A real-time monitoring method and system for plasma-MIG hybrid welding

Abstract

The present invention discloses a real-time monitoring method and system for plasma-MIG composite welding. The method comprises the following steps: connecting a plasma control cabinet through a sensor and acquiring the plasma control cabinet data in real time, establishing a plasma control cabinet list; connecting a MIG power supply device through a sensor and acquiring the MIG power supply data in real time, establishing a MIG power supply data control list; connecting a wire feeder through a sensor and acquiring the wire feeder data in real time, establishing a wire feeder data control list; matching the various parameters of the plasma control cabinet list, the MIG power supply data control list, and the wire feeder data control list according to the welding content, and by acquiring the corresponding parameters of the welding anomaly, setting an early warning threshold and sending a prompt signal. The present invention realizes real-time monitoring of parameters in welding, and classifies the monitoring list according to the welding content, realizes a differentiated monitoring system for different welding, sets different monitoring thresholds, and makes monitoring clearer and more accurate.

Description

Technical Field

[0001] The present invention relates to the field of welding technology, and in particular to a real-time monitoring method and system for plasma-MIG composite welding. Background Art

[0002] With the rapid development of industrial technology and the continuous improvement of automation, welding technology plays a vital role in industrial development. Over the past few decades, welding technology has rapidly evolved from simple welding methods to hybrid welding. Hybrid welding presents numerous challenges, requiring real-time and accurate control of data such as current and voltage. However, human energy is limited. While real-time monitoring devices have been increasingly used in welding technology, previous real-time monitoring systems were not specifically designed for hybrid welding data monitoring. Current industry challenges include a lack of effective information transmission and real-time performance, making it difficult to accurately assess process dimensions and complex data adjustment cycles. Excessive voltage and current are common during welding, necessitating the control of temperature, density, and weld formation. Welding equipment lacks accurate data statistics and analysis. Welding factors are influenced by numerous factors, making optimization and improvement of welding equipment difficult without data analysis. Traditional monitoring technologies are complex processes, and data analysis relies on data processing modules, which cannot provide quantitative data analysis.

[0003] Yang Yaohui et al.'s invention, "A CO2 Welding Parameter Monitoring Method," uses a data acquisition system to process CO2 welding parameters, displaying and saving them in real time to improve welding quality. However, this invention cannot adjust parameters based on different welding conditions, and existing technologies only target a single welding method and cannot monitor data for composite welding. Summary of the Invention

[0004] The present invention provides a real-time monitoring method and system for plasma-MIG hybrid welding, which is used to solve the problem that the hybrid welding process cannot be fully monitored in real time.

[0005] The purpose of the present invention is achieved by at least one of the following technical solutions.

[0006] A real-time monitoring method for plasma-MIG hybrid welding, comprising the following steps:

[0007] S1. Connecting to the plasma control cabinet through a sensor and acquiring the plasma control cabinet data in real time to establish a plasma control cabinet list;

[0008] S2. Connect to the MIG power supply equipment through sensors and obtain MIG power supply data in real time, and establish a MIG power supply data control list;

[0009] S3, connecting to the wire feeder through the sensor and obtaining the wire feeder data in real time, and establishing a wire feeder data control list;

[0010] S4. Match the parameters of the plasma control cabinet list, MIG power supply data control list and wire feeder data control list according to the welding content, and set the warning threshold and send a prompt signal by obtaining the corresponding parameters of the welding anomaly.

[0011] Furthermore, in step S1, the plasma control cabinet is connected via a sensor and the plasma control cabinet data is acquired in real time to establish a plasma control cabinet list, which includes the following steps:

[0012] S1.1. Real-time acquisition of voltage and current of plasma control cabinet data;

[0013] S1.2. Add the ratio of the voltage and current of the plasma control cabinet to the monitoring list;

[0014] S1.3. Classify the control cabinet voltage and current, as well as the voltage-to-current ratio, according to different welding contents; the welding contents include welding type, welding position, and welding rod diameter;

[0015] S1.4. Set different control thresholds according to different types of welding content, and output the change curve of the list parameters at the same time.

