Tracking method of multi-layer and multi-pass submerged arc welding based on arc sensing

Abstract

The present invention relates to the field of multi-layer and multi-pass weld tracking of submerged arc welding, and is a multi-layer and multi-pass cover welding tracking method of submerged arc welding based on arc sensing. Aiming at the problem that in the process of multi-layer and multi-pass cover welding of submerged arc welding, the weld seam is flush with the groove height, which reduces the weld seam tracking accuracy, a multi-layer and multi-pass cover welding tracking method of submerged arc welding based on arc sensing is proposed, which uses an adaptive swing frequency arc signal filtering method to filter out high-frequency noise in the arc signal; uses an arc sensing-based cover weld edge position recognition method to track the cover weld edge; uses an arc sensing-based cover middle weld weld deviation recognition method to track the cover middle weld; uses an arc sensing-based cover weld recognition method to identify the cover middle weld and the last weld, so as to select the corresponding weld tracking method.

Description

Technical Field

[0001] The invention relates to the field of submerged arc welding multi-layer multi-pass cover welding tracking, in particular to a submerged arc welding multi-layer multi-pass cover welding tracking method based on arc sensing. Background Art

[0002] As a thick plate welding method, multi-layer and multi-pass submerged arc welding has the advantages of beautiful weld formation and high efficiency, and is widely used in large lifting equipment, aerospace, nuclear power construction and other fields. However, when welding multi-layer and multi-pass cover welds, since the height of the cover weld is flush with the two sides of the groove, it is difficult to accurately track the cover weld according to the groove characteristics, which greatly reduces the accuracy of weld tracking. In view of the above difficulties, the present invention discloses a submerged arc welding multi-layer and multi-pass cover welding tracking method based on arc sensing, which realizes the tracking of the cover weld according to the difference in surface flatness of the cover weld. Summary of the invention

[0003] The arc sensing-based submerged arc welding multi-layer multi-pass cover welding tracking method is used to track the submerged arc welding multi-layer multi-pass cover welding seams, and is characterized in that: the arc sensing-based submerged arc welding multi-layer multi-pass cover welding tracking method is realized by using the arc sensing-based submerged arc welding multi-layer multi-pass cover welding tracking system; the arc sensing-based submerged arc welding multi-layer multi-pass cover welding tracking system is composed of a submerged arc welding power supply, a submerged arc welding robot, an arc signal acquisition system, a submerged arc welding gun swing controller, a program-controlled filter, and an encoder; the submerged arc welding power supply is used to provide the energy required for welding; the welding robot has three degrees of freedom, which are used to control the welding gun to move up and down, forward and backward, and swing perpendicular to the welding direction; the arc signal acquisition system is used to collect welding voltage; the program-controlled filter is used to filter out the high-frequency noise in the collected arc signal, and obtain a better filtering effect by changing the cutoff frequency; the encoder is connected to the swing shaft, and is used to obtain the actual swing position and swing frequency of the welding gun. The schematic diagram of the arc sensing-based submerged arc welding multi-layer multi-pass cover welding tracking system is as follows: Figure 1 shown.

[0004] The arc sensing-based submerged arc welding multi-layer and multi-pass cover welding tracking method is characterized in that: an arc signal filtering method with an adaptive swing frequency is used to filter out high-frequency noise in the arc signal; the arc signal filtering method with an adaptive swing frequency is to obtain the current swing frequency F of the welding gun through an encoder, and then modify the cutoff frequency of the programmable filter to make it consistent with the welding gun swing frequency F, thereby filtering out high-frequency noise in the arc signal; the welding gun swing frequency F is obtained by using an encoder to record the number of pulses m when the welding gun returns to the swing center twice in a row, thereby obtaining the current swing frequency F of the welding gun = f / 2m, where f is the encoder pulse output frequency.

