CN111666684A - Circumferential weld risk estimation method and device for conveying pipeline and readable storage medium - Google Patents

Circumferential weld risk estimation method and device for conveying pipeline and readable storage medium Download PDF

Info

Publication number
CN111666684A
CN111666684A CN202010505385.2A CN202010505385A CN111666684A CN 111666684 A CN111666684 A CN 111666684A CN 202010505385 A CN202010505385 A CN 202010505385A CN 111666684 A CN111666684 A CN 111666684A
Authority
CN
China
Prior art keywords
risk
index
value
weight
consistency
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202010505385.2A
Other languages
Chinese (zh)
Other versions
CN111666684B (en
Inventor
赖少川
谢成
姜红涛
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
China Petroleum and Chemical Corp
China Oil and Gas Pipeline Network Corp
Original Assignee
Sinopec Sales Co Ltd South China Branch
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Sinopec Sales Co Ltd South China Branch filed Critical Sinopec Sales Co Ltd South China Branch
Priority to CN202010505385.2A priority Critical patent/CN111666684B/en
Publication of CN111666684A publication Critical patent/CN111666684A/en
Application granted granted Critical
Publication of CN111666684B publication Critical patent/CN111666684B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/045—Combinations of networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0635—Risk analysis of enterprise or organisation activities
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30—Computing systems specially adapted for manufacturing

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Business, Economics & Management (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Human Resources & Organizations (AREA)
  • Strategic Management (AREA)
  • Economics (AREA)
  • Mathematical Physics (AREA)
  • General Engineering & Computer Science (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Data Mining & Analysis (AREA)
  • General Business, Economics & Management (AREA)
  • Marketing (AREA)
  • Pure & Applied Mathematics (AREA)
  • Mathematical Optimization (AREA)
  • Software Systems (AREA)
  • Evolutionary Computation (AREA)
  • Mathematical Analysis (AREA)
  • Computational Mathematics (AREA)
  • Development Economics (AREA)
  • Tourism & Hospitality (AREA)
  • Quality & Reliability (AREA)
  • Operations Research (AREA)
  • Game Theory and Decision Science (AREA)
  • Computing Systems (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Biophysics (AREA)
  • Educational Administration (AREA)
  • Biomedical Technology (AREA)
  • Health & Medical Sciences (AREA)
  • Computer Hardware Design (AREA)
  • Geometry (AREA)
  • Artificial Intelligence (AREA)
  • Computational Linguistics (AREA)
  • General Health & Medical Sciences (AREA)
  • Molecular Biology (AREA)
  • Algebra (AREA)
  • Databases & Information Systems (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The application discloses a circumferential weld risk estimation method and device for a conveying pipeline and a computer readable storage medium. Determining a risk estimation model corresponding to a girth weld of a conveying pipeline based on basic parameter data of the conveying pipeline of the urban building group; the risk prediction model comprises risk grade information, a score range corresponding to each risk grade, an index set for evaluating the girth weld risk and a scoring range of each index; based on a risk pre-estimation model, automatically calculating a risk weight value and a score value of each index of the girth weld according to the detection data and the basic parameter data in the pipeline; when the consistency check relation is used for checking the assignment of each risk weight value to meet the conditions, the circumferential weld risk association relation is used for determining the association degree of each index and the circumferential weld risk level based on the risk weight values and the score values to obtain the circumferential weld risk estimation information, the influence degree of human subjective factors on the circumferential weld risk estimation process is effectively reduced, and the accuracy of the circumferential weld risk estimation of the conveying pipeline is improved.

