CN112528531A - Pipeline weld quality determination method, device, equipment and storage medium - Google Patents
Pipeline weld quality determination method, device, equipment and storage medium Download PDFInfo
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Abstract
本发明实施例提供一种管道焊缝质量确定方法、装置、设备及存储介质，具体实现方案为：该方法包括：获取目标管道焊缝材料的目标载荷位移曲线以及预存于数据库中的焊缝本构参数；将焊缝本构参数输入预设的有限元仿真模型，以得到参考载荷位移曲线；根据目标载荷位移曲线和参考载荷位移曲线确定焊缝质量参数，根据焊缝质量参数确定目标管道焊缝质量，并输出目标管道焊缝质量。本发明实施例的管道焊缝质量确定方法，根据目标载荷位移曲线和参考载荷位移曲线即可以确定焊缝质量参数，提高了焊缝质量参数的准确性。同时，根据焊缝质量参数确定的目标管道焊缝质量也更为准确，从而提高了确定管道焊缝质量的准确性。
The embodiments of the present invention provide a method, device, equipment and storage medium for determining the quality of a pipeline weld. The specific implementation scheme is as follows: the method includes: acquiring a target load displacement curve of a target pipeline weld material and a weld book pre-stored in a database. Input the weld constitutive parameters into the preset finite element simulation model to obtain the reference load-displacement curve; determine the weld quality parameters according to the target load-displacement curve and the reference load-displacement curve, and determine the target pipeline weld according to the weld quality parameters seam quality, and output the target pipe weld quality. In the method for determining the quality of the pipeline weld in the embodiment of the present invention, the quality parameter of the weld can be determined according to the target load-displacement curve and the reference load-displacement curve, which improves the accuracy of the quality parameter of the weld. At the same time, the target pipeline weld quality determined according to the weld quality parameters is also more accurate, thereby improving the accuracy of determining the pipeline weld quality.
Description
Technical Field
The embodiment of the invention relates to the technical field of oil and gas resource transmission, in particular to a method, a device, equipment and a storage medium for determining the quality of a pipeline weld joint.
Background
With the continuous development of science and technology, the demand of oil and gas resources increases at a faster and faster speed, and the safe transportation of the oil and gas resources becomes more and more important. The buried pipeline as one of the lifeline projects is responsible for the main transportation task of oil and gas resources, and provides important energy guarantee for the economic development of the whole society. However, as most of the oil and gas production areas are far away from the oil and gas demand areas, pipelines face a plurality of complex natural environment threats in the oil and gas outward transportation process.
The long-distance oil and gas pipelines used for long-distance oil and gas transportation are generally formed by connecting in a welding mode, quality problems easily occur to pipeline welding seams after time washing under a complex natural environment, and once the quality problems occur to the pipeline welding seams, important consequences can be caused.
Aiming at the quality problem of the pipeline welding seam, the mode of determining the quality of the pipeline at present is often determined through manual experience, however, the mode of determining the quality problem of the pipeline welding seam through manual experience is easy to generate larger errors, and the accuracy is lower.
Disclosure of Invention
The invention provides a method, a device, equipment and a storage medium for determining the quality of a pipeline weld joint, which are used for solving the problems that the quality of the pipeline weld joint is determined through manual experience at present, so that large errors are easy to generate and the accuracy is low.
The first aspect of the embodiments of the present invention provides a method for determining quality of a weld joint of a pipeline, including:
acquiring a target load displacement curve of a target pipeline welding seam material and welding seam constitutive parameters prestored in a database;
inputting the welding seam constitutive parameters into a preset finite element simulation model to obtain a reference load displacement curve;
and determining a weld quality parameter according to the target load displacement curve and the reference load displacement curve, determining the weld quality of a target pipeline according to the weld quality parameter, and outputting the weld quality of the target pipeline.
Further, the method as described above, the weld constitutive parameters include: maximum principal strain and fracture energy.
Further, the method as described above, the weld constitutive parameters are a plurality of pairs of weld constitutive parameters consisting of a maximum principal strain and a fracture energy;
inputting the welding seam constitutive parameters into a preset finite element simulation model to obtain a reference load displacement curve, wherein the method comprises the following steps:
inputting a plurality of welding seam constitutive parameter pairs into a preset finite element simulation model so as to generate a reference load displacement curve through the preset finite element simulation model;
and outputting the reference load displacement curve through the preset finite element simulation model.
