Digital intelligent supervision platform for electro-gas welding operation

Abstract

The invention discloses an electrogas welding operation digital intelligent supervision platform, and relates to the technical field of electrogas welding operation supervision, and the technical scheme is that the electrogas welding operation digital intelligent supervision platform comprises a welding quality analysis module, a welding equipment supervision module, a welding equipment analysis module, an early warning terminal and a database. Then corresponding intelligent supervision is carried out, the welding change of the electro-gas welding equipment in the welding process is analyzed, the influence of the welding change on the corresponding welding stability of the electro-gas welding equipment and the corresponding transmission condition of the electro-gas welding equipment in the welding process are known and analyzed, and therefore the analysis result is synthesized, and the welding stability of the electro-gas welding equipment is obtained. According to the method, a welding safety evaluation model of the electro-gas welding equipment in the welding process is established, so that whether the current electro-gas welding equipment has welding potential safety hazards or not is analyzed, efficient and intelligent guarantee during electro-gas welding operation is achieved, the accident risk of electro-gas welding operation is reduced, potential safety hazards of the electro-gas welding equipment are found in time, and the accident occurrence probability is reduced and avoided; the operation safety is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of electric welding operation supervision, and in particular to a digital intelligent supervision platform for electric welding operations. Background Art

[0002] As the application of electric welding becomes increasingly widespread, the supervision of its application also needs to be gradually strengthened. The application of electric welding involves many dangerous factors, and if you are not careful, it will cause safety accidents. The emergence of digital intelligent supervision platforms has efficiently realized the intelligent supervision of electric welding operations. Based on intelligent digital technology, it can achieve comprehensive and effective supervision of electric welding equipment during welding, ensure the safety of electric welding operations, and reduce the risk of accidents in electric welding operations.

[0003] Existing technologies, such as the invention patent application with announcement number CN119048000A, disclose a digital intelligent supervision platform for electric welding operations, which includes a user management module, a filing management module, an approval management module, an equipment management module, and an early warning management module. The user management module is responsible for managing the user identities and permissions of the platform; the filing management module is used to manage and supervise the filing application and qualification approval process for electric welding operations; the approval management module is responsible for approving and processing electric welding operation applications submitted by hot work personnel; the equipment management module is responsible for monitoring and managing electric welding equipment; and the early warning management module is used to issue early warnings in a timely manner for abnormal situations to remind relevant personnel to pay attention and take necessary measures. The platform sets up strict qualification review and operation review procedures, monitors and manages electric welding equipment, and integrates advanced positioning technology, Internet of Things technology, and artificial intelligence algorithms, which greatly improves the supervision efficiency and safety of electric welding operations.

[0004] With respect to the above scheme, there are the following technical problems: the above invention is mainly based on the supervision of the application of the relevant identity and role qualifications of the operating personnel, and does not carry out intelligent supervision of the weldments in welding. It is impossible to obtain the entity data of the weldments in welding, fail to timely understand the quality form of the weldments in welding, and cannot ensure whether the welder's current electric welding setting parameters and the equipment itself are normal when welding the weldments. There are welding quality problems and welding equipment safety risks. Therefore, it is impossible to carry out corresponding supervision and analysis of the electric welding equipment based on the perspective of the weldment entity, and the corresponding welding information of the electric welding equipment in welding is not obtained. It is impossible to understand the welding changes of the electric welding equipment in welding, and it is impossible to derive the impact of the welding changes on the corresponding welding stability of the electric welding equipment. At the same time, the transmission data of the electric welding equipment in welding is not collected, and the corresponding transmission coefficient of the electric welding equipment in welding cannot be obtained. It is also impossible to establish a welding safety assessment model for the electric welding equipment in welding based on the welding changes, stability effects and transmission coefficients obtained by the above analysis. It is impossible to know in time whether there are welding safety hazards in the current electric welding equipment, and it is impossible to achieve intelligent and efficient protection of the application safety of the electric welding equipment during operation, and there are electric welding application safety risks. Summary of the Invention

[0005] In view of the above-mentioned technical deficiencies, the purpose of the present invention is to provide a digital intelligent supervision platform and system for electric welding operations.

