A method for evaluating droplet transfer stability in pulsed MIG welding of aluminum-magnesium alloys

Abstract

The present invention discloses a method for evaluating the droplet transfer stability of pulse MIG welding of aluminum-magnesium alloys, comprising the following steps: using a data acquisition card to acquire electrical signals in the welding process in real time and transmitting them to a computer, and having the computer draw an electrical signal-time graph; querying the characteristic segment after image preprocessing, obtaining the original signal data of the pulse period and the characteristic segment, and calculating the occurrence period ratio t of the voltage characteristic segment at each droplet transfer. a , duration ratio t b , Peak Sustained Ratio t c and peak voltage U m ; Calculate the above three time characteristic values and peak voltage U respectively by statistical methods m The average value and standard deviation of the data are used as the evaluation criteria for the stability of the welding process. The present invention uses the characteristic statistical data of the electrical signal during the welding process as a representation of the process stability. Compared with the use of high-speed camera to capture and analyze the droplet transfer process data, the measurement is convenient and the processing method is fast, providing a basis for judging the quality of welding.

Description

Technical Field

[0001] The invention belongs to the field of pulse MIG welding, and in particular relates to a method for evaluating droplet transfer stability in pulse MIG welding of aluminum-magnesium alloys. Background Art

[0002] Aluminum-magnesium alloys have the advantages of high strength, low density, and good heat dissipation, and have broad application prospects in aerospace, automotive manufacturing, and national defense. Compared with other aluminum-magnesium alloy welding methods, pulsed MIG welding achieves stable spray transfer at lower welding currents. Its lower heat input can effectively control welding defects during magnesium / aluminum welding, improving welding efficiency and thus gaining widespread application. In actual welding, due to the significant difference in the physical properties of aluminum and magnesium, their molten droplets are prone to spattering, explosions, and other adverse phenomena during the transfer process, greatly reducing the stability of the molten droplet transfer, which has a huge negative impact on the welding quality of aluminum-magnesium alloys. At the same time, because each molten droplet transfer is fast and short, it is difficult to capture with the human eye, and high-performance imaging equipment is relatively expensive. Welding electrical parameters, as the most direct and convenient source of information for the consumable arc welding process, have become the main method for studying molten droplet transfer.

[0003] In order to solve the problem of stability evaluation of molten droplet transition, patent CN201811465450.2 provides a welding process performance evaluation device and method for gas shielded welding wire, which specifically uses a high-speed camera and a signal recorder to synchronously collect molten droplet transition images and welding electrical signals, and then obtains the standard deviation of the welding electrical signal, molten droplet transition form, size and frequency and other related parameters through computer processing to give more specific evaluation indicators. Although this method can judge the stability of molten droplet transition with accurate numerical values, it only qualitatively characterizes the molten droplet transition form and then judges its stability based on the molten droplet size, frequency and number of spatters. The understanding of the stability of molten droplet transition is still vague. There is an obvious characteristic segment on the electrical signal during molten droplet transition, and there is a lack of connection with the electrical signal, which makes its evaluation effect lacking. Patent application CN202111252951.4 discloses a pulsed MIG welding droplet transfer monitoring device and control method. The device adjusts the welding current pulse period through fuzzy PID to match the droplet transfer period, achieving a pulse-to-drop transition form, solving defects such as spattering caused by improper droplet transfer frequency during welding, thereby improving the stability of the welding process. The method can dynamically adjust the droplet transfer frequency to maintain a stable pulse-to-drop transition. However, in the pulse-to-drop droplet transfer form, the different droplet transfer morphologies within each cycle can also cause instability in the welding process, which is reflected in the changes in welding electrical parameters. It is necessary to further link the droplet transfer with the changes in electrical signals during the welding process to achieve efficient and high-quality welding. Therefore, it is of great significance to develop a droplet transfer stability evaluation method for pulsed MIG welding of aluminum-magnesium alloys that is easy to measure, convenient to characterize, and simple to operate. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for evaluating the droplet transfer stability of pulsed MIG welding of aluminum-magnesium alloys that is easy to measure, convenient to characterize, and simple to operate, so as to solve the problems of complex methods, inconvenient operation, and vague standards in the existing droplet transfer stability evaluation. This method uses the electrical signal during the welding process as a characterization of the stability of the droplet process, and converts the stability of the droplet transfer behavior into the degree of change in the electrical signal. It can quickly and accurately analyze the quality of welding and provide a strong basis for evaluating welding quality.

