Monitoring method, system and equipment for production management control of mobile welding machine and medium

Abstract

The invention belongs to the technical field of welding machine monitoring, and provides a monitoring method, system and equipment for production management control of a mobile welding machine and a medium, and the method comprises the following steps: determining a welding task in response to a welding instruction; acquiring actual data during welding; based on the welding task, determining a theoretical data range during welding through a predetermined standard library; judging whether the actual data is within the theoretical data range or not, and if not, giving an alarm; the obtained actual welding data is compared with a theoretical data range based on welding task matching, an accurate quantitative judgment basis can be provided for monitoring of the welding process, when the actual data deviates from the theoretical range, an alarm is given in time, key parameter abnormity can be captured in the first time, and the welding quality is improved. The quality problems of poor weld fusion, air holes, cracks and the like caused by abnormal parameters are effectively prevented, the reworking cost of unqualified workpieces is reduced, whether the welding process meets the technological standard or not can be controlled in real time, and the equipment maintenance cost and the downtime are reduced.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of welding machine monitoring, and particularly relates to a mobile welding machine production management control monitoring method, system, device and medium. BACKGROUND

[0002] The welding machine converts electrical energy into heat energy, causing the welding material (such as welding wire, welding rod) and the workpiece to locally melt and form a weld, and is widely used in manufacturing. Its running state directly determines the quality of the welded workpiece, production efficiency and equipment safety. In the actual application of mobile welding machines, due to the fact that the work scene is mostly outdoor or multi-station mobile operation, it is easily affected by factors such as environmental temperature, power grid voltage fluctuation, workpiece pretreatment state, etc. If the key parameters are out of control during welding, it may not only cause quality defects such as insufficient penetration, porosity, and cracks in the weld, but also cause problems such as welding machine overload damage and energy consumption surge. Therefore, the running process needs to be monitored in real time to ensure stable production.

[0003] In the prior art, the monitoring of mobile welding machines mainly focuses on single electric parameter collection. Usually, current sensors and voltage sensors are installed at the output end of the welding machine to obtain welding current and voltage data in real time, and compare them with the preset theoretical current and voltage range. If it exceeds the range, an alarm will be issued.

[0004] However, the above monitoring method has obvious limitations: current and voltage can only reflect the electrical signal characteristics of the welding machine output end, which is independent single parameter monitoring, without considering the correlation between parameters, and thus cannot accurately judge the matching degree of energy supply and weld quality. It is easy to have the situation that the parameters meet the standards but the quality is unqualified or the parameters deviate slightly but the alarm is excessive. The monitoring effect is difficult to meet the needs of high-precision welding production, and cannot fundamentally guarantee the welding quality and production efficiency. SUMMARY

[0005] In view of the problems in the background art, the present application provides a mobile welding machine production management control monitoring method, system, device and medium.

[0006] In order to achieve the above purpose, the present application adopts the following technical scheme: In a first aspect, the present application provides a mobile welding machine production management control monitoring method, comprising: determining a welding task in response to a welding instruction; obtaining actual data during welding; determining a theoretical data range during welding based on the welding task through a pre-determined standard library; judging whether the actual data is within the theoretical data range, and if not, issuing an alarm.

[0007] Further, the actual data includes actual current, actual voltage and actual welding speed. After the actual data in the welding is acquired, further comprising: Based on the actual current and the actual voltage, determining actual power, the expression of which is: , wherein, represents actual power, represents actual voltage, represents actual current, represents power factor; Based on the actual current, actual voltage and actual welding speed, determining actual heat input, the expression of which is: , wherein, represents actual heat input, represents actual current, represents actual welding speed, represents actual voltage.

[0008] Further, the theoretical data range includes a theoretical power range and a theoretical heat input range.

[0009] Further, the judging whether the actual data is located in the theoretical data range or not, if not, issuing an alarm, specifically comprising: Judging whether the actual power is located in the theoretical power range or not, if not, issuing a first alarm; Comparing whether the actual heat input is located in the heat input range or not, if not, issuing a second alarm; If the actual power and the actual heat input are not located in the theoretical power range and the heat input range, respectively, issuing a third alarm.

