Method and system for analyzing influence of third-party construction accident control defect of gas pipeline

Abstract

The invention belongs to the field of accident analysis, and particularly discloses a gas pipeline third-party construction accident control defect influence analysis method and system, and the method comprises the following steps: determining a system task and safety constraints, building a hierarchical structure of an STAMP model according to a preset function demand and a safety target, and carrying out the analysis through combining a VSM model, identifying control defects; performing digital expression on the control defect obtained by analyzing the third-party construction accident of each gas pipeline, and obtaining a coefficient of the control defect of the third-party construction accident of the gas pipeline through Pearson correlation analysis; using a CRITIC weight method to process and calculate the coefficient of the third-party construction accident control defect of the gas pipeline obtained in the correlation analysis to obtain the weight of the third-party construction accident control defect of the gas pipeline; and finally, according to the hierarchical structure and the control defect weight, constructing a system dynamics model, and determining the key control defect of the third-party construction accident of the pipeline, thereby formulating targeted prevention and improvement measures.

Description

Technical Field

[0001] The present invention belongs to the field of accident analysis, and in particular relates to a method and system for analyzing the impact of third-party construction accident control defects on a gas pipeline. Background Art

[0002] As the main mode of gas transportation, pipeline systems play a core role in the global energy supply chain. The safe operation of pipelines is directly related to energy security and economic stability. Third-party construction damage is a major cause of pipeline accidents, which leads to damage to underground gas pipeline networks, including damage to pipeline anti-corrosion layers, scratches, deformations, bends and damage to pipelines and equipment, as well as fatigue, corrosion, leakage and stress concentration problems caused by them. Therefore, an analysis technology for the impact of control defects in third-party construction accidents of gas pipelines is needed to prevent the occurrence of third-party construction accidents of gas pipelines and reduce the impact of third-party construction accidents of gas pipelines. Summary of the invention

[0003] In order to address the deficiencies in the prior art, the present invention aims to provide an analysis method for the impact of control defects in third-party construction accidents of gas pipelines. The method uses the Pearson-Critic method to quantitatively analyze the control defects in third-party construction accidents of gas pipelines, and constructs a system dynamics model based on the hierarchical structure and control defect weights to determine the key control defects of third-party construction accidents of gas pipelines, thereby formulating targeted prevention and improvement measures, which provides a theoretical basis for effectively preventing, timely controlling and eliminating third-party construction accidents of gas pipelines.

[0004] In order to achieve the above object, the technical solution adopted by the present invention is:

[0005] The analysis method of the impact of third-party construction accident control defects on gas pipelines specifically includes the following steps:

[0006] S1. Establish third-party construction tasks and safety constraints for gas pipelines, build the hierarchical structure of the STAMP model based on preset functional requirements and safety goals, and analyze it in combination with the VSM model to identify control deficiencies;

[0007] S2. Digitally express the control defects obtained from each gas pipeline third-party construction accident, and obtain the coefficient of the control defects of the gas pipeline third-party construction accident through Pearson correlation analysis;

[0008] S3. Use the CRITIC weight method to calculate the coefficient of the third-party construction accident control defect of the gas pipeline obtained from the Pearson correlation analysis to obtain the weight of the third-party construction accident control defect of the gas pipeline;

[0009] S4. Based on the hierarchical structure and control defect weights, a system dynamics model is constructed to determine the key control defects of pipeline third-party construction accidents, and to develop targeted prevention and improvement measures.

[0010] Furthermore, step S1 specifically includes the following contents:

[0011] S1-1. The third-party construction accident of the gas pipeline is regarded as a system and divided into two modules according to safety constraints: ensuring the integrity of the gas pipeline and ensuring that the gas pipeline is not damaged by external forces;

[0012] S1-2. Establish the hierarchical structure of the STAMP model, which is divided into the physical layer, operation layer, project management layer and social system layer, to identify the control defects of pipeline third-party construction accidents;

[0013] S1-3. Establish the hierarchical structure of the VSM model, which is divided into the social system subsystem, safety decision-making subsystem, control subsystem, coordination subsystem and construction subsystem to identify the control defects of third-party construction accidents of gas pipelines.

