

[0033] In this embodiment of the invention, after obtaining the target protective gas flow rate value generated in step S2, the actual flow rate value of the current protective gas is collected by a flow sensor configured in the gas path. This flow sensor can be a thermal mass flow meter, a Coriolis mass flow sensor, or a diaphragm gas flow meter. The sampling frequency is set to 10Hz to 50Hz, and a dynamic mean filtering method is used to smooth the continuously collected instantaneous data to obtain stable and reliable real-time flow rate measurement results.

[0034] The control module calculates the difference between the real-time collected actual flow rate value and the target protective gas flow rate value to obtain the current flow rate error signal. When the absolute value of the error signal is lower than the set small fluctuation tolerance threshold (e.g., ±0.2 L / min), the current adjustment effect is considered stable. At this time, no control output action is executed, and the error trend is recorded in the error history sample for subsequent predictive adjustment. When the error signal exceeds the threshold range, the PID calculation logic is triggered.

[0035] During PID automatic adjustment, the control module sends the flow rate error signal as input to the PID controller initialized in step S1. The PID controller performs real-time calculations on the error signal according to the proportional, integral, and derivative terms. The proportional term is used to quickly correct the current deviation, the integral term is used to eliminate long-term steady-state errors, and the derivative term is used to suppress control oscillations caused by rapid changes in error, thereby generating a protective control output.

[0036] In another embodiment, to prevent excessive changes in the PID output from causing frequent actuation of the gas valve body regulating mechanism, the PID calculation results are processed by an output limiting module. This module includes output limiting, rate of change limiting, and dead zone setting. For example, when the rate of change of the PID output exceeds a preset upper limit, the output is automatically adjusted to the maximum step value within the executable range to ensure a smooth and oscillating protective gas flow rate regulation process, while simultaneously improving the service life of the valve body and actuator.

[0037] In a preferred embodiment, an adaptive PID parameter fine-tuning strategy is executed synchronously. This strategy fine-tunes the proportional, integral, and derivative coefficients in real time based on the error change trend, error correction speed, and actuator response, thereby adapting to actual application conditions such as changes in the weld pool state, welding mode switching (such as TIG / MIG switching), and gas supply pressure fluctuations, ensuring that control response speed, steady-state error, and regulation stability are in an optimal balance.

[0038] Step S4: Convert the protective gas control output into an adjustment signal to drive the opening of the electronically controlled proportional valve, and continuously control the opening of the electronically controlled proportional valve based on the adjustment signal, so that the actual flow rate of the protective gas approaches the target protective gas flow rate.

[0039] In this embodiment of the invention, the protective gas control output obtained in step S3 is first normalized to obtain an adjustment signal suitable for driving the electronically controlled proportional valve. Normalization includes mapping the control output to the physical quantities required by the valve drive interface, such as normalizing the control output to an opening command of 0%–100%, or further converting it into a corresponding analog drive signal (e.g., a 4 mA–20 mA current signal or a 0 V–5 V voltage signal), and a duty cycle for PWM drive (e.g., a 0%–100% duty cycle). A set of valve characteristic parameters (including model, minimum controllable opening, maximum opening, dead zone, and hysteresis) is maintained within the control module for subsequent linearization and limiting processing.

[0040] In a preferred embodiment, for scenarios using current-type proportional valves, the control module converts the normalized opening command into a current output of 4 mA to 20 mA; for valves using voltage input or PWM drive, it converts it into the corresponding voltage range or PWM duty cycle. The recommended frequency for the PWM drive is between 1 kHz and 10 kHz to balance response speed and actuator lifespan. When using PWM drive, the control module performs low-pass filtering simulation on the output signal before generating the duty cycle to reduce the impact of high-frequency noise on the valve body.

[0041] To overcome the nonlinear flow characteristics and dead zone effect of proportional valves, a valve linearization table or calibration lookup table (valve characteristic mapping table) is used in the mapping step. This table is obtained from factory calibration or field calibration. Before mapping the normalized command to the actual drive quantity, the control module first looks up the corresponding drive reference in the table, and then makes minor corrections based on feedback from real-time pressure and flow sensors, so that the relationship between the valve's output flow rate and the desired opening degree is approximately linear. Calibration can be obtained at the factory or during commissioning through multi-point step tests, for example, by collecting actual flow rates at five opening points: 0%, 25%, 50%, 75%, and 100%, and fitting the calibration table.

[0042] While sending the drive signal, the control module uses a closed-loop sampling strategy to monitor the proportional valve's adjustment process. The recommended closed-loop sampling period is 50 ms to 200 ms (corresponding to a control frequency of 5 Hz to 20 Hz). Within each control cycle, the following steps are executed: read the actual flow rate value from the flow sensor, read the pressure sensor and valve displacement (or current / voltage feedback) values, calculate the current error, and record historical errors for subsequent PID or adaptive algorithm calculations. If a fast-response condition is required, the sampling period can be reduced to 20 ms, but the load on the controller and bus communication must be considered.