[0010] Further, after the first alarm is issued, further comprising: determining a first alarm cause.

[0011] Further, the theoretical data range further includes a theoretical ambient temperature range and a theoretical voltage range; the actual data further includes an actual ambient temperature; The determining the first alarm cause, specifically comprising: Based on the theoretical voltage range, determining a theoretical average voltage, the expression of which is: , wherein, represents theoretical average voltage, represents upper limit of theoretical voltage range, represents lower limit of theoretical voltage range; Based on the theoretical average voltage and the actual voltage, determining a voltage difference value, the expression of which is: , wherein, represents voltage difference value; Based on the aforementioned theoretical ambient temperature range, the theoretical average temperature is determined, and its expression is as follows: In the formula, Indicates the theoretical average temperature. This indicates the upper limit of the theoretical ambient temperature range. Indicates the lower limit of the theoretical ambient temperature range; Based on the theoretical average temperature and the actual ambient temperature, the temperature difference is determined, where, Indicates the temperature difference value. Indicates the actual ambient temperature; Based on the temperature difference and voltage difference, the temperature contribution and voltage contribution are determined by a predetermined contribution coefficient. Based on the temperature and voltage contributions, the first cause of the anomaly is determined.

[0012] Furthermore, after acquiring the actual data during welding, the process also includes: preprocessing the actual data.

[0013] Secondly, this invention proposes a monitoring system for production management and control of mobile welding machines, comprising: The task determination module is used to determine the welding task in response to welding instructions; The actual data acquisition module is used to acquire actual data during welding. The theoretical data acquisition module is used to determine the range of theoretical data for welding based on the welding task and a pre-defined standard library. An alarm module is used to determine whether the actual data is within the range of the theoretical data; if not, an alarm is issued.

[0014] Thirdly, the present invention proposes a device including a memory and a processor, wherein the memory stores computer instructions that can be executed on the processor, and the processor executes the monitoring method for production management and control of a mobile welding machine according to the first aspect when executing the computer instructions.

[0015] Fourthly, the present invention proposes a computer-readable storage medium storing computer instructions thereon, which, when executed, enables the monitoring method for production management and control of the mobile welding machine as described in the first aspect.

[0016] The beneficial effects of this invention are: The method of this invention compares the acquired actual welding data with the theoretical data range based on welding task matching, providing accurate quantitative judgment basis for welding process monitoring. When the actual data deviates from the theoretical range, an alarm is triggered in time, and key parameter anomalies can be captured immediately, effectively preventing quality problems such as poor weld fusion, porosity, and cracks caused by parameter anomalies, reducing the rework cost of defective workpieces, and enabling real-time control of whether the welding process meets the process standards. This avoids equipment failures such as welding machine overload and component damage caused by parameter loss, reducing equipment maintenance costs and downtime, and improving overall production efficiency and product quality.

[0017] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures pointed out in the description and the drawings. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A flowchart of the monitoring method for production management and control of mobile welding machines according to the present invention is shown; Figure 2 A framework diagram of the monitoring system for production management and control of the mobile welding machine of the present invention is shown; Figure 3 A schematic diagram of the device structure of the present invention is shown; Figure 4 A schematic diagram of the structure of the computer-readable storage medium of the present invention is shown. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] In existing technologies, monitoring current and voltage alone is insufficient to reflect the actual energy output efficiency of a welding machine. For example, during welding, if the current is at the upper limit of the theoretical range (e.g., 180A) and the voltage is at the lower limit of the theoretical range (e.g., 22V), both may appear compliant individually. However, the power calculated by multiplying the two (3960W) may be lower than the theoretical lower limit of the welding task (4200W). In this case, the actual output energy of the welding machine is insufficient, which can easily lead to poor weld penetration. Single parameter monitoring cannot detect this problem of "parameters being compliant individually but failing in synergy." It is easy to see situations where parameters meet the standards but the quality is unqualified, or where slight deviations in parameters cause excessive alarms. Furthermore, even if the current and voltage are within the theoretical range, if the welding speed is too fast or too slow, it will still lead to an imbalance in the actual heat absorbed by the weld. Moreover, without establishing a correlation logic between parameters and quality based on the actual needs of the welding task (e.g., different energy requirements due to workpiece material and thickness), the monitoring effect is difficult to meet the needs of high-precision welding production and cannot guarantee welding quality and production efficiency.

