A high-grade steel pipeline safety scoring method, device, system and storage medium

Abstract

The application provides a high-steel-grade pipeline safety scoring method, device and system and a storage medium, and belongs to the pipeline evaluation field. The method comprises the following steps: scoring material data to obtain an initial material score set; scoring load data to obtain an initial load score set; scoring defect data to obtain an initial defect score set; performing weight analysis on the initial material score set, the initial load score set and the initial defect score set to obtain a target material weight set, a target load weight set and a target defect weight set; and performing scoring calculation on the initial material score set, the initial load score set, the initial defect score set, the target material weight set, the target load weight set and the target defect weight set to obtain a pipeline safety score. The application masters the safety state of the high-steel-grade pipeline, solves the problem that the commonly used safety evaluation method cannot be directly used for the high-steel-grade oil and gas pipeline, and provides a basis for pipeline safety management.

Description

Technical Field

[0001] This invention mainly relates to the field of pipeline evaluation technology, specifically to a method, device, system, and storage medium for safety scoring of high-grade steel pipelines. Background Technology

[0002] With advancements in pipe manufacturing technology and welding processes, oil and gas pipelines are developing towards higher steel grades and larger diameters, with increasingly higher transport pressures. Operational safety has always been a primary concern for pipeline companies, but in recent years, several high-steel pipeline failures have occurred, causing significant economic losses and adverse social impacts.

[0003] Domestic and international scholars have conducted extensive research on pipeline accidents, developing various evaluation models to calculate pipeline failure probabilities. The most commonly used models are historical data failure analysis models, fault tree analysis models, and structural reliability models. Historical data failure analysis models are primarily based on oil and gas pipeline failure databases, statistically analyzing historical oil and gas pipeline accident data to obtain the types and proportions of failure factors causing pipeline accidents, and then calculating the basic failure probability of the oil and gas pipeline. Fault tree analysis models treat pipeline failure accidents as the top event, deriving the factors causing accidents at each level until the bottom event is reached; simultaneously, they list the various factors causing accidents layer by layer in logical order, and calculations can determine the probability of a series of accidents occurring. Structural reliability models, on the other hand, consider that the causes of pipeline failures are often not singular, but rather a combination of multiple uncertain factors, and that pipeline parameters (such as yield strength, transport pressure, and defect size) often also contain various uncertainties. To accurately represent the working condition of a component, it is necessary to first establish a component function to describe its limit state, then determine the random variables and their distribution patterns, and finally calculate the failure probability. Typically, the reliability of a pipeline structure is calculated using the first-order second-order matrix method and the Monte Carlo method.

[0004] Although the above evaluation methods are widely used in low-grade steel pipelines, they cannot be directly applied to high-grade steel pipelines because the failure factors and the proportion of each factor influencing the failure of high-grade steel pipelines are different from those of low-grade steel pipelines, making it impossible to grasp the safety status of high-grade steel pipelines. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a method, apparatus, system and storage medium for safety scoring of high-grade steel pipelines, addressing the shortcomings of the prior art.

[0006] The technical solution of this invention to solve the above-mentioned technical problems is as follows: A safety scoring method for high-strength steel pipelines, comprising the following steps:

[0007] Import material data, load data, and defect data;

[0008] The material data is scored to obtain an initial material score set;

[0009] The load data is scored to obtain an initial load score set;

[0010] The defect data is scored to obtain an initial defect score set;

[0011] Weight analysis is performed on the initial material score set, the initial load score set, and the initial defect score set respectively to obtain the target material weight set, the target load weight set, and the target defect weight set.

[0012] The pipeline safety score is obtained by scoring the initial material score set, the initial load score set, the initial defect score set, the target material weight set, the target load weight set, and the target defect weight set.

[0013] Another technical solution of the present invention to solve the above-mentioned technical problems is as follows: A safety scoring device for high-strength steel pipelines, comprising:

[0014] The import module is used to import material data, load data, and defect data;

[0015] The material data scoring module is used to score the material data and obtain an initial material score set;

[0016] The load data scoring module is used to score the load data and obtain an initial load score set.

[0017] The defect data scoring module is used to score the defect data and obtain an initial defect score set.

[0018] The weighting analysis module is used to perform weighting analysis on the initial material score set, the initial load score set, and the initial defect score set respectively, and obtain the target material weight set, the target load weight set, and the target defect weight set accordingly.

[0019] The safety score acquisition module is used to calculate the scores of the initial material score set, the initial load score set, the initial defect score set, the target material weight set, the target load weight set, and the target defect weight set to obtain the pipeline safety score.

[0020] Based on the above-mentioned method for safety scoring of high-grade steel pipelines, the present invention also provides a safety scoring system for high-grade steel pipelines.

[0021] Another technical solution of the present invention to solve the above-mentioned technical problems is as follows: a high-strength steel pipeline safety scoring system, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the high-strength steel pipeline safety scoring method as described above.

[0022] Based on the above-mentioned safety scoring method for high-grade steel pipelines, the present invention also provides a computer-readable storage medium.

