Wear-resistant dredging pipeline welding method and welding process

Abstract

The invention relates to the technical field of welding, in particular to a wear-resistant dredging pipeline welding method and a wear-resistant dredging pipeline welding process. According to distribution difference characteristics of the welding parameter data at different moments, an instantaneous welding difference coefficient is obtained; obtaining an asynchronous difference coefficient; dividing the whole welding process to obtain a plurality of asynchronous comparison intervals; obtaining a comprehensive comparison score of each welding parameter data in each out-of-step comparison interval; obtaining an asynchronous feedback significant value of each type of welding parameter data; welding control is optimized and adjusted on the basis of the asynchronous feedback characteristics of each welding parameter in the welding process, and the dredging pipeline subjected to preliminary welding is obtained; and the dredging pipeline is in butt joint with the flange, a reinforcing rib plate is welded to the back face of the flange, and the finally-welded dredging pipeline is obtained. The control precision of the pipeline welding process is improved, and high-quality welding with high pipeline fitting degree is achieved.

Description

Technical Field

[0001] The present application relates to the field of welding technology, and in particular to a wear-resistant dredging pipeline welding method and welding process. Background Art

[0002] During dredging operations, pipelines face harsh environments, there is pressure inside the pipes, and a large amount of sand and stone, especially irregular impact stones, cause great wear on the pipelines. In the process of welding wear-resistant dredging pipelines, flash butt welding and butt welding are usually used, and process parameters such as welding current, voltage and welding speed are strictly controlled to ensure welding quality. However, in the actual welding process, the two ends of the pipeline are usually elliptical, and this shape causes gaps to appear at different positions. From the perspective of welding technology, the existence of such gaps will affect the welding quality and the overall performance of the pipeline; when there are gaps at both ends of the pipeline, direct welding may result in uneven welds, affecting the welding quality.

[0003] When welding pipelines using traditional automatic welding control systems, the welding parameters should remain consistent. If asynchronous disorder characteristics appear between the welding parameters during the welding process, defects such as unfused welding and bubbles will occur, making the shape and size of the molten pool unstable during welding, affecting the uniformity of the weld, and thus reducing the quality of wear-resistant dredging pipeline welding. Summary of the invention

[0004] In view of the above, it is necessary to provide a wear-resistant dredging pipeline welding method and welding process to solve the above problems.

[0005] A first aspect of the present application provides a wear-resistant dredging pipeline welding method, the method comprising:

[0006] During the preliminary welding of the dredged pipeline, the welding control was optimized and adjusted;

[0007] The specific process of optimizing and adjusting the welding control is as follows:

[0008] A1: During the dredging pipeline welding process, obtain various welding parameter data at each moment;

[0009] A2: According to the distribution difference characteristics of all kinds of welding parameter data at each moment and other moments, the instantaneous welding difference coefficient at each moment is obtained; according to the similarity between various welding parameter data at all moments in the welding process and the instantaneous welding difference coefficient, combined with the distribution of extreme points in various welding parameter data, the asynchronous difference coefficient is obtained;

[0010] A3: Based on the asynchronous difference coefficient, the entire welding process is divided to obtain several asynchronous comparison intervals; an objective weighting method is used to obtain the comprehensive comparison score of each welding parameter data in each asynchronous comparison interval; by analyzing the comprehensive comparison score of each welding parameter data in all pairwise combinations of asynchronous comparison intervals and the similarity characteristics of data distribution, the asynchronous feedback significance value of each welding parameter data is obtained;

[0011] A4: Optimize and adjust the welding control based on the asynchronous feedback characteristics of each welding parameter data to obtain the dredged pipeline with preliminary welding completed;

[0012] The dredging pipe is butt-jointed with the flange using a hydraulic device, and a reinforcing rib plate is welded on the back of the flange to obtain the final welded dredging pipe.

