Whole-process management platform suitable for welding training examination

Abstract

The invention discloses a full-process management platform suitable for welding training examination, relates to the technical field of welding examination training, and solves the technical problems that in the prior art, data acquisition and analysis cannot be carried out on a welding process, and score addition and score reduction cannot be carried out according to whole-process analysis. Specifically, a welding machine operation analysis unit analyzes welding machine operation regulation and control in the checking process; the process evaluation and analysis unit performs welding process evaluation on an examiner, collects a welding depth parameter and a welding deviation parameter, generates a process evaluation and analysis abnormal signal or a process evaluation and analysis normal signal according to parameter analysis, and sends the signal to the full-process management platform; and the full-process management platform performs score addition and score subtraction on the assessor according to the type of the received signal, and performs score setting according to the corresponding process execution degree.

Description

Technical Field

[0001] The present invention relates to the technical field of welding assessment and training, and in particular to a full-process management platform suitable for welding training and assessment. Background Art

[0002] Welding assessment training is an important part of ensuring that welders have qualified skills and knowledge. Welding assessment training usually includes the following contents: theoretical knowledge learning, welding principles, welding materials, welding processes, practical operation training, safety knowledge training, and theoretical examinations.

[0003] However, in the prior art, it is impossible to test welding material storage, welding material selection and welding machine analysis during welding training assessment, and it is impossible to ensure whether the welding control during the current welding process meets the actual process execution efficiency, and it is also impossible to conduct further assessment training and testing on the assessors. In addition, it is impossible to collect and analyze data on the welding process, and it is impossible to add or subtract points based on the analysis of the entire process, which reduces the efficiency and accuracy of the assessment training;

[0004] In view of the above technical defects, a solution is now proposed. Summary of the invention

[0005] The purpose of the present invention is to solve the above-mentioned problems and to propose a full-process management platform suitable for welding training and assessment.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] A full-process management platform suitable for welding training and assessment, comprising a full-process management platform, wherein the full-process management platform is communicatively connected with a welding material management and detection unit, a welding material selection and analysis unit, a welding operation analysis unit, and a process evaluation and analysis unit;

[0008] The welding material management and inspection unit performs storage management inspection on welding materials required for welding training and assessment, collects welding material management and inspection information, and substitutes it into the formula to obtain the welding material management and inspection coefficient of the welding material storage area, and infers whether the storage management inspection is normal based on the coefficient comparison;

[0009] The welding material selection and analysis unit conducts welding material selection analysis on the welding process performed by the examiner, obtains welding suspension information and type overlap information, generates a rematch signal or a qualified match signal based on information comparison and analysis, and sends it to the full process management platform;

[0010] The welding machine operation analysis unit analyzes the welding machine operation control during the assessment process, obtains the welding machine parameter control operation, and obtains the welding control operation according to the control operation impact. It also collects the adaptation control data and control deviation data during the assessment and training process, generates welding machine operation abnormality signal or welding machine operation normal signal based on data comparison and analysis, and sends it to the full process management platform;

[0011] The process assessment and analysis unit conducts welding process assessment on the assessors, collects welding depth parameters and welding deviation parameters, generates process assessment analysis abnormal signals or process assessment analysis normal signals based on parameter analysis, and sends them to the full-process management platform; the full-process management platform adds or subtracts points for the assessors based on the type of received signals, and sets scores based on the degree of execution of the corresponding process.

[0012] As a preferred embodiment of the present invention, the welding material management and detection information includes the shortened span of the interval value between the floating span value of the ambient temperature and humidity around the welding material in the welding material storage area and the floating span value of the ambient temperature and humidity in the area surrounding the welding material storage area, the maximum deviation value of the ventilation volume corresponding to any two storage periods in the welding material storage area, and the proportion of different types of doped storage quantities of the same batch of welding materials in the welding material storage area corresponding to any storage time to the total number of batches.

[0013] As a preferred embodiment of the present invention, if the welding material management detection coefficient of the welding material storage area exceeds the welding material management detection coefficient threshold, a management detection risk signal is generated; if the welding material management detection coefficient of the welding material storage area does not exceed the welding material management detection coefficient threshold, a management detection safety signal is generated.

[0014] As a preferred embodiment of the present invention, the welding suspension information and type overlap information are respectively the proportion of welding suspension times when the welding material type selected in the historical assessment process is consistent with the real-time plate type, and the frequency of occurrence of the welding material type and plate type corresponding to the welding process that passed the assessment in the historical assessment process and the selected welding material type and the real-time plate type.