[0043] To ensure smooth and safe regulation, the control module implements multiple protection and constraint measures before and after the output drive signal, including but not limited to: output limiting: limiting the drive quantity to the maximum / minimum allowable drive range of the valve (e.g., current not exceeding 25 mA, voltage not exceeding 12 V); rate limiting: limiting the maximum change value of the drive signal per cycle to prevent drastic valve jumps (e.g., maximum duty cycle change per cycle not exceeding 5%); dead zone compensation: feedforward compensation for the valve's inherent dead zone, for example, superimposing a small amplitude pulse when the control command crosses the dead zone boundary to overcome static friction; anti-integral saturation (anti-windup): injecting constraints into the PID integral term or adopting an integral backoff mechanism when the output is limited to avoid integrator accumulation leading to overshoot.

[0044] To improve control accuracy, the control module can employ a closed-loop control strategy with a feedforward element: in addition to the conventional PID output, a feedforward correction is calculated based on the current gas supply pressure, historical flow response curves, and valve characteristics, and then superimposed on the PID output. This allows for rapid approximation of the target flow rate during sudden input changes (such as sudden changes in welding current), thus shortening the settling time constant. The coefficient of the feedforward can be determined through online identification or commissioning experiments.

[0045] During execution, the flow response is continuously monitored and convergence is determined: when the absolute deviation between the actual flow rate and the target flow rate is lower than the steady-state tolerance (e.g., ±0.2 L / min) and the duration exceeds the steady-state holding threshold (e.g., 2 s), the control is considered to have converged; if convergence is not achieved within the maximum allowable adjustment time (e.g., 5 s to 10 s), the fault handling process is triggered, including recording fault logs, implementing degradation strategies, or issuing manual intervention alarms.

[0046] Safety and redundancy design includes: when a flow sensor malfunction is detected (e.g., no signal, abnormal jitter, or readings outside the physical range) or an abnormal response from the electronically controlled proportional valve (e.g., a significant discrepancy between the drive value and the feedback displacement), the control module can switch to a preset safety strategy. This could involve switching the valve to a predefined safe opening (closed or maintained at a safe ventilation rate) and sending an alarm message to the host computer or operator. Simultaneously, all critical data (control commands, actual flow rate, pressure, valve feedback, and fault events) is recorded for post-event analysis and performance optimization.

[0047] Ultimately, the control module uses the closed-loop control operation data for adaptive optimization: it records the input and output data for each adjustment in history and periodically performs online identification or least squares fitting to update the valve linearization table, feedforward coefficients, and PID parameters, thereby maintaining optimized regulation characteristics and reducing the frequency of manual calibration in long-term operation.

[0048] Step S5: Repeat steps S2-S4 to perform a real-time closed-loop gas control process driven by welding current.

[0049] In this embodiment of the invention, the intelligent real-time closed-loop gas control process driven by welding current is completed by cyclically executing steps S2-S4.

[0050] Preferably, before inputting the welding current value into the welding current-target flow rate relationship model to calculate the target shielding gas flow rate value in step S2, the following steps are also included:

[0051] The effectiveness of the working condition is determined based on the welding current value, which includes identifying the amplitude range, rate of change, duration and noise stability of the welding current.

[0052] Determine whether the current welding current value belongs to an effective welding state based on the effectiveness judgment of the working condition;

[0053] Welding conditions are divided by effective welding states to obtain non-welding standby state, transient arc ignition state and steady-state welding state.

[0054] Based on the steady-state welding condition, the welding current value is directly input into the welding current-target flow rate relationship model to calculate the target shielding gas flow rate value.

[0055] In one embodiment, to ensure the validity and reliability of the data input to the welding current-target flow rate relationship model, before inputting the real-time collected welding current into the model to calculate the target shielding gas flow rate value, a welding condition validity determination and condition classification process is first performed. The specific process is as follows:

[0056] The current welding current value is acquired through a current acquisition module with a preset sampling period of 10ms to 30ms, and compared and analyzed with historical current data from at least 5 to 20 sampling periods. The analysis includes current amplitude range determination, rate of change calculation, current stability identification, and noise interference feature detection. For example, when the acquired current value is lower than a set threshold (e.g., ≤1A) and lasts for more than 200ms, the condition is determined to be a non-welding standby state; when the current rises rapidly from zero at a rate greater than a set speed threshold (e.g., ≥50A / ms) but has not yet entered the steady-state range, it is determined to be a transient arc initiation state; if the current waveform enters a set steady-state range (e.g., the peak range for pulse welding or the stable range for flat welding) and continues for more than a given stable identification time (e.g., ≥300ms) and the rate of change is less than a set dynamic threshold (e.g., ≤10A / ms), the current condition is confirmed to be a steady-state welding state.

