Laser-based welding method for large-diameter thin-walled steel pipes

Abstract

The present application relates to the technical field of pipe laser welding, and particularly relates to a large-diameter thin-wall steel pipe welding method based on laser, which comprises the following steps: performing roundness correction on a large-diameter thin-wall steel pipe to be welded which has a circumferential continuous and symmetrical elliptical deformation after long-distance horizontal transportation; controlling a laser welding gun to move along the circumferential weld joint of the large-diameter thin-wall steel pipe to be welded; when it is determined that there is an abnormal risk in the welding of the large-diameter thin-wall steel pipe according to a molten pool shape representation value, determining a welding inspection strategy for the large-diameter thin-wall steel pipe according to a distance fluctuation representation value; when the first welding inspection strategy is adopted, determining whether the welding of the large-diameter thin-wall steel pipe meets the standard according to a radial vibration peak acceleration; when the second welding inspection strategy is adopted, determining whether the welding of the large-diameter thin-wall steel pipe meets the standard according to a molten depth fluctuation standard deviation; and continuing to weld the large-diameter thin-wall steel pipe which meets the preset standard until the welding of the whole ring joint is completed. The present application improves the laser welding efficiency of the large-diameter thin-wall steel pipe.

Description

Technical Field

[0001] This invention relates to the field of laser welding technology for pipe fittings, and more particularly to a laser-based welding method for large-diameter thin-walled steel pipes. Background Technology

[0002] Large-diameter thin-walled steel pipes are widely used in large-scale infrastructure projects such as long-distance water transportation, offshore wind power, and oil and gas transmission. In domestic long-distance water diversion projects, the diameter of the steel pipes can reach 3 meters or more, and the wall thickness is usually 10 to 20 millimeters, which is a typical large-diameter thin-walled structure. These steel pipes are generally transported by horizontal stacking of single 12-meter sections. After traveling hundreds to thousands of kilometers by road, the pipe openings are easily deformed into continuous circumferential symmetrical elliptical shapes due to factors such as road bumps and multi-layer stacking compression. The on-site hoisting process uses a two-point lifting technique, and the bending deformation and impact during lifting and positioning will further amplify the ellipticity.

[0003] To meet welding assembly requirements, the deformed pipe ends are typically subjected to forced rounding treatment on the construction site to bring the ellipticity back to the design standard. However, rounding treatment has two inherent limitations: first, residual slight ellipticity causes periodic slight fluctuations in the welding gap along the circumference; second, the forced deformation applied during the rounding process generates elastic stress inside the steel pipe, which is gradually released by the heat input during welding, causing non-periodic dynamic changes in the gap.

[0004] The two types of fluctuations mentioned above coexist in the welding process. The former is a normal process phenomenon, while the latter may cause welding defects. Existing laser welding quality monitoring methods usually use single-level threshold judgment, which cannot distinguish the physical source of the fluctuations. This leads to the misjudgment of normal periodic fluctuations as defects, resulting in frequent shutdowns, or the failure to detect abnormal release of elastic stress, resulting in real defects. Consequently, the first-pass yield rate of welding is low.

[0005] Therefore, how to effectively distinguish between normal process fluctuations and true defect precursors under the condition that residual ellipticity and elastic stress coexist after rounding treatment is a technical problem that urgently needs to be solved in this field.

[0006] Chinese Patent Application Publication No. CN115592270A discloses a laser-assisted TIG / GMAW composite welding device and its usage method for large-diameter thin steel pipes. The device comprises a GMAW welding torch (1), a TIG welding torch (2), a welding torch fixing device (3), a TIG power supply (4), a steel pipe to be welded (5), a weld inspection camera (6), a GMAW power supply (8), and a laser (9). This invention fixes the laser, TIG welding torch, and GMAW welding torch to specific angles and sets protective gas channels on both sides and in the middle of the welding torch. On one hand, the laser reduces the resistance of the arc channel, utilizes the arc to heat the base material, and improves the laser absorption efficiency. On the other hand, an inert gas flow protects the molten pool, preventing porosity and metal oxidation, suppressing inter-electrode current, and extending the tungsten electrode life.

[0007] It can be seen that the above technical solution does not take into account the residual slight ellipticity after the rounding treatment of the continuous symmetrical elliptic deformation of the large-diameter thin-walled steel pipe caused by long-distance horizontal transportation, as well as the change in the pipe opening gap caused by the elastic stress introduced by the rounding during the laser welding process. This affects the distinction between normal process fluctuations and the precursors of actual welding defects, resulting in blind adjustment of welding process parameters, frequent weld defects, and thus poor laser welding efficiency of large-diameter thin-walled steel pipes. Summary of the Invention

[0008] To address this, the present invention provides a laser-based welding method for large-diameter thin-walled steel pipes. This method overcomes the problems in existing technologies that fail to consider the residual minute ellipticity after rounding treatment of the continuous symmetrical elliptical deformation caused by long-distance horizontal transportation of large-diameter thin-walled steel pipes, as well as the changes in the pipe opening gap caused by elastic stress introduced during the rounding process in laser welding. These issues affect the distinction between normal process fluctuations and the precursors of actual welding defects, leading to blind adjustment of welding process parameters, frequent weld defects, and ultimately, poor laser welding efficiency for large-diameter thin-walled steel pipes.