Description

Circumferential weld risk estimation method and device for conveying pipeline and readable storage medium
Technical Field
The application relates to the technical field of safety monitoring of conveying pipelines, in particular to a circumferential weld risk estimation method and device for a conveying pipeline and a computer readable storage medium.
Background
Research shows that in recent years, most of oil and gas pipeline leakage and cracking accidents occur due to the quality problem of circumferential weld, the visible circumferential weld is the most common characteristic of the oil and gas pipeline, and the safety degree of the visible circumferential weld determines the overall reliability of the oil and gas pipeline. Once the circumferential weld cracking accident happens, damage to the surrounding environment of the oil and gas pipeline and even casualties can be caused while direct economic loss is caused. For various reasons, girth welds can have varying degrees of defects in the welding process. The defects are easy to expand under the external load of the pipeline and the corrosion action of the medium of the pipe body, so that the circumferential weld generates leakage and cracking, and finally, the leakage accident of the large-scale oil and gas pipeline is caused. It can be seen that girth weld quality, safety and reliability have a significant impact on fluid leakage from the delivery conduit.
At present, circumferential weld risk estimation is a technical means for improving the safety of oil and gas pipelines and preventing pipeline accidents. In the related technology, when the circumferential weld risk is estimated, the quantitative evaluation of the circumferential weld of the pipeline is carried out on the premise of considering the influence factors of the circumferential weld quality. The influence degrees of different factors of different pipelines on the reliability of the girth weld are different, so that the risk estimation of the girth weld in the related technology is influenced by human subjective factors to a great extent, and the accuracy of the estimation result is not high.
Disclosure of Invention
The application provides a circumferential weld risk estimation method and device for a conveying pipeline and a computer readable storage medium, which effectively reduce the degree of influence of human subjective factors on the circumferential weld risk estimation process and improve the accuracy of circumferential weld risk estimation of the conveying pipeline.
In order to solve the above technical problems, embodiments of the present invention provide the following technical solutions:
the embodiment of the invention provides a circumferential weld risk estimation method for a conveying pipeline, which comprises the following steps:
determining a risk estimation model corresponding to a girth weld of a conveying pipeline based on basic parameter data of the conveying pipeline of the urban building group; the risk estimation model comprises risk grade information, a score range corresponding to each risk grade, an index set for evaluating the girth weld risk and a scoring range of each index;
based on the risk pre-estimation model, automatically calculating a risk weight value and a score value of each index of the girth weld according to detection data in the conveying pipeline and the basic parameter data;
when the pre-constructed consistency check relation is used for checking that the assignment of each risk weight value meets the condition, determining the association degree of each index and the girth weld risk level by using the pre-constructed girth weld risk association relation based on the risk weight value and the score value of each index so as to be used for determining the risk estimation information of the girth weld.
Optionally, the risk prediction model index set includes a plurality of first-level indexes, each first-level index further includes a plurality of second-level indexes, and the determining, based on the risk weight value and the score value of each index, the association degree between each index and the circumferential weld risk level by using a circumferential weld risk association relation formula established in advance for determining the risk prediction information of the conveying pipeline includes:
respectively and sequentially calculating the index association value of each secondary index and each primary index by using the circumferential weld risk association relation;
for each first-level index, calculating according to the risk weight value and the index association degree value of each second-level index belonging to the current first-level index to obtain an index association degree matrix of the current first-level index;
calculating according to the risk weight value of each first-level index and the index association matrix to obtain a risk estimation association matrix;
and determining the risk grade of the conveying pipeline according to the risk estimation association matrix to serve as the risk estimation information to be output.
Optionally, the determining the risk level of the girth weld according to the risk prediction association matrix to output as the risk prediction information includes:
determining the maximum matrix element value from the risk prediction association matrix as a risk prediction value;
matching the risk pre-evaluation value with a value range corresponding to each risk grade in the risk pre-evaluation model;
and taking the risk grade corresponding to the score range of the risk estimated value as the risk grade of the girth weld.
Optionally, the verifying, by using a pre-established consistency verification relational expression, that the assignment of each risk weight value satisfies a condition includes:
obtaining the relative importance among all indexes by using a scaling method based on the risk estimation model in advance to construct an index weight judgment matrix;
by using
Figure BDA0002526360440000031
Calculating to obtain the maximum characteristic root value of the index weight judgment matrix;
based on the maximum feature root value utilization
Figure BDA0002526360440000032
Calculating to obtain a consistency index value;
utilizing based on the consistency index value
Figure BDA0002526360440000033
Calculating to obtain a consistency ratio;
if the consistency ratio value is within a preset allowable range, the assignment of each risk weight value meets the condition; if the consistency ratio value is not in the allowable range, the assignment of each risk weight value does not meet the condition;
in the formula, λMAXIs the maximum root of feature, (AW)iWeight factor, w, for the i-th indexiThe risk weight value of the ith index is n, and the n is the total number of the indexes; the weight factor is based on the index weightRe-judging the matrix and confirming the risk weight value of each index; CI is the consistency index value; RI is the average random consistency row index value, and CR is the consistency ratio.
Optionally, each risk weight value is determined according to the eigenvector value of the index weight judgment matrix, and after the assignment of each risk weight value does not satisfy the condition, the method further includes:
and adjusting the index weight judgment matrix according to a preset weight adjustment rule, and calculating the characteristic vector and the maximum characteristic root value of the adjusted index weight judgment matrix until the consistency ratio calculated according to the updated characteristic vector and the maximum characteristic root value is in the allowable range.
In another aspect, an embodiment of the present invention provides a circumferential weld risk estimation device for a transmission pipeline, including:
the risk estimation model determining module is used for determining a risk estimation model corresponding to a girth weld of the conveying pipeline based on basic parameter data of the conveying pipeline of the urban building group; the risk estimation model comprises risk grade information, a score range corresponding to each risk grade, an index set for evaluating the girth weld risk and a scoring range of each index;
the index weight and score calculation module is used for automatically calculating a risk weight value and a score value of each index of the girth weld according to the detection data in the conveying pipeline and the basic parameter data based on the risk estimation model;
the consistency checking module is used for checking whether the assignment of each risk weight value meets the condition or not by using a pre-constructed consistency checking relational expression;
and the risk estimation module is used for determining the association degree of each index and the girth weld risk level by using the pre-constructed girth weld risk association relation based on the risk weight value and the score value of each index when the pre-constructed consistency check relation is used for checking that the assignment of each risk weight value meets the condition, so as to determine the risk estimation information of the girth weld.
Optionally, the risk estimation module includes:
the index association value calculation submodule is used for respectively and sequentially calculating the index association value of each secondary index and each primary index by utilizing the circumferential weld risk association relation; the risk estimation model index set comprises a plurality of first-level indexes, and each first-level index further comprises a plurality of second-level indexes;
the index association degree matrix calculation submodule is used for calculating each first-level index according to the risk weight value and the index association degree value of each second-level index belonging to the current first-level index to obtain an index association degree matrix of the current first-level index;
the risk estimation association degree matrix calculation submodule is used for calculating according to the risk weight value of each primary index and the index association degree matrix to obtain a risk estimation association degree matrix;
and the risk grade determining submodule is used for determining the risk grade of the conveying pipeline according to the risk estimation association degree matrix so as to output the risk grade as the risk estimation information.
Optionally, the consistency check module includes:
the index weight judgment matrix construction submodule is used for obtaining the relative importance among the indexes by using a scaling method on the basis of the risk estimation model in advance so as to construct an index weight judgment matrix;
maximum feature root value calculation submodule for utilizing
Figure BDA0002526360440000041
Calculating to obtain the maximum characteristic root value of the index weight judgment matrix;