[0023] Another technical solution of the present invention to solve the above-mentioned technical problems is as follows: a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the high-strength steel pipeline safety scoring method as described above.

[0024] The beneficial effects of this invention are as follows: by scoring material data to obtain an initial material score set, scoring load data to obtain an initial load score set, and scoring defect data to obtain an initial defect score set, weight analysis of the initial material score set, initial load score set, and initial defect score set yields a target material weight set, a target load weight set, and a target defect weight set. The pipeline safety score is calculated by scoring the initial material score set, initial load score set, initial defect score set, target material weight set, target load weight set, and target defect weight set. This allows for the assessment of the safety status of high-strength steel pipelines, solves the problem that commonly used safety evaluation methods cannot be directly applied to high-strength steel oil and gas pipelines, and provides a basis for pipeline safety management. Attached Figure Description

[0025] Figure 1 A flowchart illustrating a safety scoring method for high-grade steel pipelines provided in an embodiment of the present invention;

[0026] Figure 2 This is a schematic diagram of a safety evaluation index system for high-strength steel pipelines, provided by an embodiment of the present invention, for a safety scoring method for high-strength steel pipelines.

[0027] Figure 3 This is a module block diagram of a high-strength steel pipeline safety scoring device provided in an embodiment of the present invention. Detailed Implementation

[0028] The principles and features of the present invention are described below with reference to the accompanying drawings. The examples given are only for explaining the present invention and are not intended to limit the scope of the present invention.

[0029] Figure 1 This is a flowchart illustrating a safety scoring method for high-grade steel pipelines provided in an embodiment of the present invention.

[0030] like Figure 1As shown, a safety scoring method for high-strength steel pipelines includes the following steps:

[0031] Import material data, load data, and defect data;

[0032] The material data is scored to obtain an initial material score set;

[0033] The load data is scored to obtain an initial load score set;

[0034] The defect data is scored to obtain an initial defect score set;

[0035] Weight analysis is performed on the initial material score set, the initial load score set, and the initial defect score set respectively to obtain the target material weight set, the target load weight set, and the target defect weight set.

[0036] The pipeline safety score is obtained by scoring the initial material score set, the initial load score set, the initial defect score set, the target material weight set, the target load weight set, and the target defect weight set.

[0037] In the above embodiments, an initial material score set is obtained by scoring the material data, an initial load score set is obtained by scoring the load data, and an initial defect score set is obtained by scoring the defect data. The target material weight set, target load weight set, and target defect weight set are obtained by weight analysis of the initial material score set, initial load score set, and initial defect score set. The pipeline safety score is obtained by calculating the scores of the initial material score set, initial load score set, initial defect score set, target material weight set, target load weight set, and target defect weight set. This allows for the assessment of the safety status of high-strength steel pipelines, solves the problem that commonly used safety evaluation methods cannot be directly applied to high-strength steel oil and gas pipelines, and provides a basis for pipeline safety management.

[0038] Optionally, as an embodiment of the present invention, the material data includes a matching coefficient, a strength design coefficient, and a pipeline failure probability.

[0039] The process of scoring the material data to obtain an initial material score set includes:

[0040] S21: Compare the matching coefficient with multiple preset material matching intervals in the preset material matching degree database. If the comparison is successful, the preset first score corresponding to the successfully matched preset material matching interval is used as the material matching degree score.

[0041] S22: Import real-time regional levels, compare the real-time regional levels with multiple preset regional levels in the preset material adaptability database, and if the comparison is successful, proceed to S23.

[0042] S23: Compare the strength design coefficient with multiple preset material fitness intervals corresponding to the preset regional level after successful comparison. If the comparison is successful, the preset second score corresponding to the preset material fitness interval is used as the material fitness score.

[0043] S24: The failure probability of the pipeline is compared with multiple preset mechanical performance parameter ranges of the pipe material in the preset pipe material mechanical performance database. If the comparison is successful, the preset third score corresponding to the successfully compared preset mechanical performance parameter range of the pipe material is used as the mechanical performance score of the pipe material. The initial material score set includes the material matching score, the material adaptability score and the mechanical performance score of the pipe material.

[0044] It should be understood that the welding materials used in the construction of high-strength steel pipelines should be compatible with the strength of the pipe material; otherwise, circumferential weld failure is likely to occur. The ratio of the yield strength of the welding material to that of the base material is the matching coefficient S.

[0045] Specifically, as shown in Table 1, when the matching coefficient S < 1, i.e., in the case of low-matching circumferential welds, significant strain concentration occurs at the circumferential weld, making it prone to fracture. In this case, the overall deformation capacity of the pipeline is relatively small. For example, the strain at the distal end of the pipeline is 0.35% and 1.2% for S = 0.8 and 0.9, respectively, and the lower the S, the lower the deformation capacity of the pipeline. When S = 1, the weld strain decreases significantly. As the matching coefficient increases, up to S = 1.1, the weld strain further decreases, and the pipeline will not fracture in the weld. It is evident that the higher the matching coefficient of the circumferential weld, the safer the circumferential weld, and the greater the deformation capacity of the pipeline (i.e., the strain at the distal end). However, the matching coefficient should not be too large; S = 1.2 satisfies the requirements well. Therefore, the material matching degree index is scored based on the matching coefficient. Table 1 is the matching coefficient scoring table.