[0005] The arc sensing-based submerged arc welding multi-layer multi-pass cover welding tracking method is characterized in that: the cover weld edge position recognition method based on arc sensing is used to identify and track the cover weld edge; the arc sensing-based cover weld edge position recognition method is based on calculating the absolute value ΔU=|U of the difference between the voltage values ​​of two adjacent sampling points within the swing period i -U i+1 |(i=1, 2, 3..., represented as sampling points), and counting the total number of sampling points n that meet the condition ΔU>0, and then comparing n with a preset threshold value to achieve the left edge recognition method of the cover weld and the right edge recognition method of the cover weld; the left edge recognition method of the cover weld refers to when tracking the left edge of the cover weld, if n>(i max / 2)+k, the welding gun deviates to the right. If n<(i max / 2)-k, the welding gun is biased to the left, otherwise it is considered that there is no deviation, where k is the preset deviation threshold, i max is the total number of sampling points in the swing cycle; the right edge recognition method of the cover weld refers to tracking the right edge of the cover weld, if n>(i max / 2)+k, the welding gun deviates to the right. If n<(i max / 2)-k, the welding gun deviates to the left, otherwise it is considered that there is no deviation; the swing cycle is the time required for the welding gun to swing from the swing center to the left, then to the right and finally back to the swing center, wherein the amplitude of the welding gun swinging to the left and to the right with respect to the swing center is equal.

[0006] The arc sensing-based submerged arc welding multi-layer multi-pass cover welding tracking method is characterized in that: the cover weld recognition method based on arc sensing is used to identify the middle weld of the cover and the last weld (i.e., the edge of the cover weld), so as to select the corresponding weld tracking method for tracking; the arc sensing-based cover weld recognition method is to calculate the arc signal standard deviation S in the swing cycle. c And compared with the preset threshold S set Comparative analysis is achieved when S c >S set When S is used, the welding of the middle weld of the cover is carried out, and the cover middle weld deviation recognition method based on arc sensing is selected to track the cover middle weld. c ≤S setWhen the last weld is welded, if the welding direction is from left to right, the cover weld right edge recognition method is selected to track the last weld; if the welding direction is from right to left, the cover weld left edge recognition method is selected to track the last weld; the cover middle weld refers to all welds except the first and last welds in the cover weld; the cover middle weld deviation recognition method based on arc sensing includes a left weld deviation recognition method and a right weld deviation recognition method; the left weld deviation recognition method refers to calculating the arc signal integral value I of the second half of the swing cycle in the swing cycle when the cover middle weld is welded in the order from left to right. ll The arc signal integral value I lp The difference between the left and right deviation thresholds ΔI lset1 With ΔI lset2 For comparative analysis, when I ll -I lp >ΔI lset1 When I ll -I lp <ΔI lset2 When the welding gun is biased to the right, it is considered that there is no deviation; the right weld deviation identification method refers to calculating the arc signal integral value I of the first half of the swing cycle in the swing cycle when welding the middle weld of the cap surface from right to left. rp The arc signal integral value I rl The difference between the left and right deviation thresholds ΔI rset1 With ΔI rset2 For comparative analysis, when I rp -I rl <ΔI rset1 When I rp -I rl >ΔI rset2 When the welding gun is considered to be right-biased, otherwise it is considered that there is no deviation. Figure 3 shown.

[0007] Advantageous Effects of the Invention

[0008] The present invention relates to the field of multi-layer and multi-pass weld tracking of submerged arc welding, and is a multi-layer and multi-pass cover welding tracking method of submerged arc welding based on arc sensing. Aiming at the problem that in the process of multi-layer and multi-pass cover welding of submerged arc welding, the weld seam is flush with the groove height, which reduces the weld seam tracking accuracy, a multi-layer and multi-pass cover welding tracking method of submerged arc welding based on arc sensing is proposed, which uses an adaptive swing frequency arc signal filtering method to filter out high-frequency noise in the arc signal; uses an arc sensing-based cover weld edge position recognition method to identify and track the cover weld edge; uses an arc sensing-based cover middle weld weld deviation method to track the cover middle weld; uses an arc sensing-based cover weld recognition method to identify the cover middle weld and the last weld, so as to select a corresponding weld tracking method. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 This is the schematic diagram of the submerged arc welding multi-layer and multi-pass cover welding tracking system based on arc sensing.