[0006] In order to solve the above technical problems, the present invention adopts the following technical solutions: The present invention provides a digital intelligent supervision platform and system for electric welding operations, including: a welding quality analysis module for intelligently supervising welds during welding, thereby obtaining the physical data of welds during welding, and then judging the quality morphology of welds during welding.

[0007] The welding equipment supervision module is used to obtain the corresponding welding information of the electric welding equipment during welding, and then analyze the welding changes of the electric welding equipment during welding, analyze the impact of the welding changes on the corresponding welding stability of the electric welding equipment, and collect the corresponding transmission data of the electric welding equipment during welding, and analyze and obtain the corresponding transmission coefficient of the electric welding equipment during welding.

[0008] The welding equipment analysis module is used to establish a welding safety assessment model for electric welding equipment during welding based on the impact of welding changes on the corresponding welding stability of electric welding equipment and the corresponding transmission coefficient of electric welding equipment during welding, and then analyze whether there are any welding safety hazards in the current electric welding equipment.

[0009] The early warning terminal is used to provide early warning when there are welding safety hazards in the electric welding equipment.

[0010] Compared with the prior art, the present invention has the following beneficial effects:

[0011] 1. The present invention provides a digital intelligent supervision platform for electric welding operations. By performing corresponding intelligent supervision based on the judged quality morphology of welds, the welding changes of electric welding equipment during welding are analyzed, and the influence of welding changes on the corresponding welding stability of electric welding equipment and the corresponding transmission conditions of electric welding equipment during welding are understood and analyzed. Based on the results of the above analysis, a welding safety assessment model for electric welding equipment during welding is established. In this way, it is analyzed whether there are welding safety hazards in the current electric welding equipment, efficient and intelligent protection of electric welding during operation is implemented, safe electric welding operations are performed, and the risk of electric welding operation accidents is reduced. This solves the shortcomings of current technologies, timely discovers potential safety hazards of electric welding equipment, further reduces and avoids the probability of electric welding equipment safety accidents, and ensures the safety of electric welding operations.

[0012] 2. Intelligently monitor the weldment in progress, and then obtain the physical data of the weldment in welding, and then judge the quality of the weldment in welding, so as to efficiently understand the current welding status of the weldment, and timely discover abnormalities in the parameters and specifications of the electric welding equipment. From this perspective, analyze the abnormal parameters of the electric welding equipment, reduce the risk of application failure of the electric welding equipment, and provide accurate and effective direction for subsequent analysis.

[0013] 3. Obtain the corresponding welding information of the electric welding equipment during welding, and then analyze the welding changes of the electric welding equipment during welding, analyze the impact of the welding changes on the corresponding welding stability of the electric welding equipment, and collect the corresponding transmission data of the electric welding equipment during welding, and analyze the corresponding transmission coefficient of the electric welding equipment during welding, so as to timely understand the welding changes of the current electric welding equipment during welding, and based on the impact of its welding changes on the electric welding equipment itself, effectively understand the basic situation corresponding to the current electric welding equipment, further reduce and avoid the probability of safety accidents of electric welding equipment, and at the same time combine the corresponding transmission data to achieve efficient protection of electric welding operation safety and extend the service life of the equipment.

[0014] 4. Based on the impact of welding changes on the corresponding welding stability of electric welding equipment and the corresponding transmission coefficient of electric welding equipment during welding, a welding safety assessment model for electric welding equipment during welding is established, and then the current electric welding equipment is analyzed to see if there are any welding safety hazards. From the perspective of comprehensive analysis of electric welding, the safety of electric welding equipment during operation is fully guaranteed, the risk of electric welding operation accidents is reduced, and comprehensive and effective supervision of electric welding equipment during welding is achieved, further reducing and avoiding the probability of electric welding equipment safety accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0016] Figure 1 This is a schematic diagram of the system structure connection of the present invention. DETAILED DESCRIPTION

[0017] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0018] See also Figure 1 As shown, a digital intelligent supervision platform for electric welding operations includes a welding quality analysis module, a welding equipment supervision module, a welding equipment analysis module, an early warning terminal and a database.