[0016] Furthermore, in step S2, the MIG power supply equipment is connected via a sensor and MIG power supply data is acquired in real time, and a MIG power supply data control list is established, including the following steps:

[0017] S2.1. Obtain the voltage and current of the MIG power supply in real time;

[0018] S2.2. Add the ratio of MIG voltage and current to the monitoring list;

[0019] S2.3. Classify the MIG voltage and current, and the voltage-to-current ratio, according to different welding conditions; the welding conditions include welding type, welding position, and electrode diameter;

[0020] S2.4. Set different control thresholds according to the type of welding content and output the change curve of the list parameters at the same time.

[0021] Furthermore, in step S3, the wire feeder is connected to the sensor and the wire feeder data is obtained in real time, and a wire feeder data control list is established, which includes the following steps:

[0022] S3.1. Obtain the speed of the wire feeder in real time;

[0023] S3.2. Classifying the speed data of the wire feeder according to different welding contents, wherein the welding contents include welding type, welding position, and welding rod diameter;

[0024] S3.3. According to the type of welding content, set different wire feeder speed control thresholds and output a wire feeder speed change curve.

[0025] Furthermore, in step S4, the parameters of the plasma control cabinet list, the MIG power supply data control list, and the wire feeder data control list are matched according to the welding content; and by obtaining the corresponding parameters corresponding to the welding anomaly, an early warning system is set and a prompt signal is sent, including the following steps:

[0026] S4.1. Classify parameters of the same welding content according to the welding content and integrate them together for real-time monitoring;

[0027] S4.2. Acquire abnormal welding parameter data under different welding contents, map and analyze the abnormal parameter data, and set an early warning threshold based on the analysis results; when the detection value of the same parameter in the same direction exceeds the early warning threshold for 5 consecutive times, the early warning system will issue an alarm reminder.

[0028] A real-time monitoring system for plasma-MIG composite welding, comprising a plasma cabinet data acquisition module, a MIG power supply data acquisition module, a wire feeder data acquisition module, and a system monitoring module;

[0029] In the plasma cabinet data acquisition module, the plasma control cabinet is connected via a sensor and the plasma control cabinet data is acquired in real time to establish a plasma control cabinet list;

[0030] In the MIG power supply data acquisition module, the sensor is connected to the MIG power supply equipment and the MIG power supply data is acquired in real time, and a MIG power supply data control list is established;

[0031] In the wire feeder data acquisition module, the wire feeder is connected through a sensor and the wire feeder data is acquired in real time, and a wire feeder data control list is established;

[0032] In the system monitoring module, the various parameters of the plasma control cabinet list, MIG power supply data control list and wire feeder data control list are matched according to the welding content; and by obtaining the corresponding parameters corresponding to the welding anomaly, the warning threshold is set and a prompt signal is sent.

[0033] Furthermore, the plasma cabinet data acquisition module includes:

[0034] The first data acquisition module: acquires the voltage and current of the plasma cabinet control cabinet data in real time;

[0035] The first data association module: adds the voltage and current ratio of the control cabinet to the monitoring list;

[0036] The first classification module classifies the control cabinet voltage and current, as well as the voltage-to-current ratio, according to different welding contents; the welding contents include welding type, welding position, and welding rod diameter;

[0037] The first threshold setting module: sets different control thresholds according to different categories of welding content, and outputs a change curve chart of list parameters at the same time.

[0038] Furthermore, the MIG power supply data acquisition module includes:

[0039] The second data acquisition module: acquires the voltage and current of the MIG power supply in real time;

[0040] The second data association module: adds the ratio of MIG voltage and current to the monitoring list;

[0041] The second classification module classifies the MIG voltage and current, as well as the voltage-to-current ratio, according to different welding contents; the welding contents include welding type, welding position, and electrode diameter;

[0042] The second threshold setting module: sets different control thresholds according to the type of welding content, and outputs a change curve chart of the list parameters at the same time.

[0043] Furthermore, the wire feeder data acquisition module includes:

[0044] The third data acquisition module: acquires the speed of the wire feeder in real time;

[0045] The third classification module classifies the speed data of the wire feeder according to different welding contents; the welding contents include welding type, welding position and welding rod diameter;

[0046] The third threshold setting module: sets different wire feeder speed control thresholds according to the type of welding content, and outputs a curve chart of the wire feeder speed change.