[0013] Among them, during the dredging pipeline welding process, the welding current is 100A, the welding speed is 58cm / min, the argon gas flow rate during the welding process is 10L / min, and the angle between the welding gun and the pipeline surface is maintained between 70 and 80 degrees.

[0014] The process of obtaining the instantaneous welding difference coefficient at each moment is as follows:

[0015] The sequence of various welding parameter data in chronological order is used as each row vector in the matching feature matrix;

[0016] For each column vector in the matching feature matrix, the Manhattan distance between each column vector and each other column vector is calculated, and the mean of all the Manhattan distances is used as the instantaneous welding difference coefficient of each column vector at the corresponding moment.

[0017] Wherein, the step of obtaining the asynchronous difference coefficient is:

[0018] The normalized result of the Pearson correlation coefficient between various welding parameter data at all moments in the welding process and the instantaneous welding difference data is used as the matching difference consistency of various welding parameter data;

[0019] Analyze the extreme value variation characteristics of each welding parameter data during the welding process and obtain the variation mean of each welding parameter data;

[0020] The absolute value of the product of the matching difference consistency and the variation mean of each welding parameter data is calculated, and the cumulative sum of the absolute values ​​of the products of all welding parameter data is taken as the asynchronous difference coefficient.

[0021] The variation mean of each welding parameter data is obtained as follows:

[0022] For each welding parameter data, the extreme values ​​in the welding parameter data are obtained, and the sequence composed of all the extreme values ​​in chronological order is used as the interference interval data sequence of each welding parameter data. The mean of all elements in the first-order difference sequence of the interference interval data sequence is calculated and recorded as the variation mean of each welding parameter data.

[0023] The number of moments included in the asynchronous comparison interval is equal to the rounded-up value of the asynchronous difference coefficient.

[0024] The formula for obtaining the asynchronous feedback significance value of each welding parameter data is specifically: Among them, p x represents the asynchronous feedback significance value of the xth welding parameter data; p c,d represents the mean of the comprehensive comparison scores of the x-th welding parameter data in the c-th and d-th asynchronous comparison intervals; k x,c and k x,d represents the x-th welding parameter data in the c-th and d-th asynchronous comparison intervals respectively; h d (k x,c ,k x,d ) represents k x,c and k x,d The Hausdorff distance between them; m represents the number of asynchronous contrast intervals.

[0025] The process of optimizing and adjusting the welding control is as follows:

[0026] The normalized results of the asynchronous feedback significant values ​​of various welding parameter data are used as the adjustment variable p, combined with the initial proportional parameter P controlled by the welding parameter data o , and obtain the proportional parameter P after adjusting various welding parameter data. The formula is: P = P o +P o ×p;

[0027] The welding control is optimized and adjusted according to the proportional parameters adjusted according to various parameter data in combination with PID control.

[0028] Among them, the diameter of the flange is smaller than the diameter of the concentric circle of the dredging pipe, and the difference is within 1 mm.

[0029] In a second aspect, an embodiment of the present application further provides a wear-resistant dredging pipe welding process, wherein the welding process implements the steps of any one of the above-mentioned wear-resistant dredging pipe welding methods.

[0030] This application has at least the following beneficial effects:

[0031] This application takes into account that the welding parameters should be kept consistent during the welding process of the pipeline. If the welding parameters are asynchronously disordered, it will lead to defects such as welding failure and bubbles, making the shape and size of the molten pool unstable. Therefore, in the dredging pipeline welding process, various welding parameter data at each moment are obtained; according to the distribution difference characteristics of all kinds of welding parameter data at each moment and other moments, the instantaneous welding difference coefficient at each moment is obtained, which is helpful to characterize the difference in the change characteristics of the welding parameter data at different moments; according to the similarity between the various welding parameter data at all moments in the welding process and the instantaneous welding difference coefficient, combined with the distribution of extreme points in various welding parameter data, the asynchronous difference coefficient is obtained, which provides a basis for the subsequent accurate division of the time interval with asynchronous comparison characteristics in the welding process; by analyzing the comprehensive comparison score of each welding parameter data in all pairwise asynchronous comparison intervals and the similarity characteristics of data distribution, the asynchronous feedback significant value of each welding parameter data is obtained, and the asynchronous response deviation characteristics of each welding parameter data can be compared, and the automatic welding control system can be adjusted. Its beneficial effect is to fully combine the parameter matching feature differences in the welding process, accurately analyze the asynchronous response deviation of the welding process parameters, improve the control accuracy of the pipeline welding process, and achieve high-quality welding with high pipeline fit. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 A flowchart of a wear-resistant dredging pipeline welding method provided in one embodiment of the present application;