[0019] The welding quality analysis module is connected to the welding equipment supervision module and the database respectively, the welding equipment supervision module is connected to the welding equipment analysis module and the database respectively, and the welding equipment analysis module is connected to the early warning terminal and the database respectively.

[0020] The welding quality analysis module is used to intelligently monitor the weldment during welding, thereby obtaining the physical data of the weldment during welding and then judging the quality of the weldment during welding.

[0021] It should be noted that visual inspection equipment is used to monitor and supervise the weldment during welding, thereby obtaining a solid image of the weldment during welding, and extracting solid data of the weldment during welding from the solid image.

[0022] It should be noted that the weld penetration safety interval, weld width safety interval and pore number safety interval for historical welders when welding weldments are set by professional welders; the weld penetration safety interval is a reference value used to determine whether the welding performed by the welder during the welding process meets the standard weldment quality morphology. The weld width safety interval and the pore number safety interval have the same function as the weld penetration safety interval, so they are not repeated here.

[0023] As an optional implementation method, the quality form of the weldment during welding is judged, and the specific evaluation process is as follows: the entity data includes weld penetration, weld width and number of pores, and the weld penetration safety interval, weld width safety interval and number of pores safety interval of the historical welder corresponding to the weldment are obtained from the database, and then the quality form evaluation value of the weldment during welding is analyzed. If the quality form evaluation value of the weldment during welding is 1, it is determined that the quality form of the weldment during welding meets the welding standards, and the welding during welding is continued to be supervised. If the quality form evaluation value of the weldment during welding is 0, it is determined that the quality form of the weldment during welding does not meet the welding standards, and an in-depth analysis is performed on the welding of the weldment by the welder using electric welding equipment to judge the quality form of the weldment during welding.

[0024] As an optional implementation, the analysis obtains the quality morphology evaluation value of the weldment during welding. The specific analysis process is as follows: by calculating the formula: Among them, Z is the quality morphology evaluation value of the weldment during welding, A μ is the μth entity data of the weldment during welding, Α′ μ is the safety interval of the μth entity data of the weldment during welding, μ is the number of the entity data, μ[1,3] and μ[1,3] are three entity data, representing the weld penetration, weld width and number of pores in the entity data respectively, and the three entity data correspond to their respective safety intervals, namely the weld penetration safety interval, the weld width safety interval and the number of pores safety interval.

[0025] It should also be noted that the entity data includes weld penetration, weld width and number of pores.

[0026] Intelligent supervision of welds in progress can be performed to obtain physical data of welds during welding, and then the quality of welds during welding can be judged, so as to efficiently understand the current welding status of welds and promptly discover abnormalities in the parameters and specifications of electric welding equipment. Based on this, the abnormal parameters of electric welding equipment can be analyzed to reduce the risk of application failure of electric welding equipment and provide accurate and effective direction for subsequent analysis.

[0027] The welding equipment supervision module is used to obtain the corresponding welding information of the electric welding equipment during welding, and then analyze the welding changes of the electric welding equipment during welding, analyze the impact of the welding changes on the corresponding welding stability of the electric welding equipment, and collect the corresponding transmission data of the electric welding equipment during welding, and analyze and obtain the corresponding transmission coefficient of the electric welding equipment during welding.