a consistency index calculation submodule for utilizing based on the maximum characteristic root value
Figure BDA0002526360440000051
Calculating to obtain a consistency index value;
a consistency ratio calculation submodule for utilizing the consistency index value based on the consistency ratio
Figure BDA0002526360440000052
Calculating to obtain a consistency ratio;
the condition judgment submodule is used for judging whether the consistency ratio value is within a preset allowable range or not according to the set condition; if the consistency ratio value is not in the allowable range, the assignment of each risk weight value does not meet the condition;
in the formula, λMAXIs the maximum root of feature, (AW)iWeight factor, w, for the i-th indexiThe risk weight value of the ith index is n, and the n is the total number of the indexes; the weight factor is determined according to the index weight judgment matrix and the risk weight value of each index; CI is the consistency index value; RI is the average random consistency row index value, and CR is the consistency ratio.
The embodiment of the invention also provides a circumferential weld risk estimation device of the conveying pipeline, which comprises a processor, wherein the processor is used for realizing the steps of the circumferential weld risk estimation method of the conveying pipeline when executing the computer program stored in the memory.
The embodiment of the invention finally provides a computer-readable storage medium, wherein a circumferential weld risk estimation program of the conveying pipeline is stored on the computer-readable storage medium, and when being executed by a processor, the circumferential weld risk estimation program of the conveying pipeline realizes the steps of the circumferential weld risk estimation method of the conveying pipeline.
The technical scheme provided by the application has the advantages that the risk estimation model of the circumferential weld is constructed based on the specific actual condition of the pipeline, the basic characteristics of the pipeline are combined with the index evaluation parameters, the risk weight values of all indexes of the circumferential weld of the pipeline are calculated based on the detection data in the pipeline and the basic data of the pipeline, the grading result is given by combining the field condition of the pipeline, and the circumferential weld is evaluated in a grading manner, so that the data comparison of subsequent models is facilitated, and the reliability of the estimation result can be ensured; through weight distribution calculation and inspection of the risk prediction model, weight calculation is carried out on different risk evaluation indexes in the evaluation process, the association level of cross-section influence factors in the weight distribution process is high, the weight value of each index on the girth weld can be comprehensively considered, the risk prediction reliability and accuracy are effectively improved, the degree of artificial subjective influence on the risk prediction process is greatly reduced, and the oil-gas pipeline weld management level is improved.
In addition, the embodiment of the invention also provides a corresponding implementation device and a computer readable storage medium for the circumferential weld risk estimation method of the conveying pipeline, so that the method has higher practicability, and the device and the computer readable storage medium have corresponding advantages.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the related art, the drawings required to be used in the description of the embodiments or the related art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a schematic flow chart of a circumferential weld risk estimation method for a conveying pipeline according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a circumferential weld risk assessment indicator system provided by an embodiment of the present invention;
fig. 3 is a flowchart illustrating an implementation manner of step S103 according to an embodiment of the present invention;
fig. 4 is a schematic flowchart of another implementation manner of step S103 according to an embodiment of the present invention;
fig. 5 is a structural diagram of a circumferential weld risk estimation apparatus for a conveying pipeline according to an embodiment of the present invention;
fig. 6 is a structural diagram of another specific embodiment of a circumferential weld risk estimation device for a conveying pipeline according to an embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the disclosure, the invention will be described in further detail with reference to the accompanying drawings and specific embodiments. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "first," "second," "third," "fourth," and the like in the description and claims of this application and in the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "comprising" and "having," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements but may include other steps or elements not expressly listed.
Having described the technical solutions of the embodiments of the present invention, various non-limiting embodiments of the present application are described in detail below.
Referring to fig. 1, fig. 1 is a schematic flow chart of a circumferential weld risk estimation method for a transmission pipeline according to an embodiment of the present invention, where the embodiment of the present invention may include the following:
s101: and determining a risk estimation model corresponding to the girth weld of the conveying pipeline based on the basic parameter data of the urban building group conveying pipeline.
In the present application, the basic parameter data is the basic data after the pipeline is built, such as position, shape information, length information, material information, external environment information and quality information. Because different conveying pipelines have certain difference, the risk estimation model is constructed according to the concrete actual conditions of the pipelines, the basic characteristics of the pipelines are fused into the risk estimation model, the follow-up data comparison is convenient, and the reliability of the estimation result is ensured. The risk prediction model can comprise risk grade information, a score range corresponding to each risk grade, an index set for evaluating the girth weld risk and a scoring range of each index. The risk prediction model can represent the self working state information of the conveying pipeline at the current moment of constructing the model. The risk level information refers to the number of set risk levels, a plurality of risk levels with different levels can be set according to the damage condition of the pipeline, the score range of the risk level of each level is different, and the current risk level can be determined based on the score condition of the conveying pipeline. The risk grade information and the score value range corresponding to each risk grade can be obtained by dividing the circumferential weld risk grade into four grades according to the standards of GB50369-2014 city-attacking construction acceptance criteria for oil and gas long-distance pipelines and the like, determining the quantization ranges corresponding to the four circumferential weld risk grades, and providing corresponding risk control requirements, wherein the specific risk grade can be shown in Table 1, for example. The index set may include a plurality of indexes for evaluating the risk, each index is an influence factor influencing the pipeline risk, each index may be a plurality of indexes at the same level or a plurality of indexes at different levels, so-called different levels, each level may be in a parallel relationship or a membership relationship, and those skilled in the art may determine the index set according to actual situations. For example, the influence factors of different attributes can be divided into different categories to form a hierarchical index set. And performing longitudinal weight distribution calculation on each evaluation index in the corresponding index set, and performing transverse comparison on indexes in different sets to obtain the weight and the score of each index.
TABLE 1 Risk level information and score Range corresponding to Each Risk level
Figure BDA0002526360440000081
S102: and based on a risk pre-estimation model, automatically calculating a risk weight value and a score value of each index of the circumferential weld according to the detection data and the basic parameter data in the conveying pipeline.
In the embodiment of the present invention, the detection data in the transmission pipeline is parameter data for detecting whether the pipeline is damaged, for example, the parameter data may be corrosion conditions in the pipe body, and pipeline strength and toughness test data. And calculating the risk weight grade of each index for evaluating the circumferential weld of the pipeline in the risk estimation model based on the detection data in the pipeline and the basic data of the pipeline, giving a scoring result by combining the field condition of the pipeline, and carrying out grading evaluation on the circumferential weld. When the indexes are scored, any scoring algorithm can be adopted, and the implementation of the method is not influenced.
In one implementation, a large amount of historical data may be used as training samples, the historical data is multiple sets of data formed by historical detection data of different types of transmission pipelines and corresponding scoring values and risk weight values of each index, a scoring model is generated by learning the historical data using, for example, a convolutional neural network model, and the model training process may refer to a corresponding training process of a neural network learning algorithm, which is not described herein again. After the model is scored after training, the risk weight values and the score values of all indexes of the girth weld can be obtained only by inputting the detection data and the basic parameter data in the conveying pipeline into the model.
S103: and when the pre-constructed consistency check relation is used for checking that the assignment of each risk weight value meets the condition, determining the association degree of each index and the girth weld risk level by using the pre-constructed girth weld risk association relation based on the risk weight value and the score value of each index so as to be used for determining the risk estimation information of the girth weld.