[0014] Furthermore, step S2 specifically includes:

[0015] S2-1. Digital expression of gas pipeline third-party construction accident control defects:

[0016] Let "A" represent a certain category, "Aa 1 " indicates the first reason of subcategory a in category A, and the rest are numbered in the same way to obtain the frequency of control defects of gas pipeline third-party construction accidents;

[0017] S2-2. Based on the Pearson correlation coefficient method, the frequency of control defects in third-party construction accidents of gas pipelines is calculated, and the correlation coefficient between control defects is obtained. The calculation formula is:

[0018]

[0019] In the formula, r represents the Pearson correlation coefficient, n represents the sample size of the data, and X i , Y i is the i-th corresponding sample, indicating the specific cause of the accident; represents the sample mean, S X , S Y Represents the sample standard deviation.

[0020] Furthermore, step S3 specifically includes:

[0021] S3-1. Establish the original index database X based on the sample values ​​of the third-party construction accident control defects of the gas pipeline:

[0022]

[0023] Among them, X np Represents the value of the pth evaluation indicator for the nth sample;

[0024] S3-2. Use standard deviation to normalize and represent the indicator variability in the form of standard deviation:

[0025]

[0026] In the formula, represents the average value of the jth evaluation index, X ij represents the value of the i-th sample on the j-th evaluation index, S j represents the standard deviation of the jth indicator;

[0027] S3-3. The conflict of indicators is expressed by the correlation coefficient, and the formula is:

[0028]

[0029] In the formula, R j Represents the correlation coefficient of the jth evaluation index; establish a control defect correlation coefficient diagram with i and j as the horizontal and vertical coordinates, r ij Represents the correlation coefficient between evaluation indicators i and j;

[0030] S3-4. Calculate the information amount of each control defect. The calculation formula is:

[0031]

[0032] In the formula, C j represents the information content of the jth control defect;

[0033] S3-5. Calculate the weight of each control deficiency using the following formula:

[0034]

[0035] Where W j Represents the weight of the j-th control defect target.

[0036] Furthermore, step S4 specifically includes:

[0037] S4-1. Establish a cause-effect relationship diagram between control deficiencies based on the hierarchical structure of the STAMP model;

[0038] S4-2. Based on the cause-effect relationship diagram between the third-party construction accident control defects of gas pipelines, establish the flow stock diagram between the effective third-party construction accident control defects of gas pipelines;

[0039] S4-3. Input the flow inventory diagram and control defect weights into the Vensim platform to determine the key control defects of gas pipeline third-party construction accidents.

[0040] Correspondingly, the present invention also proposes an analysis system for the impact of third-party construction accident control defects in gas pipelines, including a data acquisition module, a data processing module, a data analysis module and a result application module;

[0041] The data acquisition module is used to input digital expression parameters of gas pipeline third-party construction accident control defects;

[0042] The data processing module is used to obtain the correlation coefficient between the third-party construction accident control defects of the gas pipeline by using correlation analysis;

[0043] The data analysis module is used to configure the coefficient of the control defect of the third-party construction accident of the gas pipeline, and use the CRITIC weight method to calculate the control defect weight;

[0044] The result application module is used to construct a system dynamics model according to the hierarchical structure and control defect weights, determine the key control defects of pipeline third-party construction accidents, and send the results to managers at all levels through computer terminals, so that managers at all levels can formulate targeted prevention and improvement measures based on the results.

[0045] The present invention has the following beneficial effects:

[0046] The present invention divides the components of the pipeline protection system into functions based on the VSM model on the basis of the hierarchical division of the components of the pipeline protection system by the STAMP model, which makes up for the shortcomings of the STAMP model in analyzing the defects in potential organizational control. However, the accident analysis part has certain shortcomings of fuzziness and subjectivity. The Pearson coefficient method is combined with the CRITIC weight method, and the objective attributes of the data itself are fully utilized for scientific evaluation, which makes up for the shortcomings of certain subjectivity when the model is used. The Pearson-CRITIC method is used to quantitatively analyze the control defects, focusing on the analysis of the control defect weights, and combining the control defects and accident occurrence process of pipeline third-party construction damage accidents, using system dynamics theory, a system dynamics model of pipeline third-party construction damage accidents is constructed, and the system safety level is taken as the research object to determine the key control defects of gas pipeline third-party construction accidents that have the greatest impact on the changes in the system safety level, which provides a theoretical basis for effectively preventing, timely controlling and eliminating gas pipeline third-party construction accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a schematic diagram of the analytical method of the present invention;

[0048] Figure 2 The Pearson-CRITIC method of the present invention is combined with the principle flow chart;

[0049] Figure 3 is a structural diagram of the analysis system of the present invention;

[0050] Figure 4 A cause-effect relationship diagram between the control defects of the third-party construction accident of the gas pipeline of the present invention;

[0051] Figure 5 It is a flow stock diagram between the third-party construction accident control defects of the gas pipeline of the present invention;

[0052] Figure 6 It is a comparison table of correlation coefficients between various control defects in the simulation experiment of the present invention. DETAILED DESCRIPTION

[0053] The principles and features of the present invention are described below in conjunction with the accompanying drawings. The examples given are only used to explain the present invention and are not intended to limit the scope of use of the present invention.