Further, the method as described above, after inputting the weld constitutive parameters into a preset finite element simulation model to obtain a reference load displacement curve, further includes:
and constructing a mapping relation between the welding seam constitutive parameter pair and displacement data and/or load data in a reference load displacement curve through a neural network algorithm.
Further, the method for determining the weld quality parameter according to the target load displacement curve and the reference load displacement curve comprises:
selecting a plurality of key point load data from the target load displacement curve and the reference load displacement curve respectively;
obtaining an error curve according to the load data of the key point of the target load displacement curve and the load data of the corresponding key point in the reference load displacement curve;
and determining the corresponding welding seam constitutive parameter pair when the error value of the key point load data in the error curve is minimum as a welding seam quality parameter.
Further, as the method described above, before determining the corresponding weld constitutive parameter pair when the error value of the key point load data in the error curve is the minimum as the weld quality parameter, the method further includes:
and determining the minimum error value in the error curve according to a preset relative mean square error formula.
Further, the method as described above, after outputting the target pipe weld quality, further comprising:
judging whether the target pipeline weld joint belongs to a preset quality difference interval or not according to the quality of the target pipeline weld joint;
and if the numerical value of the target pipeline welding seam quality accords with the poor quality interval, sending an early warning message to early warning equipment.
A second aspect of an embodiment of the present invention provides a device for determining a weld quality of a pipeline, including:
the acquisition module is used for acquiring a target load displacement curve of a target pipeline welding seam material and welding seam constitutive parameters prestored in a database;
the reference curve generation module is used for inputting the welding seam constitutive parameters into a preset finite element simulation model so as to obtain a reference load displacement curve;
and the welding seam quality determining module is used for determining welding seam quality parameters according to the target load displacement curve and the reference load displacement curve, determining the welding seam quality of the target pipeline according to the welding seam quality parameters, and outputting the welding seam quality of the target pipeline.
Further, in the apparatus as described above, the weld constitutive parameters include: maximum principal strain and fracture energy.
Further, in the apparatus as described above, the weld constitutive parameters are a plurality of pairs of weld constitutive parameters consisting of maximum principal strain and fracture energy;
the reference curve generation module is specifically configured to:
inputting a plurality of welding seam constitutive parameter pairs into a preset finite element simulation model so as to generate a reference load displacement curve through the preset finite element simulation model; and outputting the reference load displacement curve through the preset finite element simulation model.
Further, the apparatus as described above, further comprising:
and the mapping module is used for constructing a mapping relation between the welding seam constitutive parameter pair and displacement data and/or load data in a reference load displacement curve through a neural network algorithm.
Further, in the above apparatus, when determining the weld quality parameter according to the target load displacement curve and the reference load displacement curve, the weld quality determination module is specifically configured to:
selecting a plurality of key point load data from the target load displacement curve and the reference load displacement curve respectively;
obtaining an error curve according to the load data of the key point of the target load displacement curve and the load data of the corresponding key point in the reference load displacement curve;
and determining the corresponding welding seam constitutive parameter pair when the error value of the key point load data in the error curve is minimum as a welding seam quality parameter.
Further, the apparatus as described above, the apparatus further comprising:
and the error determining module is used for determining the minimum error value in the error curve according to a preset relative mean square error formula.
Further, the apparatus as described above, further comprising:
the early warning module is used for judging whether the target pipeline weld joint belongs to a preset quality difference interval or not according to the quality of the target pipeline weld joint; and if the numerical value of the target pipeline welding seam quality accords with the poor quality interval, sending an early warning message to early warning equipment.
A third aspect of an embodiment of the present invention provides a device for determining quality of a weld of a pipeline, including: a memory, a processor;
a memory; a memory for storing the processor-executable instructions;
wherein the processor is configured to execute the method of determining pipe weld quality of any of the first aspects by the processor.
A fourth aspect of the embodiments of the present invention provides a computer-readable storage medium, in which computer-executable instructions are stored, and when the computer-executable instructions are executed by a processor, the computer-executable instructions are used to implement the method for determining the quality of the weld of the pipe according to any one of the first aspect.
