Pipeline evaluation method and device based on yield strength randomness, medium and product

Abstract

The invention discloses a pipeline evaluation method and device based on yield strength randomness, a medium and a product, relates to the technical field of natural gas pipeline evaluation, and aims to solve the problem of insufficient accuracy of evaluation results in related technologies. The method comprises the following steps: establishing a limit state function of a pipeline; based on a Monte Carlo method, collecting parameters of the pipeline for multiple times; based on the parameters and the limit state function, determining the state of the pipeline corresponding to the multiple times of collection; the state of the pipeline is a safe state, a limit state or a non-safe state; and determining the reliability of the pipeline based on the corresponding states of the pipeline acquired for multiple times.

Description

Technical Field

[0001] The present application relates to the technical field of natural gas pipeline evaluation, and in particular to a pipeline evaluation method, device, medium and product based on yield strength randomness. Background Art

[0002] In the field of natural gas transportation, by evaluating the reliability of pipelines, we can find pipeline nodes that may cause leakage, and then take corresponding treatment measures to reduce safety risks such as natural gas leakage.

[0003] The current pipeline reliability evaluation method has the problem of insufficient accuracy of evaluation results. Summary of the Invention

[0004] The purpose of this application is to provide a pipeline evaluation method, device, medium and product based on yield strength randomness, aiming to solve the problem of insufficient accuracy of evaluation results in related technologies.

[0005] To achieve the above objectives, this application adopts the following technical solutions: This application provides a pipeline evaluation method based on yield strength randomness, including: Establish the limit state function of the pipeline; Based on the Monte Carlo method, the pipeline parameters are collected multiple times; Based on parameters and limit state functions, the state of the pipeline corresponding to multiple acquisitions is determined; the state of the pipeline is a safe state, a limit state, or an unsafe state; The reliability of the pipeline is determined based on the status of the corresponding pipeline collected multiple times.

[0006] In this application, the pipeline limit state function can output pipeline state-related parameters and reflect the pipeline's condition. The Monte Carlo method is a random sampling method that can collect pipeline parameters based on a normal distribution. This ensures the randomness of data collection and, in turn, the reliability of the pipeline state determined based on these multiple collected pipeline parameters, ensuring the reliability and accuracy of pipeline evaluation.

[0007] In some embodiments, the parameters of the pipeline include at least one of the following: The yield strength of the pipeline, the tensile strength of the pipeline, the diameter of the pipeline, the wall thickness of the pipeline, the maximum depth of the corrosion zone of the pipeline, and the axial length of the corrosion zone of the pipeline.

[0008] In some embodiments, the state of the pipeline is the difference between the corrosion area and the equivalent stress of the output of the limit state function and the yield strength of the pipeline; when the difference is less than a difference threshold, the state of the pipeline is an unsafe state; when the difference is equal to the difference threshold, the state of the pipeline is a limit state; when the difference is greater than the difference threshold, the state of the pipeline is a safe state; The limit state function satisfies the following formula: ; ; in, is the difference between the equivalent stress of the corroded area and the yield strength of the pipeline; is the yield strength of the pipe; is the tensile strength of the pipe; is the pipe diameter; is the pipe wall thickness; is the maximum depth of the corrosion zone; is the axial length of the corrosion zone.

[0009] In some embodiments, determining the reliability of a pipeline based on multiple acquisitions of corresponding pipeline states includes: Determine the failure probability of the pipeline corresponding to the multiple acquisitions based on the state of the pipeline corresponding to the multiple acquisitions; the failure probability is used to indicate the probability that the pipeline is in an unsafe state; Determine the reliability of the pipeline based on the failure probability and probability threshold of the pipeline; The failure probability of the pipeline corresponding to multiple acquisitions satisfies the following formula: ; in, is the number of collections, is the failure probability, Indicates the The status of the pipeline corresponding to this collection.