[0054] like Figure 1-6 As shown, the present invention proposes an analysis method for the impact of control defects on gas pipeline third-party construction accidents. On the basis of the hierarchical division of the components of the pipeline protection system by the STAMP model, the components of the pipeline protection system are functionally divided according to the VSM model, which makes up for the shortcomings of the STAMP model in analyzing potential defects in organizational control. However, the accident analysis part has certain shortcomings of fuzziness and subjectivity. The Pearson coefficient method is combined with the CRITIC weight method to make full use of the objective attributes of the data itself for scientific evaluation, which makes up for the shortcomings of certain subjectivity when the model is used. The Pearson-CRITIC method is used to quantitatively analyze the control defects, focusing on the analysis of the control defect weights, and combining the control defects and accident occurrence process of pipeline third-party construction damage accidents. Using the system dynamics theory, a system dynamics model of pipeline third-party construction damage accidents is constructed, and the system safety level is taken as the research object to determine the key control defects of gas pipeline third-party construction accidents that affect the changes in the system safety level the most, which provides a theoretical basis for effectively preventing, timely controlling and eliminating gas pipeline third-party construction accidents. The method specifically includes the following steps:

[0055] Step S1. Establish the third-party construction tasks and safety constraints of the gas pipeline, build the hierarchical structure of the STAMP model according to the preset functional requirements and safety goals, and analyze it in combination with the VSM model to identify control defects. Specifically include:

[0056] S1-1. The third-party construction accident of the gas pipeline is regarded as a system and divided into two modules according to safety constraints: ensuring the integrity of the gas pipeline and ensuring that the gas pipeline is not damaged by external forces;

[0057] S1-2. Establish the hierarchical structure of the STAMP model, which is divided into the physical layer, operation layer, project management layer and social system layer, to identify the control defects of pipeline third-party construction accidents;

[0058] S1-3. Establish the hierarchical structure of the VSM model, which is divided into the social system subsystem, safety decision-making subsystem, control subsystem, coordination subsystem and construction subsystem to identify the control defects of third-party construction accidents of gas pipelines.

[0059] Step S2: Digitally express the control defects obtained from each gas pipeline third-party construction accident, and obtain the coefficient of the control defects of the gas pipeline third-party construction accident through Pearson correlation analysis. Specifically include:

[0060] S2-1. Digital expression of gas pipeline third-party construction accident control defects:

[0061] Let "A" represent a certain category, "Aa 1 " indicates the first reason of subcategory a in category A, and the rest are numbered in the same way to obtain the frequency of control defects of gas pipeline third-party construction accidents;

[0062] S2-2. Based on the Pearson correlation coefficient method, the frequency of control defects in third-party construction accidents of gas pipelines is calculated, and the correlation coefficient between control defects is obtained. The calculation formula is:

[0063]

[0064] In the formula, r represents the Pearson correlation coefficient, n represents the sample size of the data, and X i , Y i is the i-th corresponding sample, indicating the specific cause of the accident; represents the sample mean, S X , S Y Represents the sample standard deviation.

[0065] Step S3. Use the CRITIC weight method to calculate the coefficient of the gas pipeline third-party construction accident control defect obtained from the Pearson correlation analysis to obtain the gas pipeline third-party construction accident control defect weight. Specifically include:

[0066] S3-1. Establish the original index database X based on the sample values ​​of the third-party construction accident control defects of the gas pipeline:

[0067]

[0068] Among them, X np Represents the value of the pth evaluation indicator for the nth sample;

[0069] S3-2. Use standard deviation to normalize and represent the indicator variability in the form of standard deviation:

[0070]

[0071] In the formula, represents the average value of the jth evaluation index, X ij represents the value of the i-th sample on the j-th evaluation index, S j represents the standard deviation of the jth indicator;

[0072] S3-3. The conflict of indicators is expressed by the correlation coefficient, and the formula is:

[0073]

[0074] In the formula, R j Represents the correlation coefficient of the jth evaluation index; establish a control defect correlation coefficient diagram with i and j as the horizontal and vertical coordinates, r ij Represents the correlation coefficient between evaluation indicators i and j;

[0075] S3-4. Calculate the information amount of each control defect. The calculation formula is:

[0076]

[0077] In the formula, C j represents the information content of the jth control defect;

[0078] S3-5. Calculate the weight of each control deficiency using the following formula:

[0079]

[0080] Where W j Represents the weight of the j-th control defect target.