[0005] In order to achieve the above object, the present invention provides the following technical solutions:

[0006] A method for evaluating droplet transfer stability in pulsed MIG welding of aluminum-magnesium alloys comprises the following steps:

[0007] Step 1: Use a data acquisition card to acquire the electrical signal during the welding process in real time and transmit it to a computer, which then draws a graph of the electrical signal versus time.

[0008] Step 2: After image preprocessing, query the characteristic segment, obtain the original signal data of the pulse period and characteristic segment, and calculate the appearance period ratio t of the voltage characteristic segment at each droplet transfer. a , duration ratio t b , Peak Sustained Ratio t c and peak voltage U m ;

[0009] Step 3: Calculate the above three time characteristic values and peak voltage U using statistical methods m The average value and standard deviation of the welding process are used as the evaluation criteria for the stability of the welding process.

[0010] Preferably, the electrical signal of the welding process includes a voltage signal and a current signal, which are collected by a Hall voltage sensor and a Hall current sensor respectively and transmitted to a data acquisition card.

[0011] Preferably, the electrical signal-time diagram is an instantaneous waveform diagram of voltage-time and current-time drawn by a computer using a unified sampling time or actual time.

[0012] Preferably, the voltage characteristic segment is queried and the original data is saved through a process including filtering and smoothing, setting a range threshold, judging a change trend, and querying the maximum data.

[0013] Preferably, the raw data includes the pulse start time T0, the pulse end time T1, the characteristic appearance time t0 and its voltage U0, the characteristic end time t1, the characteristic peak time t2 and the characteristic peak voltage U m ;in:

[0014] The pulse start time T0 is the time when the welding current starts to rise from the base value;

[0015] The pulse end time T1 is the start time of the next pulse;

[0016] The characteristic occurrence time t0 is the time when the voltage suddenly increases when the welding current drops to close to the base current;

[0017] The characteristic end time t1 is the time when the voltage drops to the voltage U0 at the characteristic appearance time t0;

[0018] The characteristic peak time t2 is the time when the voltage on the characteristic segment reaches the peak value.

[0019] Preferably, the occurrence period of the characteristic segment is greater than t a is the feature appearance time t s The ratio of the pulse cycle time T;

[0020] The duration period is t bis the duration of the characteristic segment t d The ratio of the pulse cycle time T;

[0021] The peak duration ratio t c is the characteristic peak time t m With duration t d The ratio of

[0022] The characteristic peak voltage U m is the maximum value of the voltage on the characteristic segment;

[0023] Among them, the feature appearance time t s is the difference between the feature appearance time t0 and the cycle start time T0;

[0024] The pulse cycle time T is the difference between the pulse end time T1 and the pulse start time T0;

[0025] The characteristic duration t d is the difference between the feature end time t1 and the feature appearance time t0;

[0026] The characteristic peak time t m is the difference between the characteristic peak time t2 and the characteristic appearance time t0.

[0027] As a preference, the occurrence period ratio of the droplet transfer characteristic segment within at least 1000 pulse periods is calculated. a , duration ratio t b , Peak Sustained Ratio t c and peak voltage U m The characteristic value data ensures that the evaluation method is more scientific and the evaluation data can better reflect the actual situation of droplet transfer.