[0028] It should be noted that when the welder starts to weld the workpiece, the digital intelligent supervision platform will automatically carry out corresponding welding supervision, using a high-speed camera to obtain the arc image of the electric welding equipment during welding, and then using professional image analysis software to extract the initial arc amplitude and arc amplitude change frequency corresponding to the electric welding equipment during welding. Professional image analysis software includes OpenCV and TensorFlow, etc.; a voltmeter is used to obtain the initial voltage and welding voltage fluctuation value corresponding to the electric welding equipment during welding. The voltmeter is connected to the power output terminal of the electric welding equipment and the digital intelligent supervision platform respectively. When the voltmeter obtains the initial voltage during welding based on the power output terminal of the electric welding equipment, The initial voltage is sent to the digital intelligent supervision platform, and based on the voltage between the initial voltage of the electric welding equipment when welding the workpiece and the current moment, the corresponding welding voltage fluctuation value of the electric welding equipment during welding is obtained; the welding current corresponding to the electric welding equipment during welding is obtained using a Hall effect sensor, and the Hall effect sensor is installed in the welding circuit. The Hall effect sensor will automatically output a corresponding voltage signal according to the magnetic field strength generated by the current, and process and convert the voltage signal to obtain the corresponding welding current; the high-speed camera, voltmeter, gas pressure sensor and Hall effect sensor are all connected to the digital intelligent supervision platform so that the digital intelligent supervision platform can implement real-time supervision of the electric welding operation.

[0029] As an optional implementation, the welding information includes initial arc amplitude, arc amplitude change frequency, initial voltage, welding voltage fluctuation value and welding current.

[0030] As an optional embodiment, the analysis of welding changes of electric welding equipment during welding is specifically carried out as follows: by constructing a welding output change model and a welding equipment change model, the welding changes of the electric welding equipment during welding are analyzed. The welding output change model formula is: is the welding output change of the electric welding equipment during the welding period s, C1 and Y are the initial arc amplitude and arc amplitude change frequency corresponding to the electric welding equipment during welding, e(-Y*M) is an exponential function, e is a natural constant, s is the welding period of the electric welding equipment, M is the welding time of the electric welding equipment, and the time corresponding to the initial welding to the s period of the electric welding equipment is M.

[0031] Through the welding equipment change model, the expression formula is: W(s)=J1*(1-U*COS(Q*M)), W(s) is the welding equipment change corresponding to the welding time period s of the electric welding equipment, J1, U and Q are the initial voltage, welding voltage fluctuation value and welding current corresponding to the electric welding equipment during welding, cos(Q*M) is the cosine function, and the value of cos(Q*M) is [-1,1].

[0032] As an optional embodiment, the analysis of the influence of welding changes on the corresponding welding stability of the electric welding equipment is as follows: according to the welding output changes corresponding to the welding time period s of the electric welding equipment, And the welding equipment change W(s) corresponding to the welding time period s of the electric welding equipment, and then calculated by the formula: Where λ(s) is the stability trend variable of the electric welding equipment during the welding period s, D1 and D2 are the weight factors of the set welding output change and the welding equipment change, respectively, 0<D1<1, 0<D2<1.

[0033] It should also be noted that D1 and D2 are set based on the current existing technology in the relevant field. The values ​​of D1 and D2 are set based on a large amount of welding data, transmission data and influencing factors of the electric welding equipment during welding.

[0034] As an optional implementation method, the transmission data corresponding to the electric welding equipment during welding is collected and analyzed to obtain the transmission coefficient corresponding to the electric welding equipment during welding. The specific analysis process is as follows: based on the welding changes of the electric welding equipment during welding, the transmission conditions of the electric welding equipment between the initial welding changes and the current welding changes are monitored, and according to the various sensor devices installed at the transmission device of the electric welding equipment, the transmission data corresponding to the electric welding equipment at the moment of welding change is obtained.

[0035] The transmission data corresponding to the electric welding equipment at the welding change moment is compared with the preset transmission data interval corresponding to the electric welding equipment in the welding. If the transmission data corresponding to the electric welding equipment at the welding change moment is within the preset transmission data interval corresponding to the electric welding equipment in the welding, the transmission compliance coefficient corresponding to the electric welding equipment in the welding period s is recorded as r1, otherwise it is recorded as r2. The transmission coefficient X(s) corresponding to the electric welding equipment in welding is obtained by analysis, where X(s) takes the value of r1 or r2, and r1 and r2 are natural numbers.