[0046] Table 1

[0047]

[0048] Specifically, as shown in Table 2, the selection of pipe thickness should be adapted to the surrounding environment. The population density of the surrounding environment directly affects the selection of pipe wall thickness. The appropriate strength design coefficient should be selected based on the grade of the area through which the pipeline passes, thus obtaining the required pipe wall thickness. The higher the grade of the area, the lower the strength coefficient. With economic development, the grade of the area surrounding the pipeline may increase, and the strength coefficient designed at the time may no longer meet the requirements, posing a constant threat to pipeline safety. Therefore, by comparing the grade of the area surrounding the pipeline (i.e., the preset grade) with the strength coefficient designed at the time (i.e., the preset material adaptability range), it is determined whether the pipe material is suitable for the current environment. Table 2 is the material adaptability scoring table.

[0049] Table 2

[0050]

[0051]

[0052] Specifically, as shown in Table 3, the ability of the pipe to resist mechanical damage, i.e., the impact fracture toughness of the pipe body, is considered. There is no clear explicit relationship between impact toughness and pipe failure, so impact toughness cannot be used as a direct scoring criterion. Instead, a simulation calculation of the pipe failure probability based on different impact toughnesses can be used for scoring. As fracture toughness increases, the pipe failure probability decreases. Therefore, the pipe failure probability is used to score the mechanical performance indicators of the pipe. Table 3 shows the scoring table for the mechanical performance of the pipe.

[0053] Table 3

[0054]

[0055] In the above embodiments, the material data is scored to obtain an initial material score set. The safety status of high-grade steel pipelines can be known from the aspects of material matching degree, material adaptability and pipe mechanical properties. This solves the problem that commonly used safety evaluation methods cannot be directly applied to high-grade steel oil and gas pipelines, and provides a basis for pipeline safety management.

[0056] Optionally, as an embodiment of the present invention, the load data includes environmental load data and human-caused load data.

[0057] The process of scoring the load data to obtain an initial load score set includes:

[0058] The environmental load data is scored according to preset environmental load rules to obtain an environmental load score;

[0059] The human-caused load data is scored according to preset human-caused load rules to obtain human-caused load scores. The initial load score set includes the environmental load scores and the human-caused load scores.

[0060] Specifically, as shown in Table 4, excessive environmental loads directly affect pipeline safety. The pipeline's route may include crossing railways, heavy vehicle traffic, and high-risk geological disaster areas, all of which pose significant threats to pipeline safety. Based on standards SY / T6828-2017 "Technical Specification for Geological Disaster Risk Management of Oil and Gas Pipelines" and GB / T27512 "Risk Assessment Method for Buried Steel Pipelines," a graded assessment system was developed. Table 4 presents the environmental load scoring table.

[0061] Table 4

[0062]

[0063] Specifically, as shown in Table 5, the level of human activity on the ground above the pipeline is also an important factor affecting pipeline safety. There are many types of human activity. Referring to the more mature Kent method regarding third-party damage, human load indicators (i.e., human load scores) are assigned scores, as shown in Table 5.

[0064] Table 5

[0065]

[0066]

[0067] In the above embodiments, environmental load scores are obtained by scoring environmental load data according to preset environmental load rules, and human load scores are obtained by scoring human load data according to preset human load rules. The safety status of high-strength steel pipelines can be known from both environmental load and human load aspects. This solves the problem that commonly used safety evaluation methods cannot be directly applied to high-strength steel oil and gas pipelines, and provides a basis for pipeline safety management.

[0068] Optionally, as an embodiment of the present invention, the defect data includes pipeline defect repair information, construction data information, welding method information, construction quality management information, test pile spacing information, test pile time interval information, test pile stray current information, weld joint information, and pipe body defect information.

[0069] The process of scoring the defect data to obtain an initial defect score set includes:

[0070] The pipeline defect repair information is scored according to preset defect repair rules to obtain a detection and maintenance score.

[0071] The construction data information is scored according to the preset construction data scoring rules to obtain the construction data score;

[0072] The welding method information is scored according to the preset welding method scoring rules to obtain the welding method score;

[0073] The construction quality management information is scored according to the preset construction quality management system rules to obtain a construction quality management score.

[0074] The construction data score, the welding method score, and the construction quality management score are added together to obtain the construction process management score.

[0075] The test pile spacing information is scored according to the preset test pile spacing scoring rules to obtain the test pile spacing score;

[0076] The test pile time interval information is scored according to the preset test pile reading interval scoring rules to obtain the test pile time interval score;

[0077] The stray current information of the test pile is scored according to the preset stray current scoring rules to obtain the stray current score of the test pile;

[0078] The cathodic protection score is obtained by adding the test pile spacing score, the test pile time interval score, and the test pile stray current score together.