[0009] To achieve the above objectives, the present invention provides a laser-based welding method for large-diameter thin-walled steel pipes, comprising: For large-diameter thin-walled steel pipes that have undergone continuous circumferential symmetrical elliptical deformation after long-distance horizontal transportation, a rounding treatment is performed to make the ellipticity of the large-diameter thin-walled steel pipe meet the design standard. After the large-diameter thin-walled steel pipes are aligned, the cross-sectional profile data of the pipe openings at the ends to be welded of the two large-diameter thin-walled steel pipes are collected in the full circumference. A welding reference is established that corresponds one-to-one with the measurement points evenly set in the circumference of the weld. The cross-sectional profile data includes the circumferential angle coordinates that correspond one-to-one with the measurement points in the circumference of the pipe opening. For large-diameter thin-walled steel pipes after rounding, the laser welding torch is controlled to move along the circumference of the weld seam and the molten pool image at the measurement point is collected to obtain the molten pool morphology characterization value. When the welding of large-diameter thin-walled steel pipes is deemed to have abnormal risks based on the molten pool morphology characterization value, the welding inspection strategy for large-diameter thin-walled steel pipes is determined based on the distance fluctuation characterization value. The welding inspection strategy includes a first welding inspection strategy and a second welding inspection strategy. When adopting the first welding inspection strategy, the welding of the large-diameter thin-walled steel pipe is inspected according to the radial vibration peak acceleration of the large-diameter thin-walled steel pipe to determine whether it meets the preset standard. When adopting the second welding inspection strategy, the welding of the large-diameter thin-walled steel pipe is judged to meet the preset standard based on the standard deviation of the penetration depth fluctuation of the large-diameter thin-walled steel pipe. Welding continues on the large-diameter thin-walled steel pipe that meets the preset standards until the entire circumferential seam is completed.

[0010] Furthermore, the process of determining the welding state of large-diameter thin-walled steel pipes based on the molten pool morphology characterization values ​​includes: If the molten pool morphology characterization value is less than the preset molten pool morphology characterization value, the welding of the large-diameter thin-walled steel pipe is determined to be in a normal state, and welding continues. If the molten pool morphology characterization value is greater than or equal to the preset molten pool morphology characterization value, it is determined that there is an abnormal risk in the welding of large-diameter thin-walled steel pipes, and the welding inspection strategy for large-diameter thin-walled steel pipes is determined based on the distance fluctuation characterization value.

[0011] Furthermore, the acquisition of melt pool morphology characterization values ​​includes: The molten pool image at the measurement point is acquired in sync with the circumferential movement of the laser welding gun. Extract the molten pool contour from the acquired molten pool image and identify the width and length of the molten pool; Calculate the ratio of weld width to weld length, and use the ratio as the weld pool morphology coefficient corresponding to the measurement point; Record each molten pool morphology coefficient and its corresponding weld circumferential angle, and arrange them in order of angle to form a sequence of molten pool morphology coefficients. Using the current sampling time as the end point of the sliding window, extract all the molten pool morphology coefficients within the first preset sliding time window from the molten pool morphology coefficient sequence according to the first preset sliding time window; Extract the maximum and minimum values ​​of all molten pool morphology coefficients within the first preset sliding time window, calculate the difference between the maximum and minimum values, and determine the difference as the molten pool fluctuation characterization corresponding to the measurement point.

[0012] Furthermore, the process of determining the welding inspection strategy for the large-diameter thin-walled steel pipe based on the distance fluctuation characterization value includes: If the distance fluctuation characterization value is less than the preset distance fluctuation characterization value, the first welding inspection strategy shall be adopted. If the distance fluctuation characterization value is greater than or equal to the preset distance fluctuation characterization value, then the second welding inspection strategy is adopted.

[0013] Furthermore, the first welding inspection strategy is to inspect whether the welding of the large-diameter thin-walled steel pipe meets the preset standard based on the radial vibration peak acceleration of the large-diameter thin-walled steel pipe; The second welding inspection strategy is to determine whether the welding of the large-diameter thin-walled steel pipe meets the preset standard based on the standard deviation of the weld penetration fluctuation of the large-diameter thin-walled steel pipe.

[0014] Furthermore, the process of obtaining the distance fluctuation characterization value includes: Synchronized with the circumferential movement of the laser welding torch, several relative distance values ​​between the laser head and the outer wall of the steel pipe at the measurement point are collected, and the circumferential angle of the weld corresponding to each relative distance value is recorded to form a time sequence of distance fluctuations. Using the current sampling time as the end point of the sliding window, and according to the second preset sliding time window, the distance fluctuation subsequence within the second preset sliding time window is extracted from the distance fluctuation time series. The distance fluctuation subsequence contains several distance values ​​arranged in chronological order. Calculate the correlation coefficient between the distance fluctuation subsequence and the delayed distance fluctuation subsequence, wherein the delayed distance fluctuation subsequence is a sequence obtained by shifting each distance value in the distance fluctuation subsequence backward along the time axis by a preset delay time. By changing the value of the preset delay time, the above calculations are performed to obtain several correlation coefficients; Extract the maximum value among several correlation coefficients and use the maximum value as the distance fluctuation characterization value.

[0015] Furthermore, the process of verifying whether the welding of the large-diameter thin-walled steel pipe meets the preset standards based on the radial vibration peak acceleration of the large-diameter thin-walled steel pipe includes: If the radial vibration peak acceleration is less than the preset radial vibration peak acceleration, then the welding of the large-diameter thin-walled steel pipe is determined to meet the preset standard. If the radial vibration peak acceleration is greater than or equal to the preset radial vibration peak acceleration, it is determined that the welding of the large-diameter thin-walled steel pipe does not meet the preset standard, and the determination result is abnormal release of elastic stress, triggering the first alarm.