[0033] Figure 2 A schematic diagram of obtaining a significant value of asynchronous feedback provided by one embodiment of the present application;

[0034] Figure 3 A flow chart for optimizing and adjusting welding control is provided for one embodiment of the present application. DETAILED DESCRIPTION

[0035] In the description of the embodiments of the present application, words such as "exemplary", "or", "for example" and the like are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary", "or", "for example" and the like is intended to present related concepts in a concrete manner.

[0036] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art in the present application. The terms used in the specification of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application.

[0037] It should also be noted that the terms "first" and "second" in this application and the accompanying drawings are used to distinguish similar objects, rather than to describe a specific order or sequence. The method disclosed in the embodiments of the present application or the method shown in the flow chart includes one or more steps for implementing the method. Without departing from the scope of protection of the present application, the execution order of multiple steps can be interchanged with each other, and some steps can also be deleted.

[0038] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0039] The specific scheme of a wear-resistant dredging pipeline welding method and welding process provided by the present application is described in detail below with reference to the accompanying drawings.

[0040] See also Figure 1 , which shows a flow chart of steps of a wear-resistant dredging pipeline welding method provided by an embodiment of the present application, the method comprising:

[0041] The pipe made of Q355B steel plate has toughness but poor wear resistance, while the pipe made of high-strength wear-resistant steel plate has three times the wear resistance of Q355B steel plate, but poor toughness and easy to crack. Therefore, the material of the dredging pipe in this application includes at least Q355B steel plate and high-strength wear-resistant steel plate, which can have both toughness and high-strength wear resistance, while reducing procurement costs and improving work efficiency.

[0042] The first step is to optimize the welding control during the preliminary welding of the dredged pipeline.

[0043] Clean the oil, rust, oxide and other impurities within a range of at least 20 to 30 mm on the dredging pipe to be welded and on both sides, that is, polish with a stainless steel wire brush and sandpaper until the metallic luster is exposed. The reason for cleaning impurities is that impurities will reduce the bonding strength and wear resistance of the weld.

[0044] According to the set welding parameters, the pipeline is welded using submerged arc welding equipment, wherein the welding current is 100A, the welding speed is 58cm / min, the argon gas flow rate during the welding process is 10L / min, the angle between the welding gun and the pipeline surface is maintained between 70 and 80 degrees, and the welding process is controlled by an automatic welding control system. The specific welding control process is as follows:

[0045] A1: During the dredging pipeline welding process, various welding parameter data are obtained at each moment.

[0046] Normally, during the welding process, the automatic welding control system can maintain the stability of different welding parameters in the welding process to ensure the quality of welding; but due to the complexity of the environment in the actual welding process, the interference factors at different stages have different degrees of influence on the consistency deviation of the welding parameter data. Therefore, during the welding process, sensors are used to collect the welding parameter data in the welding process; specifically, current sensors, displacement sensors, flow sensors and angle sensors are used to collect the current data, welding speed data, argon gas flow data and the angle data between the welding gun and the pipe surface during the welding process, wherein the time interval for data collection is 0.1 seconds, which can be adjusted by the implementer according to the actual situation; each type of collected data is used as input, and a median filter is used to perform noise reduction processing on each type of collected data. It should be noted that the use of a median filter for noise reduction processing is a technology well known to those skilled in the art and will not be described in detail.