[0010] Figure 2 The flowchart of the submerged arc welding multi-layer and multi-pass cap welding tracking method based on arc sensing.

[0011] Figure 3 Schematic diagram of submerged arc welding multi-layer and multi-pass cover welds. DETAILED DESCRIPTION

[0012] In order to better express the technical solutions and beneficial effects of the present invention, the present invention is described below in conjunction with the accompanying drawings and implementation examples.

[0013] The implementation method of the present invention is not limited thereto.

[0014] Step 1: Obtaining the swing frequency and filtering the arc signal.

[0015] In the process of welding multi-layer and multi-pass cap welds of submerged arc welding, the different swing frequencies of the welding gun will directly affect the filtering effect of the filter on the arc signal, which reduces the welding seam tracking accuracy. To solve this problem, the present invention discloses an arc signal filtering method with adaptive swing frequency. At the beginning of welding, the encoder is used to record the number of pulses m when the welding gun returns to the swing center twice in a row, so as to obtain the current swing frequency of the welding gun F=f / 2m, where f is the encoder pulse output frequency. Then the cutoff frequency of the programmable filter is set to F, and then the arc signal is filtered.

[0016] Step 2: Track the first weld of the cover weld (edge ​​of the cover weld).

[0017] In the process of welding multi-layer and multi-pass cap welds by submerged arc welding, it is difficult to track the edge position of the cap weld according to the groove characteristics because the height of the cap weld is flush with the groove. To solve this problem, the present invention discloses a cap weld edge recognition method based on arc sensing, which can recognize and track the edge of the cap weld according to the difference in the flatness of the groove surface. When welding the left and right edges of the cap weld, the submerged arc welding robot will calculate the absolute value of the difference in voltage values ​​between two adjacent sampling points within the swing period ΔU=|U i -U i+1 |, and count the total number of sampling points n that meet the condition ΔU>0.

[0018] When the welding direction is from left to right, select the left edge tracking method of the cover weld to track the first weld of the cover weld. If n>(i max / 2)+k, the welding gun deflects to the right and controls the welding gun to move to the left; if n<(i max / 2)-k, the welding gun deviates to the left and controls the welding gun to move to the right; otherwise, it is considered that there is no deviation, where k is the preset deviation threshold, i max is the total number of sampling points in the swing period.

[0019] When the welding direction is from right to left, select the right edge tracking method of the cap weld to track the first weld of the cap weld. If n>(i max / 2)+k, the welding gun deviates to the right. If n<(i max / 2)-k, the welding gun is deviated to the left, otherwise it is considered that there is no weld deviation.

[0020] Step 3: Identify and track the middle weld and the last weld of the cover.

[0021] In the process of welding multi-layer and multi-pass cover welds by submerged arc welding, after the first weld (i.e., the edge weld on one side of the cover) is welded, the middle weld of the cover and the last weld need to be welded. Therefore, it is necessary to identify the middle weld of the cover and the last weld and select a corresponding weld tracking method. To solve this problem, the present invention discloses a cover weld identification method based on arc sensing, which is used to identify the middle weld of the cover and the last weld, and select a corresponding weld tracking method to track the weld. When welding subsequent welds, such as Figure 1 The schematic diagram of the arc sensing-based submerged arc welding multi-layer multi-pass cover welding tracking system is shown in the figure. The arc signal acquisition system collects the arc signal and transmits it to the submerged arc welding robot after filtering through a program-controlled filter. The submerged arc welding robot calculates the arc signal standard deviation S during the swing cycle. c And with the preset value S set The comparison is made to identify the middle weld and the last weld of the cover.