[0016] Furthermore, the process of obtaining the radial vibration peak acceleration of the large-diameter thin-walled steel pipe includes: Collect radial vibration acceleration at each measurement point; Take the median value of the radial vibration acceleration at all measurement points as the radial acceleration at the current moment; Continuous data acquisition is performed, and the maximum radial acceleration within the third preset sliding window is extracted as the peak radial vibration acceleration.

[0017] Furthermore, the process of determining whether the welding of the large-diameter thin-walled steel pipe meets the preset standard based on the standard deviation of the weld penetration fluctuation of the large-diameter thin-walled steel pipe includes: If the standard deviation of the weld penetration fluctuation is less than the preset standard deviation of the weld penetration fluctuation, then the welding inspection of the large-diameter thin-walled steel pipe is determined to meet the preset standard. If the standard deviation of the weld penetration fluctuation is greater than or equal to the preset standard deviation of the weld penetration fluctuation, it is determined that the welding of the large-diameter thin-walled steel pipe does not meet the preset standard, and the determination result is that the periodic gap fluctuation caused by residual ellipticity is abnormal, triggering the second alarm.

[0018] Furthermore, the process of obtaining the standard deviation of the melting depth fluctuation of the large-diameter thin-walled steel pipe includes: Synchronize with the circumferential movement of the laser welding torch, collect the corresponding penetration depth at the measurement point, record the circumferential angle of the weld corresponding to each penetration depth, and form a penetration depth time sequence. Using the current sampling time as the end point of the sliding window, extract all melt depth values ​​within the fourth preset sliding time window from the melt depth time sequence according to the fourth preset sliding time window; Calculate the standard deviation of all melt depth values ​​within the fourth preset sliding time window, and record the standard deviation as the corresponding melt depth fluctuation standard deviation of the measurement point.

[0019] Compared with existing technologies, the advantages of this invention lie in its ability to solve the problem of continuous symmetrical elliptic deformation of the pipe end caused by long-distance horizontal transportation by performing a rounding process on the large-diameter thin-walled steel pipe to be welded, ensuring that the ellipticity meets design standards. Based on the rounding process, a welding reference corresponding to each measurement point is established by collecting circumferential cross-sectional contour data, providing a precise spatial reference for subsequent welding. During welding, the presence of abnormal risks is determined based on the molten pool morphology characterization value, and different inspection strategies are selected based on the distance fluctuation characterization value. The first inspection strategy uses the radial vibration peak acceleration to determine whether the welding meets the standard, while the second inspection strategy uses the standard deviation of the weld penetration fluctuation. This scheme uses different characteristic parameters to verify the periodic gap fluctuations caused by the residual minute ellipticity after rounding and the non-periodic disturbances caused by the gradual release of elastic stress generated during welding. This effectively distinguishes between normal process fluctuations and true defect precursors, avoiding misjudgments and omissions, thereby improving the efficiency of laser welding of large-diameter thin-walled steel pipes.

[0020] Furthermore, this invention uses a two-level judgment based on the molten pool morphology characterization value, which not only ensures the continuous and stable operation of the normal welding process and avoids ineffective intervention, but also promptly triggers subsequent inspection procedures for abnormal risks that exceed the threshold, thus achieving rapid and accurate separation of normal conditions and abnormal risks, thereby improving the timeliness of response to abnormal situations.

[0021] Furthermore, by binding the first welding inspection strategy with the radial vibration peak acceleration and the second welding inspection strategy with the standard deviation of the weld penetration fluctuation, this invention achieves a precise correspondence between anomaly types and inspection parameters. It provides targeted inspection methods for two core anomalies that may occur during steel pipe welding after long-distance transportation and rounding: abnormal release of elastic stress and periodic gap fluctuation caused by residual ellipticity. These methods can accurately identify different types of welding anomalies, avoid missed or misjudged cases caused by a single inspection method, and thus improve the accuracy of welding quality inspection.

[0022] Furthermore, this invention ensures the stability and accuracy of the radial vibration peak acceleration data by collecting the radial vibration acceleration at each measurement point, taking the median value as the radial acceleration at the current moment, and then extracting the maximum value using a sliding window. It can effectively filter out interference data during the measurement process, accurately capture the radial vibration changes caused by the release of elastic stress during the welding of steel pipes after long-distance transportation and rounding, provide reliable data support for welding quality inspection and anomaly judgment, ensure the accurate identification of abnormal release of elastic stress, and thus improve the reliability of welding quality control.

[0023] Furthermore, this invention collects melt depth data at measurement points synchronously with the circumferential movement of the laser welding torch, constructs a melt depth time series, extracts melt depth values ​​using a sliding window, and calculates the standard deviation, thereby achieving precise quantification of melt depth fluctuations. It can effectively capture the periodic fluctuations in melt depth caused by residual ellipticity during the welding of steel pipes after long-distance transportation and rounding, accurately reflecting the uniformity of melt depth, thus providing reliable data support for welding quality inspection and anomaly judgment. Attached Figure Description