[0010] In some embodiments, the pipeline parameters include pipeline parameters corresponding to multiple samples at the current moment; the method further includes: Based on the parameters and corrosion rates of the pipeline corresponding to the multiple samples at the current moment, determining the maximum depth of the corrosion zone of the pipeline at multiple future moments corresponding to the multiple samples; The maximum depth of the corrosion zone of the pipeline at a future time satisfies the following formula: ; in, is the depth of the corrosion defect at a future time; is the corrosion defect depth at the current moment; is the time difference between a future moment and the current moment; is the corrosion rate; Based on parameters and limit state functions, the pipeline status corresponding to multiple acquisitions is determined, including: Determining the state of the pipeline at multiple future time points based on the pipeline parameters and the maximum depth of the corrosion zone of the pipeline at multiple future time points corresponding to the multiple samples; Based on multiple acquisitions of the corresponding pipeline status, the reliability of the pipeline is determined, including: The pipeline status at multiple future moments determines the pipeline reliability within a preset time period; the preset time period includes the current moment and multiple future moments.

[0011] In some embodiments, the corrosion rate is determined based on environmental factors of the pipeline, the AC density of the pipeline; The AC density of the pipeline is determined based on: The AC electric density of the pipeline is determined based on the average value of the effective value of the AC interference voltage of the pipeline, the soil resistivity corresponding to the pipeline, and the diameter of the damaged point of the pipeline; The AC electric density of the pipeline is determined based on the average value of the effective value of the AC interference voltage of the pipeline, the soil resistivity corresponding to the pipeline, and the diameter of the damaged point of the pipeline, which satisfies the following formula: ; in, is the AC current density in the pipeline; is the average value of the effective value of the AC interference voltage; is the soil resistivity; is the diameter of the damage point.

[0012] In some embodiments, the damage point diameter of the pipe is determined based on: Determine the diameter of the damaged point of the pipeline based on the internal defect data of the pipeline; the internal defect data of the pipeline includes the defect length and the defect width of the pipeline; The diameter of the damaged point of the pipeline is determined based on the internal defect data of the pipeline and meets the following formula: ; in, is the defect length; is the defect width; is the diameter of the damage point.

[0013] In some embodiments, the present application provides a pipeline evaluation device based on yield strength randomness, comprising: a processor and a memory configured to store processor-executable instructions; wherein the processor is configured to execute the instructions to implement any of the above optional methods.

[0014] In some embodiments, the present application provides a computer-readable storage medium having instructions stored thereon. When the instructions in the computer-readable storage medium are executed by a pipeline evaluation device based on yield strength randomness, the pipeline evaluation device based on yield strength randomness is enabled to perform any of the above-mentioned optional methods.

[0015] In some embodiments, the present application provides a computer program product, which includes computer program instructions, and when the computer program instructions are executed by a processor, implements any of the above optional methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0017] Figure 1 A flow chart of a pipeline evaluation method based on yield strength randomness provided in this application; Figure 2 This is a schematic structural diagram of a pipeline evaluation device based on yield strength randomness provided in this application. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0019] In the description of this application, it should be understood that the terms "upper," "lower," "left," "right," "front," "back," "inner," "outer," and the like, indicating directions or positional relationships, are based on the directions or relative positional relationships shown in the accompanying drawings and are intended solely to facilitate the description of this application and simplify the description. They do not indicate or imply that the devices or components referred to must have a specific direction, be constructed, or operate in a specific direction. Therefore, they should not be construed as limitations on this application. Unless otherwise specified, the above-mentioned directionality descriptions may be flexibly set in actual application, provided that the relative positional relationships shown in the accompanying drawings are met.

[0020] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature specified as "first" or "second" may explicitly or implicitly include one or more of such features. Throughout this application, unless otherwise specified, "plurality" means two or more.

[0021] In the description of this application, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," "connected," and "connected" should be understood broadly. For example, they may refer to fixed connections, detachable connections, or integral connections. They may be directly connected, indirectly connected through an intermediary, or internally connected between two components. Those skilled in the art will understand the specific meanings of these terms in this application based on the specific circumstances.

[0022] In the embodiments of the present application, the terms "comprises," "comprising," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, article, or device comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not preclude the presence of other identical elements in the process, article, or device comprising the element.

[0023] In the embodiments of this application, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of this application should not be interpreted as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0024] In the description of this specification, specific features, structures, materials or characteristics may be combined in an appropriate manner in any one or more embodiments or examples.

[0025] During pipeline manufacturing, due to factors such as material composition and processing techniques, the yield strength is not a fixed value but rather exhibits a degree of discreteness and uncertainty. Current pipeline reliability assessment methods mostly use a single yield strength value, failing to account for its randomness, resulting in inaccurate assessment results. Furthermore, existing methods fail to fully consider the combined effects of corrosion defect size and distribution on yield strength, leading to significant deviations in reliability assessment results.