[0022] Reference Figure 1 As shown, to solve the above problems, this invention proposes a monitoring method for production management and control of mobile welding machines, specifically including the following steps: S10. In response to the welding instruction, determine the welding task; S20. Obtain actual data during welding; S30. Based on the welding task, determine the theoretical data range for welding using a pre-defined standard library; S40. Determine whether the actual data is within the theoretical data range. If not, issue an alarm.

[0023] In step S10 above, the welding command is manually entered by the operator through the interactive interface or automatically obtained through the production order system. The welding command includes core welding parameters, such as the thickness of the workpiece (e.g., 10mm), material (e.g., low-carbon steel, stainless steel), and specific dimensions (e.g., 2m long, 1m wide). After receiving these parameters, the system automatically integrates them to form a clear welding task (e.g., welding a stainless steel plate 2m long, 1m wide, and 10mm thick). The welding task provides a basis for subsequent comparison of theoretical and actual data, as well as monitoring and alarm functions.

[0024] This invention provides precise quantitative judgment for welding process monitoring by comparing the acquired actual welding data with the theoretical data range based on welding task matching. When the actual data deviates from the theoretical range, an alarm is triggered in time, and key parameter anomalies can be detected immediately. This effectively prevents quality problems such as poor weld fusion, porosity, and cracks caused by parameter anomalies, reduces the rework cost of defective workpieces, and can monitor whether the welding process meets the process standards in real time. This avoids equipment failures such as welding machine overload and component damage caused by parameter loss, reduces equipment maintenance costs and downtime, and improves overall production efficiency and product quality.

[0025] In step S20 above, the actual data includes the actual current, actual voltage, and actual welding speed.

[0026] In one specific embodiment, the actual current is acquired using a Hall current sensor installed outside the positive cable at the welding machine's output end to sense current changes in real time; the actual voltage is acquired using a voltage sensor connected in parallel between the positive and negative terminals at the welding machine's output end to avoid series connection issues affecting the circuit; the actual welding speed is directly acquired through an encoder or servo feedback system installed on the drive motor. It should be further noted that the above embodiments are only illustrative of the sensor deployment logic. In actual operation, the selection and installation location of different sensors need to be adjusted according to the welding machine model and the available installation space. Therefore, the above embodiments do not constitute the sole limitation on the data acquisition method in this invention. All technical means that can achieve the requirements of current and voltage acquisition fall within the protection scope of this invention.

[0027] After obtaining the actual data during welding, the following is also included: S21. Based on the actual current and actual voltage, determine the actual power, whose expression is: In the formula, Indicates actual power. Indicates the actual voltage. Indicates the actual current. The power factor is used to reflect the actual work efficiency. The specific value of the power factor is determined by the welding machine's factory parameters, industry standards, or actual testing, and is generally between 0.85 and 0.95.

[0028] S22. Based on the actual current, actual voltage, and actual welding speed, determine the actual heat input, which is expressed as follows: In the formula, Indicates the actual heat input. Indicates the actual current. Indicates the actual welding speed. This represents the actual voltage. Wherein, This represents the electrical energy generated in one minute. The actual heat input is the heat energy absorbed by the weld seam for every centimeter the welding torch moves.

[0029] Power, as the product of current and voltage, is a comprehensive energy indicator that can directly reflect the instantaneous energy state of an electric arc. This can avoid misjudgments that may occur when monitoring current or voltage alone, and thus more comprehensively capture energy anomalies at the output of the device. In contrast, current and voltage only reflect the electrical signal characteristics in the circuit and cannot directly reflect the energy work effect.