In order to reduce the degree of the main influence of the risk weight values, after the risk weight values are calculated in S102, the reliability of the weight assignment can be further calculated, that is, whether the assignment of each risk weight value meets the condition is judged. And when the judgment is that the evaluation index weight assignment is reliable after the consistency inspection is passed, determining the association degree of each index and the girth weld risk level by using the girth weld risk association relation, determining the association degree of the indexes and the girth weld risk level layer by layer when the indexes are integrated with a plurality of layers of indexes, and finally determining the girth weld risk evaluation level. The consistency check relation and the girth joint risk association relation are pre-established relations, the consistency check relation is used for checking whether the risk weight values meet conditions, the consistency check relation can be used for judging whether the accumulated sum of the risk weight values of all indexes is not larger than a preset sum threshold value or not, other check modes can be adopted, the technical personnel in the field can define the consistency check relation according to actual conditions, and the realization of the application is not influenced. The girth weld risk association relation is used for constructing the association degree of the indexes and the risk levels, the weight influence of each index on a target event can be comprehensively considered, the girth weld risk association relation can be determined based on the actual pipeline condition, for example, the external load of the current conveying pipeline is particularly large, the corrosion effect of conveying fluid on the pipeline is very large, the high association degree setting can be carried out on the indexes reflecting the external load and the pipeline corrosion and the high risk level, the association degree setting is carried out on other indexes and the low risk level, the realization of the method is not influenced, the method can be customized by technical personnel in the field according to the actual condition, and the method is not limited in the method.
In the technical scheme provided by the embodiment of the invention, a risk estimation model of the circumferential weld is constructed based on the specific actual condition of the pipeline, the basic characteristics of the pipeline are combined with index evaluation parameters, the risk weight values of all indexes of the circumferential weld of the pipeline are calculated based on the detection data in the pipeline and the basic data of the pipeline, the grading result is given by combining the field condition of the pipeline, and the circumferential weld is evaluated in a grading manner, so that the data comparison of subsequent models is facilitated, and the reliability of the estimation result can be ensured; through weight distribution calculation and inspection of the risk prediction model, weight calculation is carried out on different risk evaluation indexes in the evaluation process, the association level of cross-section influence factors in the weight distribution process is high, the weight value of each index on the girth weld can be comprehensively considered, the risk prediction reliability and accuracy are effectively improved, the degree of artificial subjective influence on the risk prediction process is greatly reduced, and the oil-gas pipeline weld management level is improved.
The embodiment does not limit the expression form of the risk estimation model, and the risk estimation model can be constructed by utilizing the classical domain, the node domain and the object element to be evaluated for facilitating subsequent calculation. The classical domain comprises the same number of matrixes as the total number of risk level grades, and each matrix element is determined by the number of indexes and the corresponding scoring range. The section area is determined by the full risk grade of the girth weld and the corresponding score range, and the object element to be evaluated consists of indexes and corresponding scoring results. The risk estimation model is directly connected with the index set system.
Optionally, an index system shown in fig. 2 may be constructed in the present application, where the risk prediction model index set includes a plurality of first-level indexes, and each first-level index further includes a plurality of second-level indexes. The primary indexes can comprise C1 weld defects, C2 material performance, C3 external load and C4 construction quality management, and for the primary indexes of the C1 weld defects, the secondary indexes below the primary indexes can comprise C11 girth weld film quality, C12 film rechecking results, C13 internal detection precision and C14 excavation verification conditions; for the first-grade performance indexes of the C2 material, the second-grade indexes of the C2 material comprise corrosion conditions of a C21 pipe body, standard C22 strength and toughness tests and C23 welding technology and method; for the C3 external load primary indicators, the secondary indicators below it may include the C31 design operating pressure ratio, C32 tie-in type, C33 geology, and C34 stress concentration locations; for the first-level indexes of C4 construction quality management, the second-level indexes below the first-level indexes can comprise C41 construction and detection compliance, a C42 suspected black opening and a C43 repair opening.
Taking the first-level risk evaluation index C1 of the girth weld and the risk grade shown in the table 1 as an example, and M is the full risk grade range of the girth weld; c is the risk index of the whole circumferential weld; m1、M2、M3、M4Four risk classes for the girth weld; c1、C2、C3、C4Four primary indexes are provided; s1Is the first grade index to be evaluated; c11、C12、C13、C14Is C1The secondary index of (4). Classical domain (R)1、R2、R3、R4) Section (R) and matter element to be evaluated (R)e) Can be expressed in the following form:
Figure BDA0002526360440000111
Figure BDA0002526360440000112
Figure BDA0002526360440000113
the embodiment of the invention divides the index set in detail, and the constructed index system can more accurately reflect the actual condition of the conveying pipeline; in addition, the model is constructed in a matrix form, so that subsequent data processing is facilitated.
In the above embodiment, how to execute step S103 is not limited, and an implementation manner of checking that the assigned values of the risk weight values satisfy the conditions by using a pre-constructed consistency check relation is provided in this embodiment, please refer to fig. 3, which may include the following contents:
s1031: and obtaining the relative importance among the indexes by using a scaling method based on the risk prediction model in advance to construct an index weight judgment matrix.
After the risk prediction model is constructed, a ring index weight judgment matrix A can be constructed by performing weighted judgment on relative importance of each index based on contained information in the risk prediction model by using an A.L. Saaty1-9 scaling method. Specifically, a questionnaire method can be used to obtain a weighted comparison of the scoring expert group for each index. According to the Saaty1-9 scaling method, an index weight judgment matrix is established according to the relative importance among indexes, and an index weight judgment matrix A which is established by taking 4 primary indexes shown in FIG. 2 as an example can be expressed as follows:
Figure BDA0002526360440000121
the index weight judgment matrix is constructed by weighting and judging the relative importance of each index, and the risk weight value of each index can be determined by calculating the characteristic vector of the index weight judgment matrix. For example, after the product of each row of elements of the index weight determination matrix a is calculated, the obtained result is subjected to corresponding element quantity value rooting and normalization, and the determination matrix eigenvector w is obtained (0.4231, 0.2274, 0.1222, 0.2274). Then the four primary indexes of the ring weld risk evaluation are respectively C1-0.4231, C2-0.2274, C3-0.1222 and C4-0.2274.
S1032: and calculating to obtain the maximum characteristic root value of the index weight judgment matrix by using the maximum characteristic value calculation relational expression.
The present application may employ transverse linksCalculation of maximum feature root lambda by multiplication root-finding methodMAXIf (AW)iWeight factor, w, for the i-th indexiThe risk weight value of the ith index is n, and the n is the total number of the indexes; the maximum feature value calculation relation can be expressed as:
Figure BDA0002526360440000122
the weight factor may be determined according to the index weight judgment matrix and the risk weight value of each index, and the weight factor expression matrix AW calculated by taking the index weight judgment matrix and the risk weight value of each index as an example in the above example may be represented as:
Figure BDA0002526360440000123
the weight factor represents a weight shadow factor of one index corresponding to each matrix element of the matrix.
S1033: and calculating a consistency index value by utilizing a consistency index calculation relational expression based on the maximum characteristic root value.
After the maximum feature root value is obtained by calculation in S1032, a consistency index value may be calculated using a consistency index calculation relation, where CI is a consistency index value, and the consistency index calculation relation may be expressed as:
Figure BDA0002526360440000131
s1034: the consistency ratio is calculated by using a consistency ratio calculation relational expression based on the consistency index value.
The consistency ratio calculation relationship may be expressed as:
Figure BDA0002526360440000132
in the formula, RI is an average random consistency row index value, and CR is a consistency ratio. The average random consistency row index value may be as shown in table 2:
TABLE 2 table of indexes of average random consistency
Order of the scale 3 4 5 6 7 8 9 10
RI 0.52 0.89 1.12 1.26 1.36 1.41 1.46 1.49
S1025: if the consistency ratio value is within a preset allowable range, the assignment of each risk weight value meets the condition; and if the consistency ratio value is not in the allowable range, the assignment of each risk weight value does not meet the condition.