[0015] As a preferred embodiment of the present invention, if the welding interruption information exceeds the welding interruption frequency ratio threshold, or the type overlap information does not exceed the type consistent occurrence frequency threshold, a re-matching signal is generated; if the welding interruption information does not exceed the welding interruption frequency ratio threshold, and the type overlap information exceeds the type consistent occurrence frequency threshold, a matching qualified signal is generated.

[0016] As a preferred embodiment of the present invention, the adaptive control data and the control deviation data are respectively the ratio of the number of adaptive control operations to the number of non-adaptive control operations of the welding parameter control operation when the welding control operation needs to be executed at the real-time weld adjustment moment during the assessment and training process, and the cumulative deviation time between the adaptive welding control operation corresponding to the real-time weld adjustment moment during the assessment and training process and the corresponding demand moment and control moment of the welding machine parameter control operation.

[0017] As a preferred embodiment of the present invention, if the adaptive control data does not exceed the number ratio threshold, or the control deviation data exceeds the cumulative deviation time threshold, a welding machine operation abnormal signal is generated; if the adaptive control data exceeds the number ratio threshold, and the control deviation data does not exceed the cumulative deviation time threshold, a welding machine operation normal signal is generated.

[0018] As a preferred embodiment of the present invention, the welding depth parameter and the welding deviation parameter are respectively the reciprocating floating span of the welding depth at each position inside the weld on the plate surface where the assessor performs the welding process, and the deviation value ratio of the weld thickness deviation at each part of the plate surface where the assessor performs the welding process to the deviation of the undeformed surface area at each part.

[0019] As a preferred embodiment of the present invention, if the welding depth parameter exceeds the welding depth reciprocating floating span threshold, or the welding deviation parameter exceeds the deviation value ratio threshold, a process assessment and analysis abnormal signal is generated; if the welding depth parameter does not exceed the welding depth reciprocating floating span threshold, and the welding deviation parameter does not exceed the deviation value ratio threshold, a process assessment and analysis normal signal is generated.

[0020] Compared with the prior art, the present invention has the following beneficial effects:

[0021] 1. In the present invention, the welding materials required for welding training and assessment are stored and managed for inspection. Through the welding material storage and management inspection, it is inferred whether the quality of the welding materials used in the current welding training and assessment is qualified, so as to avoid abnormal welding material quality, which reduces the utilization efficiency of welding materials and affects the welding process assessment results. The deviation of the assessment of the assessor increases the execution pressure of the assessment process, and the increase in the number of assessments indirectly increases the assessment cost. The welding material selection analysis is performed on the welding process executed by the assessor to infer whether the current assessor’s selection of welding materials corresponding to the current welding process requirements is suitable, so as to avoid the current welding process corresponding to the material and the welding material being incompatible, resulting in a decline in the quality of the welding process. Incompatible welding materials will also cause damage to the plate, reducing the sustainability of the welding assessment.

[0022] 2. In the present invention, the operation control of the welding machine during the assessment process is analyzed to infer whether the welding control meets the actual process execution efficiency when the current welding process is executed, and further assessment training and detection are carried out for the assessors to ensure the execution efficiency of the welding process and improve the accuracy of the assessment training of the assessors; the welding process is evaluated for the assessors, and the system gradually eliminates the influence of welding materials, welding control and welding material selection, and is carried out in the order of the training process, which has the effect of assessment training and detection while improving the accuracy of process evaluation analysis, avoiding the welding process being affected by other factors, resulting in inaccurate assessment; at the same time, each process in the assessment process also plays a training role for the assessors, so that they understand the influence of each process. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0024] Figure 1 A flow chart of the welding assessment training of the present invention;

[0025] Figure 2 It is a principle block diagram of the whole invention. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0028] Embodiment 1

[0029] See also Figure 1 As shown in the figure, the overall process of welding training and assessment is welding material management, welding material selection, welding machine control and process assessment. Through the coordinated execution of each process and the execution and inspection of a single process, the actual welding level of the current training and assessment personnel is judged;

[0030] Embodiment 2

[0031] This embodiment is a full-process management system built to adapt to the welding training and assessment of the previous embodiment. Please refer to Figure 2 As shown, a full-process management platform suitable for welding training and assessment includes a full-process management platform, wherein the full-process management platform is communicatively connected with a welding material management and detection unit, a welding material selection and analysis unit, a welding operation analysis unit, and a process evaluation and analysis unit, wherein the full-process management platform is bidirectionally communicated with the welding material management and detection unit, the welding material selection and analysis unit, the welding operation analysis unit, and the process evaluation and analysis unit;