[0081] Step S4. Based on the hierarchical structure and control defect weights, a system dynamics model is constructed to determine the key control defects of pipeline third-party construction accidents, and to formulate targeted prevention and improvement measures. Specifically, it includes:

[0082] S4-1. Establish a cause-effect relationship diagram between control deficiencies based on the hierarchical structure of the STAMP model;

[0083] S4-2. Based on the cause-effect relationship diagram between the third-party construction accident control defects of gas pipelines, establish the flow stock diagram between the effective third-party construction accident control defects of gas pipelines;

[0084] S4-3. Input the flow inventory diagram and control defect weights into the Vensim platform to determine the key control defects of gas pipeline third-party construction accidents.

[0085] Correspondingly, the present invention also proposes an analysis system for the impact of third-party construction accident control defects on gas pipelines, the system comprising a data acquisition module, a data processing module, a data analysis module and a result application module;

[0086] Data acquisition module, used to input digital expression parameters of gas pipeline third-party construction accident control defects;

[0087] The data processing module is used to obtain the correlation coefficient between the third-party construction accident control defects of the gas pipeline by using correlation analysis;

[0088] The data analysis module is used to configure the coefficients of control defects of third-party construction accidents of gas pipelines and use the CRITIC weight method to calculate the control defect weights;

[0089] The result application module is used to build a system dynamics model based on the hierarchical structure and control defect weights, determine the key control defects of pipeline third-party construction accidents, and send the results to managers at all levels through computer terminals, so that managers at all levels can formulate targeted prevention and improvement measures based on the results.

[0090] Simulation experiment:

[0091] The present invention collects 200 existing relevant gas accident investigation reports from 2010 to 2023, and selects 47 pipeline failure accidents caused by third-party construction. They are mainly from the Ministry of Emergency Management, local emergency management departments, industry association official websites and news channels, etc., aiming to build an accident case library for analysis by the present invention.

[0092] The control defects of the 47 collected accident cases were analyzed through the STAMP model and the VSM model. Based on the classification of control defects by the STAMP model and the classification of organizational factors by the VSM model, the causes of the above accidents were statistically sorted and 30 control defects were obtained. The specific factors are shown in Table 1.

[0093] Table 1

[0094]

[0095] The Person correlation analysis method is used to process it and obtain the correlation coefficients between the control defects. The results are as follows: Figure 6as shown in the list.

[0096] After completing the correlation analysis between control defects, the original indicator database is established according to Table 1. The total number of samples is 47, with 30 evaluation indicators, forming an original indicator data matrix, and then normalized, the data is "flattened" to a fixed interval [0,1]. For the construction party's unclear pipeline distribution, the maximum value is 1 and the minimum value is 0. Substituting it into the formula, it can be calculated that x^"=1". The calculation method for other control defects is the same. The control defects after normalization are renamed to distinguish them from the data before processing. The processed name is "MMS_Construction party unclear pipeline distribution", and the same is true for the rest of the names. According to the correlation coefficient and standard deviation, the indicator variability, indicator conflict, indicator information content, and objective weight are calculated. The results are shown in Table 2.

[0097] Table 2

[0098]

[0099]

[0100] In order to establish the causal relationship between control defects based on the STAMP model hierarchy, the control defects in Table 1 are first converted into noun forms, the causal relationship between the levels is analyzed, and a system-level causal relationship diagram is established. The specific control defects and causal relationship elements correspond to each other as shown in Tables 3 and Figure 4 shown.

[0101] Table 3

[0102]

[0103]

[0104] The gas safety operation system studies the impact of each level on system safety according to the hierarchical structure of the STAMP model, which is set as the safety of the operation layer, the safety of the project management layer, and the safety of the social system layer. They are formed by the mutual influence and constraint of the internal control and feedback of the system. The safety level of the system can be regarded as determined by the safety level of the operation layer, the safety level of the project management layer, and the safety level of the social system layer. In order to determine the influencing factors of the level variables, auxiliary variables need to be determined, as shown in Table 4.