If the result passes consistency check, the characteristic vector w of the index weight judgment matrix is the weight value of the corresponding evaluation index. And if the result does not pass the consistency test, namely the assignment of each risk weight value does not meet the condition, adjusting the index weight judgment matrix according to a preset weight adjustment rule, and calculating the characteristic vector and the maximum characteristic root value of the adjusted index weight judgment matrix until the consistency ratio calculated according to the updated characteristic vector and the maximum characteristic root value is in an allowable range. For example, if the obtained consistency ratio CR is less than 0.1, the judgment matrix is proved to pass the consistency check. The weight adjustment rule is to replace the scoring method again to score each element in the index weight judgment matrix A or adjust the score value in a small range up and down on the basis of the original score value, and then calculate the characteristic vector of the index weight judgment matrix A.
For example, based on the weight factor expression matrix AW and the index weight judgment matrix a, the maximum feature root value calculated by using the calculation relation (1) is:
Figure BDA0002526360440000141
and (3) carrying out consistency check on the index weight judgment matrix A according to the formula (2) to obtain:
Figure BDA0002526360440000142
the value of the consistency ratio obtained according to the formula (3) is
Figure BDA0002526360440000143
0.0039 is less than 0.1, so the index weight judgment matrix A passes consistency test, and evaluation index weight assignment has reliability. And then, carrying out evaluation index weight calculation on each group of secondary indexes by using the same method.
According to the method, the risk weight value of each index is calculated by adopting a method for calculating the characteristic vector of the index weight judgment matrix, the indexes are scored by combining a questionnaire survey method with an A.L. Saaty1-9 scaling method, and the reliability verification is carried out on the calculated risk weight value, so that the influence of artificial subjective factors is reduced, and the risk estimation accuracy is improved.
In the foregoing embodiment, how to perform step S103 is not limited, in this embodiment, an implementation is provided that determines the association degree between each index and the girth weld risk level by using a pre-constructed girth weld risk association relation based on a risk weight value and a score value of each index, it can be understood that this step has a direct relationship with an index set, for the index system shown in fig. 2, that is, the risk prediction model index set includes a plurality of primary indexes, and each primary index further includes a plurality of secondary indexes, as shown in fig. 4, S103 may include the following steps:
s1036: and respectively and sequentially calculating the index association value of each secondary index and each primary index by using the circumferential weld risk association relation.
In the embodiment of the present invention, the circumferential weld risk correlation equation may be expressed as:
Figure BDA0002526360440000151
Figure BDA0002526360440000152
Figure BDA0002526360440000153
in the formula, KijThe degree of association of the second-level index corresponding to the first-level index is obtained; n isikScoring the secondary index; n is a radical ofjIs the grade corresponding to the index score, NiIs the overall grade corresponding to the index score, aji、bjiThe upper limit and the lower limit of the grade of the second-level index are scored; a isi、biThe upper limit and the lower limit of the grade of the whole grade of the second-level index are marked; rho is the pasting progress of the evaluation index and the corresponding threshold; j is 1, 2, 3, 4.
S1037: and for each first-level index, calculating according to the risk weight value and the index association degree value of each second-level index belonging to the current first-level index to obtain an index association degree matrix of the current first-level index.
In the embodiment of the present invention, the index association matrix may be expressed as:
Figure BDA0002526360440000154
in the formula, K (C)i) An index association matrix, w, for the ith primary indexinThe risk weight value k corresponding to each secondary index of the ith primary indexm(cin) The index association value of each secondary index of the ith primary index.
S1038: and calculating according to the risk weight value of each first-level index and the index association matrix to obtain a risk estimation association matrix.
After the index association matrix of each primary index is obtained in S1037, a risk prediction association matrix may be obtained by calculation based on the following relation:
Figure BDA0002526360440000161
wherein K (S) is a risk prediction correlation matrix, K (C)n) An index association matrix, w, for the nth primary indexcnThe risk weight value of the nth primary index.
S1039: and determining the risk grade of the conveying pipeline according to the risk estimation association matrix to be used as risk estimation information to be output.
In this step, the risk grade corresponding to the maximum value in the risk estimation association matrix can be the circumferential weld risk evaluation corresponding grade according to the maximum membership principle. That is, the risk prediction information can be output according to the following processes:
determining the maximum matrix element value from the risk prediction association degree matrix to be used as a risk prediction value;
matching the risk pre-evaluation value with a value range corresponding to each risk grade in the risk pre-evaluation model;
and taking the risk grade corresponding to the score range of the risk estimated value as the risk grade of the girth weld.
In order to make the technical solution of the present application more clearly understood, the process of determining the risk level is described by taking the index system shown in fig. 2, the risk level information shown in table 1, and the index weight determination matrix a constructed in S1021 as an example, and may include the following contents:
the index association value of each secondary index and each primary index under the index C1 can be calculated based on the calculation relation (4):
Figure BDA0002526360440000162
Figure BDA0002526360440000163
Figure BDA0002526360440000171
Figure BDA0002526360440000172
Figure BDA0002526360440000173
Figure BDA0002526360440000174
Figure BDA0002526360440000175
Figure BDA0002526360440000176
Figure BDA0002526360440000177
the index association values of the secondary indexes and the primary indexes under the C2 primary index, the C3 primary index and the C4 primary index are respectively calculated according to the above manner to obtain the girth weld risk evaluation index weight and association information, as shown in Table 3:
TABLE 3 Risk assessment index weight and relevance table for circumferential weld
Figure BDA0002526360440000178
Figure BDA0002526360440000181
Figure BDA0002526360440000191
Taking the first-level index weld defect C1 as an example, an index correlation matrix K (C1) is calculated according to the formula (5), and the calculation steps are as follows:
Figure BDA0002526360440000192
by using the method, the index association degree matrix of other first-level indexes can be calculated:
K(C2)＝(-0.3454 0.2696 -0.1055 -0.5505)。
K(C3)＝(-0.1157 0.4207 -0.3403 -0.6647)。
K(C4)＝(0.4476 -0.3238 -0.7008 -0.7665)。
according to the first-level index correlation degree and the weight coefficient, a risk prediction correlation degree matrix can be calculated by using a calculation relation (6) as follows:
Figure BDA0002526360440000201
calculating to obtain a circumferential weld risk evaluation incidence matrix, wherein KMAX(S)＝0.2114＝K1(S). And determining the risk grade of the evaluated girth weld as grade I, wherein the risk level is low and the risk can be ignored. The method is adopted to carry out long-distance oil transportationThe risk evaluation of the circumferential weld of the gas pipeline can be carried out aiming at the evaluation of a single circumferential weld and the circumferential weld in a section of pipeline. And further carrying out refined integrity evaluation on the girth weld with a high-risk evaluation result, determining low-grade items in the risk evaluation process, effectively modifying and improving the reliability of the girth weld.
It should be noted that, in the present application, there is no strict sequential execution order among the steps, and as long as a logical order is met, the steps may be executed simultaneously or according to a certain preset order, and fig. 1, fig. 3, and fig. 4 are only schematic manners, and do not represent that only such an execution order is available.
The embodiment of the invention also provides a corresponding device for the circumferential weld risk estimation method of the conveying pipeline, so that the method has higher practicability. Wherein the means can be described separately from the functional module point of view and the hardware point of view. In the following, the circumferential weld risk estimation device of the conveying pipeline provided by the embodiment of the invention is introduced, and the circumferential weld risk estimation device of the conveying pipeline described below and the circumferential weld risk estimation method of the conveying pipeline described above may be referred to in a corresponding manner.
Based on the angle of the functional module, referring to fig. 5, fig. 5 is a structural diagram of a circumferential weld risk estimation device of a conveying pipeline according to an embodiment of the present invention, in a specific implementation manner, the device may include:
the risk prediction model determining module 501 is used for determining a risk prediction model corresponding to a girth weld of a conveying pipeline based on basic parameter data of the conveying pipeline of the urban building group; the risk estimation model comprises risk grade information, a score range corresponding to each risk grade, an index set for evaluating the girth weld risk and a scoring range of each index.
And the index weight and score calculating module 502 is used for automatically calculating the risk weight value and the score value of each index of the girth weld according to the detection data and the basic parameter data in the conveying pipeline based on the risk pre-estimation model.
The consistency checking module 503 is configured to check whether the assignment of each risk weight value satisfies a condition by using a consistency checking relation established in advance.
And a risk estimation module 504, configured to determine, when the pre-established consistency check relation is used to check that the assignment of each risk weight value satisfies a condition, a degree of association between each indicator and a girth weld risk level by using the pre-established girth weld risk association relation based on the risk weight value and the score value of each indicator, so as to determine risk estimation information of the girth weld.