[0032] The full-process management platform generates a welding material management detection signal and sends it to the welding material management detection unit. After receiving the welding material management detection signal, the welding material management detection unit performs storage management detection on the welding materials required for welding training and assessment. Through the welding material storage management detection, it is inferred whether the quality of the welding materials used in the current welding training and assessment is qualified, so as to avoid abnormal welding material quality that reduces the efficiency of welding material use, affects the welding process assessment results, and causes deviations in the assessment of the assessors. At the same time, it increases the execution pressure of the assessment process and increases the number of assessments, which indirectly increases the assessment cost;

[0033] Obtain the shortened span of the interval between the floating span value of the ambient temperature and humidity around the welding material in the welding material storage area and the floating span value of the ambient temperature and humidity in the surrounding area of ​​the welding material storage area, and obtain the maximum deviation value of the ventilation volume corresponding to any two storage periods in the welding material storage area, and mark the shortened span of the interval between the floating span value of the ambient temperature and humidity around the welding material in the welding material storage area and the floating span value of the ambient temperature and humidity in the surrounding area of ​​the welding material storage area, and the maximum deviation value of the ventilation volume corresponding to any two storage periods in the welding material storage area as JGK and FLP respectively; obtain the proportion of the storage amount of different types of doping of the same batch of welding materials in the welding material storage area corresponding to any storage time and the total number of batches, and mark the proportion of the storage amount of different types of doping of the same batch of welding materials in the welding material storage area corresponding to any storage time and the total number of batches as SZB;

[0034] The above collected data are uniformly marked as welding material management and inspection information, and substituted into the formula to obtain the welding material management inspection coefficient JC of the welding material storage area, where the formula is: Among them, dhj1, dhj2, and dhj3 are preset proportional coefficients, and α is an error correction factor with a value of 0.98;

[0035] Compare the welding material management detection coefficient JC of the welding material storage area with the welding material management detection coefficient threshold:

[0036] If the welding material management detection coefficient JC of the welding material storage area exceeds the welding material management detection coefficient threshold, it is determined that the welding material storage area is susceptible to environmental influences, and a management detection risk signal is generated and sent to the full-process management platform. After receiving the management detection risk signal, the full-process management platform also performs temperature and humidity detection and ventilation volume control on the surrounding areas of the current storage area when detecting the welding material storage area;

[0037] If the welding material management detection coefficient JC of the welding material storage area does not exceed the welding material management detection coefficient threshold, it is determined that the welding material storage area is not easily affected by the environment, and a management detection safety signal is generated and sent to the full-process management platform; the full-process management platform conducts an assessment after determining that the management detection of the welding material storage area is qualified;

[0038] At the same time, a welding material selection analysis signal is generated and sent to a welding material selection analysis unit. After receiving the welding material selection analysis signal, the welding material selection analysis unit performs welding material selection analysis on the welding process performed by the examiner, and infers whether the current examiner is suitable for the welding material selection corresponding to the current welding process requirements, so as to avoid the current welding process corresponding material and welding material being incompatible, resulting in a decrease in welding process quality. Incompatible welding materials may also cause damage to the plate, reducing the sustainability of welding assessment;

[0039] The welding material type currently selected by the assessor is obtained and marked as the selected welding material type. At the same time, the proportion of welding suspension times when the selected welding material type is consistent with the real-time plate type in the historical assessment process is collected, and the frequency of the welding material type and plate type corresponding to the welding process that passed the assessment in the historical assessment process and the selected welding material type and the real-time plate type are collected. The proportion of welding suspension times when the selected welding material type is consistent with the real-time plate type in the historical assessment process and the frequency of the welding material type and plate type corresponding to the welding process that passed the assessment in the historical assessment process and the selected welding material type and the real-time plate type are marked as welding suspension information and type overlap information, respectively, and compared with the welding suspension times proportion threshold and the type consistency frequency threshold, respectively:

[0040] If the proportion of welding interruptions when the selected welding material type is consistent with the real-time plate type in the historical assessment process exceeds the threshold of the proportion of welding interruptions, or the frequency of the welding material type and plate type corresponding to the welding process that passed the assessment in the historical assessment process is consistent with the selected welding material type and the real-time plate type does not exceed the threshold of the frequency of type consistency, then it is judged that the selected welding material type and the real-time plate type need to be re-matched in the current assessment process, and a re-matching signal is generated and sent to the full-process management platform. After receiving the re-matching signal, the full-process management platform issues an assessment warning to the current assessor and reminds the assessor to change the welding material;

[0041] If the proportion of welding suspension times when the selected welding material type is consistent with the real-time plate type in the historical assessment process does not exceed the welding suspension times proportion threshold, and the frequency of the welding material type and plate type corresponding to the welding process that passed the assessment in the historical assessment process and the selected welding material type and the real-time plate type being consistent exceeds the type consistency frequency threshold, then it is determined that the selected welding material type in the current assessment process matches the real-time plate type, and a matching qualified signal is generated and sent to the full-process management platform;

[0042] After receiving the matching qualified signal, the full process management platform generates a welding machine operation analysis signal and sends the welding machine operation analysis signal to the welding machine operation analysis unit; after receiving the welding machine operation analysis signal, the welding machine operation analysis unit analyzes the welding machine operation control during the assessment process, infers whether the welding control meets the actual process execution efficiency during the current welding process execution, and further conducts assessment training and testing on the assessors to ensure the execution efficiency of the welding process and improve the assessment training accuracy of the assessors;

[0043] The welding machine parameter control operation is obtained, and the welding control operation is obtained according to the influence of the control operation. Specifically, the welding machine parameter control operation is current and voltage control, that is, when the current and voltage increase, the welding penetration, weld width and weld formation can be controlled; the corresponding welding control operation is to increase the penetration depth operation, etc.; wire feeding speed control, that is, inappropriate wire feeding speed will lead to defects such as uneven welds and accumulation; the corresponding welding control operation is to reduce weld accumulation operation;

[0044] The ratio of the number of adaptive controls to the number of non-adaptive controls of the welding parameter control operation when the welding control operation needs to be performed at the real-time weld adjustment moment during the assessment and training process is obtained, and at the same time, the cumulative deviation time between the adaptive welding control operation corresponding to the real-time weld adjustment moment during the assessment and training process and the welding machine parameter control operation corresponding to the demand time and the control time is obtained, and the ratio of the number of adaptive controls to the number of non-adaptive controls of the welding parameter control operation when the welding control operation needs to be performed at the real-time weld adjustment moment during the assessment and training process, and the cumulative deviation time between the adaptive welding control operation corresponding to the real-time weld adjustment moment during the assessment and training process and the welding machine parameter control operation corresponding to the demand time and the control time are marked as adaptive control data and control deviation data, respectively, and compared with the number ratio threshold and the cumulative deviation time threshold, respectively:

[0045] If the ratio of the number of adaptive control times of the welding parameter control operation to the number of non-adaptive control times when the welding control operation corresponding to the real-time weld adjustment moment during the assessment and training process needs to be executed does not exceed the number ratio threshold, or the cumulative deviation time between the adaptive welding control operation corresponding to the real-time weld adjustment moment during the assessment and training process and the corresponding demand moment and control moment of the welding machine parameter control operation exceeds the cumulative deviation time threshold, then it is determined that the welding machine operation control analysis during the assessment and training process is abnormal, and a welding machine operation abnormality signal is generated and sent to the full-process management platform. After receiving the welding machine operation abnormality signal, the full-process management platform performs a voice broadcast to the current assessor;

[0046] If the ratio of the number of adaptive control times of the welding parameter control operation to the number of non-adaptive control times when the welding control operation corresponding to the real-time weld adjustment moment during the assessment and training process needs to be executed exceeds the number ratio threshold, and the cumulative deviation time between the adaptive welding control operation corresponding to the real-time weld adjustment moment during the assessment and training process and the corresponding demand moment and control moment of the welding machine parameter control operation does not exceed the cumulative deviation time threshold, then it is determined that the welding machine operation control analysis during the assessment and training process is normal, a welding machine operation normal signal is generated, and the welding machine operation normal signal is sent to the full-process management platform;

[0047] At the same time, a process assessment analysis signal is generated and sent to the process assessment analysis unit. After receiving the process assessment analysis signal, the process assessment analysis unit conducts welding process assessment on the assessor. The system gradually eliminates the influence of welding materials, welding control and welding material selection, and performs the assessment in the order of the training process, which improves the accuracy of process assessment analysis while achieving the assessment and training detection effect, and avoids the welding process being affected by other factors, resulting in inaccurate assessment. At the same time, each process in the assessment process also plays a training role for the assessor, so that he understands the influence of each process;