[0030] Heat input is calculated using current, voltage, and welding speed. It directly quantifies the actual energy absorbed by the weld. Different materials and thicknesses of workpieces have distinctly different heat requirements (e.g., thick steel plates require sufficient heat to ensure penetration, while thin aluminum plates require controlled heat to avoid burn-through). Heat input directly reflects this energy matching degree and serves as a direct basis for judging key quality indicators such as weld penetration, weld width, and grain structure. Compared to electrical parameters like current and voltage, heat input not only includes electrical signal characteristics but also integrates the welding speed parameter, reflecting the synergistic relationship between energy output and efficiency (e.g., even if current and voltage meet standards, excessive speed will still lead to insufficient heat input). Compared to a single welding speed parameter, heat input incorporates the energy output dimension, avoiding the problem of compliant speed but insufficient energy. Therefore, heat input is closer to the essence of the welding process than a single parameter, enabling more accurate alarms for welding defects caused by energy supply imbalances, and providing an effective basis for quality control.

[0031] In step S30 above, the standard library is pre-determined based on welding technical specifications and historical practice data. For welding different materials, workpiece thicknesses, and workpiece properties, there are already clear process standards (such as current, voltage, power, welding speed, heat input, etc.), which can be directly converted into basic parameters within the standard library. Furthermore, by collecting a large amount of data under the same working conditions in advance, and through statistical analysis and verification, data for different welding tasks can be determined. Integrating these data with the verified parameters allows for the pre-construction of the standard library, providing a basis for matching theoretical data to subsequent tasks.

[0032] The theoretical data range includes the theoretical power range and the theoretical heat input range.

[0033] In step S40 above, it is determined whether the actual data is within the theoretical data range. If not, an alarm is issued, which specifically includes the following steps: S401. Determine whether the actual power is within the theoretical power range. If not, issue the first alarm. S402. Check if the actual heat input is within the heat input range. If not, issue a second alarm. S403. If the actual power and actual heat input are not within the theoretical power range and heat input range, a third alarm will be issued.

[0034] Three different alarms (first alarm, second alarm, and third alarm) can be indicated by different colored warning lights or buzzers of different frequencies. This multi-dimensional alarm design allows for intuitive and rapid identification of the abnormal type in the current welding process, thereby accurately pinpointing the problem.

[0035] After the first alarm is issued, the process also includes: S50, determining the cause of the first alarm.

[0036] If the actual power is not within the theoretical power range, the actual data also includes the actual ambient temperature; the theoretical data range also includes the theoretical ambient temperature range and the theoretical voltage range.

[0037] In one specific embodiment, the ambient temperature is obtained by a temperature sensor, which is installed in a ventilated area within 1-2 meters of the welding machine body, away from heat sources (such as the welding machine's heat dissipation vents) to avoid localized overheating that could lead to data deviation. The temperature sensor needs to be fixed on a stable bracket to prevent welding vibration from affecting the measurement accuracy.

[0038] S511. Based on the theoretical voltage range, determine the theoretical average voltage, whose expression is: In the formula, Represents the theoretical average voltage. This indicates the upper limit of the theoretical voltage range. Indicates the lower limit of the theoretical voltage range; For example, if the theoretical voltage range is 200-220V, then... It is 220V. 200V It is 210V.

[0039] S512. Based on the theoretical average voltage and the actual voltage, determine the voltage difference, the expression of which is: In the formula, Indicates the voltage difference; S513. Based on the theoretical ambient temperature range, determine the theoretical average temperature, whose expression is: In the formula, Indicates the theoretical average temperature. This indicates the upper limit of the theoretical ambient temperature range. Indicates the lower limit of the theoretical ambient temperature range; S514. Based on the theoretical average temperature and the actual ambient temperature, determine the temperature difference, the expression of which is: In the formula, Indicates the temperature difference value. Indicates the actual ambient temperature; S515. Based on the temperature difference and voltage difference, determine the temperature contribution and voltage contribution through a predetermined contribution coefficient. The expression for calculating the temperature contribution is: In the formula, Indicates the temperature contribution coefficient. Indicates the contribution of temperature.