[0028] As a preferred option, the supporting hardware equipment used includes a shielding gas cylinder, a pulse MIG welding power supply, a wire feeding mechanism, a MIG welding gun, a Hall current sensor, a Hall voltage sensor, a data acquisition card and a computer, wherein:

[0029] The Hall current sensor is connected between the workpiece and the negative electrode of the welding power supply;

[0030] The Hall voltage sensor is connected to the positive electrode of the welding power supply and the workpiece;

[0031] The Hall current sensor and the Hall voltage sensor are respectively connected to a data acquisition card, and the data acquisition card transmits the signals to a computer for processing.

[0032] Preferably, the stability of the statistical data is positively correlated with the droplet transfer and the welding process stability.

[0033] Compared with the prior art, the droplet transfer stability evaluation method for pulsed MIG welding of aluminum-magnesium alloys designed in the present invention has the following beneficial effects:

[0034] (1) The present invention corresponds the droplet transfer process to the welding electrical signal one by one, and characterizes the droplet transfer process by the characteristics of the regular changes in the electrical signal. Compared with the use of high-speed video to shoot and analyze the droplet transfer process, the system processing difficulty is reduced and the system response speed is fully improved.

[0035] (2) The present invention uses Hall current and voltage sensors to detect the current and voltage signals during the droplet transfer process, respectively. The design is simple and convenient while the operation is stable and reliable.

[0036] (3) The welding process signal in the present invention has the characteristics of randomness. It is analyzed with the help of statistical methods and the characteristic quantities with clear physical meaning are extracted to characterize it. It is both global and capable of compressing and processing a large amount of data information.

[0037] (4) The droplet transfer stability evaluation method of the present invention uses the stability of the characteristic value data obtained by the simple parameter method to evaluate the stability of the droplet transfer process, which is easy to understand and easy to use. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 This is a schematic structural diagram of the pulse MIG welding device for aluminum-magnesium alloys in the present invention;

[0039] Figure 2 Schematic diagram of the waveform of voltage and current signals during pulsed MIG welding;

[0040] Figure 3 This is a schematic diagram of the principle of the sudden increase characteristic section of the voltage signal during droplet transfer;

[0041] Figure 4 This is a flow chart for processing voltage characteristic signals of pulsed MIG welding of aluminum-magnesium alloy;

[0042] Figure 5 It is a schematic diagram of the characteristic value of the pulse voltage signal within a pulse cycle;

[0043] Figure 6 This is a statistical diagram of the characteristic values of pulse MIG when the droplet transfer is unstable;

[0044] Figure 7 This is the characteristic value statistics diagram of pulse MIG when the droplet transfer is stable;

[0045] The reference numerals are as follows: 1-shielding gas cylinder, 2-welding power supply, 3-wire feeding mechanism, 4-welding gun, 5-workpiece, 6-Hall voltage sensor, 7-Hall current sensor, 8-acquisition card, 9-computer, F s- axial thrust, T-pulse cycle time, T0-pulse start time, T1-pulse end time, t0-characteristic appearance time, t1-characteristic end time, t2-characteristic peak time, t s - Feature appearance time, t d - Characteristic duration, t m - Characteristic peak time, U0 - Voltage at the time of characteristic appearance, U m - Characteristic peak voltage. DETAILED DESCRIPTION

[0046] The present invention will be described below with reference to the accompanying drawings and specific embodiments.

[0047] The method for evaluating the droplet transfer stability of pulsed MIG welding of aluminum-magnesium alloys in the present invention uses a supporting device such as Figure 1 As shown, the hardware equipment includes a shielding gas cylinder 1, a pulse MIG welding power supply 2, a wire feeding mechanism 3, a MIG welding gun 4, a Hall voltage sensor 6, a Hall current sensor 7, a data acquisition card 8 and a computer 9; the negative pole of the pulse MIG welding power supply 2 is connected to the workpiece 5, and the positive pole is connected to the MIG welding gun 4; the Hall voltage sensor 6 is connected between the positive pole of the pulse MIG welding power supply 2 and the workpiece 5, and the Hall current sensor 7 is connected between the negative pole of the pulse MIG welding power supply 2 and the workpiece 5; the data acquisition card 8 is respectively connected to the Hall voltage sensor 6 and the Hall current sensor 7, and then connected to the computer 9.