[0048] The reciprocating floating span of the welding depth corresponding to each position inside the weld on the plate surface where the assessor performs the welding process is obtained, and at the same time, the deviation value ratio of the weld thickness deviation at each position on the plate surface where the assessor performs the welding process to the deviation of the undeformed surface area at each position is obtained, and the reciprocating floating span of the welding depth corresponding to each position inside the weld on the plate surface where the assessor performs the welding process and the deviation value ratio of the weld thickness deviation at each position on the plate surface where the assessor performs the welding process and the deviation value ratio of the undeformed surface area deviation at each position are marked as welding depth parameters and welding deviation parameters, respectively, and compared with the welding depth reciprocating floating span threshold and the deviation value ratio threshold, respectively:

[0049] If the reciprocating floating span of the welding depth at each position inside the weld on the plate surface where the assessor performs the welding process exceeds the reciprocating floating span threshold of the welding depth, or the corresponding deviation value ratio of the weld thickness deviation at each position on the plate surface where the assessor performs the welding process and the non-deformed surface area deviation at each position exceeds the deviation value ratio threshold, then the welding process assessment analysis of the assessor is judged to be abnormal, and a process assessment analysis abnormality signal is generated and sent to the full-process management platform;

[0050] If the reciprocating floating span of the welding depth at each position inside the weld on the plate surface where the assessor performs the welding process does not exceed the reciprocating floating span threshold of the welding depth, and the corresponding deviation value ratio of the weld thickness deviation at each position on the plate surface where the assessor performs the welding process and the non-deformed surface area deviation at each position does not exceed the deviation value ratio threshold, then the welding process assessment analysis of the assessor is judged to be normal, a normal process assessment analysis signal is generated, and the normal process assessment analysis signal is sent to the full-process management platform;

[0051] The full-process management platform adds or subtracts points for the assessors according to the type of received signals, and sets the score according to the execution degree of the corresponding process. For example, if the weld thickness deviation is 5 mm, one point will be subtracted, and if it is 4 mm, 0.8 points will be subtracted. Among them, rematching signals, abnormal welding machine operation signals, and abnormal process assessment and analysis signals are all subtraction signals, and matching qualified signals, normal welding machine operation signals, and normal process assessment and analysis signals are all addition signals.

[0052] The above formulas are obtained by collecting a large amount of data and performing software simulation, and a formula close to the actual value is selected. The coefficients in the formula are set by technicians in this field according to actual conditions;

[0053] When the present invention is in use, the welding material management and detection unit performs storage management detection on the welding materials required for welding training and assessment, collects welding material management and detection information, substitutes it into the formula to obtain the welding material management and detection coefficient of the welding material storage area, and infers whether the storage management and detection is normal based on the coefficient comparison; the welding material selection and analysis unit performs welding material selection analysis on the welding process performed by the assessor, obtains welding termination information and type overlap information, generates a rematch signal or a match qualified signal based on the information comparison and analysis, and sends it to the full-process management platform; the welding machine operation analysis unit analyzes the operation and control of the welding machine during the assessment process, and obtains the welding machine parameter control operation information. , and obtain the welding control operation according to the influence of the control operation, and collect the adaptation control data and control deviation data during the assessment and training process, generate the welding machine operation abnormal signal or the welding machine operation normal signal according to the data comparison and analysis, and send it to the whole process management platform; the process assessment and analysis unit conducts welding process assessment on the assessor, collects the welding depth parameters and welding deviation parameters, and generates the process assessment analysis abnormal signal or the process assessment analysis normal signal according to the parameter analysis, and sends it to the whole process management platform; the whole process management platform adds or subtracts points for the assessor according to the type of received signal, and sets the score according to the corresponding process execution degree.