[0047] A2: According to the distribution difference characteristics of all kinds of welding parameter data at each moment and other moments, the instantaneous welding difference coefficient at each moment is obtained; according to the similarity between various welding parameter data at all moments in the welding process and the instantaneous welding difference coefficient, combined with the distribution of extreme points in various welding parameter data, the asynchronous difference coefficient is obtained.

[0048] In the welding operation of wear-resistant dredging pipelines, flanges are usually used to assemble and fix the pipelines to achieve uniform distribution of pipeline gaps and reduce the gaps at both ends of the pipelines. During the welding process, the welding direction and the stability of various welding parameters need to be controlled. Once the changes in welding parameters show asynchronous and disordered characteristics, it is very likely that the shape and size of the molten pool will lose stability during welding, which will cause defects such as incomplete welding and bubbles, seriously reducing the welding quality.

[0049] Traditional welding control methods often only make single adjustments to the deviation between the actual detection value and the preset value of each welding parameter, but ignore the matching relationship between the changes in welding parameters caused by different influencing factors during the actual welding process. For example, when the welding current shows asynchronous disorder characteristics, the heat output of the arc will increase, which will lead to a corresponding increase in the penetration depth and width of the weld. At this time, if the welding speed remains unchanged, excessive heat will cause the weld metal to overheat, which may cause coarse grains and deteriorate the structure, and have an adverse effect on the mechanical properties of the weld.

[0050] Based on the above analysis, in the welding process of wear-resistant dredging pipelines, the control of each welding parameter data should fully consider the matching influence relationship between different welding parameters, and combine the consistency change differences of the actual welding process to deeply analyze the asynchronous disorder characteristics of different welding parameters during the welding advancement process.

[0051] During the welding process, if the stability of the welding quality is to be maintained, the matching relationship between the numerical values ​​of the welding parameters at different times should be consistent; therefore, in order to further compare the matching state differences of the welding parameters at different times, for the various welding parameter data collected, the sequence of various welding parameter data in chronological order is used as each row in the matching feature matrix, that is, the matching feature matrix is ​​a matrix composed of all kinds of welding parameter data, and each row vector of the matching feature matrix is ​​arranged according to the current data, welding speed data, argon gas flow data and the angle data between the welding gun and the pipe surface; it should be noted that the implementer can adjust the arrangement method of the row vectors of the matching feature matrix according to the actual situation, and this application does not impose any restrictions on this.

[0052] During the welding process, if some of the parameters change due to environmental interference factors, the matching difference will not change significantly in a short time range; therefore, for each column of elements in the matching feature matrix, the Manhattan distance between each column of elements and each other column of elements is calculated, and the mean of all the Manhattan distances is used as the instantaneous welding difference coefficient of each column of elements. The instantaneous welding difference coefficient reflects the difference in matching status of welding parameters at different times compared to the overall welding process.

[0053] Furthermore, a sequence of instantaneous welding difference coefficients corresponding to all moments in chronological order is taken as a welding difference coefficient sequence; if the change of one welding parameter data affected by interference is consistent with the change of other welding parameter matching characteristics, the asynchronous disorder characteristics of this welding parameter data are more significant; therefore, for each welding parameter data in the welding process, the Pearson correlation coefficient between the welding parameter data and the welding difference data sequence is calculated, and the larger the Pearson correlation coefficient, the stronger the consistency between the data change characteristics in the welding parameter data time series and the matching state change characteristics between multiple parameters; the Pearson correlation coefficients corresponding to all kinds of welding parameter data are taken as input, and the Softmax function is used to obtain the normalized results of the Pearson correlation coefficients corresponding to each welding parameter data, and the matching difference consistency of various welding parameter data is obtained, and the normalized result reflects the relative characteristics of the consistency of each welding parameter data compared with the matching relationship difference among all welding parameters.