[0057] After classifying the working conditions, different processing logics are executed based on different working conditions. Specifically: for non-welding standby states, the welding current-target flow rate relationship model is not invoked; instead, the shielding gas flow rate is maintained within the holding pressure or low-consumption standby range (e.g., 0.5–1.5 L / min). For transient arc ignition states, the model's start-up correction mode is adopted, and a high-response adjustment strategy is activated for a short period to ensure that the shielding gas reaches the target flow rate range predicted by the model in the starting region (e.g., 3–6 L / min) in advance, thereby reducing the oxidation risk during the arc ignition stage. For steady-state welding states, the real-time welding current value is directly input into the welding current-target flow rate relationship model, and the corresponding target shielding gas flow rate value is calculated based on the model. For example, when the welding current is 120A, the model outputs a target shielding gas flow rate value of 9.2 L / min.

[0058] Preferably, the welding condition classification based on effective welding conditions includes:

[0059] Identify the time periods during which welding actions occur and do not occur based on the amplitude range of the welding current, and confirm the time range of the non-welding standby state.

[0060] By utilizing the characteristics of the rate of change and duration of welding current, the start and end frames of the transient arc ignition state are identified, and the time interval of the transient arc ignition state is obtained.

[0061] Based on the continuous characteristics of welding current in terms of amplitude, rate of change and noise stability, the time interval of steady-state welding is determined.

[0062] Welding conditions are divided based on the time division results, resulting in non-welding standby state, transient arc initiation state, and steady-state welding state.

[0063] In one embodiment, to achieve dynamic adaptive control of the welding shielding gas flow, it is necessary to first divide the real-time welding conditions. Welding current data is continuously collected at a fixed sampling period (e.g., 10ms), and the collected current signals are buffered in a sliding time window of 1 to 3 seconds. The current amplitude, rate of change, and signal waveform stability within the window are calculated and analyzed to determine the welding state at different stages.

[0064] Welding activity is identified based on the range of welding current amplitude. When the real-time current value remains below the set current recognition threshold (e.g., ≤2A) for more than 200ms, it is determined that no welding activity occurred during that period, and this period is defined as the non-welding standby state range. This stage typically corresponds to the shielding gas being in a low-consumption maintenance flow state.

[0065] Subsequently, the transient arc initiation state interval is identified by calculating the current change rate and current sustaining time. When a rapid increase in current is detected within one sampling period (e.g., change rate ≥ 50 A / ms) and it enters the effective current range (e.g., ≥ 20 A), but its waveform still exhibits significant fluctuations and has not reached the stable range limit, this moment is recorded as the starting frame of the transient arc initiation state. When the current change rate gradually decreases to a set stable range (e.g., ≤ 10 A / ms) and remains continuously stable for more than a preset time threshold (e.g., ≥ 300 ms), this moment is recorded as the ending frame of the transient arc initiation state, and the complete time interval of the transient arc initiation state is determined.

[0066] After identifying the transient phase, the mean square fluctuation of the welding current, short-time rate of change, and noise disturbance level are further calculated. When the current amplitude is detected to be within a stable operating range (e.g., 80A to 150A or its corresponding set range) and the rate of change remains in a low fluctuation range (e.g., ≤5A / ms), while the noise amplitude remains within the set stable threshold (e.g., ≤±2A), and continues to exceed the set time condition (e.g., 300 to 800ms), this time period is defined as the steady-state welding state range.

[0067] Finally, the analysis results based on time period division are integrated to generate a labeled sequence of three welding conditions: non-welding standby state, transient arc ignition state, and steady-state welding state. This sequence is used to guide subsequent prediction of welding gas flow rate, selection of PID control response time, and call of model transition processing logic, thereby achieving precise zonal control of welding shielding gas.

[0068] Preferably, the calculation of the target protective gas flow rate value based on the non-welding standby state further includes:

[0069] Based on the non-welding standby state, the continuous events of the state and the stability of current fluctuations are obtained;

[0070] The gas release trend is analyzed based on the continuous events and the stability of current fluctuations. The protective gas retention requirement in the non-welding standby state is confirmed by the analysis results. The protective gas retention requirement is used to maintain the residual protective gas curtain inside and around the welding torch.

[0071] The reduction in the target protective gas flow rate is calculated based on the protective gas retention requirement, resulting in the reduced target protective gas flow rate.

[0072] In one embodiment, when it is determined that the current welding process is in a non-welding standby state, the control module first records the duration of this state and, based on the sampling period (e.g., 10ms to 20ms), uses a sliding window method to statistically analyze the fluctuation parameters of the welding current over a continuous period. The mean square fluctuation amplitude, maximum fluctuation amplitude, and short-time rate of change are extracted from the collected current signal to quantify the stability of the current signal fluctuation. For example, if the welding current value remains at 0A or below a set noise threshold (e.g., ≤1.5A) for 500ms continuously, and the mean square fluctuation amplitude meets the stable range condition (e.g., ≤0.3A), it is confirmed that this period belongs to a non-welding process with stable current.