[0048] The waveforms of the current and voltage signals during the pulse MIG welding process of the present invention are as follows: Figure 2 As shown in the figure, the welding current and voltage waveforms show periodic changes with time. In a pulse cycle time T, the current rises rapidly from the base value to the peak value and then falls back to the base value. At this time, the voltage and current change trends are roughly the same. However, when the current drops from the peak value to close to the base value, the voltage will rebound, which appears as a "spike" on the waveform. After reaching the peak value, it resumes its downward trend. The four characteristic values that need to be identified are the appearance period of the "spike" and the period of t a Duration t d , peak time t m and peak voltage U m In addition, the current and voltage signals obtained by the data acquisition card are mixed with noise, irregular random interference signals and other periodic high-frequency interference signals. These noises appear as "burrs" on the waveform graph. These "burrs" make it difficult to identify the characteristic signals. Therefore, necessary filtering and noise reduction measures must be taken without distorting the characteristic signals.

[0049] The principle of the sudden increase in the voltage signal during droplet transfer in the present invention is as follows: Figure 3As shown in the figure, during the droplet transfer, when the current decreases from the peak value, most of the droplet 11 at the end of the welding wire 10 is covered by the arc root, and the current passing through the droplet 11 will generate an axial thrust F that promotes the droplet transfer. s , thereby compressing the molten droplet 11 to form a thin neck, reducing the height of the unshed molten droplet 11, shortening the length of the welding arc 12, and causing the arc voltage to decrease.

[0050] When the current drops to near the base value, the cross-section of the neck of droplet 11 continues to decrease before it detaches. At the same time, because the Mg element easily evaporates, a large amount of metal vapor forms on the surface around the neck, making the space there more ionized. The arc flash area climbs to the top of the droplet, at which point the arc 12 lengthens and the arc voltage begins to rise. As droplet 11 detaches, the arc flash area jumps from the upper surface of the droplet to the new surface of the wire end, extending the arc 12 to its maximum length. The arc voltage reaches its peak, and the arc resumes stable burning. Thereafter, the arc 12 length remains at the initial state of the pulse. As the welding current further decreases, the arc voltage also continues to decrease, forming a voltage characteristic segment with a "spike."

[0051] The method for evaluating droplet transfer stability during pulsed MIG welding of aluminum-magnesium alloys of the present invention comprises the following steps:

[0052] Step 1: Use the data acquisition card 8 to acquire the electrical signal during the welding process in real time and transmit it to the computer 9, and then the computer 9 draws the voltage-time graph and the current-time graph;

[0053] Step 2: After image preprocessing, query the characteristic segment, obtain the original signal data of the pulse period and the characteristic segment, and calculate the appearance period ratio t of the characteristic segment at each droplet transfer. a , duration ratio t b , Peak Sustained Ratio t c ;

[0054] Step 3: Count the original data of at least 1000 sets of characteristic values and calculate the above three time characteristic values and peak voltage U respectively. m The average value and standard deviation are plotted into a histogram, which is used as the evaluation standard for the stability of the welding process.

[0055] The voltage characteristic signal processing flow of the present invention is as follows: Figure 4 As shown:

[0056] First, the voltage and current waveforms are smoothed and amplitude thresholds are set to avoid abnormal fluctuations in data within a short period of time;

[0057] Next, get the original data value:

[0058] (1) According to the rising trend of the current, determine the pulse starting time T0;

[0059] (2) After the current reaches its peak value and the voltage shows an upward trend, determine the time t0 when the characteristic appears and the voltage U0 at this time;

[0060] (3) When the voltage reaches the peak, determine the characteristic peak time t2 and the characteristic peak voltage U m ;

[0061] (4) When the voltage drops to U0, determine the characteristic end time t1;

[0062] (5) When it is detected that the current has an upward trend again, the pulse end time T1 is determined;

[0063] Finally, calculate and save the four eigenvalue data to complete a feature statistics.