[0026] To solve the above problems, the present application provides a pipeline evaluation method based on yield strength randomness.

[0027] like Figure 1 As shown, this application provides a pipeline evaluation method based on yield strength randomness, including: S101-S104: S101. Establish a limit state function of the pipeline.

[0028] In a possible implementation, the limit state function can be established through the correlation between the yield strength of the pipeline, the tensile strength of the pipeline, the diameter of the pipeline, the wall thickness of the pipeline, the maximum depth of the corrosion zone of the pipeline, and the axial length of the corrosion zone of the pipeline.

[0029] S102. Based on the Monte Carlo method, the pipeline parameters are collected multiple times.

[0030] It should be noted that the yield strength experimental data of different batches of pipes were collected and the mean and standard deviation of the normal distribution were fitted. After collecting the data, it was found that the yield strength of the pipe met N (455.65, 13.36 2 ) is normally distributed, and the tensile strength meets a certain distribution probability. The Monte Carlo method randomly collects data that meets this normal distribution during each sampling process. This ensures the randomness of data collection and, therefore, the reliability of the evaluation results.

[0031] S103: Determine the state of the pipeline corresponding to the multiple acquisitions based on the parameters and the limit state function.

[0032] The status of the pipeline is safe, limit or unsafe.

[0033] In one possible implementation, the parameters collected multiple times can be input into the limit state function respectively to obtain the parameters of the pipeline state corresponding to the multiple collected parameters (such as the difference between the equivalent stress of the pipeline corrosion area and the pipeline yield strength).

[0034] S104: Determine the reliability of the pipeline based on the status of the corresponding pipeline collected multiple times.

[0035] It should be understood that the pipeline limit state function can output pipeline state-related parameters and reflect the pipeline's condition. The Monte Carlo method is a random sampling method that can collect pipeline parameters based on a normal distribution. This ensures the randomness of data collection and, in turn, the reliability of the pipeline state determined based on these multiple collected pipeline parameters, ensuring the reliability and accuracy of pipeline evaluation.

[0036] In some embodiments, the pipeline parameter includes at least one of the following: yield strength of the pipeline, tensile strength of the pipeline, diameter of the pipeline, wall thickness of the pipeline, maximum depth of the corrosion zone of the pipeline, and axial length of the corrosion zone of the pipeline.

[0037] In one possible implementation, the crack conditions along the entire pipeline can be acquired through magnetic flux leakage or ultrasound, and data such as the length, depth, width, and circumferential position of the cracks can be collected. That is, data on the corrosion zone of the pipeline can be acquired through magnetic flux leakage or ultrasound.

[0038] In some embodiments, the state of the pipeline is the difference between the corrosion area output by the limit state function and the equivalent stress and the yield strength of the pipeline; when the difference is less than a difference threshold, the state of the pipeline is an unsafe state; when the difference is equal to the difference threshold, the state of the pipeline is a limit state; when the difference is greater than the difference threshold, the state of the pipeline is a safe state.

[0039] The limit state function satisfies the following formula 1 and formula 2: Formula 1; Formula 2; in, It is the difference between the equivalent stress of the corrosion area and the yield strength of the pipeline, in MPa; is the yield strength of the pipe, in MPa; The unit of tensile strength of the pipeline is MPa; is the pipe diameter, in mm; is the pipe wall thickness, in mm; is the maximum depth of the corrosion zone, in mm; is the axial length of the corrosion zone, in mm.

[0040] In some embodiments, determining the reliability of a pipeline based on multiple acquisitions of corresponding pipeline states includes: Determine the failure probability of the pipeline corresponding to the multiple acquisitions based on the state of the pipeline corresponding to the multiple acquisitions; the failure probability is used to indicate the probability that the pipeline is in an unsafe state; The reliability of the pipeline is determined based on the failure probability of the pipeline and the probability threshold.

[0041] The failure probability of the pipeline corresponding to multiple acquisitions satisfies the following formula 3: Formula 3; in, is the number of collections, is the failure probability, Indicates the The status of the pipeline corresponding to this collection.