[0073] After determining the current stability, the release trend of the shielding gas inside the welding torch and at the nozzle exit area is analyzed based on the duration of the non-welding standby state and the ambient gas diffusion conditions. The release trend analysis includes: estimating the diffusion rate of the residual gas flow at the nozzle exit, determining the amount of gas trapped due to the resistance of the welding torch cavity structure, and making dynamic corrections based on ambient airflow disturbances (such as wind speed compensation parameters and the convection effect of residual heat from the welding arc). If the current state is detected for a short duration (e.g., ≤2 seconds), the shielding gas still has a certain residual gas curtain, maintaining a low release rate; if the duration is long (e.g., ≥5 seconds), it is determined that the residual shielding gas has basically dissipated, at which point the shielding requirement increases to ensure that the surrounding environment still has an effective inert shielding atmosphere when welding restarts.

[0074] Subsequently, based on the venting trend analysis results, the shielding gas retention requirement value for the non-welding standby state is generated. This requirement value is used to maintain a minimum but continuous shielding gas flow to form a low-speed gas curtain to avoid oxidation contamination and backflow of moisture inside the welding torch. For example, under the condition that the welding torch nozzle specification is Φ12mm and the shielding gas type is argon, the basic retention flow rate corresponding to the shielding requirement can be set to... It can also be fine-tuned according to working conditions.

[0075] Finally, the calculated protective gas retention requirement is used as a reduction factor in the baseline target flow rate model to calculate the reduction in the original target protective gas flow rate. For example, when the baseline target flow rate is 12 L / min and the protection requirement reduction ratio is 60%, the reduced target protective gas flow rate is adjusted to approximately 4.8–5.2 L / min. The calculation results are used as the target protective gas flow output parameters in the non-welding standby state and input to the PID controller for subsequent proportional valve opening adjustment.

[0076] Preferably, the analysis of gas release trends based on sustained events and the stability of current fluctuations includes:

[0077] The duration of the discharge behavior is determined based on the state persistence event;

[0078] The real-time welding current during the discharge cycle is smoothed to construct a stable fluctuation curve;

[0079] By analyzing the local fluctuation direction, fall amplitude, and continuous change pattern of the fluctuation stability curve through the current fluctuation stability degree analysis, and mapping them one by one with the corresponding state continuous events, the current-gas correlation strength is obtained.

[0080] The trend of gas release was confirmed by the trend change in the current-gas correlation strength.

[0081] In one embodiment, when the welding condition is detected to be in a non-welding standby state, the control module first records the current state duration event, namely the start time of the state, the current cumulative duration, and the corresponding timestamp sequence. For example, with a sampling period of 50ms, if the welding current does not exceed the preset action threshold of 2A within 20 consecutive sampling periods, the time period is automatically determined to be a valid non-welding judgment interval, and the cumulative duration of the state duration event is continuously updated.

[0082] Subsequently, the effective period of the protective gas venting behavior is determined based on the sustained event. The effective period is consistent with the sampling frequency, such as 1s, 2s, or a dynamically changing period interval, and serves as the window boundary condition for subsequent analysis. Within the effective period, real-time welding current data is acquired. This current sequence is processed using sliding window mean filtering, exponential smoothing filtering, or Savitzky-Golay filtering to eliminate measurement noise and environmental interference, generating a corresponding fluctuation stability curve. This fluctuation stability curve reflects the true energy change characteristics during gas switching, rather than instantaneous signal spikes.

[0083] After generating the stable fluctuation curve, based on the local fluctuation structure of the curve, the local fluctuation direction (rising, falling, or stable) and the magnitude of the pullback (e.g., Variations within a certain range and continuous variation patterns (such as gradual decay patterns, step-like variation patterns, or completely stationary patterns). These characteristics are mapped one-to-one with the state-duration events corresponding to the action period, for example:

[0084]

[0085] Through mapping analysis, a current-gas correlation strength is generated for each operating cycle. This correlation strength reflects the degree of logical coupling between changes in the current signal and the protective gas release behavior. The correlation strength level can be represented by three categories: high, medium, and low, with quantified value ranges, for example... Continuous parameters within an interval.

[0086] Finally, based on the trend of the current-gas correlation strength over time, the corresponding gas release trend is confirmed. For example, if the correlation strength shows a rapid decreasing trend, it is determined that the shielding gas release rate is relatively fast, and the minimum retention flow rate needs to be increased; if the correlation strength remains moderate and gradually tends to stabilize, it is determined that the gas release is in a slow decay state; if the correlation strength remains low for a long time, it is determined that the shielding gas has been basically released, and a low flow rate maintenance mode needs to be entered. After the analysis is completed, the release trend is used as the input parameter for the subsequent target shielding gas flow rate calculation and PID dynamic correction module to ensure that the shielding gas supply can still meet the welding environment requirements under the premise of energy saving.