[0064] The original data of the characteristic value of the pulse voltage signal within the pulse period of the present invention is selected as follows Figure 5 As shown:

[0065] First, the data selection for 5 moments:

[0066] (1) The pulse start time T0 is the moment when the welding current starts to rise from the base value;

[0067] (2) The pulse end time T1 is the start time of the next pulse;

[0068] (3) The characteristic appearance time t0 is the moment when the voltage suddenly increases when the welding current drops to close to the base current;

[0069] (4) The characteristic end time t1 is the time when the voltage drops to the voltage at the characteristic appearance time t0;

[0070] (5) Characteristic peak time t2 is the time when the voltage on the characteristic segment reaches its peak value.

[0071] The second is the data calculation of 3 times:

[0072] (1) Feature appearance time t s is the difference between the characteristic start time t0 and the pulse start time T0;

[0073] (2) Characteristic duration t d is the difference between the feature end time t1 and the feature appearance time t0;

[0074] (3) Characteristic peak time t m is the difference between the characteristic peak time t2 and the characteristic appearance time t0;

[0075] Finally, the data of the four eigenvalues is obtained:

[0076] (1) The occurrence period is t ais the feature appearance time t s The ratio of the pulse cycle time T;

[0077] (2) Duration period ratio t b is the characteristic duration t d The ratio of the pulse cycle time T;

[0078] (3) Peak duration ratio t c is the characteristic peak time t m With characteristic duration t d The ratio of

[0079] (4) Characteristic peak voltage U m is the maximum voltage on the characteristic segment.

[0080] Example 1

[0081] PulseMIG-500 was used to butt-weld two 2024 aluminum alloy plates. The two plates had the same dimensions, 4 mm thick, 4000 mm long, and 200 mm wide. The welding wire was ER4043 with a diameter of 1.2 mm. The base value of the welding current was 25 A, the peak value was 180 A, the pulse frequency was 100 Hz, the welding speed was 0.5 m / min, and the welding shielding gas was 99.999% high-purity argon with a gas flow rate of 20 L / min.

[0082] A method for evaluating droplet transfer stability in pulsed MIG welding of aluminum-magnesium alloys is specifically performed in the following steps:

[0083] Step 1: Use current and voltage sensors to collect current signals and voltage signals at the end of the welding torch. The electrical signals during the welding process are transmitted to a computer through a data acquisition card and filtered using software. While eliminating high-frequency noise in the electrical signals, the sudden changes in the signals are kept undistorted. The computer then plots voltage-time and current-time graphs.

[0084] Step 2: Smooth the voltage and current waveforms and set the amplitude threshold to avoid abnormal fluctuations in the data in a short period of time. Obtain the original data values: pulse start time T0, feature appearance time t0 and voltage U0 at this time, feature peak time t2, feature peak voltage U m , characteristic end time t1 and pulse end time T1, and calculate the period ratio t a , duration ratio t b , Peak Sustained Ratio t c and save;

[0085] Step 3: Count the original data of 2000 sets of characteristic values and calculate the above three time characteristic values and peak voltage U respectively. m The mean and standard deviation are plotted as a histogram.

[0086] The characteristic value comparison when the droplet transfer is stable is as follows Figure 6 and 7 As shown in Figure 2, the smaller the characteristic value, the more stable the droplet transfer process.

[0087] The above are only preferred embodiments of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions based on the concept of the present invention are within the scope of protection of the present invention. It should be noted that for those skilled in the art, various improvements that do not depart from the principles of the present invention should be considered as within the scope of protection of the present invention.