The embodiment of the invention provides a method, a device, equipment and a storage medium for determining the quality of a pipeline weld joint, wherein the method comprises the following steps: acquiring a target load displacement curve of a target pipeline welding seam material and welding seam constitutive parameters prestored in a database; inputting the welding seam constitutive parameters into a preset finite element simulation model to obtain a reference load displacement curve; and determining a weld quality parameter according to the target load displacement curve and the reference load displacement curve, determining the weld quality of a target pipeline according to the weld quality parameter, and outputting the weld quality of the target pipeline. According to the method for determining the quality of the pipeline welding seam, the reference load displacement curve is obtained by obtaining the target load displacement curve of the target pipeline welding seam material and the welding seam constitutive parameters prestored in the database, and then the welding seam constitutive parameters are input into a preset finite element simulation model. Because the target load displacement curve is related to the target pipeline welding seam material, the reference load displacement curve is related to the constitutive parameters of the welding seam for reference, the welding seam quality parameters can be determined according to the target load displacement curve and the reference load displacement curve, and the accuracy of the welding seam quality parameters is improved. Meanwhile, the target pipeline welding seam quality determined according to the welding seam quality parameters is more accurate, so that the accuracy of determining the pipeline welding seam quality is improved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
FIG. 1 is a scene diagram of a method for determining the weld quality of a pipeline, in which embodiments of the present invention may be implemented;
FIG. 2 is a schematic flow chart of a method for determining the weld quality of a pipeline according to an embodiment of the present invention;
FIG. 3 is a schematic flow chart of a method for determining the weld quality of a pipeline according to another embodiment of the present invention;
FIG. 4 is a schematic structural diagram of a device for determining the weld quality of a pipeline according to an embodiment of the present invention;
FIG. 5 is a schematic structural diagram of a device for determining the weld quality of a pipeline according to another embodiment of the present invention;
fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
With the above figures, certain embodiments of the invention have been illustrated and described in more detail below. The drawings and the description are not intended to limit the scope of the inventive concept in any way, but rather to illustrate it by those skilled in the art with reference to specific embodiments.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the invention, as detailed in the appended claims.
The technical solution of the present invention will be described in detail below with specific examples. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present invention will be described below with reference to the accompanying drawings.
For a clear understanding of the technical solutions of the present application, a detailed description of the prior art solutions is first provided. The long-distance oil and gas pipelines used for long-distance oil and gas transportation are generally formed by connecting in a welding mode, quality problems easily occur to pipeline welding seams after time washing under a complex natural environment, and once the quality problems occur to the pipeline welding seams, important consequences can be caused. At present, aiming at the quality problem of the pipeline welding seam, the quality parameter of the pipeline welding seam is mainly determined through manual experience, and then the quality problem of the pipeline welding seam is determined according to the quality parameter of the pipeline welding seam. In such a mode, people with abundant experience for many years are required to determine the quality parameters of the pipeline welding seam through self experience, a large amount of manpower is consumed, and meanwhile, the determined quality parameters of the pipeline welding seam are not matched with the corresponding pipeline welding seam condition, so that a large error is easily generated, and the accuracy is low.
Therefore, the inventor finds that, in order to avoid the problem that a large error is easily generated in the current quality determination method, the accuracy is low in research aiming at the technical problem of the quality of the pipeline welding seam in the prior art. The welding seam constitutive parameters can be input into a preset finite element simulation model to obtain a reference load displacement curve. And determining the quality parameter of the welding seam according to the target load displacement curve and the reference load displacement curve, and determining the quality of the welding seam of the target pipeline according to the quality parameter of the welding seam, so that the accuracy of the quality of the welding seam of the target pipeline can be improved through the target load displacement curve and the reference load displacement curve with higher accuracy.
The inventor proposes a technical scheme of the application based on the creative discovery.