[0047] Furthermore, the system monitoring module includes:

[0048] Parameter integration module: classifies parameters of the same welding content according to the welding content and integrates them together for real-time monitoring;

[0049] Monitoring module: obtains abnormal welding parameter data under different welding contents, maps and analyzes the abnormal parameter data, and sets the warning threshold based on the analysis results; when the detection value of the same parameter in the same direction exceeds the warning threshold for 5 consecutive times, the monitoring module issues an alarm reminder.

[0050] Compared with the prior art, the advantages of the present invention are:

[0051] The composite welding monitoring system collects data from sensors connected to the plasma control cabinet, MIG power supply equipment and wire feeder and integrates them to achieve comprehensive control of the three systems, achieve real-time monitoring of welding parameters, and classify the monitoring list according to the welding content to achieve different monitoring systems for different welding types, welding positions and electrode diameters, and set different monitoring thresholds to make monitoring clearer and more accurate. At the same time, through the analysis of parameters corresponding to welding anomalies, an early warning system is set up to warn of defects in advance. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 This is a schematic diagram of a platform device used for plasma-MIG composite welding according to the present invention;

[0053] Figure 2 Schematic diagram of a real-time monitoring method for plasma-MIG composite welding according to the present invention;

[0054] Figure 3 This is a schematic diagram of a real-time monitoring system for plasma-MIG composite welding according to the present invention. DETAILED DESCRIPTION

[0055] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0056] Example:

[0057] In one embodiment, the hybrid welding system collects data by connecting the components of the hybrid welding platform via sensors, such as the hybrid welding platform. Figure 1 As shown, it includes a manipulator control cabinet 1, a welding platform 2, a composite welding gun 3, a welding robot 4, a wire feeder 5, a plasma control cabinet 6 and a MIG power supply 7. The wire feeder 5 feeds the solder to the welding platform 2, the welding robot 4 controls the composite welding gun 3 for welding, and the manipulator control cabinet 1 controls the welding robot 4; the plasma control cabinet 6 and the MIG power supply 7 connect the composite welding gun to provide voltage, current and plasma airflow for welding.

[0058] A real-time monitoring method for plasma-MIG composite welding, such as Figure 2 As shown, the following steps are included:

[0059] S1, connecting to the plasma control cabinet through the sensor and obtaining the plasma control cabinet data in real time, and establishing a plasma control cabinet list, including the following steps:

[0060] S1.1. Real-time acquisition of voltage and current of plasma control cabinet data;

[0061] S1.2. Add the ratio of the voltage and current of the plasma control cabinet to the monitoring list;

[0062] S1.3. Classify the control cabinet voltage and current, as well as the voltage-to-current ratio, according to different welding contents; the welding contents include welding type, welding position, and welding rod diameter;

[0063] In one embodiment, welding types include acid welding rods and alkaline welding rods; welding positions include flat welding, horizontal welding, and vertical welding; welding diameters include 3.2 mm, 4 mm, and 5 mm; acid welding rods plus flat welding and a diameter of 3.2 mm are classified into one category and a control threshold is set; acid welding rods plus flat welding and a diameter of 4 mm are classified into one category and another set of control thresholds is set, and so on;

[0064] S1.4. Set different control thresholds according to different types of welding content, and output the change curve of list parameters at the same time;

[0065] In one embodiment, for flat welding with an acid electrode and a welding rod diameter of 4 mm, the control range of the current is 160 to 210 A, and the specific threshold value is set according to the mean standard deviation of the historical data combined with the control range and the parameter weight, that is, between 1.6 and 2.1 times the standard deviation, and within the control range of the category described in this welding content, the corresponding parameter weight is obtained by factor analysis. If the parameter weight is greater than 0.5, the threshold is appropriately reduced and set to 1.6 times the standard deviation. If the parameter weight is less than 0.5, the threshold is set to 2.1 times the standard deviation. If the parameter weight is equal to 0.5, the threshold is set to 1.8 times the standard deviation. The upper and lower limits of each parameter control are the corresponding parameter mean + / - threshold value.

