Method and apparatus for evaluating stability of arc welding process, and device and medium

Abstract

A method and apparatus for evaluating the stability of an arc welding process, and a device and a medium. The method comprises the following steps: acquiring a welding current signal and an arc voltage signal during arc welding; using a central frequency method and a trial algorithm to determine key parameters of VMD, wherein the key parameters comprise the number K of decomposition layers and a penalty factor α; on the basis of the key parameters, performing VMD on the welding current signal and the arc voltage signal to obtain K intrinsic mode functions (IMFs), and calculating the variance of each IMF after decomposition; on the basis of the variance of each IMF, calculating a current VMD – a variance entropy and a voltage VMD – a variance entropy; and on the basis of the current VMD – the variance entropy and the voltage VMD – the variance entropy, evaluating the stability of the arc welding process, so as to obtain an evaluation result.

Description

Arc welding process stability evaluation method, device, equipment and medium Technical Field

[0001] The embodiments of the present invention relate to the field of welding technology, and in particular to a method and device, equipment and medium for evaluating the stability of an arc welding process. Background Art

[0002] Welding technology is currently the most widely used key foundational process in industrial manufacturing. Pulsed MIG welding, with its ability to control droplet transfer and welding heat input using periodically varying pulsed current, effectively welds thin sheets, spatially positioned welds, and heat-sensitive materials, is a primary form of welding technology. With increasing demands for high quality, high efficiency, and refined weld products, the acquisition and processing of welding process stability and quality information has become a crucial component of the informatization of the welding manufacturing industry.

[0003] However, the algorithms used in existing welding process stability evaluation methods are relatively complex and inefficient. Therefore, how to efficiently obtain the welding process stability evaluation results has become a technical problem that needs to be solved urgently.

[0004] Summary of the Invention

[0005] The embodiments of the present invention provide a method and device, equipment and medium for evaluating the stability of an arc welding process, which can efficiently obtain the evaluation results of the welding process stability.

[0006] In a first aspect, an embodiment of the present invention provides a method for evaluating the stability of an arc welding process, comprising:

[0007] Obtaining welding current signal and arc voltage signal during arc welding process;

[0008] Determine the key parameters of VMD decomposition using the center frequency method and trial algorithm, wherein the key parameters include the decomposition level K and the penalty factor α;

[0009] Performing VMD decomposition on the welding current signal and the arc voltage signal according to the key parameters to obtain K modal components, and calculating the variance of each modal component IMF after decomposition;

[0010] The current VMD-variance entropy and voltage VMD-variance entropy are calculated based on the variance of each modal component IMF;

[0011] The stability of the arc welding process is evaluated according to the current VMD-variance entropy and the voltage VMD-variance entropy to obtain an evaluation result.

[0012] In some embodiments, the modal component IMF is expressed as follows: k (t) = Ak (t)cos(φ k (t))

[0013] Among them, u k (t) is the kth decomposition signal (k=1,2,…,K), A k (t) is u k (t) the instantaneous envelope amplitude, φ k (t) is u k The instantaneous phase of (t).

[0014] In some embodiments, the VMD decomposition constrained variational model is represented as follows:

[0015] Among them, u k ={u1,u2,…,u K} is the modal function set, ω k ={ω1,ω2,…,ω K} is the center frequency set, K represents the number of modal decompositions, is the partial derivative of the function with respect to time t, δ(t) is the unit pulse function, j is the imaginary unit, and * represents the convolution operation.

[0016] In some embodiments, the method further comprises:

[0017] Introduce the penalty factor α and the Lagrangian operator λ(t), transform the inequality constraint into an equality constraint, and solve the optimal solution of the constraint problem of the variational model. Let LA=L({u k},{ω k},{λ(t)}), the corresponding augmented Lagrangian expression is as follows:

[0018] The alternating direction multiplier method is used to update and iterate the constraint problem of the variational model and find the optimal solution, so as to decompose the original signal into K modal components IMF.