[0024] Figure 1 This is a flowchart of a laser-based welding method for large-diameter thin-walled steel pipes according to an embodiment of the present invention; Figure 2 This is a flowchart illustrating how the welding state of a large-diameter thin-walled steel pipe is determined based on the molten pool morphology characterization value, according to an embodiment of the present invention. Figure 3 This is a flowchart illustrating the process of determining a welding inspection strategy for a large-diameter thin-walled steel pipe based on the distance fluctuation characterization value of the large-diameter thin-walled steel pipe, as described in an embodiment of the present invention. Figure 4 This is a flowchart illustrating an embodiment of the present invention for verifying whether the welding of a large-diameter thin-walled steel pipe conforms to a preset standard based on the radial vibration peak acceleration of the large-diameter thin-walled steel pipe. Detailed Implementation

[0025] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0026] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0027] It should be noted that the data in this embodiment are all derived from a comprehensive analysis and evaluation of historical test data and corresponding historical test results from the three months prior to this test. Those skilled in the art will understand that the method described in this invention can determine the above-mentioned parameters in the following ways: selecting the value with the highest proportion based on the data distribution as the preset standard parameter; using weighted summation to obtain the value as the preset standard parameter; substituting each historical data point into a specific formula and using the value obtained by that formula as the preset standard parameter; or other selection methods, as long as the method described in this invention can clearly define different specific situations in the single-item judgment process through the obtained values.

[0028] Please see Figure 1 , Figure 2 , Figure 3 as well as Figure 4 The flowcharts shown are, respectively, a laser-based welding method for large-diameter thin-walled steel pipes according to an embodiment of the present invention; a flowchart for determining the welding state of large-diameter thin-walled steel pipes based on molten pool morphology characterization values ​​according to an embodiment of the present invention; a flowchart for determining the welding inspection strategy of large-diameter thin-walled steel pipes based on distance fluctuation characterization values ​​according to an embodiment of the present invention; and a flowchart for inspecting whether the welding of large-diameter thin-walled steel pipes meets preset standards based on radial vibration peak acceleration according to an embodiment of the present invention.

[0029] This invention provides a laser-based method for welding large-diameter thin-walled steel pipes, comprising: Step S1 involves rounding a large-diameter thin-walled steel pipe to be welded that has undergone continuous circumferential symmetrical elliptical deformation after long-distance horizontal transportation, ensuring that the ellipticity of the pipe meets the design standard. In this embodiment, the steel pipe is made of Q355C, with an outer diameter of 3400mm, a wall thickness of 12mm, a diameter-to-thickness ratio of 283, and a relative wall thickness of 0.0035. After 1200km of horizontal road transportation and on-site two-point hoisting, the measured ellipticity of the pipe opening was 1.8%, exceeding the design allowable standard (ellipticity ≤ 0.5%). A hydraulic rounding machine was used on-site to force round the pipe opening, controlling the ellipticity to 0.4% after rounding. Step S2: After the large-diameter thin-walled steel pipes are aligned, the cross-sectional profile data of the pipe openings at the ends to be welded of the two large-diameter thin-walled steel pipes are collected in the entire circumference. A welding reference is established corresponding to the measurement points evenly distributed in the circumference of the weld. The cross-sectional profile data includes the circumferential angle coordinates corresponding to the measurement points in the circumference of the pipe opening. In this embodiment, a laser profile scanner is used to collect the cross-sectional profile data of the ends to be welded in the entire circumference. 360 measurement points are evenly distributed in the circumference (one every 1°). Each measurement point records the circumferential angle and the radial coordinates of the pipe wall. Step S3: For the large-diameter thin-walled steel pipe after rounding, a fiber laser is used with a wavelength of 1070nm, a rated power of 12kW, a reference laser power of 8kW, a welding speed of 1.2m / min, a defocusing amount of +2mm, and argon as the shielding gas with a flow rate of 20L / min. The wire feeder's reference wire feeding speed is 5.5m / min. The welding torch moves circumferentially along the circumferential seam, driven by a servo motor. The encoder provides real-time feedback of the circumferential angle, synchronized with the circumferential movement of the laser welding torch. A high-speed CMOS camera (sampling frequency 200Hz, with a narrow-band filter) is used to acquire images of the molten pool at each measurement point, and the molten pool morphology characterization value is obtained. Step S4: When it is determined that there is an abnormal risk in the welding of large-diameter thin-walled steel pipe based on the molten pool morphology characterization value, the welding inspection strategy of large-diameter thin-walled steel pipe is determined based on the distance fluctuation characterization value. The welding inspection strategy includes a first welding inspection strategy and a second welding inspection strategy. Step S5: When adopting the first welding inspection strategy, the welding of the large-diameter thin-walled steel pipe is inspected according to the radial vibration peak acceleration of the large-diameter thin-walled steel pipe to see if it meets the preset standard. Step S6: When adopting the second welding inspection strategy, determine whether the welding of the large-diameter thin-walled steel pipe meets the preset standard based on the standard deviation of the weld penetration fluctuation of the large-diameter thin-walled steel pipe. Step S7: Continue welding the large-diameter thin-walled steel pipe that meets the preset standards until the entire circumferential seam is welded.

[0030] It should be noted that the data in this embodiment are all results obtained through preliminary experiments before this test using the method described in this invention. Each preset value can be adjusted according to the specific application, as long as the method described in this invention can clearly define different specific situations in the single-item judgment process through the acquired values. The preset values ​​set in this embodiment are all obtained from preliminary experiments, including the correction coefficients, which were also selected through experimental verification.

[0031] Specifically, the process of determining the welding state of large-diameter thin-walled steel pipes based on the molten pool morphology characteristics includes: If the molten pool morphology characterization value is less than the preset molten pool morphology characterization value of 0.12, the welding of the large-diameter thin-walled steel pipe is determined to be in a normal state, and welding continues. If the molten pool morphology characterization value is greater than or equal to the preset molten pool morphology characterization value, it is determined that there is an abnormal risk in the welding of large-diameter thin-walled steel pipes, and the welding inspection strategy for large-diameter thin-walled steel pipes is determined based on the distance fluctuation characterization value.