Claims

1. A method for evaluating droplet transfer stability in pulsed MIG welding of aluminum-magnesium alloys, characterized in that: The steps include: Step 1: Use a data acquisition card to acquire the electrical signal during the welding process in real time and transmit it to a computer, which then draws a graph of the electrical signal versus time. Step 2: After image preprocessing, query the characteristic segment, obtain the original signal data of the pulse period and characteristic segment, and calculate the appearance period ratio of the voltage characteristic segment at each droplet transition. t a , duration ratio t b , Peak Sustained Ratio t c and characteristic peak voltage U m ; Step 3: Calculate the above three time characteristic values and characteristic peak voltage respectively using statistical methods U m The average value and standard deviation of the welding process are used as the evaluation criteria for the stability of the welding process. The raw data includes the pulse start time T 0. Pulse end time T 1. Feature appearance time t 0 and its voltage U 0. Feature end time t 1. Feature peak moment t 2 and characteristic peak voltage U m ;in: The pulse start time T 0 is the moment when the welding current starts to rise from the base value; The pulse end time T 1 is the start time of the next pulse; The feature appears at t 0 is the moment when the voltage suddenly increases when the welding current drops to close to the base current; The feature end time t 1 is the time when the voltage drops to the time when the characteristic appears t 0 voltage U 0 moment; The characteristic peak moment t 2 is the moment when the voltage on the characteristic segment reaches its peak value; The occurrence period of the characteristic segment is t a Feature appearance time t s and pulse cycle time T The ratio of The duration ratio t b The duration of the feature segment t d and pulse cycle time T The ratio of Peak Sustainability Ratio t c Characteristic peak time t m With duration t d The ratio of The characteristic peak voltage U m is the maximum value of the voltage on the characteristic segment; where: The feature appears at t s Feature appearance time t 0 and the start time of the cycle T The difference of 0; The pulse cycle time T The pulse end time T 1 and pulse start time T The difference of 0; The characteristic duration t d Feature end time t 1 and the moment of feature appearance t The difference of 0; The characteristic peak time t m Characteristic peak moment t 2 and feature appearance time t The difference of 0; The voltage characteristic section is: in one pulse cycle time T In the waveform, the current rises rapidly from the base value to the peak value and then falls back to the base value. At this time, the voltage and current change trends are roughly the same, but when the current drops from the peak value to close to the base value, the voltage rebounds, which appears as a "spike" on the waveform graph. After reaching the peak value, it resumes its downward trend.

2. The method for evaluating droplet transfer stability in pulsed MIG welding of aluminum-magnesium alloy according to claim 1, characterized in that: The electrical signals of the welding process include voltage signals and current signals, which are collected by a Hall voltage sensor and a Hall current sensor respectively and transmitted to a data acquisition card.

3. The method for evaluating droplet transfer stability in pulsed MIG welding of aluminum-magnesium alloy according to claim 1, characterized in that: The electrical signal-time diagram is an instantaneous waveform diagram of voltage-time and current-time drawn by a computer using a unified sampling time or actual time.

4. The method for evaluating droplet transfer stability in pulsed MIG welding of aluminum-magnesium alloy according to claim 1, wherein: The voltage characteristic segment is queried and the original data is saved through a process including filtering and smoothing, setting range thresholds, judging change trends, and querying maximum data.

5. The method for evaluating droplet transfer stability in pulsed MIG welding of aluminum-magnesium alloy according to claim 1, wherein: The occurrence period ratio of the droplet transfer characteristic segment within at least 1000 pulse cycles is counted t a , duration ratio t b , Peak Sustained Ratio t c and characteristic peak voltage U m The characteristic value data.

6. The method for evaluating droplet transfer stability in pulsed MIG welding of aluminum-magnesium alloy according to claim 1, wherein: The supporting hardware equipment used includes shielding gas cylinder, pulse MIG welding power supply, wire feeding mechanism, MIG welding gun, Hall current sensor, Hall voltage sensor, data acquisition card and computer, among which: The Hall current sensor is connected between the workpiece and the negative electrode of the welding power supply; The Hall voltage sensor is connected to the positive electrode of the welding power supply and the workpiece; The Hall current sensor and the Hall voltage sensor are respectively connected to a data acquisition card, and the data acquisition card transmits the signals to a computer for processing.

7. The method for evaluating droplet transfer stability in pulsed MIG welding of aluminum-magnesium alloy according to claim 1, wherein: The stability of statistical data is positively correlated with the stability of droplet transfer and welding process.

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