[0019] In some embodiments, performing VMD decomposition on the welding current signal and the arc voltage signal according to the key parameters to obtain K modal components, and calculating the variance of each modal component IMF after decomposition, includes:

[0020] The welding current signal and the arc voltage signal are decomposed into K modal components. The decomposed modal components IMF are represented as a time series consisting of N data points as follows: k ={x1,x2,…,x N}

[0021] The variance of each IMF component after VMD decomposition is expressed as follows:

[0022] in,

[0023] In some embodiments, the current VMD-variance entropy and the voltage VMD-variance entropy are expressed as follows:

[0024] Among them, M k for That is, the proportion of the variance of the kth IMF component in the total variance of all IMFs, and it satisfies

[0025] In a second aspect, an embodiment of the present invention further provides a welding system, which includes an industrial computer, a main control card, an electrical signal sensor, a welding gun, a wire feeding mechanism, a traveling mechanism, a welding power supply and a gas cylinder, wherein the electrical signal sensor, the wire feeding mechanism and the traveling mechanism are electrically connected to the main control card respectively, the main control card is communicatively connected to the industrial computer, the welding gun is arranged on the traveling mechanism, and the industrial computer executes the arc welding process stability evaluation method as described in the first aspect.

[0026] In a third aspect, an embodiment of the present invention further provides an arc welding process stability evaluation device, the device comprising:

[0027] An acquisition module is used to acquire a welding current signal and an arc voltage signal during an arc welding process;

[0028] A determination module, configured to determine key parameters of VMD decomposition using a center frequency method and a trial algorithm, wherein the key parameters include a decomposition level K and a penalty factor α;

[0029] a decomposition module, configured to perform VMD decomposition on the welding current signal and the arc voltage signal according to the key parameters to obtain K modal components, and calculate the variance of the IMF of each modal component after decomposition;

[0030] A calculation module is used to calculate the current VMD-variance entropy and the voltage VMD-variance entropy according to the variance of each modal component IMF;

[0031] The evaluation module is used to evaluate the stability of the arc welding process according to the current VMD-variance entropy and the voltage VMD-variance entropy to obtain an evaluation result.

[0032] In a fourth aspect, an embodiment of the present invention further provides an electronic device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the arc welding process stability evaluation method as described in the first aspect when executing the computer program.

[0033] In a fifth aspect, an embodiment of the present invention further provides a computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions are used to execute the arc welding process stability evaluation method as described in the first aspect.

[0034] According to the embodiment of the present invention, an arc welding process stability evaluation method, device, equipment and medium are provided, wherein the arc welding process stability evaluation method includes: obtaining a welding current signal and an arc voltage signal of the arc welding process; using a center frequency method and a trial algorithm to determine key parameters of VMD decomposition, the key parameters including the decomposition layer number K and the penalty factor α; performing VMD decomposition on the welding current signal and the arc voltage signal according to the key parameters to obtain K modal components, and calculating the variance of each modal component IMF after decomposition; calculating the current VMD-variance entropy and the voltage VMD-variance entropy according to the variance of each modal component IMF; evaluating the stability of the arc welding process according to the current VMD-variance entropy and the voltage VMD-variance entropy to obtain an evaluation result. The present invention uses the center frequency method and trial and error algorithm to determine the key parameters of VMD: the decomposition level K and the penalty factor α. It then performs VMD decomposition on the welding current signal and arc voltage signal, effectively separating the noise signal and completely reconstructing the original signal. The stability of the welding process is evaluated by extracting the variance entropy of the modal components (IMFs) of the welding current signal and arc voltage signal after VMD decomposition. Based on this, the embodiment of the present invention performs variational modal decomposition on the welding electrical signal during the welding process, calculates the variance entropy corresponding to the decomposed modal components (IMFs), and combines the current VMD-variance entropy and voltage VMD-variance entropy to evaluate the stability of the welding process, thereby efficiently obtaining the welding process stability evaluation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] FIG1 is a flow chart of a method for evaluating the stability of an arc welding process according to an embodiment of the present invention;

[0036] FIG2 is a schematic structural diagram of a welding system provided by one embodiment of the present invention;

[0037] FIG3 is a pulsed MIG welding current waveform diagram provided by one embodiment of the present invention;