[0054] Furthermore, the analysis intervals of the asynchronous characteristics in the welding process are divided by the relative characteristics of the consistency of the welding parameter data compared to the matching relationship difference; specifically, for each welding parameter data, the extreme values ​​in the welding parameter data at all times are obtained, and the sequence composed of all the extreme values ​​in chronological order is used as the interference interval data sequence of each welding parameter data, and the mean of all elements in the first-order difference sequence of the interference interval data sequence is calculated, which is recorded as the variation mean of each welding parameter data; the variation mean reflects the fluctuation range of the response changes of the welding parameter data in different stages.

[0055] Based on the analysis results of the stage response variation range of each welding parameter data and the consistency difference compared with the welding parameter matching feature difference, the asynchronous difference coefficient is obtained. The specific calculation relationship is: Where h represents the asynchronous difference coefficient in the dredging pipeline welding control process; a x represents the matching difference consistency of the xth welding parameter data, b x represents the mean variation of the x-th welding parameter data; n represents the number of types of welding parameter data; the larger the asynchronous difference coefficient, the more significant the interference effect of different welding parameters will become over time during the welding process; that is, the asynchronous characteristics of the welding parameters show obvious differences over a longer time range.

[0056] A3: Based on the asynchronous difference coefficient, the entire welding process is divided to obtain several asynchronous comparison intervals; the entropy weight method is used to obtain the comprehensive comparison score of each welding parameter data in each asynchronous comparison interval; by analyzing the comprehensive comparison score of each welding parameter data in all pairwise combinations of asynchronous comparison intervals and the similarity characteristics of data distribution, the asynchronous feedback significance value of each welding parameter data is obtained.

[0057] Based on the asynchronous difference coefficient, the time interval of the welding parameter data obtained in the current welding process is evenly divided, wherein the number of moments corresponding to each divided time interval is equal to the upward integer value of the asynchronous difference coefficient, and each divided time interval is used as an asynchronous comparison interval. It should be noted that the number of moments corresponding to the last time interval may be less than the upward integer value of the asynchronous difference coefficient. The purpose of interval division based on the asynchronous difference coefficient is to consider the influence of different interference factors in the welding process, and the differences in the asynchronous response interval ranges between the welding parameters. If the comparison is performed within an interval that is too small or too large, it is impossible to accurately analyze the matching characteristic relationship between the responses of the welding parameters.

[0058] Therefore, each type of welding parameter data is divided according to the divided asynchronous comparison interval. Specifically, for each type of welding parameter data, the elements of the welding parameter data in each asynchronous comparison interval are organized into a set in chronological order as the asynchronous comparison sequence of the welding parameter data. The asynchronous comparison sequences of all types of parameter data in the same asynchronous comparison interval are taken as input, and the topsis algorithm based on the entropy weight method is used for multidimensional data comparison. Specifically, the standard deviation of each asynchronous comparison sequence is used as a very small indicator, and the entropy weight method is used to obtain the weight of each welding parameter data, and the comprehensive comparison score of each welding parameter data in the asynchronous comparison interval is output. The comprehensive comparison score reflects the significant characteristics of the asynchronous response of each parameter data of the pipeline compared with other parameters; the asynchronous feedback significance value of each welding parameter data is calculated based on the comprehensive comparison score, and the specific calculation relationship is: Among them, p x represents the asynchronous feedback significance value of the xth welding parameter data; p c,d represents the mean of the comprehensive comparison scores of the x-th welding parameter data in the c-th and d-th asynchronous comparison intervals; k x,c and k x,d They represent the asynchronous comparison sequence of the x-th welding parameter data in the c-th and d-th asynchronous comparison intervals, that is, the x-th welding parameter data in the c-th and d-th asynchronous comparison intervals; hd(k x,c ,k x,d ) represents k x,c and k x,d The Hausdorff distance between them; m represents the number of asynchronous comparison intervals; the larger the calculated asynchronous feedback significance value is, the more significant the difference in the matching characteristics of the welding parameter data caused by interference factors during the welding process is compared with other parameters, that is, the greater the possibility of asynchronous deviation.