An application scenario of the method for determining the quality of the weld joint of the pipeline provided by the embodiment of the invention is described below. As shown in fig. 1, 1 is a first electronic device, 2 is a second electronic device, and 3 is a third electronic device. The network architecture of the application scene corresponding to the method for determining the quality of the pipeline weld joint, provided by the embodiment of the invention, comprises the following steps: a first electronic device 1, a second electronic device 2 and a third electronic device 3. The second electronic device 2 stores a target load displacement curve of a target pipeline weld material and a weld constitutive parameter in advance, wherein the weld constitutive parameter corresponds to the target pipeline weld material. The first electronic device 1 obtains a target load displacement curve and a weld constitutive parameter of a target pipeline weld material sent by the second electronic device 2. And then inputting the constitutive parameters of the welding seam into a preset finite element simulation model to obtain a reference load displacement curve. And determining the quality parameters of the welding seam according to the target load displacement curve and the reference load displacement curve. And then, determining the weld quality of the target pipeline according to the weld quality parameters. And finally, outputting the weld quality of the target pipeline to the third electronic device 3, and performing subsequent related processing according to the weld quality of the target pipeline through the third electronic device 3, for example, generating a corresponding target pipeline maintenance scheme according to the weld quality of the target pipeline, and for example, performing timing analysis, early warning processing and the like according to the weld quality of the target pipeline. Therefore, the target pipeline welding seam quality obtained through the more accurate target load displacement curve and the reference load displacement curve is higher in accuracy compared with a manual experience mode.
According to the method for determining the quality of the pipeline welding seam, provided by the embodiment of the invention, the reference load displacement curve is obtained by obtaining the target load displacement curve of the target pipeline welding seam material and the welding seam constitutive parameters prestored in the database and then inputting the welding seam constitutive parameters into a preset finite element simulation model. Because the target load displacement curve is related to the target pipeline welding seam material, the reference load displacement curve is related to the constitutive parameters of the welding seam for reference, the welding seam quality parameters can be determined according to the target load displacement curve and the reference load displacement curve, and the accuracy of the welding seam quality parameters is improved. Meanwhile, the target pipeline welding seam quality determined according to the welding seam quality parameters is more accurate, so that the accuracy of determining the pipeline welding seam quality is improved.
The embodiments of the present invention will be described with reference to the accompanying drawings.
Fig. 2 is a schematic flow chart of a method for determining a pipe weld quality according to an embodiment of the present invention, and as shown in fig. 2, in this embodiment, an execution subject of the embodiment of the present invention is a pipe weld quality determining device, and the pipe weld quality determining device may be integrated in an electronic device. The method for determining the quality of the welding seam of the pipeline provided by the embodiment comprises the following steps:
and S101, acquiring a target load displacement curve of a target pipeline welding seam material and welding seam constitutive parameters prestored in a database.
First, in this embodiment, a target load displacement curve of a target pipeline weld material may be obtained by a three-point bending experimental instrument, or may be obtained by a preset database, which is not limited in this embodiment.
In this embodiment, the target load displacement curve is a load displacement curve of a target pipeline weld material, and the weld constitutive parameter is a parameter corresponding to the target pipeline weld material. Different pipeline weld joint materials correspond to different weld joint constitutive parameters. Meanwhile, the weld constitutive parameters can be a better set of each weld constitutive parameter in the historical weld quality determination process, and are prestored in a database.
And S102, inputting the constitutive parameters of the welding seam into a preset finite element simulation model to obtain a reference load displacement curve.
In this embodiment, the input end of the preset finite element simulation model is the weld constitutive parameter, the output end is the corresponding reference load displacement curve, and the output reference load displacement curve also changes correspondingly with the change of the weld constitutive parameter.
In the embodiment, the corresponding reference load displacement curve can be generated through a plurality of groups of welding seam constitutive parameters, and the accuracy of subsequent determination of the welding seam quality parameters can be improved through a plurality of data optimization modes.
And S103, determining a weld quality parameter according to the target load displacement curve and the reference load displacement curve, determining the weld quality of the target pipeline according to the weld quality parameter, and outputting the weld quality of the target pipeline.
In this embodiment, the reference load displacement curve corresponds to the constitutive parameters of the weld, and the constitutive parameters of the weld are related to the quality of the weld of the pipeline. The welding seam constitutive parameters comprise maximum principal strain and fracture energy, and the two parameters are related to the fracture and fission degree of the welding seam of the pipeline, so that a more accurate reference load displacement curve can be obtained according to the welding seam constitutive parameters, more accurate welding seam quality parameters are determined according to the target load displacement curve and the reference load displacement curve, and the accuracy of determining the welding seam quality of the target pipeline is further improved.