[0079] The weld joint information is scored according to the preset welding defect scoring rules to obtain the welding defect score;

[0080] The pipe defect information is scored according to the preset pipe defect scoring rules to obtain the pipe defect score. The initial defect score set includes the inspection and maintenance score, the construction process management score, the cathodic protection score, the welding defect score, and the pipe defect score.

[0081] Specifically, as shown in Table 6, periodic inspection and maintenance mainly considers whether defects detected internally / externally are repaired in a timely manner. According to standards GB / T 27699, GB / T 21447, and GB / T 30582, the inspection cycles for newly built pipelines and existing pipelines differ. Therefore, periodic inspection and maintenance indicators are scored from three aspects: inspection method, inspection cycle, and defect repair status. The periodic inspection and maintenance score (i.e., the inspection and maintenance score) is the sum of the internal inspection score and the external inspection score. Table 6 is the inspection and maintenance scoring table (i.e., the preset defect repair rules).

[0082] Table 6

[0083]

[0084]

[0085] Specifically, as shown in Table 7, construction quality is a crucial foundation for pipeline safety. Construction process management refers to whether the construction management system can effectively guarantee quality, mainly considering three aspects: construction data, welding methods, and the construction quality management system. The construction process management score (i.e., construction process management score) = construction data score (i.e., construction data rating) + welding method score (i.e., welding method rating) + construction quality management system score (i.e., construction quality management rating). Table 7 shows the construction process management score table.

[0086] Table 7

[0087]

[0088] In Table 7, the judgment of construction data is the preset construction data scoring rule, the judgment of welding method is the preset welding method scoring rule, and the judgment of construction quality management system is the preset construction quality management system rule.

[0089] Specifically, as shown in Table 8, cathodic protection is the primary protective measure for pipelines. The quality of a cathodic protection system depends on two factors: first, whether the protection voltage and protection length meet the design and specification requirements; and second, the need for frequent inspections to ensure the normal operation of the cathodic protection system. The effectiveness of the cathodic protection system can be scored from three aspects: the spacing of the test piles, the test time interval, and stray current. The cathodic protection system score (i.e., the cathodic protection score) = spacing score (i.e., test pile spacing score) + reading interval score (i.e., test pile time interval score) + stray current score (i.e., test pile stray current score). Table 8 shows the cathodic protection scoring table.

[0090] Table 8

[0091]

[0092] In Table 8, the determination of the spacing score is the preset test pile spacing score rule, the determination of the reading interval score is the preset test pile reading interval score rule, and the determination of the stray current is the preset test pile stray current score rule.

[0093] It should be understood that, as shown in Table 9, the nature, quantity, and density of defects in welded joints in GB3323-87 can be classified into quality grades I, II, III, and IV. Therefore, scoring rules (i.e., welding defect scoring) are established according to the welding quality grades. Table 9 is the welding defect scoring table.

[0094] Table 9

[0095]

[0096] It should be understood that, as shown in Table 10, SY / T 6477 specifies that the safety of a pipe body can be determined by the failure assessment curve in the failure assessment diagram for pipe body defects. When the point calculated for the defect being assessed is below the curve, the pipeline is considered safe. Therefore, a scoring rule (i.e., pipe body defect scoring) is established. Table 10 is the pipe body defect scoring table.

[0097] Table 10

[0098]

[0099]

[0100] In the above embodiments, the defect data is scored to obtain an initial defect score set. This allows us to understand the safety status of high-strength steel pipelines from aspects such as inspection and maintenance, construction process management, cathodic protection, welding defects, and pipe body defects. This solves the problem that commonly used safety evaluation methods cannot be directly applied to high-strength steel oil and gas pipelines, and provides a basis for pipeline safety management.

[0101] Optionally, as an embodiment of the present invention, the process of performing weight analysis on the initial material score set, the initial load score set, and the initial defect score set to obtain the target material weight set, the target load weight set, and the target defect weight set includes:

[0102] The initial material score set, the initial load score set, and the initial defect score set are constructed into matrices using the analytic hierarchy process, respectively, to obtain the material score matrix, the load score matrix, and the defect score matrix.

[0103] The eigenvectors of the material scoring matrix, the load scoring matrix, and the defect scoring matrix are calculated respectively to obtain multiple target material weights, multiple target load weights, and multiple target defect weights.

[0104] A target material weight set is obtained by combining all the target material weights, a target load weight set is obtained by combining all the target load weights, and a target defect weight set is obtained by combining all the target defect weights.

[0105] It should be understood that the three primary indicators—material (i.e., the initial material score set), load (i.e., the initial load score set), and defect (i.e., the initial defect score set)—have different impacts on the overall system safety. Each secondary indicator also has a different impact on the primary indicator. Therefore, different weight values ​​need to be set for different indicators.

[0106] It should be understood that the Analytic Hierarchy Process (AHP) is used to assign corresponding weight values ​​to different indicators.

[0107] Specifically, the Analytic Hierarchy Process (AHP) was first proposed by American operations research expert Saaty in the 1970s. Currently, this method has been widely used in many fields. Its core idea is to decompose complex problems into several levels and obtain the weight of each factor by comparing pairs at each level.