[0059] The schematic diagram of obtaining the asynchronous feedback saliency value is as follows: Figure 2 shown.

[0060] A4: Based on the asynchronous feedback characteristics of each welding parameter data, the welding control is optimized and adjusted to obtain the dredged pipeline with preliminary welding completed.

[0061] If the asynchronous feedback characteristics are more significant, it means that the welding parameters are more likely to have continuous asynchronous characteristics due to interference during the welding process, that is, there may be asynchronous deviations in the welding control process, resulting in an offset in the welding control; therefore, the welding control is optimized and adjusted based on the asynchronous feedback characteristics of each welding parameter during the welding process.

[0062] Specifically, the automatic welding control system is used to control the dredging pipeline welding process mainly through a programmable logic controller (PLC), wherein the feedback control for each welding parameter is realized by a PID control algorithm; the asynchronous feedback significance value calculated from all kinds of welding parameter data collected up to the current moment is used as input, and the normalized results of all asynchronous feedback significance values ​​are obtained by using a Z-score normalization algorithm, recorded as a regulating variable, and the control parameters of the PID response are adjusted. Specifically, the adjustment method of the control parameters of the PID response for one of the welding parameters is as follows: P x =P o +P o ×p x , where P x represents the proportional parameter adjusted for the xth welding parameter data, P o is the initial proportional parameter controlled by the xth welding parameter data, and the initial proportional parameter is determined by the attenuation curve method; p x The adjustment variable representing the xth welding parameter data is thus obtained by adjusting the control parameters in the automatic welding control system based on the input adjustment variables in the above manner to obtain the dredged pipeline that has been preliminarily welded.

[0063] Among them, the flow chart for optimizing and adjusting welding control is as follows Figure 3 shown.

[0064] The second step: use a hydraulic device to connect the dredging pipe to the flange, weld a reinforcing rib plate on the back of the flange, and obtain the final welded dredging pipe.

[0065] Aim the pressure head of the prepared low-pressure hydraulic device at one end of the dredging pipeline, slowly start the hydraulic device, make the pressure act evenly on the pipeline, dock the end of the pipeline to the flange, and gradually press the pipeline port into the flange with a certain pressure. During the pressing process, ensure that the pipeline axis is consistent with the flange axis to prevent deviation or tilt. The pressure should be controlled at 13MPa to avoid deformation and damage of the pipeline or flange due to excessive pressure, and the pressure can be adjusted according to factors such as pipeline material, specifications and flange model. When the pipeline is completely pressed into the flange and reaches the predetermined position, maintain the pressure for 10 minutes to make the pipeline and flange fully fit, and then slowly release the pressure of the hydraulic device to complete the installation of the pipeline flange, so that the welding gap is more uniform, and the concentricity of the pipeline is controlled at 10mm, which improves the stability and uniformity of the pipeline system.

[0066] It should be noted that the diameter of the flange should be smaller than the diameter of the concentric circle of the pipe, and the difference should be within 1 mm. The value of this embodiment is 1 mm; the diameter of the flange is smaller than the diameter of the concentric circle of the pipe, which helps to ensure that the end of the pipe can be more tightly connected to the flange. The back of the flange is welded by submerged arc welding to ensure its connection strength and sealing. Before submerged arc welding, the welding surface of the flange and the pipe is thoroughly cleaned and pretreated to remove impurities such as oil stains and oxide scale to ensure the welding quality. The reinforcing ribs are evenly welded on the back of the flange. The thickness, height and number of the ribs are determined according to factors such as the diameter of the pipeline, the pressure level and the operating conditions. The thickness of the ribs is 5 to 10 mm, and the height is 0.6 to 0.8 times the thickness of the flange. The welding of the ribs and the flange adopts a continuous fillet weld, and the weld height is not less than 0.7 times the thickness of the ribs.