[0036] It should be noted again that the transmission data includes wire feeding speed fluctuation frequency, wire feeding force and wire feeding position offset, etc.; the various sensing devices include rotary encoders, pressure sensors and laser displacement sensors, and each sensor is connected to the digital intelligent monitoring platform; the rotary encoder converts the rotation angle and speed of the motor into a pulse signal through the internal photoelectric conversion device, so as to obtain the wire feeding speed fluctuation frequency corresponding to the electric welding equipment at the welding change moment; the pressure sensor is based on monitoring the contact point of the wire feeding wheel with the welding wire, and converts the monitored pressure into an electrical signal output, thereby obtaining the wire feeding force corresponding to the electric welding equipment at the welding change moment; the laser displacement sensor is based on monitoring the welding wire position corresponding to the electric welding equipment, and compares it with the set welding wire position to obtain the wire feeding position offset corresponding to the gas welding equipment at the welding change moment.

[0037] Obtain the corresponding welding information of the electric welding equipment during welding, and then analyze the welding changes of the electric welding equipment during welding, analyze the impact of the welding changes on the corresponding welding stability of the electric welding equipment, and collect the corresponding transmission data of the electric welding equipment during welding, and analyze the corresponding transmission coefficient of the electric welding equipment during welding, so as to timely understand the welding changes of the current electric welding equipment during welding, and based on the impact of its welding changes on the electric welding equipment itself, effectively understand the basic situation corresponding to the current electric welding equipment, further reduce and avoid the probability of safety accidents of electric welding equipment, and at the same time combine the corresponding transmission data to achieve efficient protection of electric welding operation safety and extend the service life of the equipment.

[0038] The welding equipment analysis module is used to establish a welding safety assessment model for electric welding equipment during welding based on the impact of welding changes on the corresponding welding stability of electric welding equipment and the corresponding transmission coefficient of electric welding equipment during welding, and then analyze whether there are any welding safety hazards in the current electric welding equipment.

[0039] As an optional embodiment, the welding safety assessment model of the electric welding equipment during welding is established. The specific establishment process is as follows: Based on the stability trend variable λ(s) corresponding to the electric welding equipment during the welding period s and the transmission coefficient X(s) corresponding to the electric welding equipment during the welding period s, the welding safety assessment model expression formula is obtained: Then the safety result value of the electric welding equipment corresponding to the welding period s is analyzed and obtained β1 and β2 are the weight factors of the set stability trend variable and the transmission coefficient, respectively, 0<β1<1, 0<β2<1.

[0040] It should be noted that the setting process of β1 and β2 is consistent with the setting process of D1 and D2, so it will not be described in detail.

[0041] As an optional implementation manner, the analysis of whether the current electric welding equipment has welding safety hazards is as follows: the safety result value corresponding to the electric welding equipment in the welding time period s is compared with the reference safety result threshold corresponding to the electric welding equipment stored in the database. If the safety result value corresponding to the electric welding equipment in the welding time period s is less than the reference safety result threshold corresponding to the electric welding equipment stored in the database, it is determined that the electric welding equipment has welding safety hazards in the welding time period s. If the safety result value corresponding to the electric welding equipment in the welding time period s is greater than or equal to the reference safety result threshold corresponding to the electric welding equipment stored in the database, it is determined that the electric welding equipment does not have welding safety hazards in the welding time period s. And so on, the analysis is performed to determine whether the current electric welding equipment has welding safety hazards.

[0042] It should also be noted that the reference safety result threshold corresponding to the electric welding equipment is set by professional welders; the reference safety result threshold is a reference value used to determine whether the electric welding equipment has welding safety hazards.

[0043] Based on the impact of welding changes on the corresponding welding stability of electric welding equipment and the corresponding transmission coefficient of electric welding equipment during welding, a welding safety assessment model for electric welding equipment during welding is established, and then the current electric welding equipment is analyzed to see if there are welding safety hazards. From the perspective of comprehensive analysis of electric welding, the safety of electric welding equipment during operation is fully guaranteed, the risk of electric welding operation accidents is reduced, and comprehensive and effective supervision of electric welding equipment during welding is achieved, further reducing and avoiding the probability of electric welding equipment safety accidents.

[0044] The database is used to store entity data, entity data safety intervals, welding information, transmission data, transmission data intervals and reference safety result thresholds.