In this embodiment, the quality of the output target pipeline weld joint may be generated by a user or other electronic devices to generate a quality maintenance scheme for the target pipeline, or the user may be prompted to maintain the target pipeline weld joint in advance by an early warning mode when the quality of the target pipeline weld joint is poor by an early warning device, so as to avoid serious consequences.
According to the method for determining the quality of the pipeline welding seam, provided by the embodiment of the invention, a target load displacement curve of a target pipeline welding seam material and welding seam constitutive parameters prestored in a database are obtained. And inputting the constitutive parameters of the welding seam into a preset finite element simulation model to obtain a reference load displacement curve. And determining the quality parameter of the welding seam according to the target load displacement curve and the reference load displacement curve, determining the quality of the welding seam of the target pipeline according to the quality parameter of the welding seam, and outputting the quality of the welding seam of the target pipeline. According to the method for determining the quality of the pipeline welding seam, the reference load displacement curve is obtained by obtaining the target load displacement curve of the target pipeline welding seam material and the welding seam constitutive parameters prestored in the database, and then the welding seam constitutive parameters are input into a preset finite element simulation model. Because the target load displacement curve is related to the target pipeline welding seam material, the reference load displacement curve is related to the constitutive parameters of the welding seam for reference, the welding seam quality parameters can be determined according to the target load displacement curve and the reference load displacement curve, and the accuracy of the welding seam quality parameters is improved. Meanwhile, the target pipeline welding seam quality determined according to the welding seam quality parameters is more accurate, so that the accuracy of determining the pipeline welding seam quality is improved.
Fig. 3 is a schematic flow chart of a method for determining the quality of a weld joint of a pipeline according to another embodiment of the present invention, and as shown in fig. 3, the method for determining the quality of a weld joint of a pipeline according to the present embodiment is further detailed in the steps based on the method for determining the quality of a weld joint of a pipeline according to the previous embodiment of the present invention. The method for determining the quality of the weld joint of the pipeline provided by the embodiment comprises the following steps.
Step S201, a target load displacement curve of a target pipeline welding seam material and welding seam constitutive parameters prestored in a database are obtained.
In this embodiment, the implementation manner of step 201 is similar to that of step 101 in the previous embodiment of the present invention, and is not described in detail here.
Wherein step 202 is a further refinement of step 102.
Optionally, in this embodiment, the weld constitutive parameters include: maximum principal strain and fracture energy. Meanwhile, the weld constitutive parameters are a plurality of weld constitutive parameter pairs consisting of maximum principal strain and fracture energy.
In this example, the fracture energy: the energy, defined as the energy required to generate a unit area of fracture, is one of the damage parameters that can characterize the fracture propagation. Maximum principal strain: when any point on the plane is simultaneously acted by forces in several directions, each direction generates certain strain, wherein the strain generated by the maximum force is the maximum main strain which is used as the initiation control standard and the crack propagation direction determination criterion.
In this embodiment, the weld constitutive parameters are a plurality of weld constitutive parameter pairs formed by the maximum principal strain and the fracture energy, wherein the plurality of weld constitutive parameters may be 5, 6 or other numbers, and may be set according to actual requirements, which is not limited in this embodiment.
Each weld constitutive parameter pair may include values for both the maximum principal strain and the energy to break. Such as maximum principal strain a and fracture energy a, maximum principal strain B and fracture energy B, maximum principal strain C and fracture energy C.
Step S202, inputting the plurality of welding seam constitutive parameter pairs into a preset finite element simulation model so as to generate a reference load displacement curve through the preset finite element simulation model. And meanwhile, outputting a reference load displacement curve through a preset finite element simulation model.
In this embodiment, a plurality of welding seam constitutive parameter pairs are all input into a preset finite element simulation model, so that a corresponding reference load displacement curve can be generated, and the load data on the reference load displacement curve and the welding seam constitutive parameter pairs have a corresponding relationship. Therefore, a foundation is provided for subsequently calculating the lowest error value of the key point data between the target load displacement curve and the reference load displacement curve so as to obtain the corresponding welding seam constitutive parameter pair.