[0040] The expression for calculating the voltage contribution is: In the formula, Indicates the voltage contribution coefficient. This indicates the voltage contribution.

[0041] S516. Based on the temperature contribution and voltage contribution, determine the first cause of the anomaly.

[0042] In step S515 above, the contribution coefficient is obtained by training with historical data. In a specific embodiment, the contribution coefficient is determined by constructing the power difference using the least squares method. The regression model for each factor is expressed as follows: In the formula, This is the power difference. , and The contribution coefficient to be determined is... This is the error term; then, based on historical data under the same working conditions (sample size ≥ 500 groups, including corresponding...),... , (Data), with the least squares method as its core, by minimizing the sum of squared errors Construct the objective function and solve it using iterative calculation methods such as gradient descent. smallest and Initial values; finally, a dataset not used in training is partitioned from historical data as a validation set, and the data in the validation set is... Substituting the values ​​into the regression model containing the initial coefficients, the predicted values ​​are calculated. , then calculate If the deviation rate is ≤5%, then the coefficients in that group are determined as the final values. If the deviation exceeds the range, the above model construction and iterative calculation steps are repeated until the model deviation corresponding to the coefficients meets the accuracy requirements. It should be further noted that the sample size and the 5% deviation rate can be adjusted according to the actual situation and are not intended to limit the present invention.

[0043] In a specific embodiment, the temperature contribution coefficient is 0.015, the voltage contribution coefficient is 0.01, the temperature difference is 2℃, and the voltage difference is 5V. Therefore, the temperature contribution is 0.03, and the voltage contribution is 0.05. It can be seen that the voltage contribution is greater than the temperature contribution, indicating that the fluctuation of the power input voltage has a more significant impact on power anomalies and is the main factor causing power deviations from the theoretical range. Compared to ambient temperature deviations, voltage issues (such as checking the stability of the mains voltage and installing voltage regulators) should be prioritized for investigation and handling to more efficiently resolve power anomaly problems.

[0044] Power anomalies directly reflect the output characteristics of the welding machine itself, and the root cause can be relatively accurately located by analyzing directly related data such as voltage and temperature. However, since heat input is a highly comprehensive process indicator, in addition to being affected by measurable electrical parameters, it is also easily affected by factors that are difficult to quantify in real time, such as wire extension length, workpiece surface cleanliness, oxide layer thickness, shielding gas effectiveness, and even welder's operating techniques. These variables are usually not directly captured by existing sensors, so it is not possible to directly locate the cause of the anomaly through data. In this case, manual troubleshooting is required.

[0045] After acquiring the actual welding data, the process also includes: preprocessing the actual data. After acquiring the actual current, actual voltage, actual welding speed, and actual ambient temperature, data preprocessing steps are required: First, outlier removal is performed, based on the 3σ principle (using the mean of each data point as the center, removing data exceeding three times the standard deviation above and below the mean (such as extreme current values ​​caused by momentary sensor malfunctions); then, data cleaning is performed to remove redundant data collected repeatedly (such as current data recorded repeatedly at the same timestamp), and a small number of missing data are filled in using linear interpolation (such as filling missing welding speed data within a certain second with the average speed of the two adjacent seconds).

[0046] Reference Figure 2 As shown, based on the same inventive concept as the above methods, this invention also proposes a monitoring system for production management and control of mobile welding machines, including: Task determination module 110 is used to determine the welding task in response to welding instructions; The actual data acquisition module 120 is used to acquire actual data during welding. The theoretical data acquisition module 130 is used to determine the range of theoretical data for welding based on the welding task and a pre-defined standard library. The alarm module 140 is used to determine whether the actual data is within the theoretical data range. If not, an alarm is issued.

[0047] It should be further noted that the above system and method correspond one-to-one, and the design, architecture, and operating mechanism of each functional module are closely aligned with the steps and stages of the method described below. Therefore, this paper provides a complete exposition of the method and a brief introduction to the above system. It should also be noted that, based on the complete exposition of the method, those skilled in the art can clearly understand the structure and operating logic of the system.