[0045] The early warning terminal is used to provide early warning when there are welding safety hazards in the electric welding equipment.

[0046] The embodiment of the present invention performs corresponding intelligent supervision based on the judged quality morphology of the weldment, analyzes the welding changes of the electric welding equipment during welding, and understands and analyzes the impact of the welding changes on the corresponding welding stability of the electric welding equipment and the corresponding transmission conditions of the electric welding equipment during welding, thereby comprehensively combining the results of the above analysis to establish a welding safety assessment model for the electric welding equipment during welding, thereby analyzing whether the current electric welding equipment has welding safety hazards, implementing efficient and intelligent protection during electric welding operations, performing safe electric welding operations, reducing the risk of electric welding operation accidents, solving the deficiencies in current technologies, timely discovering potential safety hazards of electric welding equipment, further reducing and avoiding the probability of electric welding equipment safety accidents, and ensuring the safety of electric welding operations.

[0047] The above content is merely an example and explanation of the concept of the present invention. Those skilled in the art may make various modifications or additions to the described specific embodiments or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they should all fall within the scope of protection of the present invention.

Claims

1. A digital intelligent monitoring platform for electric welding operations, characterized in that: include: The welding quality analysis module is used to intelligently monitor the weldment during welding, thereby obtaining the physical data of the weldment during welding and then evaluating the quality of the weldment during welding; The welding equipment monitoring module is used to obtain the corresponding welding information of the electric welding equipment during welding, and then analyze the welding changes of the electric welding equipment during welding, analyze the impact of the welding changes on the corresponding welding stability of the electric welding equipment, and collect the corresponding transmission data of the electric welding equipment during welding to analyze and obtain the corresponding transmission coefficient of the electric welding equipment during welding; The welding equipment analysis module is used to establish a welding safety assessment model for electric welding equipment during welding based on the impact of welding changes on the corresponding welding stability of electric welding equipment and the corresponding transmission coefficient of electric welding equipment during welding, and then analyze whether there are any welding safety hazards in the current electric welding equipment; The early warning terminal is used to provide early warning when there are welding safety hazards in the electric welding equipment.

2. A digital intelligent monitoring platform for electric welding operations according to claim 1, characterized in that: The evaluation process of the quality of weldments during welding is as follows: The entity data safety interval of the historical welder corresponding to the weldment is obtained from the database, and then the quality form evaluation value of the weldment during welding is analyzed. If the quality form evaluation value of the weldment during welding is 1, it is determined that the quality form of the weldment during welding meets the welding standards, and the welding during welding is continued to be supervised. If the quality form evaluation value of the weldment during welding is 0, it is determined that the quality form of the weldment during welding does not meet the welding standards, and an in-depth analysis is performed on the welder's welding when using electric welding equipment to weld the weldment to judge the quality form of the weldment during welding.

3. A digital intelligent monitoring platform for electric welding operations as claimed in claim 2, characterized in that: The analysis obtains the quality morphology evaluation value of the weldment during welding, and the analysis process is as follows: By calculation formula: Among them, Z is the quality morphology evaluation value of the weldment during welding, A μ is the μth entity data of the weldment during welding, Α′ μ is the safety interval of the μth entity data of the weldment during welding, μ is the number of the entity data, μ[1,3] and μ[1,3] are three entity data, representing the weld penetration, weld width and number of pores in the entity data respectively, and the three entity data correspond to their respective safety intervals, namely the weld penetration safety interval, the weld width safety interval and the number of pores safety interval.

4. A digital intelligent monitoring platform for electric welding operations as claimed in claim 3, characterized in that: The welding information includes initial arc amplitude, arc amplitude change frequency, initial voltage, welding voltage fluctuation value and welding current.