[0042] In some embodiments, the pipeline parameters include pipeline parameters corresponding to multiple samples at the current moment; the method further includes: Based on the parameters and corrosion rates of the pipeline corresponding to the multiple samples at the current moment, determining the maximum depth of the corrosion zone of the pipeline at multiple future moments corresponding to the multiple samples; The maximum depth of the corrosion zone of the pipeline at a future time satisfies the following formula 4: Formula 4; in, is the depth of the corrosion defect at a future time, in mm; is the corrosion defect depth at the current moment, in mm; The time difference between a future moment and the current moment, in units of a (i.e., years); is the corrosion rate, in mm / a; Based on parameters and limit state functions, the pipeline status corresponding to multiple acquisitions is determined, including: Determining the state of the pipeline at multiple future time points based on the pipeline parameters and the maximum depth of the corrosion zone of the pipeline at multiple future time points corresponding to the multiple samples; Based on multiple acquisitions of the corresponding pipeline status, the reliability of the pipeline is determined, including: The pipeline status at multiple future moments determines the pipeline reliability within a preset time period; the preset time period includes the current moment and multiple future moments.

[0043] In some embodiments, the corrosion rate is determined based on environmental factors of the pipeline, the AC density of the pipeline; The AC density of the pipeline is determined based on: The AC electric density of the pipeline is determined based on the average value of the effective value of the AC interference voltage of the pipeline, the soil resistivity corresponding to the pipeline, and the diameter of the damaged point of the pipeline.

[0044] The AC electric density of the pipeline is determined based on the average value of the effective value of the AC interference voltage of the pipeline, the soil resistivity corresponding to the pipeline, and the diameter of the damaged point of the pipeline, which satisfies the following formula 5: Formula 5; in, is the AC current density of the pipeline, in units of ; is the average value of the effective value of the AC interference voltage, in V; is the soil resistivity, in units of ; is the diameter of the damage point, in m.

[0045] In some embodiments, the diameter of the damaged point of the pipeline is determined based on the following method: the diameter of the damaged point of the pipeline is determined based on internal defect data of the pipeline; the internal defect data of the pipeline includes the defect length and the defect width of the pipeline.

[0046] The diameter of the damaged point of the pipeline is determined based on the internal defect data of the pipeline and satisfies the following formula 6: Formula 6; in, is the defect length, in mm; is the defect width, in mm; The diameter of the damaged point, in mm.

[0047] It should be noted that the damage point diameter obtained based on Formula 6 can also be called the equivalent diameter.

[0048] In the embodiments of the present application, the functional modules of the pipeline evaluation device based on yield strength randomness can be divided according to the above-mentioned method examples. For example, each functional module can be divided according to each function, or two or more functions can be integrated into a processing module. The above-mentioned integrated modules can be implemented in the form of hardware or software functional modules. It should be noted that the division of modules in the embodiments of the present application is schematic and is only a logical functional division. In actual implementation, other division methods may be used.

[0049] In the case of dividing each functional module into corresponding functional modules, Figure 2 A possible structural diagram of the pipeline evaluation device based on yield strength randomness involved in the above embodiment is shown. Figure 2 As shown, the pipeline evaluation device based on yield strength randomness may include: a processing module 201 , an acquisition module 202 and a determination module 203 .

[0050] Processing module 201, used to establish a limit state function of the pipeline; An acquisition module 202 is configured to acquire pipeline parameters multiple times based on a Monte Carlo method; The determination module 203 is used to determine the state of the pipeline corresponding to the multiple acquisitions based on the parameters and the limit state function; the state of the pipeline is a safe state, a limit state or an unsafe state; The determination module 203 is further configured to determine the reliability of the pipeline based on the states of the corresponding pipelines acquired multiple times.

[0051] The above are only specific embodiments of the present application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A pipeline evaluation method based on yield strength randomness, characterized in that: The method comprises: Establish the limit state function of the pipeline; Based on the Monte Carlo method, the parameters of the pipeline are collected multiple times; Based on the parameters and the limit state function, determining the state of the pipeline corresponding to the multiple acquisitions; the state of the pipeline is a safe state, a limit state, or an unsafe state; The reliability of the pipeline is determined based on the states of the pipeline corresponding to the multiple acquisitions.

2. The method according to claim 1, characterized in that The parameters of the pipeline include at least one of the following: The yield strength of the pipeline, the tensile strength of the pipeline, the diameter of the pipeline, the wall thickness of the pipeline, the maximum depth of the corrosion zone of the pipeline, and the axial length of the corrosion zone of the pipeline.