[0032] Specifically, the molten pool morphology characterization value represents the fluctuation range of the molten pool morphology, accurately capturing subtle changes in the width and length of the molten pool during welding. In this embodiment, residual ellipticity after rounding will cause periodic minor fluctuations in the weld gap, and the release of elastic stress will cause non-periodic disturbances in the gap. Both of these conditions will cause fluctuations in the molten pool morphology, while under normal welding conditions, the molten pool morphology is stable and the fluctuation range is extremely small.

[0033] In this embodiment, steel pipes with ellipticity meeting the standard and no abnormal stress release were selected for rounding. Twenty circumferential welds were completed under standard welding process parameters. During the weld trials, the molten pool morphology characteristics of each measurement point were continuously collected. Simultaneously, non-destructive testing was performed on each weld to confirm its quality. Subsequently, statistical analysis was conducted on the molten pool morphology characteristics of all qualified welds. The calculated arithmetic mean μ was approximately 0.07, and the sample standard deviation σ was approximately 0.015. The statistical results showed that the distribution of these characteristics conformed to a normal distribution. Based on the statistical process control principle, the upper limit for normal process fluctuations was set to μ + 3σ, i.e., 0.07 + 3 × 0.015 = 0.115. This upper limit can cover 99.7% of normal process fluctuations, effectively avoiding misjudgment of normal fluctuations. Finally, considering the slight differences in material, surface condition, and ambient temperature between different batches of steel pipes, the value was rounded up to 0.12 from 0.115. Ultimately, the preset molten pool morphology characteristic value was determined to be 0.12.

[0034] Specifically, obtaining the molten pool morphology characterization values ​​includes: The molten pool image at the measurement point is acquired synchronously with the circumferential movement of the laser welding torch using a high-speed CMOS camera (sampling frequency 200Hz, with narrow band filter); The acquired raw images of the molten pool are sequentially converted to grayscale, denoised by median filtering, and processed by Canny edge extraction. The outline of the molten pool is identified and segmented. The width and length of the molten pool are obtained by taking the welding direction as the length direction of the molten pool and the direction perpendicular to the welding direction as the width direction of the molten pool. Calculate the ratio of weld width to weld length, and use the ratio as the weld pool morphology coefficient corresponding to the measurement point; All the molten pool morphology coefficients corresponding to the measurement points are bound to their circumferential angular coordinates one by one and arranged in order from 0° to 360° of circumferential angle to form a continuous sequence of molten pool morphology coefficients. Using the current sampling time as the end point of the sliding window, and according to the first preset sliding time window (window duration 0.5s), extract all the molten pool morphology coefficients within the first preset sliding time window from the molten pool morphology coefficient sequence; Extract the maximum and minimum values ​​of all molten pool morphology coefficients within the first preset sliding time window, calculate the difference between the maximum and minimum values, and determine the difference as the molten pool fluctuation characterization corresponding to the measurement point.

[0035] Specifically, the process of determining the welding inspection strategy for large-diameter thin-walled steel pipes based on the distance fluctuation characterization values ​​includes: If the distance fluctuation characterization value is less than the preset distance fluctuation characterization value of 0.65, the first welding inspection strategy shall be adopted. If the distance fluctuation characterization value is greater than or equal to the preset distance fluctuation characterization value, then the second welding inspection strategy is adopted.

[0036] Specifically, the distance fluctuation characterization value is the maximum correlation coefficient extracted through autocorrelation analysis. Its magnitude directly reflects the periodicity of the relative distance fluctuation between the laser head and the outer wall of the steel pipe. When the steel pipe has residual ellipticity, the gap changes periodically along the circumference. During the uniform movement of the welding torch, the distance between the laser head and the pipe wall exhibits a regular fluctuation consistent with the elliptical period. In this case, the autocorrelation function of the distance fluctuation time series will show a significant peak at the delay time corresponding to the elliptical period, and the maximum correlation coefficient approaches 1. When elastic stress release causes non-periodic rebound or displacement at the pipe opening, the distance fluctuation becomes random or sudden. The autocorrelation function of the time series shows low correlation coefficients at each delay time, and the maximum correlation coefficient decreases. Therefore, by analyzing the magnitude of the distance fluctuation characterization value, the physical source of abnormal fluctuations can be effectively distinguished: high values ​​correspond to periodic gap fluctuations caused by residual ellipticity, while low values ​​correspond to non-periodic disturbances caused by elastic stress release.

[0037] Specifically, the preset distance fluctuation characterization value is 0.65, which is based on the statistical analysis results of two sets of benchmark welding tests. The first set of benchmark tests selected steel pipes that met the ellipticity standard after rounding treatment and had no obvious elastic stress release for welding tests. The distance fluctuation time series was collected and the corresponding distance fluctuation characterization value was calculated. The data from 10 sets of tests showed that the characterization value was distributed between 0.71 and 0.86, with a mean of 0.79 and a standard deviation of 0.045. The second set of benchmark tests selected steel pipes that were confirmed by strain gauge monitoring to have significant elastic stress release but met the ellipticity standard for welding tests. Similarly, the distance fluctuation characterization value calculated was distributed between 0.42 and 0.58, with a mean of 0.51 and a standard deviation of 0.049. The data obtained from the two sets of experiments do not overlap, and the dividing range is between 0.58 and 0.71. In order to balance the accuracy of the judgment and the robustness of engineering applications, the median value between the means of the two sets of experimental data was selected and rounded. Finally, the preset distance fluctuation characterization value was determined to be 0.65. This threshold can ensure the accurate distinction between periodic fluctuations and non-periodic disturbances and has high identification reliability.