And S203, constructing a mapping relation between the welding seam constitutive parameter pair and displacement data and/or load data in the reference load displacement curve through a neural network algorithm.
In this embodiment, the mapping relationship between the welding seam constitutive parameter pair and the displacement data and/or the load data in the reference load displacement curve is established through the neural network algorithm, so that the mapping efficiency between the welding seam constitutive parameter pair and the displacement data and/or the load data in the reference load displacement curve can be improved, and the overall efficiency is improved.
Step S204, a plurality of key point load data are respectively selected from the target load displacement curve and the reference load displacement curve.
In this embodiment, the target load displacement curve and the reference load displacement curve include load data and displacement data. The number of the plurality of key points may be 12, 10, or other number of key points, and may be set according to actual needs, which is not limited in this embodiment.
And S205, obtaining an error curve according to the key point load data of the target load displacement curve and the corresponding key point load data in the reference load displacement curve.
In this embodiment, the load data of the key point of the target load displacement curve and the load data of the corresponding key point in the reference load displacement curve are subjected to corresponding relation, and an error value between the load data of the key point of the target load displacement curve and the load data of the corresponding key point in the reference load displacement curve is calculated. And generating an error curve according to the obtained plurality of error values.
And S206, determining the corresponding welding seam constitutive parameter pair when the error value of the key point load data in the error curve is minimum as a welding seam quality parameter, determining the welding seam quality of the target pipeline according to the welding seam quality parameter, and outputting the welding seam quality of the target pipeline.
In this embodiment, since the mapping relationship between the weld constitutive parameter pair and the displacement data and/or the load data in the reference load displacement curve is constructed through the neural network algorithm, when the minimum error value in the error curve is obtained through calculation, the corresponding load value in the reference load displacement curve can be obtained according to the minimum error value, and thus the corresponding weld constitutive parameter pair can be obtained according to the load value in the reference load displacement curve. At this time, the pair of constitutive parameters of the weld is the optimal pair of constitutive parameters of the weld of the target pipeline. Therefore, the optimal weld constitutive parameter pair is determined as the weld quality parameter, so that the accuracy of the weld quality parameter can be improved.
In this embodiment, at the same time, the optimal weld constitutive parameter pair may be input into a preset finite element simulation model, and the obtained optimal load displacement curve is compared with the target load displacement curve, so as to verify whether the optimal load displacement curve approximately coincides with the target load displacement curve, and if approximately coincides, it may be determined that the obtained weld constitutive parameter pair is the optimal weld constitutive parameter pair of the target pipeline weld material.
Optionally, in this embodiment, before determining, as the weld quality parameter, the weld constitutive parameter pair corresponding to the minimum error value of the key point load data in the error curve, the method further includes:
and determining the minimum error value in the error curve according to a preset relative mean square error formula.
In this embodiment, the minimum error value in the error curve can be calculated more accurately by using a preset relative mean square error formula.
And step S207, judging whether the target pipeline weld joint belongs to a preset quality difference interval according to the quality of the target pipeline weld joint.
And if the numerical value of the target pipeline welding seam quality accords with the poor quality interval, sending the early warning message to early warning equipment.
In this embodiment, when the target pipeline welding seam quality belongs to the preset poor quality interval, it needs to be maintained to represent the target pipeline welding seam, and at this moment, the early warning information is sent to the early warning equipment to early warn through the early warning equipment, and the efficiency of maintenance can be improved.