[0038] FIG4 is a comparison diagram of weld seam formations with different gas supply rates according to an embodiment of the present invention;

[0039] FIG5 is a comparison diagram of current VMD-variance entropy and voltage VMD-variance entropy for different air delivery rates provided by one embodiment of the present invention;

[0040] FIG6 is a schematic diagram of an arc welding process stability evaluation device provided by one embodiment of the present invention;

[0041] FIG7 is a schematic diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0042] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0043] It should be noted that although the device schematics illustrate functional module divisions and the flowcharts illustrate logical sequences, in certain circumstances, the steps shown or described may be performed in a sequence that differs from the module divisions in the device or the sequence in the flowcharts. The terms "first," "second," and so on, used in the specification, claims, and accompanying drawings are used to distinguish similar items and are not necessarily intended to describe a specific sequence or precedence.

[0044] In the embodiments of the present invention, words such as "further," "exemplarily," or "optionally" are used to indicate examples, illustrations, or explanations and should not be interpreted as being more preferred or advantageous over other embodiments or designs. The use of words such as "further," "exemplarily," or "optionally" is intended to present related concepts in a concrete manner.

[0045] First, some terms involved in this invention are analyzed:

[0046] VMD: (Variational Mode Decomposition) variational mode decomposition;

[0047] IMF: (Intrinsic Mode Functions) modal component.

[0048] In order to more conveniently describe the working principle of the embodiment of the present invention later, an introduction to relevant technical scenarios is first given below.

[0049] Welding technology is currently the most widely used key foundational process in industrial manufacturing. Pulsed MIG welding, with its ability to control droplet transfer and welding heat input using periodically varying pulsed current, effectively welds thin sheets, spatially positioned welds, and heat-sensitive materials, is a primary form of welding technology. With increasing demands for high quality, high efficiency, and refined weld products, the acquisition and processing of welding process stability and quality information has become a crucial component of the informatization of the welding manufacturing industry.

[0050] However, the algorithms used in existing welding process stability evaluation methods are relatively complex and inefficient. Therefore, how to efficiently obtain the welding process stability evaluation results has become a technical problem that needs to be solved urgently.

[0051] Based on this, the present invention provides a method, device, equipment, and medium for evaluating the stability of an arc welding process. The method comprises: obtaining a welding current signal and an arc voltage signal during the arc welding process; determining key parameters for VMD decomposition using a center frequency method and a trial-and-error algorithm, the key parameters including the number of decomposition layers K and a penalty factor α; performing VMD decomposition on the welding current signal and the arc voltage signal based on the key parameters to obtain K modal components, and calculating the variance of each decomposed modal component IMF; calculating the current VMD-variance entropy and the voltage VMD-variance entropy based on the variance of each modal component IMF; and evaluating the stability of the arc welding process based on the current VMD-variance entropy and the voltage VMD-variance entropy to obtain an evaluation result. The present invention uses the center frequency method and trial and error algorithm to determine the key parameters of VMD: the decomposition level K and the penalty factor α. It then performs VMD decomposition on the welding current signal and arc voltage signal, effectively separating the noise signal and completely reconstructing the original signal. The stability of the welding process is evaluated by extracting the variance entropy of the modal components (IMFs) of the welding current signal and arc voltage signal after VMD decomposition. Based on this, the embodiment of the present invention performs variational modal decomposition on the welding electrical signal during the welding process, calculates the variance entropy corresponding to the decomposed modal components (IMFs), and combines the current VMD-variance entropy and voltage VMD-variance entropy to evaluate the stability of the welding process, thereby efficiently obtaining the welding process stability evaluation results.

[0052] The embodiments of the present invention are further described below with reference to the accompanying drawings.

[0053] As shown in FIG1 , FIG1 is a flowchart of an arc welding process stability evaluation method provided by one embodiment of the present invention. The arc welding process stability evaluation method may include but is not limited to steps S101 to S105 .