[0022] When S c>S set When welding the middle weld of the cover, if the welding sequence is from left to right, the submerged arc welding robot will calculate the arc signal integral value I of the second half of the swing cycle in the swing cycle. ll The arc signal integral value I lp The difference between the left and right deviation thresholds ΔI lset1 With ΔI lset2 For comparative analysis, when I ll -I lp >ΔI lset1 When I ll -I lp <ΔI lset2 When the welding gun deviates to the right, the welding gun is controlled to move to the left. Otherwise, it is considered that there is no deviation and the welding gun swing position remains unchanged. If the welding sequence is from right to left, the arc signal integral value I of the first half of the swing cycle is calculated. rp The arc signal integral value I rl The difference between the left and right deviation thresholds ΔI rset1 With ΔI rset2 For comparative analysis, when I rp -I rl <ΔI rset1 When I rp -I rl >ΔI rset2 When the welding gun is considered to be deviated to the right, the welding gun is controlled to move to the left. Otherwise, it is considered that there is no deviation and the swing position of the welding gun remains unchanged.

[0023] When S≤S set When the last weld is welded, the arc sensor-based cover weld edge position recognition method is selected to track the weld. The submerged arc welding robot calculates the absolute value of the difference between the voltage values ​​of two adjacent sampling points within the swing period ΔU = |U i -U i+1 |, and count the total number of sampling points n that meet the condition ΔU>0.

[0024] When the welding direction is from left to right, if n>(i max / 2)+k, the welding gun deflects to the left and controls the welding gun to move to the right; if n<(i max / 2)-k, the welding gun deviates to the right and controls the welding gun to move to the left. Otherwise, it is considered that there is no deviation and the swing position of the welding gun remains unchanged.

[0025] When the welding direction is from right to left, if n>(i max / 2)+k, the welding gun deflects to the right and controls the welding gun to move to the left; if n<(i max / 2)-k, the welding gun deviates to the left and is controlled to move to the right. Otherwise, it is considered that there is no deviation and the swing position of the welding gun remains unchanged.

Claims

1. A submerged arc welding multi-layer multi-pass cover welding tracking method based on arc sensing is used to track submerged arc welding multi-layer multi-pass cover welds, characterized in that: The submerged arc welding multi-layer and multi-pass cover welding tracking method based on arc sensing is realized by using a submerged arc welding multi-layer and multi-pass cover welding tracking system based on arc sensing; the submerged arc welding multi-layer and multi-pass cover welding tracking system based on arc sensing is composed of a submerged arc welding power supply, a submerged arc welding robot, an arc signal acquisition system, a programmable filter, and an encoder; the submerged arc welding power supply is used to provide the energy required for welding; the welding robot has three degrees of freedom, which are used to control the welding gun to move up and down, forward and backward, and to swing perpendicular to the welding direction; the arc signal acquisition system is used to collect welding voltage; the programmable filter has the characteristics of programmability and can change its own parameters through control signals. number, so as to obtain the best filtering effect, which is used to filter out the high-frequency noise in the collected arc signal; the encoder is connected to the swing shaft, which is used to obtain the actual swing position of the welding gun; the arc sensing-based submerged arc welding multi-layer and multi-pass cover welding tracking method includes three steps, step 1 is to use the arc signal filtering method with adaptive swing frequency to filter out the high-frequency noise in the arc signal, step 2 is to use the cover weld edge position recognition method based on arc sensing to identify and track the cover weld edge, step 3 is to use the cover weld recognition method based on arc sensing to identify the cover middle weld and the last weld, and select the corresponding weld tracking method for tracking, wherein the last weld refers to the cover weld edge.