[0087] Preferably, the calculation of the target protective gas flow rate based on the transient arc initiation state further includes:

[0088] Based on the rise of the welding current during the transient arc initiation period, the current change trend towards stabilization is identified.

[0089] Based on the fluctuation amplitude and continuity of change in the current change trend, the transient arc initiation state is divided into the initial disturbance segment, the transitional stabilization segment, and the near-steady-state segment.

[0090] The target protective gas flow rate value for the transient arc initiation state is generated by analyzing the stage response relationship between the initial disturbance stage, the transition stabilization stage, and the near-steady-state stage.

[0091] In one embodiment, once the welding current detection unit identifies that the current welding process has entered a transient arc ignition state, the controller begins to record and analyze real-time welding current change data during the transient arc ignition period. The criteria for determining the transient arc ignition state can be set as threshold requirements corresponding to the customer's welding machine model and welding material. For example, when the welding current rapidly jumps from 0A to ≥15A and exhibits non-stationary fluctuations between 100ms and 350ms, the current state is marked as the transient arc ignition stage, and the adaptive target control mechanism is activated.

[0092] Subsequently, real-time sampling values ​​of the welding current were continuously acquired at a sampling period of 10ms, and the current variation trend was analyzed using a sliding calculation method. The direction of change, growth slope, peak point position, and continuity characteristics in the current variation curve were calculated and extracted, such as detecting whether the current exhibited obvious peaks, repeated small declines, or a monotonic trend of continuous growth. Based on the analysis results of the above variation trends, the transient arc initiation state was divided into three stages: the initial disturbance stage, the transitional stabilization stage, and the near-steady-state stage, and different target gas flow rate generation strategies were executed for each stage.

[0093] The initial disturbance phase is defined as the time period from the detection of the welding arc to the initial stable decline of the current, typically ranging from 50 to 120 ms initially. During this phase, the current fluctuation amplitude is usually large, for example, the fluctuation range can reach [missing value]. Once the control system recognizes this characteristic, it increases the instantaneous flow rate to a higher value to establish a stable protective gas curtain in the early stages of molten metal droplet formation. For example, the target flow rate is set to 1.3 times the calibrated baseline value, and the proportional valve response speed is prioritized.

[0094] When the fluctuation of the detected current decreases to a smaller range (e.g., fluctuation range ≤ ±8A) and the trend shows periodic buffering or gradually smoothing, the current state is identified as entering the transitional stabilization phase. During this phase, the control strategy gradually transitions the target gas flow rate from the higher output of the initial disturbance phase to the steady-state target output. For example, a linear gradual reduction method or a step adjustment method can be used to make the shielding gas flow produce a response that converges stepwise as the welding state gradually stabilizes. During this phase, the gas flow rate is generally controlled at the calibrated target value. The range is doubled to balance protective performance with gas saving effect.

[0095] When the welding current fluctuation stabilizes within a preset stable range (e.g., within ±3A) and continues to exceed a set sampling period threshold (e.g., for ≥80ms), the current state is determined to have entered a near-steady-state phase. Upon entering this phase, the control system gradually adjusts the target shielding gas flow rate to a steady-state target value that matches the welding current-target flow rate relationship model, and executes a smoothing filtering strategy to avoid gas flow output fluctuations caused by control command switching.

[0096] Finally, the target flow rate output curves corresponding to the above three stages are combined to generate the corresponding transient arc ignition state flow rate response control command, which is used as the input of the PID closed-loop control module to achieve dynamic optimal shielding gas control in the transient welding process.

[0097] Preferably, the target protective gas flow rate value for the transient arc initiation state is generated by analyzing the stage response relationship between the initial disturbance stage, the transitional stabilization stage, and the near-steady-state stage, including:

[0098] Determine the response interval corresponding to the initial disturbance segment, and generate the initial compensation velocity based on the fluctuation rhythm of the current change within the response interval;

[0099] By identifying the directional continuity and amplitude attenuation trend of current change in the transition stabilization phase, the initial compensation flow rate is reduced to obtain the first adjusted compensation flow rate.

[0100] The first adjustment compensation flow rate is adjusted based on the gradual trend of current change in the near steady-state range, and the second adjustment compensation flow rate is obtained.

[0101] The target protective gas flow rate value for the transient arc initiation state is confirmed based on the second adjustment compensation flow rate.

[0102] In one embodiment, when the welding system detects that the welding process has entered a transient arc initiation state, the controller begins to analyze the current changes in stages and generates corresponding protective gas flow rate control values ​​based on the current characteristics of different stages.