[0108] Specifically, taking the three indicators of the material category (i.e., the initial material score set) as an example, two indicators u are selected each time. i with u j Compare pairwise to determine the importance of each indicator to pipeline safety, using a. i,j This indicates the ratio of the importance of the two. i,j The values ​​are determined using the 9-point scale method proposed by Saaty, as shown in Table 11. Table 11 is the judgment scale table.

[0109] Table 11

[0110]

[0111] It should be understood that, as shown in Table 12, based on the actual situation of the pipeline and according to the judgment scale, the index weight judgment matrix A = [a i,j (i.e., material rating matrix, load rating matrix, or defect rating matrix), Table 12 is a ranking list of judgment matrices.

[0112] Table 12

[0113]

[0114] In the above embodiments, weight analysis is performed on the initial material score set, the initial load score set, and the initial defect score set to obtain the target material weight set, the target load weight set, and the target defect weight set, respectively. This solves the problem that commonly used safety evaluation methods cannot be directly applied to high-grade steel oil and gas pipelines, and provides a basis for pipeline safety management.

[0115] Optionally, as an embodiment of the present invention, the process of calculating the eigenvectors of the material scoring matrix, the load scoring matrix, and the defect scoring matrix respectively, and obtaining the corresponding multiple target material weights, multiple target load weights, and multiple target defect weights includes:

[0116] The eigenvectors of the material scoring matrix, the load scoring matrix, and the defect scoring matrix are calculated using the first formula, respectively, to obtain multiple target material weights, multiple target load weights, and multiple target defect weights. The first formula is:

[0117]

[0118] in,

[0119] Among them, W i This refers to the target material weight corresponding to the i-th initial material score in the initial material score set, the target load weight corresponding to the i-th initial load score in the initial load score set, or the target defect weight corresponding to the i-th initial defect score in the initial defect score set. Let be the normalized material weight corresponding to the i-th initial material score in the initial material score set, the normalized load weight corresponding to the i-th initial load score in the initial load score set, or the normalized defect weight corresponding to the i-th initial defect score in the initial defect score set; n is the total number of initial material scores in the initial material score set, the total number of initial load scores in the initial load score set, or the total number of initial defect scores in the initial defect score set; and a ij The material score in the i-th row and j-th column of the material score matrix, the load score in the i-th row and j-th column of the load score matrix, or the defect score in the i-th row and j-th column of the defect score matrix.

[0120] It should be understood that the judgment matrix A = (a) is calculated using the root method. ij ) 3×3 The maximum eigenvalue λ of (i.e., the material rating matrix, load rating matrix, or defect rating matrix) max , λ max The corresponding feature vector W is the index set U = [u i Indicators u in [the text] i The weight value.

[0121] Specifically, (1) calculate the judgment matrix A = (a ij ) 3×3 (i.e., the product of the elements in each row of the material rating matrix, load rating matrix, or defect rating matrix) M i The formula is as follows:

[0122]

[0123] (2) Calculate M i 3 square roots The formula is as follows:

[0124]

[0125] (3) For vectors Normalization is performed using the following formula:

[0126]

[0127] The obtained W = (W1 W2 W3) is λ. maxThe corresponding eigenvector (i.e., target material weight, target load weight, or target defect weight), that is, the factor set U = [u i [Various factors u] i The weight values ​​are calculated using the same method for other indicators.

[0128] In the above embodiments, the eigenvectors of the material scoring matrix, load scoring matrix, and defect scoring matrix are calculated respectively, and the target material weight, target load weight, and target defect weight are obtained accordingly. This solves the problem that commonly used safety evaluation methods cannot be directly applied to high-grade steel oil and gas pipelines, and provides a basis for pipeline safety management.

[0129] Optionally, as an embodiment of the present invention, the process of calculating scores for the initial material score set, the initial load score set, the initial defect score set, the target material weight set, the target load weight set, and the target defect weight set to obtain a pipeline safety score includes:

[0130] The pipeline safety score is obtained by calculating scores for the initial material score set, the initial load score set, the initial defect score set, multiple target material weights, multiple target load weights, and multiple target defect weights using the second formula:

[0131]

[0132] Where F represents the pipeline safety score, W i The target material weight corresponding to the i-th initial material score in the initial material score set, the target load weight corresponding to the i-th initial load score in the initial load score set, or the target defect weight corresponding to the i-th initial defect score in the initial defect score set, u i Let be the i-th initial material score in the initial material score set, the i-th initial load score in the initial load score set, or the i-th initial defect score in the initial defect score set, and m be the sum of the initial material scores in the initial material score set, the total number of initial load scores in the initial load score set, and the total number of initial defect scores in the initial defect score set.

[0133] It should be understood that, based on the pipeline score (i.e., pipeline safety score), pipeline safety (i.e., pipeline safety score) is divided into four levels: excellent, good, qualified, and poor, as shown in Table 13. Table 13 is the pipeline safety level classification table.