2. The arc sensing-based submerged arc welding multi-layer multi-pass cover welding tracking method according to claim 1, characterized in that: An arc signal filtering method with an adaptive swing frequency is used to filter out high-frequency noise in the arc signal; the arc signal filtering method with an adaptive swing frequency is to obtain the current swing frequency F of the welding gun through an encoder, and then modify the cutoff frequency of the programmable filter to make it consistent with the swing frequency F of the welding gun, thereby filtering out the high-frequency noise in the arc signal; the welding gun swing frequency F is obtained by using an encoder to record the number of pulses m when the welding gun returns to the swing center twice in a row, thereby obtaining the current swing frequency F of the welding gun = f / 2m, where f is the encoder pulse output frequency.

3. The arc sensing-based submerged arc welding multi-layer multi-pass cover welding tracking method according to claim 1, characterized in that: The cover weld edge position recognition method based on arc sensing is used to identify and track the cover weld edge; the cover weld edge position recognition method based on arc sensing is to calculate the absolute value of the difference between the voltage values ​​of two adjacent sampling points in the swing period ΔU=|U i -U i+1 |, where i = 1, 2, 3, ..., represents sampling points, and the total number of sampling points n that meet the condition ΔU>0 is counted, and then n is compared with a preset threshold value to achieve the left edge recognition method and the right edge recognition method of the cover weld; the left edge recognition method of the cover weld refers to when tracking the left edge of the cover weld, if n>(i max / 2)+k, the welding gun deviates to the right. If n<(i max / 2)-k, the welding gun is biased to the left, otherwise it is considered that there is no deviation, where k is the preset deviation threshold, i max is the total number of sampling points in the swing cycle; the right edge recognition method of the cover weld refers to tracking the right edge of the cover weld, if n>(i max / 2)+k, the welding gun deviates to the right. If n<(i max I2)-k, the welding gun deviates to the left, otherwise it is considered that there is no deviation; the swing cycle is the time required for the welding gun to swing from the swing center to the left, then to the right and finally back to the swing center, wherein the amplitude of the welding gun swinging to the left and to the right with the swing center as the reference is equal.

4. The arc sensing-based submerged arc welding multi-layer multi-pass cover welding tracking method according to claim 1, characterized in that: The cover weld recognition method based on arc sensing is used to identify the middle weld and the last weld of the cover, and the corresponding weld tracking method is selected for tracking, wherein the last weld refers to the edge of the cover weld; the cover weld recognition method based on arc sensing is by calculating the standard deviation S of the arc signal in the swing cycle c And with the preset threshold S set Comparative analysis is achieved when S c >S set When S is used, the welding of the middle weld of the cover is carried out, and the cover middle weld deviation recognition method based on arc sensing is selected to track the weld. c ≤S set When the last weld is welded, if the welding direction is from left to right, the cover weld right edge recognition method is selected to track the last weld, and if the welding direction is from right to left, the cover weld left edge recognition method is selected to track the last weld; the cover middle weld refers to all welds in the cover weld except the first and the last weld; the cover middle weld deviation recognition method based on arc sensing includes a left weld deviation recognition method and a right weld deviation recognition method; the left weld deviation recognition method refers to when the cover middle weld is welded in the order from left to right, calculating the arc signal integral value Ill of the second half of the swing cycle and the arc signal integral value Ill of the first half of the swing cycle in the swing cycle. lp The difference between the left and right deviation thresholds ΔI lset1 With ΔI lset2 For comparative analysis, when I ll -I lp >ΔI lset1 When I ll -I lp <ΔI lset2 When the welding gun is biased to the right, it is considered that there is no deviation; the right weld deviation identification method refers to calculating the arc signal integral value I of the first half of the swing cycle in the swing cycle when welding the middle weld of the cap surface from right to left. rp The arc signal integral value I rl The difference between the left and right deviation thresholds ΔI rset1 With ΔI rset2 For comparative analysis, when I rp -I rl <ΔI rset1 When I rp -I rl >ΔI rset2 When , the welding gun is considered to be deviated to the right, otherwise it is considered that there is no deviation.

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