5. A digital intelligent monitoring platform for electric welding operations as claimed in claim 4, characterized in that: The analysis process of welding changes of electric welding equipment during welding is as follows: By constructing the welding output change model and the welding equipment change model, the welding changes of the electric welding equipment during welding are analyzed. The welding output change model formula is: is the welding output change of the electric welding equipment during the welding period s, C1 and Y are the initial arc amplitude and arc amplitude change frequency of the electric welding equipment during welding, e(-Y*M) is an exponential function, e is a natural constant, s is the welding period of the electric welding equipment, M is the welding time of the electric welding equipment, and the time between the initial welding and the s period of the electric welding equipment is M; Through the welding equipment change model, the expression formula is: W(s)=J1*(1-U*COS(Q*M)), W(s) is the welding equipment change corresponding to the welding time period s of the electric welding equipment, J1, U and Q are the initial voltage, welding voltage fluctuation value and welding current corresponding to the electric welding equipment during welding, cos(Q*M) is the cosine function, and the value of cos(Q*M) is [-1,1].

6. A digital intelligent monitoring platform for electric welding operations as claimed in claim 5, characterized in that: The analysis process of the influence of welding changes on the corresponding welding stability of electric welding equipment is as follows: According to the welding output change of the electric welding equipment during the welding period s And the welding equipment change W(s) corresponding to the welding time period s of the electric welding equipment, and then calculated by the formula: Where λ(s) is the stability trend variable of the electric welding equipment during the welding period s, D1 and D2 are the weight factors of the set welding output change and the welding equipment change, respectively, 0<D1<1, 0<D2<1.

7. A digital intelligent monitoring platform for electric welding operations according to claim 6, characterized in that: The transmission data corresponding to the electric welding equipment during welding is collected and analyzed to obtain the transmission coefficient corresponding to the electric welding equipment during welding. The analysis process is as follows: Based on the welding changes of the electric welding equipment during welding, the transmission status of the electric welding equipment between the initial welding change and the current welding change is monitored, and the transmission data corresponding to the welding change moment of the electric welding equipment is obtained according to the various sensor devices installed on the transmission device of the electric welding equipment; The transmission data corresponding to the electric welding equipment at the welding change moment is compared with the preset transmission data interval corresponding to the electric welding equipment in the welding. If the transmission data corresponding to the electric welding equipment at the welding change moment is within the preset transmission data interval corresponding to the electric welding equipment in the welding, the transmission compliance coefficient corresponding to the electric welding equipment in the welding period s is recorded as r1, otherwise it is recorded as r2. The transmission coefficient X(s) corresponding to the electric welding equipment in welding is obtained by analysis, where X(s) takes the value of r1 or r2, and r1 and r2 are natural numbers.

8. A digital intelligent monitoring platform for electric welding operations as claimed in claim 7, characterized in that: The specific establishment process of the welding safety assessment model for electric welding equipment during welding is as follows: Based on the stability trend variable λ(s) corresponding to the welding time period s of the electric welding equipment and the transmission coefficient X(s) corresponding to the welding time period s of the electric welding equipment, the expression formula of the welding safety assessment model is obtained: Then the safety result value of the electric welding equipment corresponding to the welding period s is analyzed and obtained β1 and β2 are the weight factors of the set stability trend variable and the transmission coefficient, respectively, 0<β1<1, 0<β2<1.

9. A digital intelligent monitoring platform for electric welding operations as claimed in claim 8, characterized in that: The analysis process for whether the current electric welding equipment has welding safety hazards is as follows: The safety result value corresponding to the electric welding equipment in the welding time period s is compared with the reference safety result threshold corresponding to the electric welding equipment stored in the database. If the safety result value corresponding to the electric welding equipment in the welding time period s is less than the reference safety result threshold corresponding to the electric welding equipment stored in the database, it is determined that the electric welding equipment has a welding safety hazard in the welding time period s. If the safety result value corresponding to the electric welding equipment in the welding time period s is greater than or equal to the reference safety result threshold corresponding to the electric welding equipment stored in the database, it is determined that the electric welding equipment does not have a welding safety hazard in the welding time period s. Similarly, it is analyzed to determine whether the current electric welding equipment has a welding safety hazard.

10. A noise reduction test system for stamping equipment security according to claim 1, characterized in that: The system also includes a database for storing entity data, entity data safety intervals, welding information, transmission data, transmission data intervals, and reference safety result thresholds.

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