[0105] Table 4

[0106]

[0107] In order to fully express the factors at all levels that affect the security level of the system and show the internal factors affecting the security level of each level, the security level of the system is determined by the security level of each level. The flow stock diagram is drawn as follows: Figure 5 shown.

[0108] Before simulation, it is also necessary to determine the initial values ​​of the variables and the formulas between the variables.

[0109] The specific formula of the level variable is as follows:

[0110] System security level = social system level security level + project management level security level + operation level security level;

[0111] Social system level security level = database construction + supervision and inspection + knowledge promotion + linkage mechanism;

[0112] Safety level of project management level = safety officer configuration + safety training and education + safety culture + safety supervision + emergency response + management system and procedures + hidden danger investigation system;

[0113] Operational safety level = safety awareness + on-site operation;

[0114] The relationship formula of auxiliary variables can be calculated by multiplying the weight of the control defect that affects a variable by the correlation coefficient between the two. For example, the configuration of the safety officer is affected by the safety input, so the value of the safety officer configuration is equal to the weight of the safety input 3.27 multiplied by the correlation coefficient between the safety officer configuration and the safety input 0.125. The main formulas of other auxiliary variables are as follows:

[0115] Safety culture = knowledge promotion * 0.48;

[0116] Pipeline protection plan = communication and communication with pipeline companies*0.501+safety supervision*0.062;

[0117] Safety awareness = safety training and education * 0.035;

[0118] On-site operation = safety awareness*0.11+command*0.056+pipeline location recognition+pipeline protection plan*0.139;

[0119] Safety officer configuration = safety investment * 0.125;

[0120] Exchange and communication with pipeline companies = linkage channel * 0.501;

[0121] Safety training and education = safety investment * 0.66;

[0122] According to the flow inventory diagram and the control defect weights, the simulated values ​​of the system safety level are obtained by inputting them into the Vensim platform, as shown in Table 5.

[0123] Table 5

[0124]

[0125] Through the above analysis, it can be concluded that the establishment of the linkage mechanism has the greatest impact on the system security level. Finally, according to the level of control defects in the hierarchy, it is explained that although the weight of the linkage mechanism between enterprises is not the highest, it has the greatest impact on the system security level and is the reason for the key control defect.

[0126] Establishing and improving the linkage mechanism is a key control defect in preventing pipeline third-party accidents. By calculating the weights and sorting the weights, measures are taken for the control defects with higher weights. The changes in the system safety level are demonstrated through simulation, thus reflecting the degree of influence of the control defects on the system. The results show that the establishment and improvement of the linkage mechanism has the greatest impact on the system safety level. This is because after the linkage mechanism is established, it will act between the social system layer and the project management layer, and also act within the project management layer, thereby affecting the operation layer, while the safety awareness acts between the project management layer and the operation layer, and has a small impact range in the system.

[0127] Therefore, in reality, the establishment of a sound linkage mechanism can be achieved by the gas safety management department establishing a linkage mechanism between departments and enterprises. For example, if a construction project involves underground gas pipelines, when the construction unit obtains the construction permit, the department that issued the construction permit can remind or notify the construction unit to contact the gas company. At the same time, the construction project information will be notified to the gas company, and the results of the contact between the construction unit and the gas company will be reviewed.

[0128] Obviously, the embodiments described above are only some embodiments of the present application, rather than all embodiments. The preferred embodiments of the present application are given in the accompanying drawings, but they do not limit the patent scope of the present application. The present application can be implemented in many different forms. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosure of the present application more thorough and comprehensive. Although the present application is described in detail with reference to the aforementioned embodiments, for those skilled in the art, it is still possible to modify the technical solutions recorded in the aforementioned specific implementation methods, or to perform equivalent replacement of some of the technical features therein. Any equivalent structure made using the contents of the specification and drawings of this application, directly or indirectly used in other related technical fields, is similarly within the scope of patent protection of this application.

Claims

1. An analysis method for the impact of third-party construction accident control defects on gas pipelines, characterized by: The method specifically comprises the following steps: S1. Establish third-party construction tasks and safety constraints for gas pipelines, build the hierarchical structure of the STAMP model based on preset functional requirements and safety goals, and analyze it in combination with the VSM model to identify control deficiencies; S2. Digitally express the control defects obtained from each gas pipeline third-party construction accident, and obtain the coefficient of the control defects of the gas pipeline third-party construction accident through Pearson correlation analysis; S3. Use the CRITIC weight method to calculate the coefficient of the third-party construction accident control defect of the gas pipeline obtained from the Pearson correlation analysis to obtain the weight of the third-party construction accident control defect of the gas pipeline; S4. Based on the hierarchical structure and control defect weights, a system dynamics model is constructed to determine the key control defects of pipeline third-party construction accidents, and to develop targeted prevention and improvement measures.