[0038] Specifically, the first welding inspection strategy is to inspect whether the welding of the large-diameter thin-walled steel pipe meets the preset standard based on the radial vibration peak acceleration of the large-diameter thin-walled steel pipe. The second welding inspection strategy is to determine whether the welding of the large-diameter thin-walled steel pipe meets the preset standard based on the standard deviation of the weld penetration fluctuation of the large-diameter thin-walled steel pipe.

[0039] Specifically, the process of obtaining the distance fluctuation characterization value includes: Synchronized with the circumferential movement of the laser welding torch, a laser displacement sensor (sampling frequency 1kHz) is used to collect several relative distance values ​​from the laser head end face to the outer wall of the steel pipe at the measurement point, and the circumferential angle of the weld corresponding to each relative distance value is recorded to form a distance fluctuation time sequence. Using the current sampling time as the end point of the sliding window, and according to the second preset sliding time window (window duration 2s), the distance fluctuation subsequence within the second preset sliding time window is extracted from the distance fluctuation time series. The distance fluctuation subsequence contains several distance values ​​arranged in chronological order. Multiple delay processing steps were applied to the distance fluctuation subsequence, generating delayed subsequences with delay durations of 1ms, 2ms, ..., 1000ms, using a delay step of 1ms. Each delayed subsequence was obtained by shifting the original distance fluctuation subsequence backward along the time axis by the corresponding delay duration. The Pearson linear correlation coefficient between the original distance fluctuation subsequence and each delayed subsequence was calculated, yielding a correlation coefficient corresponding to each delay duration. Correlation coefficients corresponding to delay durations of 0 were removed to avoid computational distortion caused by autocorrelation always being 1. Extract the maximum value among several correlation coefficients and use the maximum value as the distance fluctuation characterization value.

[0040] Specifically, the process of verifying whether the welding of the large-diameter thin-walled steel pipe meets the preset standards based on the radial vibration peak acceleration of the large-diameter thin-walled steel pipe includes: If the peak radial vibration acceleration is less than the preset peak radial vibration acceleration of 0.5 m / s² 2 If the welding of the large-diameter thin-walled steel pipe meets the preset standard, then it is determined that the welding meets the preset standard. If the radial vibration peak acceleration is greater than or equal to the preset radial vibration peak acceleration, the welding of the large-diameter thin-walled steel pipe is determined to be non-compliant with the preset standard, and the determination result is abnormal release of elastic stress, triggering the first alarm. The first alarm includes: immediately cutting off the laser output, stopping wire feeding, controlling the welding torch to retract 50mm in the opposite direction of the current travel direction, and displaying the prompt message "Abnormal release of elastic stress, it is recommended to check the corresponding angle position of the weld" on the human-machine interface. At the same time, the current abnormal data and the corresponding weld circumferential angle are recorded in the database for subsequent quality traceability and re-welding positioning.

[0041] Specifically, elastic stress is stored as elastic potential energy inside the rounded steel pipe. When the welding heat input causes a decrease in the local metal yield strength, this energy is released in the form of sudden rebound, manifesting as a transient impact of radial vibration at the pipe end. The peak radial acceleration can directly quantify the intensity of this transient impact. During normal welding, the elastic stress is released smoothly with the heat input, resulting in a low peak vibration value; when stress is concentrated or accompanied by crack initiation, the peak vibration value increases significantly.

[0042] Specifically, the preset peak radial vibration acceleration is 0.5 m / s². 2 This value was determined as follows: Welding tests were conducted on 20 reference welds on a rounded steel pipe with acceptable ellipticity and no welding defects, and the radial vibration peak acceleration data of all welds were collected. Under normal welding conditions, the statistical average radial vibration peak acceleration corresponding to the smooth release of elastic stress was 0.27 m / s². 2 The standard deviation is 0.06 m / s 2 Take the average value plus three times the standard deviation (0.27 + 0.18 = 0.45 m / s) 2 Furthermore, the measured peak values ​​during abnormal stress release (accompanied by spatter or molten pool disturbance) in field tests were all greater than 0.55 m / s. 2 Based on the distribution characteristics, the preset radial vibration peak acceleration is set to 0.5 m / s². 2 .

[0043] Specifically, the process of obtaining the radial vibration peak acceleration of the large-diameter thin-walled steel pipe includes: Radial vibration acceleration at each measurement point was collected using an accelerometer (sensitivity 100mV / g, sampling frequency 2kHz). Take the median value of the radial vibration acceleration at all measurement points as the radial acceleration at the current moment; Continuous data acquisition is performed, and the maximum radial acceleration within the third preset sliding window (window duration 0.2s) is extracted as the peak radial vibration acceleration.