[0048] Reference Figure 3 As shown, based on the same inventive concept as the above method, the present invention also proposes a device, including a memory and a processor, wherein the memory stores computer instructions that can be executed on the processor, and the processor executes the above-mentioned monitoring method for production management and control of mobile welding machines when executing the computer instructions.

[0049] Reference Figure 4 As shown, based on the same inventive concept as the above method, the present invention also proposes a computer-readable storage medium storing computer instructions thereon, which can realize the above-mentioned monitoring method for production management and control of mobile welding machines when the computer instructions are executed.

[0050] Any references to memory, storage, database, or other media used in the embodiments provided in this invention may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory.

[0051] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0052] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A monitoring method for mobile welding machine production management control, characterized by, The method comprises the following steps: in response to a welding instruction, determining a welding task; acquiring actual data during welding; based on the welding task, determining a theoretical data range during welding through a pre-determined standard library; judging whether the actual data is within the theoretical data range, and if not, issuing an alarm; the actual data includes actual current, actual voltage and actual welding speed; after acquiring the actual data during welding, the method further comprises the following step: based on the actual current and the actual voltage, determining actual power; the theoretical data range includes a theoretical power range and a theoretical heat input range, and the judging step includes the following steps: judging whether the actual power is within the theoretical power range, and if not, issuing a first alarm; comparing whether the actual heat input is within the heat input range, and if not, issuing a second alarm; if neither the actual power nor the actual heat input is within the theoretical power range and the heat input range, issuing a third alarm; after issuing the first alarm, the method further comprises the following step: determining a first alarm cause; the theoretical data range further includes a theoretical ambient temperature range and a theoretical voltage range, and the actual data further includes actual ambient temperature; the determining step of the first alarm cause includes the following steps: Based on the theoretical voltage range, a theoretical average voltage is determined, expressed as: wherein denotes the theoretical average voltage, denotes the upper limit of the theoretical voltage range, denotes the lower limit of the theoretical voltage range; Based on the theoretical average voltage and the actual voltage, a voltage difference value is determined, expressed as: , where represents the voltage difference value. Based on the theoretical ambient temperature range, a theoretical average temperature is determined, expressed as: wherein denotes the theoretical average temperature, denotes the upper limit of the theoretical ambient temperature range, denotes the lower limit of the theoretical ambient temperature range. Based on the theoretical average temperature and the actual ambient temperature, a temperature difference value is determined, where represents the temperature difference value, represents the actual ambient temperature; based on the temperature difference and the voltage difference, determining temperature contribution and voltage contribution through pre-determined contribution coefficients; based on the temperature contribution and the voltage contribution, determining a first abnormal cause.

2. The monitoring method of mobile welder production management control according to claim 1, characterized in that, The actual power is expressed by: wherein represents the actual power, represents the actual voltage, represents the actual current, represents the power factor; Based on the actual current, actual voltage and actual welding speed, an actual heat input is determined, expressed as: , where represents the actual heat input, represents the actual current, represents the actual welding speed, represents the actual voltage.

3. The monitoring method of mobile welder production management control according to claim 2, characterized in that, after acquiring the actual data during welding, the method further comprises the following step: pre-processing the actual data.

4. A monitoring system for mobile welding machine production management control, characterized in that, The method comprises the following steps: a task determining module for determining a welding task in response to a welding instruction; an actual data acquiring module for acquiring actual data during welding; a theoretical data acquiring module for determining a theoretical data range during welding based on the welding task through a pre-determined standard library; an alarm module for judging whether the actual data is within the theoretical data range, and if not, issuing an alarm.

5. An apparatus comprising a memory and a processor, said memory having stored thereon computer instructions executable on said processor, characterized in that, The processor executes the computer instructions to perform the monitoring method of the mobile welding machine production management control according to any one of claims 1 to 3.

6. A computer readable storage medium having computer instructions stored thereon, wherein: when the computer instructions are executed, the monitoring method of the mobile welding machine production management control according to any one of claims 1 to 3 can be implemented.

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