[0134] Table 13

[0135]

[0136] Specifically, based on the actual condition of the pipeline to be evaluated, each evaluation indicator is scored; according to the weight allocation method described above, an indicator weight judgment matrix is ​​established, and the weight coefficient of each indicator is calculated; the score of each indicator is multiplied by its corresponding weight coefficient to obtain the corrected score for that indicator; the corrected scores of each indicator are accumulated to finally obtain the safety score of the pipeline segment, as shown in the following formula:

[0137]

[0138] In the above embodiments, the pipeline safety score is obtained by scoring the initial material score set, initial load score set, initial defect score set, multiple target material weights, multiple target load weights, and multiple target defect weights using the second formula. This allows for the assessment of the safety status of high-strength steel pipelines, solves the problem that commonly used safety evaluation methods cannot be directly applied to high-strength steel oil and gas pipelines, and provides a basis for pipeline safety management.

[0139] Optionally, as another embodiment of the present invention, the present invention is used to understand the safety status of high-strength steel pipelines, identify weak points in safety, and provide a basis for pipeline safety management.

[0140] Alternatively, as another embodiment of the present invention, such as Figure 2 As shown, this invention establishes a safety evaluation index system for high-strength steel pipelines. Analysis of high-strength steel pipeline failure events reveals that the main failure influencing factors are directly related to the pipe's material properties, its adaptability to the surrounding environment, internal and external loads, pipe defects, and maintenance. Insufficient pipe material strength, excessive internal and external loads, or pipe defects can all lead to pipeline failure. Therefore, the influencing factors of pipeline failure are categorized into three main types: materials, loads, and defects, as primary indicators. These are further subdivided into ten secondary indicators: material matching degree, material adaptability, pipe mechanical properties, environmental loads, human-induced loads, regular inspection and maintenance, construction process management, effectiveness of the cathodic protection system, welding defect status, and pipe defect status.

[0141] Optionally, as another embodiment of the present invention, the present invention constructs a safety evaluation index system for high-strength steel pipelines by fault tree analysis of failure events of high-strength steel pipelines, and proposes a safety evaluation method applicable to high-strength steel oil and gas pipelines, thus solving the problem that commonly used safety evaluation methods cannot be directly applied to high-strength steel oil and gas pipelines.

[0142] Optionally, as another embodiment of the present invention, four pipe sections are selected from a certain X70 pipeline: two sections between Puxian Station and Yangcheng Station (section 1 and section 2), and two sections between Lixin Station and Qingshan Station (section 3 and section 4). Two pipe sections (section 5 and section 6) are also selected from a certain X65 pipeline: one between Enshi Station and Langping Station, and the other between Wuhan West Station and Qianjiang Station. Based on design documents, construction data, operation and maintenance records, and other relevant reports, safety indicators are scored for the pipe sections to be evaluated. Table 14 shows the safety scores for each pipe section.

[0143] Table 14

[0144]

[0145] Using the Analytic Hierarchy Process (AHP), the vectors corresponding to the maximum eigenvalues ​​of each type of indicator were calculated, yielding the weights of each indicator: Material type W1 = (0.0619 0.1858 0.1858), Load type W2 = (0.0403 0.2015), and Defect type W3 = (0.0917 0.0265 0.1586 0.154 0.325). Table 15 shows the indicator weights.

[0146] Table 15

[0147]

[0148]

[0149] According to the safety score calculation formula, the safety scores of each indicator for each pipe section are weighted and calculated with the weight of each indicator to obtain the final pipe section safety score. As shown in Table 16, Table 16 shows the pipe section scores.

[0150] Table 16

[0151]

[0152] In Table 16, according to the safety classification, pipe sections 1 and 6 are rated as good, while the rest are rated as qualified. Pipe sections 2, 3, and 4 scored lower, mainly due to low scores in the material adaptability index. After reviewing the data, it was found that urban development and construction around these three pipe sections have led to an increase in the regional safety level, while the pipe material strength coefficient remains at the low level designed in the past, failing to meet current safety requirements. This should be given serious attention by management, and corrective measures should be taken promptly.

[0153] Figure 3 This is a module block diagram of a high-strength steel pipeline safety scoring device provided in an embodiment of the present invention.

[0154] Alternatively, as another embodiment of the present invention, such as Figure 3 As shown, a safety scoring device for high-strength steel pipelines includes:

[0155] The import module is used to import material data, load data, and defect data;

[0156] The material data scoring module is used to score the material data and obtain an initial material score set;

[0157] The load data scoring module is used to score the load data and obtain an initial load score set.

[0158] The defect data scoring module is used to score the defect data and obtain an initial defect score set.

[0159] The weighting analysis module is used to perform weighting analysis on the initial material score set, the initial load score set, and the initial defect score set respectively, and obtain the target material weight set, the target load weight set, and the target defect weight set accordingly.

[0160] The safety score acquisition module is used to calculate the scores of the initial material score set, the initial load score set, the initial defect score set, the target material weight set, the target load weight set, and the target defect weight set to obtain the pipeline safety score.