[0067] At this point, the welding of the dredging pipeline is completed, and the final welded dredging pipeline is obtained.

[0068] Based on the same inventive concept as the above method, an embodiment of the present application further provides a wear-resistant dredging pipe welding process, and the welding process implements the steps of any one of the above-mentioned wear-resistant dredging pipe welding methods.

[0069] In summary, considering the welding process of pipelines, the welding parameters should be kept consistent. If the welding parameters are asynchronously disordered, it will lead to defects such as welding failure and bubbles, making the shape and size of the molten pool unstable. Therefore, in the dredging pipeline welding process, various welding parameter data at each moment are obtained; according to the distribution difference characteristics of all kinds of welding parameter data at each moment and other moments, the instantaneous welding difference coefficient at each moment is obtained, which is helpful to characterize the difference in the change characteristics of welding parameter data at different moments; according to the similarity between various welding parameter data at all moments in the welding process and the instantaneous welding difference coefficient, combined with the distribution of extreme points in various welding parameter data, the asynchronous difference coefficient is obtained, which provides a basis for the subsequent accurate division of time intervals with asynchronous contrast characteristics in the welding process; by analyzing the comprehensive comparison score of each welding parameter data in all pairwise asynchronous comparison intervals and the similarity characteristics of data distribution, the asynchronous feedback significance value of each welding parameter data is obtained, and the asynchronous response deviation characteristics of each welding parameter data can be compared, and the automatic welding control system can be adjusted. Its beneficial effect is to fully combine the parameter matching feature differences in the welding process, accurately analyze the asynchronous response deviation of the welding process parameters, improve the control accuracy of the pipeline welding process, and achieve high-quality welding with high pipeline fit.

[0070] The flowchart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to the embodiment of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of a code contains one or more executable instructions for realizing the specified logical function. In some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two continuous boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. In the description corresponding to the flowchart and block diagram in the accompanying drawings, the operations or steps corresponding to different boxes can also occur in a different order from the order disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two continuous operations or steps can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. Each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented by a dedicated hardware-based system that performs the specified functions or actions, or may be implemented by a combination of dedicated hardware and computer instructions.

[0071] For those skilled in the art, it is obvious that the present application is not limited to the details of the above exemplary embodiments, and the present application can be implemented in other specific forms without departing from the basic features of the present application. Therefore, no matter from which point of view, the above embodiments of the present application should be regarded as exemplary and non-restrictive; the technical solutions recorded in the above embodiments are modified, or some of the technical features are replaced by equivalents, which does not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application.

Claims

1. A wear-resistant dredging pipeline welding method, characterized in that: The method comprises the following steps: During the preliminary welding of the dredged pipeline, the welding control was optimized and adjusted; The specific process of optimizing and adjusting the welding control is as follows: A1: During the dredging pipeline welding process, obtain various welding parameter data at each moment; A2: According to the distribution difference characteristics of all kinds of welding parameter data at each moment and other moments, the instantaneous welding difference coefficient at each moment is obtained; according to the similarity between various welding parameter data at all moments in the welding process and the instantaneous welding difference coefficient, combined with the distribution of extreme points in various welding parameter data, the asynchronous difference coefficient is obtained; A3: Based on the asynchronous difference coefficient, the entire welding process is divided to obtain several asynchronous comparison intervals; an objective weighting method is used to obtain the comprehensive comparison score of each welding parameter data in each asynchronous comparison interval; by analyzing the comprehensive comparison score of each welding parameter data in all pairwise combinations of asynchronous comparison intervals and the similarity characteristics of data distribution, the asynchronous feedback significance value of each welding parameter data is obtained; A4: Optimize and adjust the welding control based on the asynchronous feedback characteristics of each welding parameter data to obtain the dredged pipeline with preliminary welding completed; The dredging pipe is butt-jointed with the flange using a hydraulic device, and a reinforcing rib plate is welded on the back of the flange to obtain the final welded dredging pipe.