[0066] Real-time acquisition of the voltage and current of the plasma cabinet control cabinet data; adding the ratio of the control cabinet's voltage and current, i.e., resistance, to the monitoring list; because sometimes the change in current may be caused by the voltage, but it is also possible that the voltage does not change, but the current changes, in which case the resistance may have changed, so adding resistance to the monitoring list makes monitoring more comprehensive; classifying the control cabinet voltage and current, as well as the voltage-to-current ratio, according to different welding contents; this helps to set different monitoring thresholds for different types, allowing for more accurate and reliable monitoring; because different welding requirements have different corresponding parameter settings, they must be distinguished; otherwise, the purpose of monitoring, i.e., timely detection of problems and sending reminders, cannot be achieved. Output the change curves of each parameter, making the parameter change trend clear at a glance and making monitoring clearer and more intuitive. Different thresholds are set according to the weight of the parameter. The control standard with a high weight is relatively strict, minimizing the occurrence of failures.

[0067] S2. Connect the MIG power supply equipment through the sensor and obtain the MIG power supply data in real time, and establish a MIG power supply data control list, including the following steps:

[0068] S2.1. Obtain the voltage and current of the MIG power supply in real time;

[0069] S2.2. Add the ratio of MIG voltage and current to the monitoring list;

[0070] S2.3. Classify the MIG voltage and current, and the voltage-to-current ratio, according to different welding conditions; the welding conditions include welding type, welding position, and electrode diameter;

[0071] S2.4. Set different control thresholds according to the type of welding content and output the change curve of the list parameters at the same time.

[0072] Acquire the voltage and current of the MIG power supply in real time; add the ratio of MIG voltage to current to the monitoring list; because sometimes the change in current may be caused by voltage, but it is also possible that the voltage does not change, but the current changes, in which case it may be a change in resistance, so adding resistance to the monitoring list makes monitoring more comprehensive; classify the MIG voltage and current, as well as the voltage-to-current ratio, according to different welding contents; this helps to set different monitoring thresholds for different types, allowing for more accurate and reliable monitoring; because different welding requirements have different corresponding parameter settings, they must be distinguished; otherwise, the purpose of monitoring, that is, to detect problems in a timely manner and send reminders, cannot be achieved. Output the change curve of each parameter, making the parameter change trend clear at a glance and making monitoring clearer and more intuitive.

[0073] S3, connecting to the wire feeder through the sensor and obtaining the wire feeder data in real time, and establishing a wire feeder data control list, including the following steps:

[0074] S3.1. Obtain the speed of the wire feeder in real time;

[0075] S3.2. Classifying the speed data of the wire feeder according to different welding contents, wherein the welding contents include welding type, welding position, and welding rod diameter;

[0076] S3.3. According to the type of welding content, set different wire feeder speed control thresholds and output a wire feeder speed change curve.

[0077] Real-time acquisition of wire feeder speed; categorizing wire feeder speed data based on different welding conditions; enabling more accurate and reliable monitoring by setting different monitoring thresholds for different welding types; because different welding requirements require different corresponding parameter settings, they must be distinguished; otherwise, the purpose of monitoring, namely, timely detection of problems and notifications, cannot be achieved. Outputting the change curves of each parameter makes the parameter change trend clear at a glance, making monitoring clearer and more intuitive.

[0078] S4, matching the parameters of the plasma control cabinet list, MIG power supply data control list, and wire feeder data control list according to the welding content, and obtaining the corresponding parameters of the welding anomaly, setting the warning threshold and sending the prompt signal, including the following steps:

[0079] S4.1. Classify parameters of the same welding content according to the welding content and integrate them together for real-time monitoring;

[0080] In one embodiment, acid electrodes with flat welding and a diameter of 3.2 mm are classified into one category, and the voltage and current of the plasma control cabinet and the ratio of voltage to current, the MIG voltage and current and the ratio of voltage to current, and the speed of the wire feeder of this type are integrated together to form a unified control page and list of this type; content selection is added to the control page, and options of different categories are set. When an option of a category is selected, the corresponding parameters and changes are displayed in the list;