2. The method for analyzing the impact of third-party construction accident control defects on gas pipelines according to claim 1 is characterized by: Step S1 specifically includes the following contents: S1-1. The third-party construction accident of the gas pipeline is regarded as a system and divided into two modules according to safety constraints: ensuring the integrity of the gas pipeline and ensuring that the gas pipeline is not damaged by external forces; S1-2. Establish the hierarchical structure of the STAMP model, which is divided into the physical layer, operation layer, project management layer and social system layer, to identify the control defects of pipeline third-party construction accidents; S1-3. Establish the hierarchical structure of the VSM model, which is divided into the social system subsystem, safety decision-making subsystem, control subsystem, coordination subsystem and construction subsystem to identify the control defects of third-party construction accidents of gas pipelines.

3. The method for analyzing the impact of third-party construction accident control defects on gas pipelines according to claim 1 is characterized by: Step S2 specifically includes: S2-1. Digital expression of gas pipeline third-party construction accident control defects: Let "A" represent a certain category, "Aa1" represent the first cause of category a in category A, and the rest of the numbers are similar, to obtain the frequency of gas pipeline third-party construction accident control defects; S2-2. Based on the Pearson correlation coefficient method, the frequency of control defects in third-party construction accidents of gas pipelines is calculated, and the correlation coefficient between control defects is obtained. The calculation formula is: In the formula, r represents the Pearson correlation coefficient, n represents the sample size of the data, and X i , Y i is the i-th corresponding sample, indicating the specific cause of the accident; represents the sample mean, S X , S Y Represents the sample standard deviation.

4. The method for analyzing the impact of third-party construction accident control defects on gas pipelines according to claim 3 is characterized by: Step S3 specifically includes: S3-1. Establish the original index database X based on the sample values ​​of the third-party construction accident control defects of the gas pipeline: Among them, X np Represents the value of the pth evaluation indicator for the nth sample; S3-2. Use standard deviation to normalize and represent the indicator variability in the form of standard deviation: In the formula, represents the average value of the jth evaluation index, X ij represents the value of the i-th sample on the j-th evaluation index, S j represents the standard deviation of the jth indicator; S3-3. The conflict of indicators is expressed by the correlation coefficient, and the formula is: In the formula, R j Represents the correlation coefficient of the jth evaluation index; establish a control defect correlation coefficient diagram with i and j as the horizontal and vertical coordinates, r ij Represents the correlation coefficient between evaluation indicators i and j; S3-4. Calculate the information amount of each control defect. The calculation formula is: In the formula, C j represents the information content of the jth control defect; S3-5. Calculate the weight of each control deficiency using the following formula: Where W j Represents the weight of the j-th control defect target.

5. The method for analyzing the impact of third-party construction accident control defects on gas pipelines according to claim 1 is characterized by: Step S4 specifically includes: S4-1. Establish a cause-effect relationship diagram between control deficiencies based on the hierarchical structure of the STAMP model; S4-2. Based on the cause-effect relationship diagram between the third-party construction accident control defects of gas pipelines, establish the flow stock diagram between the effective third-party construction accident control defects of gas pipelines; S4-3. Input the flow inventory diagram and control defect weights into the Vensim platform to determine the key control defects of gas pipeline third-party construction accidents.

6. The analysis method of the impact of third-party construction accident control defects of gas pipelines according to claim 1 is implemented based on the analysis system of the impact of third-party construction accident control defects of gas pipelines, and is characterized by: The system includes a data acquisition module, a data processing module, a data analysis module and a result application module; The data acquisition module is used to input digital expression parameters of gas pipeline third-party construction accident control defects; The data processing module is used to obtain the correlation coefficient between the third-party construction accident control defects of the gas pipeline by using correlation analysis; The data analysis module is used to configure the coefficient of the control defect of the third-party construction accident of the gas pipeline, and use the CRITIC weight method to calculate the control defect weight; The result application module is used to construct a system dynamics model according to the hierarchical structure and control defect weights, determine the key control defects of pipeline third-party construction accidents, and send the results to managers at all levels through computer terminals, so that managers at all levels can formulate targeted prevention and improvement measures based on the results.

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