[0161] Optionally, another embodiment of the present invention provides a high-strength steel pipeline safety scoring system, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the high-strength steel pipeline safety scoring method described above. This system can be a computer or similar system.

[0162] Optionally, another embodiment of the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the high-strength pipeline safety scoring method as described above.

[0163] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0164] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the above-described apparatus and unit can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0165] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed.

[0166] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of the embodiments of the present invention, depending on actual needs.

[0167] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0168] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0169] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A high steel grade pipeline safety scoring method, characterized by, The method comprises the following steps: Importing material data, load data and defect data; Scoring the material data to obtain an initial material score set, the material data including a matching coefficient, a strength design coefficient and a pipeline failure probability; Scoring the load data to obtain an initial load score set, the load data including environmental load data and artificial load data; Scoring the defect data to obtain an initial defect score set, the defect data including pipeline defect repair information, construction information, welding method information, construction quality management information, test pile spacing information, test pile time interval information, test pile stray current information, welding joint information and pipe body defect information; Performing weight analysis on the initial material score set, the initial load score set and the initial defect score set respectively to obtain a target material weight set, a target load weight set and a target defect weight set; Performing score calculation on the initial material score set, the initial load score set, the initial defect score set, the target material weight set, the target load weight set and the target defect weight set to obtain a pipeline safety score; The process of performing weight analysis on the initial material score set, the initial load score set and the initial defect score set respectively to obtain a target material weight set, a target load weight set and a target defect weight set comprises: Performing matrix construction on the initial material score set, the initial load score set and the initial defect score set respectively by using an analytic hierarchy process algorithm to obtain a material score matrix, a load score matrix and a defect score matrix; Calculating eigenvectors of the material score matrix, the load score matrix and the defect score matrix respectively to obtain a plurality of target material weights, a plurality of target load weights and a plurality of target defect weights; Obtaining a target material weight set by collecting all the target material weights, obtaining a target load weight set by collecting all the target load weights, and obtaining a target defect weight set by collecting all the target defect weights; The process of calculating eigenvectors of the material score matrix, the load score matrix and the defect score matrix respectively to obtain a plurality of target material weights, a plurality of target load weights and a plurality of target defect weights comprises: Calculating eigenvectors of the material score matrix, the load score matrix and the defect score matrix respectively by using a first formula to obtain a plurality of target material weights, a plurality of target load weights and a plurality of target defect weights, the first formula being: ， wherein , in, For the first material in the initial material score set The target material weight or initial load score set corresponding to the initial material score. The target load weight corresponding to the initial load score or the first initial defect score set. The target defect weights corresponding to the initial defect scores. For the first material in the initial material score set The set of material weights or initial load scores corresponding to the initial material score is the first one. The first initial load score corresponds to the unnormalized load weight or the first initial defect score set. The defect weights to be normalized correspond to the initial defect scores. This refers to the total number of initial material scores in the initial material score set, the total number of initial load scores in the initial load score set, or the total number of initial defect scores in the initial defect score set. The first element in the material rating matrix The first row The first item in the material rating or load rating matrix The first row The first column in the load rating or defect rating matrix The first row Defect scoring is listed.

2. The high-grade pipeline safety scoring method according to claim 1, characterized in that The process of scoring the material data to obtain an initial material score set comprises: S21: comparing the matching coefficient with a plurality of preset material matching intervals in a preset material matching degree database, and if the comparison is successful, taking a preset first score corresponding to the preset material matching interval of which the comparison is successful as a material matching degree score; S22: import a real-time region level, compare the real-time region level with a plurality of preset region levels in a preset material fitness database, if the comparison is successful, execute S23; S23: compare the strength design coefficient with a plurality of preset material fitness intervals corresponding to the preset region level after the comparison is successful, if the comparison is successful, take a preset second score corresponding to the preset material fitness interval as a material fitness score; S24: compare the pipeline failure probability with a plurality of preset pipe mechanical property parameter intervals in a preset pipe mechanical property database, if the comparison is successful, take a preset third score corresponding to the preset pipe mechanical property parameter interval after the comparison is successful as a pipe mechanical property score, and the initial material score set includes the material matching degree score, the material fitness score and the pipe mechanical property score.

3. The high-grade pipeline safety scoring method according to claim 1, wherein the process of scoring the load data to obtain an initial load score set includes: scoring the environmental load data according to a preset environmental load rule to obtain an environmental load score; scoring the artificial load data according to a preset artificial load rule to obtain an artificial load score, and the initial load score set includes the environmental load score and the artificial load score.