[0081] S4.2. Acquire abnormal welding parameter data under different welding conditions, map and analyze the abnormal parameter data, and set an early warning threshold based on the analysis results; if the value of the same parameter in the same direction exceeds the early warning threshold for five consecutive times, the early warning system will issue an alarm reminder;

[0082] In one embodiment, abnormal parameters corresponding to poor welding over a period of time are obtained. The period of time can be one week or two weeks, depending on the situation. The welding content is classified, for example, acid welding rods plus flat welding with a diameter of 3.2 mm are classified into one category. Under this classification, the poor types are further divided, and the parameters in the monitoring list corresponding to the poor types are extracted. The poor group and the normal group are compared, and modeling is performed using a fitting model. The modeling can be completed using tools such as JMP and MINITAB. The parameters with greater influence are ranked in front and included in the key monitoring. The distribution of various parameters of defective products in the normal group is statistically analyzed. If the parameters corresponding to greater than or equal to 82% of the defects are 93% and above and / or 7% and below the probability of normal parameter distribution, the values ​​corresponding to the 93% and / or 7% parameter distributions are used as warning thresholds; if there is no distribution concentration of the corresponding parameters during welding abnormality, the original control threshold + / - 1%, that is, the upper control limit minus 1% and the lower control limit plus 1%, is used as the warning range.

[0083] The plasma control cabinet data is connected through sensors and the plasma control cabinet data is obtained in real time to establish a plasma control cabinet list; the composite welding monitoring system is connected to the MIG power supply equipment through sensors and obtains the MIG power supply data in real time to establish a MIG power supply data control list; the composite welding monitoring system is connected to the wire feeder through sensors and obtains the wire feeder data in real time to establish a wire feeder data control list; the composite welding system matches the various parameters of the plasma control cabinet list, MIG power supply data control list and wire feeder data control list according to the welding content; and by obtaining the corresponding parameters for welding anomalies, an early warning system is set and a prompt signal is sent.

[0084] The parameters of the same welding content are classified and integrated together for real-time monitoring through welding content; and content selection is added to the control page, and options of different categories are set, which can quickly eliminate the welding content selection monitoring page and integrate the content together to achieve real-time, intuitive, fast and accurate monitoring. The abnormal welding parameter data under different welding contents are obtained through the composite welding monitoring system, and the abnormal parameter data are mapped to the monitoring system and analyzed, and the early warning threshold is set according to the analysis results; when the detection value of the same parameter in the same direction exceeds the control threshold for 5 consecutive times, the monitoring system will issue an alarm reminder, which can accurately issue an early warning according to the defect type and adjust the corresponding operation in the welding process, thereby reducing the defect rate and improving work efficiency.

[0085] The effect of the above technical solution is: the composite welding monitoring system collects data from sensors connected to the plasma control cabinet, MIG power supply equipment and wire feeder and integrates them to achieve comprehensive control of the three systems, achieve real-time monitoring of welding parameters, and classify the monitoring list according to the welding content to achieve different monitoring systems for different welding types, welding positions and electrode diameters, and set different monitoring thresholds to make monitoring clearer and more accurate. At the same time, through the analysis of parameters corresponding to welding anomalies, an early warning system is set up to warn of defects in advance.

[0086] A real-time monitoring system for plasma-MIG hybrid welding, such as Figure 3 As shown, it includes a plasma cabinet data acquisition module, a MIG power supply data acquisition module, a wire feeder data acquisition module and a system monitoring module;

[0087] In the plasma cabinet data acquisition module, the plasma control cabinet is connected via a sensor and the plasma control cabinet data is acquired in real time to establish a plasma control cabinet list;

[0088] In the MIG power supply data acquisition module, the sensor is connected to the MIG power supply equipment and the MIG power supply data is acquired in real time, and a MIG power supply data control list is established;

[0089] In the wire feeder data acquisition module, the wire feeder is connected through a sensor and the wire feeder data is acquired in real time, and a wire feeder data control list is established;

[0090] In the system monitoring module, the various parameters of the plasma control cabinet list, MIG power supply data control list and wire feeder data control list are matched according to the welding content; and by obtaining the corresponding parameters corresponding to the welding anomaly, the warning threshold is set and a prompt signal is sent.