[0054] Step S101: obtaining a welding current signal and an arc voltage signal during an arc welding process;

[0055] Step S102: using the center frequency method and trial algorithm to determine the key parameters of VMD decomposition, the key parameters including the decomposition level K and the penalty factor α;

[0056] Step S103: performing VMD decomposition on the welding current signal and the arc voltage signal according to the key parameters to obtain K modal components, and calculating the variance of each modal component IMF after decomposition;

[0057] Step S104: Calculating the current VMD-variance entropy and the voltage VMD-variance entropy according to the variance of each modal component IMF;

[0058] Step S105: Evaluate the stability of the arc welding process according to the current VMD-variance entropy and the voltage VMD-variance entropy to obtain an evaluation result.

[0059] In one embodiment, the existing EMD method defines the modal component as a signal whose number of local extreme values ​​and zero crossings differs by no more than 1. Unlike the original EMD method, the VMD method redefines the IMF as an amplitude-frequency modulated signal based on the modulation criterion: k (t) = A k (t)cos(φ k (t))

[0060] Among them, u k (t) is the kth decomposition signal (k=1,2,…,K), A k (t) is u k (t) the instantaneous envelope amplitude, φ k (t) is u k (t) instantaneous phase; instantaneous envelope amplitude A k (t) and instantaneous frequency ω k (t) = φ k '(t) is greater than the phase φ k (t) Much slower.

[0061] The VMD decomposition method is the process of solving the variational problem. The variational problem requires that the sum of the bandwidths of the center frequencies of each modal component is minimized and the sum of all modal components is equal to the original signal. To this end, each modal function u k (t) Perform Hi lbert transform to obtain the corresponding IMF single marginal spectrum, which is consistent with the estimated IMF center frequency e -jωkt Multiply them together to modulate the single-edge spectrum of each mode to the corresponding baseband, and then analyze the gradient square L of the signal 2 Norm, calculate the bandwidth of each modal signal. The constrained variational model of variational mode decomposition is as follows:

[0062] Among them, u k ={u1,u2,…,u K} is the modal function set, ω k ={ω1,ω2,…,ω K} is the center frequency set, K represents the number of modal decompositions, is the partial derivative of the function with respect to time t, δ(t) is the unit pulse function, j is the imaginary unit, and * represents the convolution operation.

[0063] Introduce the penalty factor α and the Lagrangian operator λ(t), transform the inequality constraint into an equality constraint, and solve the optimal solution of the constraint problem of the variational model. Let LA=L({u k},{ω k},{λ(t)}), the corresponding augmented Lagrangian expression is as follows:

[0064] The alternating direction multiplier method is used to update and iterate the constraint problem of the variational model and find the optimal solution, so as to decompose the original signal into K modal components IMF.

[0065] In one embodiment, information entropy, also known as Shannon entropy, describes the uncertainty of information. It was originally applied in the field of statistical thermodynamics to describe the degree of disorder in a thermodynamic system. The more disordered the system, the higher the information entropy value, and vice versa. The formula for information entropy is:

[0066] p i (i=1,2,…,Q) is the probability of Q possible events occurring, and where -logp i is the amount of information contained in the i-th possible event.

[0067] The VMD method decomposes the welding current signal into K modal components. The decomposed IMFs form a time series with N data points:

[0068] x k ={x1,x2,…,x N}

[0069] The variance of each IMF component after VMD decomposition is expressed as follows:

[0070] in, And introduce the concept of information entropy to construct the variance entropy MREH based on VMD:

[0071] Among them, M k for That is, the proportion of the variance of the kth IMF component in the total variance of all IMFs, and it satisfies

[0072] In one embodiment, by extracting characteristics for evaluating welding process stability and analyzing the relationship between welding process parameters and welding process stability, the welding process parameters are adjusted to improve welding process quality and efficiency. Specifically, the present invention performs variational modal decomposition on the welding electrical signal during the welding process, calculates the variance entropy corresponding to the decomposed modal components, and combines the current VMD-variance entropy and voltage VMD-variance entropy to evaluate welding process stability. This allows remote monitoring of welding process stability in a single-person operation, ensuring safety and efficiency. It should be noted that the more stable the welding process, the lower the VMD-variance entropy, and the present invention is more effective in evaluating welding process stability.