[0103] First, the controller divides the welding current curve during the transient arc ignition period into three stages based on a pre-set time window and current threshold: the initial disturbance stage, the transition stabilization stage, and the near-steady-state stage. The division rules can be determined based on the rate of increase, fluctuation amplitude, and duration of the welding current. For example, the initial disturbance stage is the period when the current rises rapidly and fluctuates significantly; the transition stabilization stage is the period when the current fluctuation amplitude gradually decreases and its direction is continuous; and the near-steady-state stage is the period when the current fluctuation amplitude is gentle and tends to stabilize.

[0104] During the initial disturbance phase, the controller analyzes the fluctuation rhythm of the welding current, including the amplitude and frequency changes between peaks and troughs. For example, if the current fluctuation amplitude is ±20 A and the period is approximately 50 ms, it indicates a rapid increase in shielding gas demand. Based on the fluctuation rhythm, the controller generates an initial compensation flow rate, increasing the shielding gas flow rate to the calibrated value. This is to ensure that a stable protective gas curtain can be formed in the early stages of droplet formation.

[0105] After entering the transition and stabilization phase, the continuity of the current change direction and the amplitude decay trend are analyzed. For example, the current fluctuation amplitude gradually decreases to ±8 A and shows a continuous downward trend. Based on the amplitude decay rate, the controller gradually reduces the initial compensation flow rate generated in the initial disturbance phase to match the protective gas flow rate with the gradual stabilization of the current. The adjustment method can adopt a linear reduction or a segmented reduction strategy to obtain the first adjustment compensation flow rate, avoiding waste caused by excessive gas flow rate, while still ensuring the integrity of the gas curtain.

[0106] Once the current enters the near-steady-state range, a smooth current fluctuation is detected, and the duration reaches a preset threshold (e.g., ≥80ms). At this point, the shielding gas demand further decreases. Based on the smooth trend near the steady-state range, the controller makes a final correction to the first adjustment compensation flow rate, ensuring that the shielding gas flow rate approaches the steady-state target value set in the welding current-target flow rate relationship model, thus obtaining the second adjustment compensation flow rate. During this stage, filtering or buffering is simultaneously applied to smooth the shielding gas output and prevent sudden flow rate changes from disturbing the welding zone.

[0107] The second adjustment compensation flow rate is used as the target shielding gas flow rate value during the transient arc initiation stage, and serves as the input command for the PID controller to execute closed-loop regulation. Through the above-mentioned staged analysis and adjustment, the shielding gas flow is rapidly established in the initial stage of arc initiation, and then smoothly transitions to a steady-state value, achieving gas shielding optimization and resource conservation in the transient welding process.

[0108] As an example of the present invention, reference is made to Figure 2 As shown, step S4 in this example includes:

[0109] Step S41: Format and convert the protective gas control output to obtain the adjustment signal;

[0110] Step S42: Based on the difference between the adjustment signal and the proportional valve opening of the electronically controlled proportional valve, a continuous opening adjustment process is executed, wherein the continuous opening adjustment process includes smoothing, gradually increasing and dynamically correcting the adjustment signal;

[0111] Step S43: During the opening change of the proportional valve, the actual flow rate of the target protective gas is collected and compared in real time. When there is a deviation trend between the actual flow rate and the flow rate of the target protective gas, the micro-amplitude dynamic iterative update of the adjustment signal is automatically triggered to obtain the iterated adjustment signal.

[0112] Step S44: Based on the iterative adjustment signal, stabilize the opening of the proportional valve and gradually bring the actual flow rate of the target protective gas closer to the target protective gas flow rate.

[0113] In one embodiment, the protective gas control quantity output by the PID controller is numerically formatted, for example, converting the floating-point control quantity into a standard control signal format recognizable by the proportional valve (e.g., 0~10 V or 4~20 mA). Simultaneously, the signal undergoes digital filtering to remove high-frequency noise components from the control quantity, ensuring a smooth and stable adjustment signal. After formatting and filtering, the generated adjustment signal can directly drive the electronically controlled proportional valve.

[0114] The controller performs a continuous valve opening adjustment process based on the difference between the adjustment signal and the current opening of the proportional valve. During the adjustment process, the controller smooths the adjustment signal to prevent instantaneous jumps in the valve opening; simultaneously, a gradual increase strategy is adopted to gradually approach the target value of the valve opening; during the adjustment process, the proportional valve response is monitored in real time, and the adjustment signal is dynamically corrected, for example, by making slight adjustments based on the valve response hysteresis or nonlinear characteristics, thereby ensuring continuous and stable changes in the valve opening.