[0091] Furthermore, the plasma cabinet data acquisition module includes:

[0092] The first data acquisition module: acquires the voltage and current of the plasma cabinet control cabinet data in real time;

[0093] The first data association module: adds the voltage and current ratio of the control cabinet to the monitoring list;

[0094] The first classification module classifies the control cabinet voltage and current, as well as the voltage-to-current ratio, according to different welding contents; the welding contents include welding type, welding position, and welding rod diameter;

[0095] The first threshold setting module: sets different control thresholds according to different categories of welding content, and outputs a change curve chart of list parameters at the same time.

[0096] Furthermore, the MIG power supply data acquisition module includes:

[0097] The second data acquisition module: acquires the voltage and current of the MIG power supply in real time;

[0098] The second data association module: adds the ratio of MIG voltage and current to the monitoring list;

[0099] The second classification module classifies the MIG voltage and current, as well as the voltage-to-current ratio, according to different welding contents; the welding contents include welding type, welding position, and electrode diameter;

[0100] The second threshold setting module: sets different control thresholds according to the type of welding content, and outputs a change curve chart of the list parameters at the same time.

[0101] Furthermore, the wire feeder data acquisition module includes:

[0102] The third data acquisition module: acquires the speed of the wire feeder in real time;

[0103] The third classification module classifies the speed data of the wire feeder according to different welding contents; the welding contents include welding type, welding position and welding rod diameter;

[0104] The third threshold setting module: sets different wire feeder speed control thresholds according to the type of welding content, and outputs a curve chart of the wire feeder speed change.

[0105] Furthermore, the system monitoring module includes:

[0106] Parameter integration module: classifies parameters of the same welding content according to the welding content and integrates them together for real-time monitoring;

[0107] Monitoring module: obtains abnormal welding parameter data under different welding contents, maps and analyzes the abnormal parameter data, and sets the warning threshold based on the analysis results; when the detection value of the same parameter in the same direction exceeds the warning threshold for 5 consecutive times, the monitoring module issues an alarm reminder.

[0108] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A real-time monitoring method for plasma-MIG hybrid welding, characterized in that: The steps include: S1. Connecting a plasma control cabinet via a sensor and acquiring the plasma control cabinet data in real time to establish a plasma control cabinet list. Connecting a plasma control cabinet via a sensor and acquiring the plasma control cabinet data in real time to establish a plasma control cabinet list includes the following steps: S1.

1. Real-time acquisition of voltage and current of plasma control cabinet data; S1.

2. Add the ratio of the voltage and current of the plasma control cabinet to the monitoring list; S1.

3. Classify the control cabinet voltage and current, as well as the voltage-to-current ratio, according to different welding contents; the welding contents include welding type, welding position, and welding rod diameter; S1.

4. Set different control thresholds according to different types of welding content, and output the change curve of list parameters at the same time; S2, connecting the MIG power supply device through the sensor and obtaining the MIG power supply data in real time, and establishing a MIG power supply data control list; connecting the MIG power supply device through the sensor and obtaining the MIG power supply data in real time, and establishing a MIG power supply data control list, including the following steps: S2.

1. Obtain the voltage and current of the MIG power supply in real time; S2.

2. Add the ratio of MIG voltage and current to the monitoring list; S2.

3. Classify the MIG voltage and current, and the voltage-to-current ratio, according to different welding conditions; the welding conditions include welding type, welding position, and electrode diameter; S2.

4. Set different control thresholds according to the type of welding content and output the change curve of the list parameters at the same time; S3, connecting the wire feeder through the sensor and obtaining the wire feeder data in real time, and establishing a wire feeder data control list; connecting the wire feeder through the sensor and obtaining the wire feeder data in real time, and establishing a wire feeder data control list, including the following steps: S3.

1. Obtain the speed of the wire feeder in real time; S3.

2. Classifying the speed data of the wire feeder according to different welding contents, wherein the welding contents include welding type, welding position, and welding rod diameter; S3.