[0073] Based on this, the present invention uses the center frequency method and trial algorithm to determine the key parameters of VMD: the decomposition layer number K and the penalty factor α, and then performs VMD decomposition on the welding current signal and arc voltage signal, which can effectively separate the noise signal and completely reconstruct the original signal, and evaluate the stability of the welding process by extracting the variance entropy of each modal component IMF of the welding current signal and arc voltage signal after VMD decomposition. Based on this, the embodiment of the present invention performs variational modal decomposition on the welding electrical signal of the welding process, and then calculates the variance entropy corresponding to the decomposed modal component IMF, combining the current VMD-variance entropy and the voltage VMD-variance entropy to evaluate the stability of the welding process, thereby efficiently obtaining the welding process stability evaluation result.

[0074] In addition, as shown in FIG2 , one embodiment of the present invention further discloses a welding system, comprising an industrial computer, a main control card, an electrical signal sensor, a welding gun, a wire feed mechanism, a traveling mechanism, a welding power source, and a gas cylinder. The electrical signal sensor, the wire feed mechanism, and the traveling mechanism are electrically connected to the main control card, which is in communication with the industrial computer. The welding gun is mounted on the traveling mechanism, and the welding parameters of the welding gun include: welding speed, wire feed speed, peak current, peak time, base current, and base time. As shown in FIG3 , the welding waveform of the electrical signal sensor is divided into an arc starting waveform, a pulse waveform, and an arc ending waveform. The industrial computer executes the arc welding process stability evaluation method described in any of the previous embodiments. In addition, the control interface of the industrial computer can automatically display the corresponding pulse frequency, duty cycle, and average current according to the set values.

[0075] In one embodiment, welding tests were conducted using a proprietary MIG welding system. The test substrate was a Q235 steel plate measuring 100 mm × 300 mm × 4 mm. A φ1.2 mm HTW-50 carbon steel wire was used, and the shielding gas was 99.99% pure argon. A synchronous welding current and voltage acquisition sensor was used to collect the current and voltage signals during the welding process, with a sampling frequency of 5000 Hz. Pulsed MIG welding tests were conducted using different process parameters, yielding three sets of current and voltage signals at different shielding gas flow rates. During welding, the pulse base current was set to 55 A, the pulse base time to 8 ms, the pulse peak current to 325 A, the pulse peak time to 7 ms, the pulse frequency to 67 Hz, the wire feed speed to 8.7 m / min, and the welding method to be flat cladding. The shielding gas flow rate was used as a variable to alter the stability of the welding process. Welding tests were conducted according to Table 1 below.

[0076] Table 1 Comparison of protective gas flow rates

[0077] As shown in Figure 4, the weld formation is shown. From (a), (b) and (c) in Figure 4, respectively, the weld formation with a gas supply volume of 20L / min, the weld formation with a gas supply volume of 10L / min, and the weld formation with a gas supply volume of 0L / min, it can be seen that the stability of the welding process changes from good to bad.

[0078] Four tests were conducted for each group with different shielding gas flow rates, resulting in 12 groups of current and voltage signals. The test time was kept consistent as much as possible. In this embodiment of the present invention, 1 second of data was used as a sample for analysis. After stable welding, 5 second time steps were sampled at intervals to obtain 25,000 data points, which were then divided into five equal segments for analysis. This means 5,000 data points were sampled every 1 second, resulting in a total of 60 current and 60 voltage sample data points. Key parameter analysis was performed on the 12 groups of current and voltage signals, with K set to 13 and α to 5,000 as the optimal solution. The VMD-variance entropy calculation process was performed to obtain the current VMD-variance entropy and voltage VMD-variance entropy for different gas flow rates, as shown in Figure 5.

[0079] Combining the calculated results of the VMD-variance entropy of current and voltage, since a smaller VMD-variance entropy indicates a more stable welding process, it can be predicted that the first welding process with a gas flow rate of 20 L / min has the best stability, the second welding process with a gas flow rate of 10 L / min has the second best stability, and the third welding process with a gas flow rate of 0 L / min has the worst stability. The welding process stability assessed by the VMD-variance entropy of the welding process current and voltage corresponds to the actual weld formation effect. Therefore, the VMD-variance entropy can effectively evaluate the stability of the welding process and can better reflect the stability of the welding process.