4. The high-grade pipeline safety scoring method according to claim 1, wherein the process of scoring the defect data to obtain an initial defect score set includes: scoring the pipeline defect repair information according to a preset defect repair rule to obtain a detection and maintenance score; scoring the construction data information according to a preset construction data scoring rule to obtain a construction data score; scoring the welding method information according to a preset welding method scoring rule to obtain a welding method score; scoring the construction quality management information according to a preset construction quality management rule to obtain a construction quality management score; adding the construction data score, the welding method score and the construction quality management score to obtain a construction process management score; scoring the test pile spacing information according to a preset test pile spacing scoring rule to obtain a test pile spacing score; scoring the test pile time interval information according to a preset test pile reading interval scoring rule to obtain a test pile time interval score; scoring the test pile stray current information according to a preset test pile stray current scoring rule to obtain a test pile stray current score; adding the test pile spacing score, the test pile time interval score and the test pile stray current score to obtain a cathodic protection score; scoring the welding joint information according to a preset welding defect scoring rule to obtain a welding defect score; scoring the pipe body defect information according to a preset pipe body defect scoring rule to obtain a pipe body defect score, and the initial defect score set includes the detection and maintenance score, the construction process management score, the cathodic protection score, the welding defect score and the pipe body defect score. ​ ​ 5. The high-grade pipe safety rating method of claim 1, wherein, The process of performing score calculation on the initial material score set, the initial load score set, the initial defect score set, the target material weight set, the target load weight set and the target defect weight set to obtain the pipeline safety score comprises: performing score calculation on the initial material score set, the initial load score set, the initial defect score set, the plurality of target material weights, the plurality of target load weights and the plurality of target defect weights by a second formula to obtain the pipeline safety score, the second formula being: ， in, To score pipeline safety, For the first material in the initial material score set The target material weight or initial load score set corresponding to the initial material score. The target load weight corresponding to the initial load score or the first initial defect score set. The target defect weights corresponding to the initial defect scores. For the first material in the initial material score set The first initial material score or initial load score set The first initial load score or initial defect score set An initial defect score, It is the sum of the initial material scores in the initial material score set, the total number of initial load scores in the initial load score set, and the total number of initial defect scores in the initial defect score set.

6. A high steel grade pipeline safety scoring device characterized by, comprising: an import module configured to import material data, load data and defect data; a material data scoring module configured to score the material data to obtain an initial material score set, the material data comprising a matching coefficient, a strength design coefficient and a pipeline failure probability; a load data scoring module configured to score the load data to obtain an initial load score set, the load data comprising environmental load data and artificial load data; a defect data scoring module configured to score the defect data to obtain an initial defect score set, the defect data comprising pipeline defect repair information, construction data information, welding method information, construction quality management information, test pile spacing information, test pile time interval information, test pile stray current information, welding joint information and pipe body defect information; a weight analysis module configured to perform weight analysis on the initial material score set, the initial load score set and the initial defect score set respectively to obtain a target material weight set, a target load weight set and a target defect weight set respectively; a safety score obtaining module configured to perform score calculation on the initial material score set, the initial load score set, the initial defect score set, the target material weight set, the target load weight set and the target defect weight set to obtain the pipeline safety score; the weight analysis module is specifically configured to: perform matrix construction on the initial material score set, the initial load score set and the initial defect score set respectively by using an analytic hierarchy process algorithm to obtain a material score matrix, a load score matrix and a defect score matrix respectively; calculate eigenvectors of the material score matrix, the load score matrix and the defect score matrix respectively to obtain a plurality of target material weights, a plurality of target load weights and a plurality of target defect weights respectively; obtain a target material weight set by collecting all the target material weights, obtain a target load weight set by collecting all the target load weights, and obtain a target defect weight set by collecting all the target defect weights; in the weight analysis module, the process of calculating eigenvectors of the material score matrix, the load score matrix and the defect score matrix respectively to obtain a plurality of target material weights, a plurality of target load weights and a plurality of target defect weights respectively comprises: The characteristic vectors of the material score matrix, the load score matrix and the defect score matrix are calculated by a first formula, respectively, to obtain a plurality of target material weights, a plurality of target load weights and a plurality of target defect weights, the first formula being: ， wherein , wherein, a target material weight corresponding to the i-th initial material score in the initial material score set or a target load weight corresponding to the i-th initial load score in the initial load score set or a target defect weight corresponding to the i-th initial defect score in the initial defect score set, a to-be-normalized material weight corresponding to the i-th initial material score in the initial material score set or a to-be-normalized load weight corresponding to the i-th initial load score in the initial load score set or a to-be-normalized defect weight corresponding to the i-th initial defect score in the initial defect score set, a total number of initial material scores in the initial material score set or a total number of initial load scores in the initial load score set or a total number of initial defect scores in the initial defect score set, a material score in the i-th row and the j-th column in the material score matrix or a load score in the i-th row and the j-th column in the load score matrix or a defect score in the i-th row and the j-th column in the defect score matrix, a defect score in the i-th row and the j-th column in the defect score matrix.​​​​​​​​​​​ 7. A high steel grade pipeline safety scoring system comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein, The computer program, when executed by the processor, implements the high-grade steel pipeline safety scoring method according to any one of claims 1 to 5.

8. A computer-readable storage medium storing a computer program, the computer program comprising instructions that, when executed by a computer, cause the computer to perform the method of any one of claims 1 to 7. The computer program, when executed by the processor, implements the high-grade steel pipeline safety scoring method according to any one of claims 1 to 5.

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