According to the method for determining the quality of the pipeline welding seam, the target load displacement curve of the target pipeline welding seam material and the welding seam constitutive parameters prestored in the database are obtained, and then a plurality of welding seam constitutive parameter pairs are all input into a preset finite element simulation model, so that a reference load displacement curve is generated through the preset finite element simulation model. After the mapping relation between the welding seam constitutive parameter pair and the displacement data and/or the load data in the reference load displacement curve is established through a neural network algorithm, the error curve can be obtained by comparing the load data of each selected key point between the target load displacement curve and the reference load displacement curve. Because the mapping relation between the welding seam constitutive parameter pairs and the displacement data and/or the load data in the reference load displacement curve is established through the neural network algorithm, when the minimum error value in the error curve is obtained through calculation, the corresponding load value in the reference load displacement curve can be obtained according to the minimum error value, and therefore the corresponding welding seam constitutive parameter pairs can be obtained according to the load value in the reference load displacement curve. At this time, the pair of constitutive parameters of the weld is the optimal pair of constitutive parameters of the weld of the target pipeline. Therefore, the optimal welding seam constitutive parameter pair is determined as the welding seam quality parameter, so that the accuracy of the welding seam quality parameter can be improved, and the accuracy of determining the welding seam quality of the pipeline is improved.
Fig. 4 is a schematic structural diagram of a pipe weld quality determining apparatus according to an embodiment of the present invention, and as shown in fig. 4, in this embodiment, the pipe weld quality determining apparatus 300 includes:
the acquiring module 301 is configured to acquire a target load displacement curve of a target pipeline weld material and weld constitutive parameters pre-stored in a database.
And a reference curve generating module 302, configured to input the welding seam constitutive parameters into a preset finite element simulation model to obtain a reference load displacement curve.
And the weld quality determining module 303 is configured to determine a weld quality parameter according to the target load displacement curve and the reference load displacement curve, determine the weld quality of the target pipeline according to the weld quality parameter, and output the weld quality of the target pipeline.
The device for determining the quality of the weld joint of the pipeline provided by this embodiment may implement the technical solution of the method embodiment shown in fig. 2, and the implementation principle and technical effect thereof are similar to those of the method embodiment shown in fig. 2, and are not described in detail herein.
Meanwhile, fig. 5 is a schematic structural diagram of a device for determining the quality of a weld joint of a pipeline according to another embodiment of the present invention, and as shown in fig. 5, the device for determining the quality of a weld joint of a pipeline according to another embodiment of the present invention is further refined on the basis of the device for determining the quality of a weld joint of a pipeline according to the previous embodiment.
Optionally, in this embodiment, the weld constitutive parameters include: maximum principal strain and fracture energy.
Optionally, in this embodiment, the weld constitutive parameters are a plurality of weld constitutive parameter pairs formed by the maximum principal strain and the fracture energy.
The reference curve generation module 302 is specifically configured to:
and inputting the plurality of welding seam constitutive parameter pairs into a preset finite element simulation model so as to generate a reference load displacement curve through the preset finite element simulation model. And outputting a reference load displacement curve through a preset finite element simulation model.
Optionally, in this embodiment, the apparatus 400 for determining the quality of the weld of the pipeline further includes:
and the mapping module 401 is configured to construct a mapping relationship between the weld constitutive parameter pair and the displacement data and/or the load data in the reference load displacement curve through a neural network algorithm.
Optionally, in this embodiment, when determining the weld quality parameter according to the target load displacement curve and the reference load displacement curve, the weld quality determining module 303 is specifically configured to:
and selecting a plurality of key point load data from the target load displacement curve and the reference load displacement curve respectively. And obtaining an error curve according to the load data of the key point of the target load displacement curve and the load data of the corresponding key point in the reference load displacement curve. And determining the corresponding welding seam constitutive parameter pair when the error value of the key point load data in the error curve is minimum as the welding seam quality parameter.
Optionally, in this embodiment, the method further includes:
and the error determining module is used for determining the minimum error value in the error curve according to a preset relative mean square error formula.
Optionally, in this embodiment, the method further includes:
and the early warning module 402 is configured to judge whether the target pipeline weld seam belongs to a preset poor quality interval according to the quality of the target pipeline weld seam. And if the numerical value of the target pipeline welding seam quality accords with the poor quality interval, sending the early warning message to early warning equipment.
The device for determining the quality of the weld joint of the pipeline provided by this embodiment may implement the technical solutions of the method embodiments shown in fig. 2 to 3, and the implementation principles and technical effects thereof are similar to those of the method embodiments shown in fig. 2 to 3, and are not described in detail herein.
The invention also provides an electronic device and a computer-readable storage medium according to the embodiments of the invention.