[0080] Based on this, the present invention provides a welding system based on the pulsed MIG welding method. This welding system more conveniently achieves high-precision control of parameters such as wire feed motor speed, pulse power supply current duty cycle, peak value, base value, and frequency. Furthermore, the design of the application program interface makes control more convenient and efficient, thereby improving the stability and accuracy of the control effect. Finally, the stability of the welding process is evaluated using the VMD-variance entropy method. These innovations and technical advantages can provide higher-quality, more stable welding and control methods for the production or manufacturing industry, and have important practical significance for promoting the development of industrial automation and intelligent manufacturing.

[0081] In addition, as shown in FIG6 , an embodiment of the present invention further discloses an arc welding process stability evaluation device, which includes:

[0082] An acquisition module 110 is used to acquire a welding current signal and an arc voltage signal during an arc welding process;

[0083] A determination module 120 is used to determine key parameters of VMD decomposition using a center frequency method and a trial algorithm, wherein the key parameters include the number of decomposition levels K and a penalty factor α;

[0084] A decomposition module 130 is used to perform VMD decomposition on the welding current signal and the arc voltage signal according to the key parameters to obtain K modal components and calculate the variance of each modal component IMF after decomposition;

[0085] A calculation module 140 is configured to calculate the current VMD-variance entropy and the voltage VMD-variance entropy based on the variance of each modal component IMF;

[0086] The evaluation module 150 is used to evaluate the stability of the arc welding process according to the current VMD-variance entropy and the voltage VMD-variance entropy to obtain an evaluation result.

[0087] The arc welding process stability evaluation device of an embodiment of the present invention is used to execute the arc welding process stability evaluation method in the above embodiment. Its specific processing process is the same as the arc welding process stability evaluation method in the above embodiment, and will not be repeated here.

[0088] In addition, as shown in Figure 7, an embodiment of the present invention also discloses an electronic device, including: at least one processor 210; at least one memory 220, for storing at least one program; when the at least one program is executed by the at least one processor 210, an arc welding process stability evaluation method as in any of the previous embodiments is implemented.

[0089] In addition, an embodiment of the present invention further discloses a computer-readable storage medium storing computer-executable instructions for executing the arc welding process stability evaluation method as described in any of the previous embodiments.

[0090] The system architecture and application scenarios described in the embodiments of the present invention are intended to more clearly illustrate the technical solutions of the embodiments of the present invention and do not constitute a limitation on the technical solutions provided by the embodiments of the present invention. Those skilled in the art will appreciate that with the evolution of the system architecture and the emergence of new application scenarios, the technical solutions provided by the embodiments of the present invention are equally applicable to similar technical problems.

[0091] Those skilled in the art will appreciate that all or some of the steps in the methods, systems, and functional modules / units in the devices disclosed above may be implemented as software, firmware, hardware, or appropriate combinations thereof.

[0092] In a hardware implementation, the division between the functional modules / units mentioned in the above description does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed by several physical components in cooperation. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit. Such software may be distributed on a computer-readable medium, which may include a computer storage medium (or non-transitory medium) and a communication medium (or temporary medium). As known to those skilled in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, as is well known to those skilled in the art, communication media typically embodies computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

[0093] As used in this specification, the terms "component," "module," "system," and the like are used to refer to computer-related entities, hardware, firmware, a combination of hardware and software, software, or software in execution. For example, a component can be, but is not limited to, a process running on a processor, a processor, an object, an executable file, an execution thread, a program, or a computer. By way of illustration, both applications running on a computing device and a computing device can be components. One or more components can reside in a process or execution thread, and a component can be located on one computer or distributed between two or more computers. In addition, these components can be executed from various computer-readable media having various data structures stored thereon. Components can communicate, for example, through local or remote processes based on signals having one or more data packets (e.g., data from two components interacting with another component on a local system, a distributed system, or a network, such as the Internet interacting with other systems via signals).