[0044] Specifically, the process of determining whether the welding of the large-diameter thin-walled steel pipe meets the preset standard based on the standard deviation of the weld penetration fluctuation includes: If the standard deviation of the weld penetration fluctuation is less than the preset standard deviation of the weld penetration fluctuation of 0.30 mm, then the welding inspection of the large-diameter thin-walled steel pipe is determined to meet the preset standard. If the standard deviation of the weld penetration fluctuation is greater than or equal to the preset standard deviation of the weld penetration fluctuation, it is determined that the welding of the large-diameter thin-walled steel pipe does not meet the preset standard, and the determination result is that the periodic gap fluctuation is abnormal due to residual ellipticity, triggering a second alarm. The second alarm includes: immediately cutting off the laser output, stopping the wire feeding, controlling the welding torch to retract 50 mm in the opposite direction of the current welding direction, and displaying the prompt message "Periodic gap fluctuation exceeds the limit, which may cause incomplete penetration or insufficient weld penetration. It is recommended to check the gap or adjust the parameters" on the human-machine interface. At the same time, the current abnormal data and the corresponding weld circumferential angle are recorded in the database for subsequent quality traceability and repair welding positioning.

[0045] Specifically, residual ellipticity causes the weld gap to vary periodically and continuously along the circumference, directly affecting the weld penetration: a larger gap results in a smaller weld penetration, and a smaller gap results in a larger weld penetration. The standard deviation of weld penetration fluctuation reflects the degree of dispersion of the weld penetration value from the average value within a sliding window, quantifying the intensity of periodic fluctuations. During normal welding, the weld penetration fluctuates periodically within the allowable range, with a small standard deviation; when the gap fluctuation amplitude exceeds the normal range (e.g., insufficient rounding or increased local deformation at the nozzle), the weld penetration fluctuation amplitude increases, and the standard deviation rises accordingly.

[0046] Specifically, the preset standard deviation of weld penetration fluctuation is set at 0.30 mm. This is calibrated as follows: Welding tests are conducted on 20 reference welds on rounded steel pipes with compliant ellipticity and assembly gaps meeting design requirements, and the weld penetration time sequence data for all welds are collected. Under normal welding conditions, the statistical mean of the standard deviation of weld penetration fluctuation is 0.19 mm, and the standard deviation is 0.035 mm. Taking the mean plus three times the standard deviation (0.19 + 0.105 = 0.295 mm), the preset standard deviation of weld penetration fluctuation is set at 0.30 mm.

[0047] Specifically, the process of obtaining the standard deviation of the melting depth fluctuation of the large-diameter thin-walled steel pipe includes: Synchronized with the circumferential movement of the laser welding torch, an optical coherence tomography sensor (sampling frequency 500Hz) is used to collect the corresponding penetration depth at the measurement point, and the circumferential angle of the weld corresponding to each penetration depth is recorded to form a penetration depth time sequence. Using the current sampling time as the end point of the sliding window, extract all melt depth values ​​within the fourth preset sliding time window (window duration 0.8s) from the melt depth time sequence. Calculate the standard deviation of all melt depth values ​​within the fourth preset sliding time window, and record the standard deviation as the corresponding melt depth fluctuation standard deviation of the measurement point.

[0048] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A laser-based welding method for large-diameter thin-walled steel pipes, characterized in that, include: For large-diameter thin-walled steel pipes that have undergone continuous circumferential symmetrical elliptical deformation after long-distance horizontal transportation, a rounding treatment is performed to make the ellipticity of the large-diameter thin-walled steel pipe meet the design standard. For the large-diameter thin-walled steel pipes after rounding and assembly, the cross-sectional profile data of the pipe openings at the ends to be welded of the two large-diameter thin-walled steel pipes are collected in the full circumference. Welding references are established with the measurement points evenly set in the circumference of the weld seam corresponding one-to-one. The cross-sectional profile data includes the circumferential angle coordinates corresponding one-to-one with the measurement points in the circumference of the pipe opening. For large-diameter thin-walled steel pipes after rounding, the laser welding torch is controlled to move along the circumference of the weld seam and the molten pool image at the measurement point is collected to obtain the molten pool morphology characterization value. When the welding of large-diameter thin-walled steel pipes is deemed to have abnormal risks based on the molten pool morphology characterization value, the welding inspection strategy for large-diameter thin-walled steel pipes is determined based on the distance fluctuation characterization value. The welding inspection strategy includes a first welding inspection strategy and a second welding inspection strategy. When adopting the first welding inspection strategy, the welding of the large-diameter thin-walled steel pipe is inspected according to the radial vibration peak acceleration of the large-diameter thin-walled steel pipe to determine whether it meets the preset standard. When adopting the second welding inspection strategy, the welding of the large-diameter thin-walled steel pipe is judged to meet the preset standard based on the standard deviation of the penetration depth fluctuation of the large-diameter thin-walled steel pipe. Welding continues on the large-diameter thin-walled steel pipe that meets the preset standards until the entire circumferential seam is completed.

2. The laser-based welding method for large-diameter thin-walled steel pipes according to claim 1, characterized in that, The process of determining the welding status of large-diameter thin-walled steel pipes based on the molten pool morphology characteristics includes: If the molten pool morphology characterization value is less than the preset molten pool morphology characterization value, the welding of the large-diameter thin-walled steel pipe is determined to be in a normal state, and welding continues. If the molten pool morphology characterization value is greater than or equal to the preset molten pool morphology characterization value, it is determined that there is an abnormal risk in the welding of large-diameter thin-walled steel pipes, and the welding inspection strategy for large-diameter thin-walled steel pipes is determined based on the distance fluctuation characterization value.