2. A wear-resistant dredging pipeline welding method as claimed in claim 1, characterized in that: During the dredging pipeline welding process, the welding current was 100A, the welding speed was 58cm / min, the argon gas flow rate during the welding process was 10L / min, and the angle between the welding gun and the pipeline surface was maintained between 70 and 80 degrees.

3. A wear-resistant dredging pipeline welding method as claimed in claim 1, characterized in that: The process of obtaining the instantaneous welding difference coefficient at each moment is as follows: The sequence of various welding parameter data in chronological order is used as each row vector in the matching feature matrix; For each column vector in the matching feature matrix, the Manhattan distance between each column vector and each other column vector is calculated, and the mean of all the Manhattan distances is used as the instantaneous welding difference coefficient of each column vector at the corresponding moment.

4. A wear-resistant dredging pipeline welding method as claimed in claim 1, characterized in that: The steps of obtaining the asynchronous difference coefficient are: The normalized result of the Pearson correlation coefficient between various welding parameter data at all moments in the welding process and the instantaneous welding difference data is used as the matching difference consistency of various welding parameter data; Analyze the extreme value variation characteristics of each welding parameter data during the welding process and obtain the variation mean of each welding parameter data; The absolute value of the product of the matching difference consistency and the variation mean of each welding parameter data is calculated, and the cumulative sum of the absolute values ​​of the products of all welding parameter data is taken as the asynchronous difference coefficient.

5. A wear-resistant dredging pipeline welding method as claimed in claim 4, characterized in that: The variation mean of each welding parameter data is obtained as follows: For each welding parameter data, the extreme values ​​in the welding parameter data are obtained, and the sequence composed of all the extreme values ​​in chronological order is used as the interference interval data sequence of each welding parameter data. The mean of all elements in the first-order difference sequence of the interference interval data sequence is calculated and recorded as the variation mean of each welding parameter data.

6. A wear-resistant dredging pipeline welding method as claimed in claim 1, characterized in that: The number of moments included in the asynchronous comparison interval is equal to the rounded-up value of the asynchronous difference coefficient.

7. A wear-resistant dredging pipeline welding method as claimed in claim 1, characterized in that: The formula for obtaining the asynchronous feedback significance value of each welding parameter data is specifically: Among them, p x represents the asynchronous feedback significance value of the xth welding parameter data; p c,d represents the mean of the comprehensive comparison scores of the x-th welding parameter data in the c-th and d-th asynchronous comparison intervals; k x,c and k x,d represents the xth welding parameter data in the cth and dth asynchronous comparison intervals respectively; hd(k x,c ,k x,d ) represents k x,c and k x,d The Hausdorff distance between them; m represents the number of asynchronous contrast intervals.

8. A wear-resistant dredging pipeline welding method as claimed in claim 1, characterized in that: The process of optimizing and adjusting the welding control is as follows: The normalized results of the asynchronous feedback significant values ​​of various welding parameter data are used as the adjustment variable p, combined with the initial proportional parameter P controlled by the welding parameter data o , and obtain the proportional parameter P after adjusting various welding parameter data. The formula is: P = P o +P o ×p; The welding control is optimized and adjusted according to the proportional parameters adjusted according to various parameter data in combination with PID control.

9. A wear-resistant dredging pipeline welding method as claimed in claim 1, characterized in that: The diameter of the flange is smaller than the diameter of the concentric circle of the dredging pipe, and the difference is within 1 mm.

10. A wear-resistant dredging pipeline welding process, characterized in that: The welding process implements the steps of a wear-resistant dredging pipeline welding method as described in any one of claims 1-9.

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