Optionally, in some implementations of this embodiment, the risk estimation module 504 may include, for example:
the index association value calculation submodule is used for respectively and sequentially calculating the index association value of each secondary index and each primary index by utilizing the circumferential weld risk association relation; the risk estimation model index set comprises a plurality of first-level indexes, and each first-level index further comprises a plurality of second-level indexes.
And the index association degree matrix calculation submodule is used for calculating each first-level index according to the risk weight value and the index association degree value of each second-level index belonging to the current first-level index to obtain the index association degree matrix of the current first-level index.
And the risk estimation association matrix calculation submodule is used for calculating to obtain a risk estimation association matrix according to the risk weight value of each primary index and the index association matrix.
And the risk grade determining submodule is used for determining the risk grade of the conveying pipeline according to the risk estimation association degree matrix so as to output the risk grade as risk estimation information.
In other embodiments of this embodiment, the consistency check module 503 may include:
and the index weight judgment matrix construction submodule is used for obtaining the relative importance among the indexes by using a scaling method on the basis of the risk estimation model in advance so as to construct an index weight judgment matrix.
Maximum feature root value calculation submodule for utilizing
Figure BDA0002526360440000211
And calculating to obtain the maximum characteristic root value of the index weight judgment matrix.
A consistency index calculation submodule for utilizing based on the maximum characteristic root value
Figure BDA0002526360440000221
And calculating to obtain a consistency index value.
A consistency ratio calculation submodule for utilizing the consistency index value
Figure BDA0002526360440000222
The consistency ratio is calculated.
The condition judgment submodule is used for judging whether the consistency ratio value is within a preset allowable range or not according to the set condition; and if the consistency ratio value is not in the allowable range, the assignment of each risk weight value does not meet the condition.
In the formula, λMAXIs the maximum characteristic root value (AW)iWeight factor, w, for the i-th indexiThe risk weight value of the ith index is n, and the n is the total number of the indexes; the weight factor is determined according to the index weight judgment matrix and the risk weight value of each index; CI is a consistency index value; RI is the average random consistency row index value, and CR is the consistency ratio.
As an optional implementation manner of the present application, the apparatus may further include a weight adjustment module, where the weight adjustment module is configured to adjust the index weight determination matrix according to a preset weight adjustment rule, and calculate a feature vector and a maximum feature root value of the adjusted index weight determination matrix until a consistency ratio calculated according to the updated feature vector and the maximum feature root value is within an allowable range.
The functions of each functional module of the circumferential weld risk estimation device of the conveying pipeline according to the embodiment of the present invention may be specifically implemented according to the method in the embodiment of the method, and the specific implementation process may refer to the related description of the embodiment of the method, which is not described herein again.
Therefore, the method and the device effectively reduce the influence degree of the circumferential weld risk estimation process by human subjective factors, and improve the accuracy of the circumferential weld risk estimation of the conveying pipeline.
The circumferential weld risk estimation device for the conveying pipeline is described from the perspective of the functional module, and further, the application also provides a circumferential weld risk estimation device for the conveying pipeline, which is described from the perspective of hardware. Fig. 6 is a structural diagram of another circumferential weld risk estimation device for a conveying pipeline according to an embodiment of the present disclosure. As shown in fig. 6, the apparatus comprises a memory 60 for storing a computer program;
a processor 61, configured to execute a computer program to implement the steps of the circumferential weld risk estimation method for a transmission pipeline according to any of the above embodiments.
The processor 61 may include one or more processing cores, such as a 4-core processor, an 8-core processor, and the like. The processor 61 may be implemented in at least one hardware form of a DSP (Digital Signal Processing), an FPGA (Field-Programmable Gate Array), and a PLA (Programmable Logic Array). The processor 61 may also include a main processor and a coprocessor, where the main processor is a processor for processing data in an awake state, and is also called a Central Processing Unit (CPU); a coprocessor is a low power processor for processing data in a standby state. In some embodiments, the processor 61 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content required to be displayed on the display screen. In some embodiments, the processor 61 may further include an AI (Artificial Intelligence) processor for processing computing operations related to machine learning.
Memory 60 may include one or more computer-readable storage media, which may be non-transitory. Memory 60 may also include high speed random access memory, as well as non-volatile memory, such as one or more magnetic disk storage devices, flash memory storage devices. In this embodiment, the memory 60 is at least used for storing a computer program 601, wherein the computer program is loaded and executed by the processor 61, and then the relevant steps of the circumferential weld risk estimation method for a transmission pipeline disclosed in any one of the foregoing embodiments can be implemented. In addition, the resources stored by the memory 60 may also include an operating system 602, data 603, and the like, and the storage may be transient storage or permanent storage. Operating system 602 may include Windows, Unix, Linux, etc., among others. Data 603 may include, but is not limited to, data corresponding to test results, and the like.
In some embodiments, the circumferential weld risk estimation device of the conveying pipeline may further include a display screen 62, an input/output interface 63, a communication interface 64, a power supply 65, and a communication bus 66, and may further include a sensor 67, for example.
Those skilled in the art will appreciate that the configuration shown in FIG. 6 does not constitute a limitation of the girth weld risk estimation arrangement of the delivery conduit and may include more or fewer components than those shown, such as sensors 67.
The functions of each functional module of the circumferential weld risk estimation device of the conveying pipeline according to the embodiment of the present invention may be specifically implemented according to the method in the embodiment of the method, and the specific implementation process may refer to the related description of the embodiment of the method, which is not described herein again.
Therefore, the method and the device effectively reduce the influence degree of the circumferential weld risk estimation process by human subjective factors, and improve the accuracy of the circumferential weld risk estimation of the conveying pipeline.
It is understood that, if the circumferential weld risk estimation method of the conveying pipeline in the above embodiments is implemented in the form of a software functional unit and sold or used as a stand-alone product, it may be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application may be substantially or partially implemented in the form of a software product, which is stored in a storage medium and executes all or part of the steps of the methods of the embodiments of the present application, or all or part of the technical solutions. And the aforementioned storage medium includes: a U disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), an electrically erasable programmable ROM, a register, a hard disk, a removable magnetic disk, a CD-ROM, a magnetic or optical disk, and other various media capable of storing program codes.
Based on this, the embodiment of the present invention further provides a computer-readable storage medium, in which a circumferential weld risk estimation program of a conveying pipeline is stored, and when the circumferential weld risk estimation program of the conveying pipeline is executed by a processor, the steps of the circumferential weld risk estimation method of the conveying pipeline according to any one of the above embodiments are provided.
The functions of the functional modules of the computer-readable storage medium according to the embodiment of the present invention may be specifically implemented according to the method in the foregoing method embodiment, and the specific implementation process may refer to the related description of the foregoing method embodiment, which is not described herein again.
Therefore, the method and the device effectively reduce the influence degree of the circumferential weld risk estimation process by human subjective factors, and improve the accuracy of the circumferential weld risk estimation of the conveying pipeline.
The embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same or similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The circumferential weld risk estimation method and device for the conveying pipeline and the computer readable storage medium provided by the application are described in detail above. The principles and embodiments of the present invention are explained herein using specific examples, which are presented only to assist in understanding the method and its core concepts. It should be noted that, for those skilled in the art, it is possible to make various improvements and modifications to the present invention without departing from the principle of the present invention, and those improvements and modifications also fall within the scope of the claims of the present application.