[0115] During the proportional valve's opening change, the actual flow rate of the protective gas is collected in real time by a flow sensor and compared with the target protective gas flow rate. When a deviation trend in the actual flow rate is detected (e.g., below or above the target value), the controller automatically triggers a micro-amplitude dynamic iterative update of the adjustment signal. The iterative update methods include gain fine-tuning, dynamic correction of PID parameters, or the use of an adaptive iterative algorithm to make subtle adjustments to the adjustment signal to quickly correct the flow rate deviation.

[0116] After iterative updates, the proportional valve opening gradually stabilizes, preventing frequent fluctuations or overshoot. Simultaneously, through closed-loop feedback, the actual shielding gas flow rate gradually approaches the target flow rate, achieving precise flow control. Throughout the welding process, steps S41 to S44 are continuously executed to ensure the shielding gas flow rate remains at an optimal level under different welding conditions, thereby achieving stable welding atmosphere and energy-saving control.

[0117] Preferably, when there is a deviation trend between the actual flow rate value and the target protective gas flow rate value, the automatic triggering of micro-amplitude dynamic iterative updates of the adjustment signal includes:

[0118] When there is a deviation trend between the actual flow rate value and the target protective gas flow rate value, signal conditioning demand data is obtained based on the directionality and change tendency of the deviation trend.

[0119] The update step size of the regulation signal is adjusted according to the signal regulation requirement data to obtain the iterative regulation signal.

[0120] In one embodiment, the difference between the actual flow velocity and the target flow velocity is calculated in real time, and the trend of this difference within a certain time window is analyzed, including the direction of increase or decrease, the rate of change, and the continuity of the difference. For example, if the actual flow velocity is continuously lower than the target flow velocity and the difference gradually increases, the deviation trend is judged as "low flow velocity increasing demand"; if the actual flow velocity is higher than the target flow velocity and the difference gradually decreases, the deviation trend is judged as "high flow velocity decreasing demand". Through the above analysis, signal adjustment demand data is generated, which records the magnitude, direction, and tendency of the deviation, for subsequent iterative adjustment. The controller automatically determines the update step size and direction of the adjustment signal based on the generated signal adjustment demand data. Specific operations include: if the deviation trend has a large magnitude and changes rapidly, the update step size is increased to make the adjustment signal quickly approach the target value; if the deviation trend has a small magnitude and changes slowly, the update step size is decreased to prevent overshoot or oscillation; after adjusting the update step size, the adjustment signal is increased or decreased according to the deviation direction to generate an iterative adjustment signal. The iterative adjustment signal is then used to drive the electronically controlled proportional valve to achieve closed-loop fine control of the flow velocity.

[0121] Therefore, the embodiments should be considered as exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of the equivalents of the application are intended to be included within the invention.

[0122] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features of the invention herein.

Claims

1. A PID-based intelligent fuel-saving control method, characterized in that, Includes the following steps: Step S1: Load the preset welding current-target flow rate relationship model and initialize the proportional coefficient, integral coefficient, and derivative coefficient of the PID controller; Step S2: Obtain the real-time welding current value and input it into the welding current-target flow rate relationship model to calculate the target shielding gas flow rate value; wherein, before inputting the welding current value into the welding current-target flow rate relationship model to calculate the target shielding gas flow rate value in step S2, the following steps are also included: The effectiveness of the working condition is determined based on the welding current value, which includes identifying the amplitude range, rate of change, duration and noise stability of the welding current. Determine whether the current welding current value belongs to an effective welding state based on the effectiveness judgment of the working condition; Welding conditions are divided by effective welding states to obtain non-welding standby state, transient arc ignition state and steady-state welding state. The target shielding gas velocity is calculated by directly inputting the welding current value into the welding current-target velocity relationship model based on the steady-state welding state; the calculation of the target shielding gas velocity based on the non-welding standby state also includes: The duration of the state and the stability of current fluctuations are obtained based on the non-welding standby state. The gas release trend is analyzed based on the duration of the state and the stability of the current fluctuation. The protective gas retention requirement in the non-welding standby state is confirmed by the analysis results. The protective gas retention requirement is used to maintain the residual protective gas curtain inside and around the welding torch. The reduction in the target protective gas flow rate is calculated based on the protective gas retention requirement, yielding the reduced target protective gas flow rate. The calculation of the target protective gas flow rate based on the transient arc initiation state also includes: Based on the rise of the welding current during the transient arc initiation period, the current change trend towards stabilization is identified. Based on the fluctuation amplitude and continuity of change in the current change trend, the transient arc initiation state is divided into the initial disturbance segment, the transitional stabilization segment, and the near-steady-state segment. The target protective gas velocity value for the transient arc initiation state is generated by analyzing the stage response relationship between the initial disturbance stage, the transitional stabilization stage, and the near-steady-state stage. Specifically, the generation of the target protective gas velocity value for the transient arc initiation state by analyzing the stage response relationship between the initial disturbance stage, the transitional stabilization stage, and the near-steady-state stage includes: Determine the response interval corresponding to the initial disturbance segment, and generate the initial compensation velocity based on the fluctuation rhythm of the current change within the response interval; By identifying the directional continuity and amplitude attenuation trend of current change in the transition stabilization phase, the initial compensation flow rate is reduced to obtain the first adjusted compensation flow rate. The first adjustment compensation flow rate is adjusted based on the gradual trend of current change in the near steady-state range, and the second adjustment compensation flow rate is obtained. The target protective gas flow rate value for the transient arc initiation state is confirmed based on the second adjustment compensation flow rate. Step S3: By comparing the target protective gas flow rate with the actual protective gas flow rate, confirm the flow rate error signal; input the flow rate error signal into the initialized PID controller to obtain the protective gas control output; Step S4: Convert the protective gas control output into an adjustment signal to drive the opening of the electronically controlled proportional valve, and continuously control the opening of the electronically controlled proportional valve based on the adjustment signal, so that the actual flow rate of the protective gas approaches the target protective gas flow rate. Step S5: Repeat steps S2-S4 to perform a real-time closed-loop gas control process driven by welding current.