[0054] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A full-process management platform suitable for welding training and assessment, It is characterized in that It includes a full-process management platform, which is connected to the welding material management and detection unit, welding material selection and analysis unit, welding operation analysis unit and process evaluation and analysis unit; The welding material management and inspection unit performs storage management inspection on welding materials required for welding training and assessment, collects welding material management and inspection information, and substitutes it into the formula to obtain the welding material management and inspection coefficient of the welding material storage area, and infers whether the storage management inspection is normal based on the coefficient comparison; The welding material selection and analysis unit conducts welding material selection analysis on the welding process performed by the examiner, obtains welding suspension information and type overlap information, generates a rematch signal or a qualified match signal based on information comparison and analysis, and sends it to the full process management platform; The welding machine operation analysis unit analyzes the welding machine operation control during the assessment process, obtains the welding machine parameter control operation, and obtains the welding control operation according to the control operation impact. It also collects the adaptation control data and control deviation data during the assessment and training process, generates welding machine operation abnormality signal or welding machine operation normal signal based on data comparison and analysis, and sends it to the full process management platform; The process assessment and analysis unit conducts welding process assessment on the assessors, collects welding depth parameters and welding deviation parameters, generates process assessment analysis abnormal signals or process assessment analysis normal signals based on parameter analysis, and sends them to the full process management platform; The full-process management platform adds or subtracts points for assessors based on the type of signal received, and sets scores based on the degree of execution of the corresponding process.

2. A full-process management platform suitable for welding training and assessment according to claim 1, It is characterized in that The welding material management and inspection information includes the shortened span of the interval between the floating span value of the ambient temperature and humidity around the welding materials in the welding material storage area and the floating span value of the ambient temperature and humidity in the area surrounding the welding material storage area, the maximum deviation value of the ventilation volume corresponding to any two storage cycles in the welding material storage area, and the proportion of different types of doped storage quantities of the same batch of welding materials in the welding material storage area corresponding to any storage time to the total number of batches.

3. A full-process management platform suitable for welding training and assessment according to claim 2, It is characterized in that If the welding material management inspection coefficient of the welding material storage area exceeds the welding material management inspection coefficient threshold, a management inspection risk signal is generated; if the welding material management inspection coefficient of the welding material storage area does not exceed the welding material management inspection coefficient threshold, a management inspection safety signal is generated.

4. According to claim 1, a full-process management platform suitable for welding training and assessment, It is characterized in that The welding suspension information and type overlap information are respectively the proportion of welding suspension times when the welding material type selected in the historical assessment process is consistent with the real-time plate type, and the frequency of occurrence of the welding material type and plate type corresponding to the welding process that passed the assessment in the historical assessment process and the selected welding material type and real-time plate type.

5. According to claim 4, a full-process management platform suitable for welding training and assessment, It is characterized in that If the welding interruption information exceeds the welding interruption frequency ratio threshold, or the type overlap information does not exceed the type consistent occurrence frequency threshold, a re-matching signal is generated; if the welding interruption information does not exceed the welding interruption frequency ratio threshold, and the type overlap information exceeds the type consistent occurrence frequency threshold, a matching qualified signal is generated.

6. A full-process management platform suitable for welding training and assessment according to claim 1, It is characterized in that The adaptive control data and the control deviation data are respectively the ratio of the number of adaptive control operations to the number of non-adaptive control operations of welding parameter control operations when the welding control operation needs to be performed at the real-time weld adjustment moment during the assessment and training process, and the cumulative deviation time between the adaptive welding control operation corresponding to the real-time weld adjustment moment during the assessment and training process and the demand moment and the control moment corresponding to the welding machine parameter control operation.

7. A full-process management platform suitable for welding training and assessment according to claim 6, It is characterized in that If the adaptive control data does not exceed the number ratio threshold, or the control deviation data exceeds the cumulative deviation time threshold, an abnormal welding machine operation signal is generated; if the adaptive control data exceeds the number ratio threshold, and the control deviation data does not exceed the cumulative deviation time threshold, a normal welding machine operation signal is generated.

8. According to claim 1, a full-process management platform suitable for welding training and assessment, It is characterized in that The welding depth parameter and the welding deviation parameter are respectively the reciprocating floating span of the welding depth at each position inside the weld on the plate surface where the assessor performs the welding process, and the deviation value ratio of the weld thickness deviation at each part of the plate surface where the assessor performs the welding process to the deviation of the undeformed surface area at each part.

9. A full-process management platform suitable for welding training and assessment according to claim 8, It is characterized in that If the welding depth parameter exceeds the welding depth reciprocating floating span threshold, or the welding deviation parameter exceeds the deviation value ratio threshold, a process assessment analysis abnormal signal is generated; if the welding depth parameter does not exceed the welding depth reciprocating floating span threshold, and the welding deviation parameter does not exceed the deviation value ratio threshold, a process assessment analysis normal signal is generated.

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