Claims (10)

1. A circumferential weld risk estimation method for a conveying pipeline is characterized by comprising the following steps:
determining a risk estimation model corresponding to a girth weld of a conveying pipeline based on basic parameter data of the conveying pipeline of the urban building group; the risk estimation model comprises risk grade information, a score range corresponding to each risk grade, an index set for evaluating the girth weld risk and a scoring range of each index;
based on the risk pre-estimation model, automatically calculating a risk weight value and a score value of each index of the girth weld according to detection data in the conveying pipeline and the basic parameter data;
when the pre-constructed consistency check relation is used for checking that the assignment of each risk weight value meets the condition, determining the association degree of each index and the girth weld risk level by using the pre-constructed girth weld risk association relation based on the risk weight value and the score value of each index so as to be used for determining the risk estimation information of the girth weld.
2. The circumferential weld risk estimation method of the transmission pipeline according to claim 1, wherein the risk estimation model index set includes a plurality of primary indexes, each of the primary indexes further includes a plurality of secondary indexes, and determining the degree of association between each index and the circumferential weld risk level by using a pre-established circumferential weld risk association relation based on a risk weight value and a score value of each index for determining the risk estimation information of the transmission pipeline includes:
respectively and sequentially calculating the index association value of each secondary index and each primary index by using the circumferential weld risk association relation;
for each first-level index, calculating according to the risk weight value and the index association degree value of each second-level index belonging to the current first-level index to obtain an index association degree matrix of the current first-level index;
calculating according to the risk weight value of each first-level index and the index association matrix to obtain a risk estimation association matrix;
and determining the risk grade of the conveying pipeline according to the risk estimation association matrix to serve as the risk estimation information to be output.
3. The circumferential weld risk estimation method of the conveying pipeline according to claim 2, wherein the determining the risk level of the circumferential weld according to the risk estimation correlation matrix to output as the risk estimation information comprises:
determining the maximum matrix element value from the risk prediction association matrix as a risk prediction value;
matching the risk pre-evaluation value with a value range corresponding to each risk grade in the risk pre-evaluation model;
and taking the risk grade corresponding to the score range of the risk estimated value as the risk grade of the girth weld.
4. The circumferential weld risk estimation method of the conveying pipeline according to any one of claims 1 to 3, wherein the verifying that the assignment of each risk weight value meets the condition by using a pre-constructed consistency check relation comprises:
obtaining the relative importance among all indexes by using a scaling method based on the risk estimation model in advance to construct an index weight judgment matrix;
by using
Figure FDA0002526360430000021
Calculating to obtain the index weightJudging the maximum characteristic root value of the matrix;
based on the maximum feature root value utilization
Figure FDA0002526360430000022
Calculating to obtain a consistency index value;
utilizing based on the consistency index value
Figure FDA0002526360430000023
Calculating to obtain a consistency ratio;
if the consistency ratio value is within a preset allowable range, the assignment of each risk weight value meets the condition; if the consistency ratio value is not in the allowable range, the assignment of each risk weight value does not meet the condition;
in the formula, λMAXIs the maximum root of feature, (AW)iWeight factor, w, for the i-th indexiThe risk weight value of the ith index is n, and the n is the total number of the indexes; the weight factor is determined according to the index weight judgment matrix and the risk weight value of each index; CI is the consistency index value; RI is the average random consistency row index value, and CR is the consistency ratio.
5. The circumferential weld risk estimation method of a transmission pipeline according to claim 4, wherein each risk weight value is determined according to an eigenvector value of the index weight judgment matrix, and after the assignment of each risk weight value does not satisfy a condition, the method further comprises:
and adjusting the index weight judgment matrix according to a preset weight adjustment rule, and calculating the characteristic vector and the maximum characteristic root value of the adjusted index weight judgment matrix until the consistency ratio calculated according to the updated characteristic vector and the maximum characteristic root value is in the allowable range.
6. The utility model provides a circumferential weld risk prediction device of pipeline which characterized in that includes:
the risk estimation model determining module is used for determining a risk estimation model corresponding to a girth weld of the conveying pipeline based on basic parameter data of the conveying pipeline of the urban building group; the risk estimation model comprises risk grade information, a score range corresponding to each risk grade, an index set for evaluating the girth weld risk and a scoring range of each index;
the index weight and score calculation module is used for automatically calculating a risk weight value and a score value of each index of the girth weld according to the detection data in the conveying pipeline and the basic parameter data based on the risk estimation model;
the consistency checking module is used for checking whether the assignment of each risk weight value meets the condition or not by using a pre-constructed consistency checking relational expression;
and the risk estimation module is used for determining the association degree of each index and the girth weld risk level by using the pre-constructed girth weld risk association relation based on the risk weight value and the score value of each index when the pre-constructed consistency check relation is used for checking that the assignment of each risk weight value meets the condition, so as to determine the risk estimation information of the girth weld.
7. The circumferential weld risk estimation device of a conveying pipeline according to claim 6, wherein the risk estimation module comprises:
the index association value calculation submodule is used for respectively and sequentially calculating the index association value of each secondary index and each primary index by utilizing the circumferential weld risk association relation; the risk estimation model index set comprises a plurality of first-level indexes, and each first-level index further comprises a plurality of second-level indexes;
the index association degree matrix calculation submodule is used for calculating each first-level index according to the risk weight value and the index association degree value of each second-level index belonging to the current first-level index to obtain an index association degree matrix of the current first-level index;
the risk estimation association degree matrix calculation submodule is used for calculating according to the risk weight value of each primary index and the index association degree matrix to obtain a risk estimation association degree matrix;
and the risk grade determining submodule is used for determining the risk grade of the conveying pipeline according to the risk estimation association degree matrix so as to output the risk grade as the risk estimation information.
8. The girth weld risk estimation device of a conveying pipeline according to claim 6 or 7, wherein the consistency check module comprises:
the index weight judgment matrix construction submodule is used for obtaining the relative importance among the indexes by using a scaling method on the basis of the risk estimation model in advance so as to construct an index weight judgment matrix;
maximum feature root value calculation submodule for utilizing
Figure FDA0002526360430000041
Calculating to obtain the maximum characteristic root value of the index weight judgment matrix;
a consistency index calculation submodule for utilizing based on the maximum characteristic root value
Figure FDA0002526360430000042
Calculating to obtain a consistency index value;
a consistency ratio calculation submodule for utilizing the consistency index value based on the consistency ratio
Figure FDA0002526360430000043
Calculating to obtain a consistency ratio;
the condition judgment submodule is used for judging whether the consistency ratio value is within a preset allowable range or not according to the set condition; if the consistency ratio value is not in the allowable range, the assignment of each risk weight value does not meet the condition;
in the formula, λMAXIs the maximum root of feature, (AW)iWeight factor, w, for the i-th indexiThe risk weight value of the ith index is n, and the n is the total number of the indexes; the weight factor is determined according to the index weight judgment matrix and the risk weight value of each index(ii) a CI is the consistency index value; RI is the average random consistency row index value, and CR is the consistency ratio.
9. A circumferential weld risk estimation device for a transportation pipeline, comprising a processor for implementing the steps of the circumferential weld risk estimation method for a transportation pipeline according to any one of claims 1 to 5 when executing a computer program stored in a memory.
10. A computer readable storage medium, wherein the computer readable storage medium stores thereon a girth weld risk estimation program of a transmission pipeline, which when executed by a processor implements the steps of the girth weld risk estimation method of the transmission pipeline according to any one of claims 1 to 5.
CN202010505385.2A 2020-06-05 2020-06-05 Circumferential weld risk prediction method and device for conveying pipeline and readable storage medium Active CN111666684B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202010505385.2A CN111666684B (en) 2020-06-05 2020-06-05 Circumferential weld risk prediction method and device for conveying pipeline and readable storage medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202010505385.2A CN111666684B (en) 2020-06-05 2020-06-05 Circumferential weld risk prediction method and device for conveying pipeline and readable storage medium