3. The laser-based welding method for large-diameter thin-walled steel pipes according to claim 2, characterized in that, The acquisition of melt pool morphology characterization values ​​includes: The molten pool image at the measurement point is acquired in sync with the circumferential movement of the laser welding gun. Extract the molten pool contour from the acquired molten pool image and identify the width and length of the molten pool; Calculate the ratio of weld width to weld length, and use the ratio as the weld pool morphology coefficient corresponding to the measurement point; Record each molten pool morphology coefficient and its corresponding weld circumferential angle, and arrange them in order of angle to form a sequence of molten pool morphology coefficients. Using the current sampling time as the end point of the sliding window, extract all the molten pool morphology coefficients within the first preset sliding time window from the molten pool morphology coefficient sequence according to the first preset sliding time window; Extract the maximum and minimum values ​​of all molten pool morphology coefficients within the first preset sliding time window, calculate the difference between the maximum and minimum values, and determine the difference as the molten pool fluctuation characterization corresponding to the measurement point.

4. The laser-based welding method for large-diameter thin-walled steel pipes according to claim 3, characterized in that, The process of determining the welding inspection strategy for large-diameter thin-walled steel pipes based on the distance fluctuation characterization values ​​includes: If the distance fluctuation characterization value is less than the preset distance fluctuation characterization value, the first welding inspection strategy shall be adopted. If the distance fluctuation characterization value is greater than or equal to the preset distance fluctuation characterization value, then the second welding inspection strategy is adopted.

5. The laser-based welding method for large-diameter thin-walled steel pipes according to claim 4, characterized in that, The first welding inspection strategy is to inspect whether the welding of the large-diameter thin-walled steel pipe meets the preset standard based on the radial vibration peak acceleration of the large-diameter thin-walled steel pipe. The second welding inspection strategy is to determine whether the welding of the large-diameter thin-walled steel pipe meets the preset standard based on the standard deviation of the weld penetration fluctuation of the large-diameter thin-walled steel pipe.

6. The laser-based welding method for large-diameter thin-walled steel pipes according to claim 4, characterized in that, The process of obtaining the distance fluctuation characterization value includes: Synchronized with the circumferential movement of the laser welding torch, several relative distance values ​​between the laser head and the outer wall of the steel pipe at the measurement point are collected, and the circumferential angle of the weld corresponding to each relative distance value is recorded to form a time sequence of distance fluctuations. Using the current sampling time as the end point of the sliding window, and according to the second preset sliding time window, the distance fluctuation subsequence within the second preset sliding time window is extracted from the distance fluctuation time series. The distance fluctuation subsequence contains several distance values ​​arranged in chronological order. Calculate the correlation coefficient between the distance fluctuation subsequence and the delayed distance fluctuation subsequence, wherein the delayed distance fluctuation subsequence is a sequence obtained by shifting each distance value in the distance fluctuation subsequence backward along the time axis by a preset delay time. By changing the value of the preset delay time, the above calculations are performed to obtain several correlation coefficients; Extract the maximum value among several correlation coefficients and use the maximum value as the distance fluctuation characterization value.

7. The laser-based welding method for large-diameter thin-walled steel pipes according to claim 5, characterized in that, The process of verifying whether the welding of the large-diameter thin-walled steel pipe meets the preset standards based on the radial vibration peak acceleration of the large-diameter thin-walled steel pipe includes: If the radial vibration peak acceleration is less than the preset radial vibration peak acceleration, then the welding of the large-diameter thin-walled steel pipe is determined to meet the preset standard. If the radial vibration peak acceleration is greater than or equal to the preset radial vibration peak acceleration, it is determined that the welding of the large-diameter thin-walled steel pipe does not meet the preset standard, and the determination result is abnormal release of elastic stress, triggering the first alarm.

8. The laser-based welding method for large-diameter thin-walled steel pipes according to claim 7, characterized in that, The process of obtaining the radial vibration peak acceleration of the large-diameter thin-walled steel pipe includes: Collect radial vibration acceleration at each measurement point; Take the median value of the radial vibration acceleration at all measurement points as the radial acceleration at the current moment; Continuous data acquisition is performed, and the maximum radial acceleration within the third preset sliding window is extracted as the peak radial vibration acceleration.

9. The laser-based welding method for large-diameter thin-walled steel pipes according to claim 5, characterized in that, The process of determining whether the welding of large-diameter thin-walled steel pipes meets the preset standards based on the standard deviation of the weld penetration fluctuation includes: If the standard deviation of the weld penetration fluctuation is less than the preset standard deviation of the weld penetration fluctuation, then the welding inspection of the large-diameter thin-walled steel pipe is determined to meet the preset standard. If the standard deviation of the weld penetration fluctuation is greater than or equal to the preset standard deviation of the weld penetration fluctuation, it is determined that the welding of the large-diameter thin-walled steel pipe does not meet the preset standard, and the determination result is that the periodic gap fluctuation caused by residual ellipticity is abnormal, triggering the second alarm.

10. The laser-based welding method for large-diameter thin-walled steel pipes according to claim 9, characterized in that, The process of obtaining the standard deviation of the melting depth fluctuation of the large-diameter thin-walled steel pipe includes: Synchronize with the circumferential movement of the laser welding torch, collect the corresponding penetration depth at the measurement point, record the circumferential angle of the weld corresponding to each penetration depth, and form a penetration depth time sequence. Using the current sampling time as the end point of the sliding window, extract all melt depth values ​​within the fourth preset sliding time window from the melt depth time sequence according to the fourth preset sliding time window; Calculate the standard deviation of all melt depth values ​​within the fourth preset sliding time window, and record the standard deviation as the corresponding melt depth fluctuation standard deviation of the measurement point.

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