Claims

1. A method for evaluating the stability of an arc welding process, comprising: Acquire welding current signal and arc voltage signal during arc welding process; Determine the key parameters of VMD decomposition by using the center frequency method and trial algorithm, wherein the key parameters include the decomposition level K and the penalty factor α; Perform VMD decomposition on the welding current signal and the arc voltage signal according to the key parameters to obtain K modal components, and calculate the variance of each modal component IMF after decomposition; The current VMD-variance entropy and voltage VMD-variance entropy are calculated based on the variance of each modal component IMF; The stability of the arc welding process is evaluated according to the current VMD-variance entropy and the voltage VMD-variance entropy to obtain an evaluation result.

2. The method according to claim 1, characterized in that The modal component IMF is expressed as follows: k (t) = A k (t)cos(φ k (t)) Among them, u k (t) is the kth decomposition signal (k=1,2,…,K), A k (t) is u k (t) is the instantaneous envelope amplitude, φ k (t) is u k The instantaneous phase of (t).

3. The method according to claim 2, characterized in that The VMD decomposition constrained variational model is expressed as follows: Among them, u k ={u1,u2,…,u K } is the set of modal functions, ω k ={ω1,ω2,…,ω K } is the center frequency set, K represents the number of modal decompositions, is the partial derivative of the function with respect to time t, δ(t) is the unit pulse function, j is the imaginary unit, and * represents the convolution operation.

4. The method according to claim 3, characterized in that The method further comprises: Introduce the penalty factor α and the Lagrangian operator λ(t), transform the inequality constraint into an equality constraint, and solve the optimal solution of the constraint problem of the variational model. Let LA = L({u k },{ω k },{λ(t)}), the corresponding augmented Lagrangian expression is as follows: The alternating direction multiplier method is used to iterate the constraint problem of the variational model and find the optimal solution, so as to decompose the original signal into K modal components IMF.

5. The method according to claim 1, characterized in that The step of performing VMD decomposition on the welding current signal and the arc voltage signal according to the key parameters to obtain K modal components, and calculating the variance of each modal component IMF after decomposition includes: The welding current signal and the arc voltage signal are decomposed into K modal components. The decomposed modal components IMF are represented as a time series consisting of N data points as follows: x k ={x1,x2,…,x N } The variance of each IMF component after VMD decomposition is expressed as follows: in, 6. The method according to claim 5, characterized in that The current VMD-variance entropy and the voltage VMD-variance entropy are expressed as follows: Among them, M k for That is, the proportion of the variance of the kth IMF component in the sum of all IMF variances, and it satisfies 7. A welding system, characterized in that: The welding system includes an industrial computer, a main control card, an electrical signal sensor, a welding gun, a wire feeding mechanism, a traveling mechanism, a welding power source and a gas cylinder. The electrical signal sensor, the wire feeding mechanism and the traveling mechanism are electrically connected to the main control card respectively. The main control card is communicatively connected to the industrial computer. The welding gun is arranged on the traveling mechanism. The industrial computer executes the arc welding process stability evaluation method as described in any one of claims 1 to 6.

8. An arc welding process stability evaluation device, characterized in that: The device comprises: An acquisition module, used for acquiring a welding current signal and an arc voltage signal during an arc welding process; A determination module, used to determine key parameters of VMD decomposition using a center frequency method and a trial algorithm, wherein the key parameters include a decomposition layer number K and a penalty factor α; A decomposition module, used for performing VMD decomposition on the welding current signal and the arc voltage signal according to the key parameters to obtain K modal components, and calculating the variance of each modal component IMF after decomposition; A calculation module, used for calculating the current VMD-variance entropy and the voltage VMD-variance entropy according to the variance of each modal component IMF; The evaluation module is used to evaluate the stability of the arc welding process according to the current VMD-variance entropy and the voltage VMD-variance entropy to obtain an evaluation result.

9. An electronic device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the arc welding process stability evaluation method as described in any one of claims 1 to 6 when executing the computer program.

10. A computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions are used to execute the arc welding process stability evaluation method according to any one of claims 1 to 6.

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