Publications (2)

Publication Number Publication Date
CN111666684A true CN111666684A (en) 2020-09-15
CN111666684B CN111666684B (en) 2023-08-29

Family

ID=72386442

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202010505385.2A Active CN111666684B (en) 2020-06-05 2020-06-05 Circumferential weld risk prediction method and device for conveying pipeline and readable storage medium

Country Status (1)

Country Link
CN (1) CN111666684B (en)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112257280A (en) * 2020-10-29 2021-01-22 桂林电子科技大学 Liquid-solid phase continuous form prediction method for reflow soldering BGA group soldering points
CN114662391A (en) * 2022-03-24 2022-06-24 深圳市深水水务咨询有限公司 Method and system for improving anti-leakage performance of water supply and drainage pipeline
CN116341966A (en) * 2023-03-16 2023-06-27 中国石油大学(北京) Pipeline girth weld vulnerability evaluation method and device, electronic equipment and storage medium

Citations (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110155711A1 (en) * 2009-12-31 2011-06-30 Thomas Edward Doyle Adaptive control of arc welding parameters
US20160145994A1 (en) * 2014-11-20 2016-05-26 Petrochina Company Limited Evaluation Method and Evaluation Device for Water Breakthrough Risk of Production Wells in Aquifer Drive Gas Reservoirs
WO2017008180A1 (en) * 2015-07-16 2017-01-19 广东产品质量监督检验研究院 Photovoltaic module failure risk determination method
CN107283083A (en) * 2016-03-31 2017-10-24 中国石油天然气股份有限公司 circumferential weld evaluation method and device
CN108224096A (en) * 2018-01-03 2018-06-29 中国石油大学(华东) A kind of city oil-gas pipeline major accident Risk-warning appraisal procedure
CN108764641A (en) * 2018-04-27 2018-11-06 中国石油天然气股份有限公司 Oil-gas pipeline body and welding seam defect risk evaluation method
CN108921372A (en) * 2018-05-17 2018-11-30 西南交通大学 Based on step analysis and the freeway tunnel operation security risk evaluating method that matter-element can be opened up
CN109118074A (en) * 2018-08-03 2019-01-01 广州供电局有限公司 Electric operating methods of risk assessment, device, computer equipment and storage medium
CN109815981A (en) * 2018-12-19 2019-05-28 中国石油天然气股份有限公司 Method and device for determining risk level of girth weld and readable storage medium
CN110728449A (en) * 2019-10-10 2020-01-24 广西电网有限责任公司 Risk management and control evaluation method
WO2020037942A1 (en) * 2018-08-20 2020-02-27 平安科技（深圳）有限公司 Risk prediction processing method and apparatus, computer device and medium
CN110851918A (en) * 2018-07-25 2020-02-28 中国石油化工股份有限公司 Method and device for evaluating reliability of pipeline girth weld defects
CN111156425A (en) * 2020-01-15 2020-05-15 中国石油大学(北京) Pipeline state monitoring method, device and system

Patent Citations (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110155711A1 (en) * 2009-12-31 2011-06-30 Thomas Edward Doyle Adaptive control of arc welding parameters
US20160145994A1 (en) * 2014-11-20 2016-05-26 Petrochina Company Limited Evaluation Method and Evaluation Device for Water Breakthrough Risk of Production Wells in Aquifer Drive Gas Reservoirs
WO2017008180A1 (en) * 2015-07-16 2017-01-19 广东产品质量监督检验研究院 Photovoltaic module failure risk determination method
CN107283083A (en) * 2016-03-31 2017-10-24 中国石油天然气股份有限公司 circumferential weld evaluation method and device
CN108224096A (en) * 2018-01-03 2018-06-29 中国石油大学(华东) A kind of city oil-gas pipeline major accident Risk-warning appraisal procedure
CN108764641A (en) * 2018-04-27 2018-11-06 中国石油天然气股份有限公司 Oil-gas pipeline body and welding seam defect risk evaluation method
CN108921372A (en) * 2018-05-17 2018-11-30 西南交通大学 Based on step analysis and the freeway tunnel operation security risk evaluating method that matter-element can be opened up
CN110851918A (en) * 2018-07-25 2020-02-28 中国石油化工股份有限公司 Method and device for evaluating reliability of pipeline girth weld defects
CN109118074A (en) * 2018-08-03 2019-01-01 广州供电局有限公司 Electric operating methods of risk assessment, device, computer equipment and storage medium
WO2020037942A1 (en) * 2018-08-20 2020-02-27 平安科技（深圳）有限公司 Risk prediction processing method and apparatus, computer device and medium
CN109815981A (en) * 2018-12-19 2019-05-28 中国石油天然气股份有限公司 Method and device for determining risk level of girth weld and readable storage medium
CN110728449A (en) * 2019-10-10 2020-01-24 广西电网有限责任公司 Risk management and control evaluation method
CN111156425A (en) * 2020-01-15 2020-05-15 中国石油大学(北京) Pipeline state monitoring method, device and system

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
崔祥;张云宁;吴蓉;杨帆;: "基于物元可拓理论的输变电工程造价风险评价" *
王露;范小艳;张长征;: "基于物元可拓理论的高层建筑施工安全风险评估研究" *

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112257280A (en) * 2020-10-29 2021-01-22 桂林电子科技大学 Liquid-solid phase continuous form prediction method for reflow soldering BGA group soldering points
CN114662391A (en) * 2022-03-24 2022-06-24 深圳市深水水务咨询有限公司 Method and system for improving anti-leakage performance of water supply and drainage pipeline
CN116341966A (en) * 2023-03-16 2023-06-27 中国石油大学(北京) Pipeline girth weld vulnerability evaluation method and device, electronic equipment and storage medium
CN116341966B (en) * 2023-03-16 2023-12-22 中国石油大学(北京) Pipeline girth weld vulnerability evaluation method and device, electronic equipment and storage medium

Also Published As

Publication number Publication date
CN111666684B (en) 2023-08-29

Similar Documents

Publication Publication Date Title
CN111666684B (en) Circumferential weld risk prediction method and device for conveying pipeline and readable storage medium
El-Abbasy et al. Artificial neural network models for predicting condition of offshore oil and gas pipelines
CN105825342A (en) Pipeline failure possibility evaluation method and system
CN104063612B (en) A kind of Tunnel Engineering risk profiles fuzzy evaluation method and assessment system
CN108801387B (en) System and method for measuring remaining oil quantity of airplane fuel tank based on learning model
CN111737642A (en) Comprehensive evaluation method for failure risk of submarine pipeline based on fuzzy network analysis method
CN109325263A (en) Truss bridge damage position neural network based and damage extent identification method
CN103868985A (en) Defect quantified comprehensive safety judgment method for on-service pressure container
Chen et al. Considering the decision maker’s attitudinal character to solve multi-criteria decision-making problems in an intuitionistic fuzzy environment
CN111664365A (en) Oil and gas pipeline leakage detection method based on improved VMD and 1DCNN
CN107230021A (en) The method of high frequency zone water supply network leakage region
CN115270527B (en) Real-time assessment method, equipment and storage medium for road collapse risk
CN113379238A (en) Risk assessment method and device and electronic equipment
CN111861238A (en) Expressway bridge engineering risk assessment method and device and computer equipment
CN102103715A (en) Negative binomial regression-based maritime traffic accident investigation analysis and prediction method
CN103838931A (en) Method for evaluating remanufacturing access period of engineering mechanical arm rest class structure
CN112016857B (en) Polyethylene pipeline earthquake vulnerability assessment method based on cloud theory
CN112257942A (en) Stress corrosion cracking prediction method and system
Shabani et al. Probabilistic modelling of free spanning pipelines considering multiple failure modes
CN110990938B (en) Soft measurement method for tunnel face in rock digging state
CN117993306B (en) Method, system and medium for calibrating simulation parameters of pipe network
CN106327404A (en) Multi-source data collision detection and resolution method for comprehensive disaster assessment
Li et al. An empirical formula to assess ultimate strength of initially deflected plate: Part 2= combined longitudinal compression and lateral pressure
CN114638166A (en) Method, system, equipment and medium for identifying and predicting fatigue damage of process pipeline
Qiao et al. Dynamic assessment method for human factor risk of manned deep submergence operation system based on SPAR-H and SD

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant
TR01 Transfer of patent right

Effective date of registration: 20230919

Address after: 100000 22 Chaoyangmen North Street, Chaoyang District, Beijing.

Patentee after: CHINA PETROLEUM & CHEMICAL Corp.

Patentee after: National Petroleum and natural gas pipeline network Group Co.,Ltd.

Address before: Room 1402, No. 81 Zhongshan 7th Road, Liwan District, Guangzhou City, Guangdong Province, 510145

Patentee before: South China branch of Sinopec Sales Co.,Ltd.

TR01 Transfer of patent right