As shown in fig. 6, fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present invention. Electronic devices are intended for various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 6, the electronic apparatus includes: a processor 501 and a memory 502. The various components are interconnected using different buses and may be mounted on a common motherboard or in other manners as desired. The processor may process instructions for execution within the electronic device.
The memory 502 is a non-transitory computer readable storage medium provided by the present invention. Wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the method of determining the quality of a weld of a pipe as provided by the present invention. The non-transitory computer readable storage medium of the present invention stores computer instructions for causing a computer to execute the pipe weld quality determination method provided by the present invention.
The memory 502, which is a non-transitory computer-readable storage medium, may be used to store non-transitory software programs, non-transitory computer-executable programs, and modules, such as program instructions/modules corresponding to the pipe weld quality determination method in the embodiments of the present invention (e.g., the acquisition module 301, the reference curve generation module 302, and the weld quality determination module 303 shown in fig. 4). The processor 501 executes various functional applications of the server and data processing by running non-transitory software programs, instructions and modules stored in the memory 502, namely, implements the pipe weld quality determination method in the above-described method embodiments.
Other embodiments of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the embodiments of the invention following, in general, the principles of the embodiments of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the embodiments of the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of embodiments of the invention being indicated by the following claims.
It is to be understood that the embodiments of the present invention are not limited to the precise arrangements described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of embodiments of the invention is limited only by the appended claims.
Claims (10)
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116227282A (en) * | 2023-02-01 | 2023-06-06 | 中国石油大学(北京) | Method and equipment for determining stress-strain relation parameters of girth weld zone material |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160084802A1 (en) * | 2014-09-19 | 2016-03-24 | King Fahd University Of Petroleum And Minerals | Process for determining weld quality using flexural characteristics |
| CN106407614A (en) * | 2016-11-08 | 2017-02-15 | 武汉大学 | Method for acquiring weld seam structure mechanical parameters in combination with nanoindentation and finite elements |
| CN108240526A (en) * | 2018-01-31 | 2018-07-03 | 中国石油大学(北京) | Buried oil-gas pipeline antishock device and buried oil-gas pipeline system |
| CN109299568A (en) * | 2018-10-24 | 2019-02-01 | 南京航空航天大学 | Inverse method of constitutive model of welded joints based on nanoindentation test |
| CN110598357A (en) * | 2019-09-25 | 2019-12-20 | 华中科技大学 | A method, device, equipment and storage medium for stress deformation simulation of welded joints |
-
2020
- 2020-11-11 CN CN202011255204.1A patent/CN112528531B/en not_active Expired - Fee Related
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160084802A1 (en) * | 2014-09-19 | 2016-03-24 | King Fahd University Of Petroleum And Minerals | Process for determining weld quality using flexural characteristics |
| CN106407614A (en) * | 2016-11-08 | 2017-02-15 | 武汉大学 | Method for acquiring weld seam structure mechanical parameters in combination with nanoindentation and finite elements |
| CN108240526A (en) * | 2018-01-31 | 2018-07-03 | 中国石油大学(北京) | Buried oil-gas pipeline antishock device and buried oil-gas pipeline system |
| CN109299568A (en) * | 2018-10-24 | 2019-02-01 | 南京航空航天大学 | Inverse method of constitutive model of welded joints based on nanoindentation test |
| CN110598357A (en) * | 2019-09-25 | 2019-12-20 | 华中科技大学 | A method, device, equipment and storage medium for stress deformation simulation of welded joints |
Non-Patent Citations (3)
| Title |
|---|
| KAI WU 等: "Fracture response of 1422-mm diameter pipe with double-V groove weld joints and circumferential crack in fusion line", 《ENGINEERING FAILURE ANALYSIS》 * |
| 刘小刚 等: "TC4钛合金扩散焊接头的力学性能", 《航空动力学报》 * |
| 张宏 等: "直径1 422 mm X80 管道环焊接头应变能力数值模拟方法", 《油气储运》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116227282A (en) * | 2023-02-01 | 2023-06-06 | 中国石油大学(北京) | Method and equipment for determining stress-strain relation parameters of girth weld zone material |
| CN116227282B (en) * | 2023-02-01 | 2023-12-08 | 中国石油大学(北京) | Method and equipment for determining stress-strain relationship parameters of materials in girth weld area |
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