3. The method according to claim 2, characterized in that The state of the pipeline is the difference between the corrosion zone output by the limit state function and the equivalent stress and the yield strength of the pipeline; when the difference is less than a difference threshold, the state of the pipeline is an unsafe state; when the difference is equal to the difference threshold, the state of the pipeline is a limit state; when the difference is greater than the difference threshold, the state of the pipeline is a safe state; The limit state function satisfies the following formula: ; ； in, is the difference between the equivalent stress of the corroded area and the yield strength of the pipeline; is the yield strength of the pipe; is the tensile strength of the pipe; is the pipe diameter; is the pipe wall thickness; is the maximum depth of the corrosion zone; is the axial length of the corrosion zone.

4. The method according to claim 2, characterized in that The determining the reliability of the pipeline based on the states of the pipeline corresponding to the multiple acquisitions includes: Determining, based on the states of the pipeline corresponding to the multiple acquisitions, a failure probability of the pipeline corresponding to the multiple acquisitions; the failure probability is used to indicate a probability that the pipeline is in an unsafe state; Determining the reliability of the pipeline based on the failure probability of the pipeline and a probability threshold; The failure probability of the pipeline corresponding to the multiple acquisitions satisfies the following formula: ； in, is the number of collections, is the failure probability, Indicates the The status of the pipeline corresponding to the acquisition.

5. The method according to claim 2, characterized in that The parameters of the pipeline include parameters of the pipeline corresponding to multiple samples at the current moment; the method further includes: Determining the maximum depth of the corrosion zone of the pipeline at multiple future moments corresponding to each of the multiple samples based on the parameters and corrosion rate of the pipeline corresponding to the multiple samples at the current moment; The maximum depth of the corrosion zone of the pipeline at a future time satisfies the following formula: ； in, is the depth of the corrosion defect at the future moment; is the corrosion defect depth at the current moment; is the time difference between the future moment and the current moment; is the corrosion rate; The determining, based on the parameter and the limit state function, the state of the pipeline corresponding to the multiple acquisitions includes: Determining the state of the pipeline at the multiple future moments based on the pipeline parameters and the maximum depths of the corrosion zone of the pipeline at the multiple future moments corresponding to the multiple samples; The determining the reliability of the pipeline based on the states of the pipeline corresponding to the multiple acquisitions includes: The states of the pipeline at the multiple future moments are used to determine the reliability of the pipeline within a preset time period; the preset time period includes the current moment and the multiple future moments.

6. The method according to claim 5, characterized in that The corrosion rate is determined based on environmental factors of the pipeline and the AC density of the pipeline; The AC density of the pipeline is determined based on the following method: Determining the AC electric density of the pipeline based on an average value of the effective value of the AC interference voltage of the pipeline, the soil resistivity corresponding to the pipeline, and the diameter of the damaged point of the pipeline; The AC density of the pipeline is determined based on the average value of the effective value of the AC interference voltage of the pipeline, the soil resistivity corresponding to the pipeline, and the diameter of the damaged point of the pipeline, and satisfies the following formula: ； in, is the AC current density of the pipeline; is the average value of the effective value of the AC interference voltage; is the soil resistivity; is the diameter of the damage point.

7. The method according to claim 6, characterized in that The diameter of the damaged point of the pipe is determined based on the following method: Determining the diameter of the damaged point of the pipeline based on the internal defect data of the pipeline; the internal defect data of the pipeline includes the defect length of the pipeline and the defect width of the pipeline; The diameter of the damaged point of the pipeline is determined based on the internal defect data of the pipeline to satisfy the following formula: ； in, is the defect length; is the defect width; is the diameter of the damage point.

8. A pipeline evaluation device based on yield strength randomness, characterized in that: The pipeline evaluation device based on yield strength randomness includes: processor; a memory configured to store instructions executable by the processor; The processor is configured to execute the instructions to implement the method according to any one of claims 1 to 7.

9. A computer-readable storage medium having instructions stored thereon, characterized in that: When the instructions in the computer-readable storage medium are executed by a pipeline evaluation device based on yield strength randomness, the pipeline evaluation device based on yield strength randomness is enabled to perform the method according to any one of claims 1 to 7.

10. A computer program product, characterized in that The computer program product comprises computer program instructions, which implement the method according to any one of claims 1 to 7 when executed by a processor.

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