2. The intelligent fuel-saving control method based on PID according to claim 1, characterized in that, Welding conditions are classified based on effective welding status, including: Identify the time periods during which welding actions occur and do not occur based on the amplitude range of the welding current, and confirm the time range of the non-welding standby state. By utilizing the characteristics of the rate of change and duration of welding current, the start and end frames of the transient arc ignition state are identified, and the time interval of the transient arc ignition state is obtained. Based on the continuous characteristics of welding current in terms of amplitude, rate of change and noise stability, the time interval of steady-state welding is determined. Welding conditions are divided based on the time division results, resulting in non-welding standby state, transient arc initiation state, and steady-state welding state.

3. The intelligent fuel-saving control method based on PID according to claim 1, characterized in that, Analysis of gas release trends based on the duration of the condition and the stability of current fluctuations includes: The duration of the release behavior is determined based on the duration of the state. The real-time welding current during the discharge cycle is smoothed to construct a stable fluctuation curve; By analyzing the local fluctuation direction, fall amplitude, and continuous change pattern of the fluctuation stability curve through the current fluctuation stability degree analysis, and mapping them one by one with the corresponding state duration, the current-gas correlation strength is obtained. The trend of gas release was confirmed by the trend change in the current-gas correlation strength.

4. The intelligent fuel-saving control method based on PID according to claim 1, characterized in that, Step S4 includes the following steps: Step S41: Format and convert the protective gas control output to obtain the adjustment signal; Step S42: Based on the difference between the adjustment signal and the proportional valve opening of the electronically controlled proportional valve, a continuous opening adjustment process is executed, wherein the continuous opening adjustment process includes smoothing, gradually increasing and dynamically correcting the adjustment signal; Step S43: During the opening change of the proportional valve, the actual flow rate of the target protective gas is collected and compared in real time. When there is a deviation trend between the actual flow rate and the flow rate of the target protective gas, the micro-amplitude dynamic iterative update of the adjustment signal is automatically triggered to obtain the iterated adjustment signal. Step S44: Based on the iterative adjustment signal, stabilize the opening of the proportional valve and gradually bring the actual flow rate of the target protective gas closer to the target protective gas flow rate.

5. The intelligent fuel-saving control method based on PID according to claim 4, characterized in that, When there is a deviation trend between the actual flow rate and the target protective gas flow rate, the automatic triggering of micro-amplitude dynamic iterative updates to the adjustment signal includes: When there is a deviation trend between the actual flow rate value and the target protective gas flow rate value, signal conditioning demand data is obtained based on the directionality and change tendency of the deviation trend. The update step size of the regulation signal is adjusted according to the signal regulation requirement data to obtain the iterative regulation signal.

6. A PID-based intelligent fuel-saving control device, characterized in that, For executing the PID-based intelligent fuel-saving control method as described in claim 1, the PID-based intelligent fuel-saving control device includes: The model initialization module is used to load the preset welding current-target flow rate relationship model and initialize the proportional coefficient, integral coefficient, and derivative coefficient of the PID controller. The current acquisition module is used to acquire the real-time welding current value and input the welding current value into the welding current-target flow rate relationship model to calculate the target shielding gas flow rate value; The error control module is used to confirm the flow rate error signal by comparing the target protective gas flow rate value with the actual protective gas flow rate value; the flow rate error signal is then input into the initialized PID controller to obtain the protective gas control output. The valve control execution module is used to convert the protective gas control output into an adjustment signal to drive the opening of the electronically controlled proportional valve, and to continuously control the opening of the electronically controlled proportional valve based on the adjustment signal, so that the actual flow rate of the protective gas approaches the target protective gas flow rate. The closed-loop operation module is used to cyclically execute steps S2-S4 to perform a real-time closed-loop gas control process driven by welding current.

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