3. Set different wire feeder speed control thresholds according to the type of welding content, and output a wire feeder speed change curve graph; S4. Match the parameters of the plasma control cabinet list, MIG power supply data control list and wire feeder data control list according to the welding content, and set the warning threshold and send a prompt signal by obtaining the corresponding parameters of the welding anomaly.

2. A real-time monitoring method for plasma-MIG hybrid welding according to claim 1, characterized in that: In step S4, the parameters of the plasma control cabinet list, the MIG power supply data control list, and the wire feeder data control list are mapped according to the welding content; and by obtaining the corresponding parameters corresponding to the welding anomalies, an early warning system is set and a prompt signal is sent, including the following steps: S4.

1. Classify parameters of the same welding content according to the welding content and integrate them together for real-time monitoring; S4.

2. Acquire abnormal welding parameter data under different welding contents, map and analyze the abnormal parameter data, and set an early warning threshold based on the analysis results; when the detection value of the same parameter in the same direction exceeds the early warning threshold for 5 consecutive times, the early warning system will issue an alarm reminder.

3. A real-time monitoring system for plasma-MIG hybrid welding that implements the real-time monitoring method of claim 1, characterized in that: The system includes: a plasma cabinet data acquisition module, a MIG power supply data acquisition module, a wire feeder data acquisition module and a system monitoring module; In the plasma cabinet data acquisition module, the plasma control cabinet is connected via a sensor and the plasma control cabinet data is acquired in real time to establish a plasma control cabinet list; In the MIG power supply data acquisition module, the sensor is connected to the MIG power supply equipment and the MIG power supply data is acquired in real time, and a MIG power supply data control list is established; In the wire feeder data acquisition module, the wire feeder is connected through a sensor and the wire feeder data is acquired in real time, and a wire feeder data control list is established; In the system monitoring module, the various parameters of the plasma control cabinet list, MIG power supply data control list and wire feeder data control list are matched according to the welding content; and by obtaining the corresponding parameters corresponding to the welding anomaly, the warning threshold is set and a prompt signal is sent.

4. A real-time monitoring system for plasma-MIG hybrid welding according to claim 3, characterized in that: The plasma cabinet data acquisition module includes: The first data acquisition module: acquires the voltage and current of the plasma cabinet control cabinet data in real time; The first data association module: adds the voltage and current ratio of the control cabinet to the monitoring list; The first classification module classifies the control cabinet voltage and current, as well as the voltage-to-current ratio, according to different welding contents; the welding contents include welding type, welding position, and welding rod diameter; The first threshold setting module: sets different control thresholds according to different categories of welding content, and outputs a change curve chart of list parameters at the same time.

5. The real-time monitoring system for plasma-MIG hybrid welding according to claim 3, characterized in that: The MIG power supply data acquisition module includes: Second data acquisition module: real-time acquisition of the voltage and current of the MIG power supply; The second data association module: adds the ratio of MIG voltage and current to the monitoring list; The second classification module classifies the MIG voltage and current, as well as the voltage-to-current ratio, according to different welding contents; the welding contents include welding type, welding position, and electrode diameter; The second threshold setting module: sets different control thresholds according to the type of welding content, and outputs a change curve chart of the list parameters at the same time.

6. The real-time monitoring system for plasma-MIG hybrid welding according to claim 3, characterized in that: The wire feeder data acquisition module includes: The third data acquisition module: acquires the speed of the wire feeder in real time; The third classification module classifies the speed data of the wire feeder according to different welding contents; the welding contents include welding type, welding position and welding rod diameter; The third threshold setting module: sets different wire feeder speed control thresholds according to the type of welding content, and outputs a curve chart of the wire feeder speed change.

7. The real-time monitoring system for plasma-MIG hybrid welding according to claim 3, characterized in that: The system monitoring module includes: Parameter integration module: classifies parameters of the same welding content according to the welding content and integrates them together for real-time monitoring; Monitoring module: obtains abnormal welding parameter data under different welding contents, maps and analyzes the abnormal parameter data, and sets the warning threshold based on the analysis results; when the detection value of the same parameter in the same direction exceeds the warning threshold for 5 consecutive times, the monitoring module issues an alarm reminder.

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