Analysis Method and System for Influences of Control Defects in Third-Party Construction Accidents of Gas Pipelines

Abstract

The present invention belongs to the field of accident analysis, and specifically discloses an analysis method and system for the influence of control defects in third-party construction accidents of gas pipelines. The analysis method includes the following steps: establishing system tasks and safety constraints, constructing the hierarchical structure of the STAMP model according to preset functional requirements and safety objectives, and analyzing in combination with the VSM model to identify control defects; digitally expressing the control defects obtained from the analysis of each third-party construction accident of gas pipelines, and obtaining the coefficient of control defects in third-party construction accidents of gas pipelines through Pearson correlation analysis; using the CRITIC weight method to process and calculate the coefficient of control defects in third-party construction accidents of gas pipelines obtained from the correlation analysis to obtain the weight of control defects in third-party construction accidents of gas pipelines; finally, according to the hierarchical structure and the weight of control defects, constructing a system dynamics model to determine the key control defects in third-party construction accidents of pipelines, so as to formulate targeted prevention and improvement measures.

Description

Technical Field

[0001] The present invention belongs to the field of accident analysis, and particularly relates to an analysis method and system for the influence of control defects in third-party construction accidents of gas pipelines. Background Art

[0002] As the main transportation mode of gas, 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 pipe networks, including damage to pipeline anticorrosion layers, scratching, deformation, bending and damage of pipelines and equipment, as well as resulting fatigue, corrosion, leakage and stress concentration problems. Therefore, an analysis technology for the influence 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 solve the deficiencies of the prior art, the present invention aims to provide an analysis method for the influence of control defects in third-party construction accidents of gas pipelines. This method uses the Pearson-Critic method to quantitatively analyze the control defects in third-party construction accidents of gas pipelines, constructs a system dynamics model according to the hierarchical structure and control defect weights, determines the key control defects in third-party construction accidents of gas pipelines, and thus formulates targeted prevention and improvement measures, providing a theoretical basis for effectively preventing, timely controlling and eliminating third-party construction accidents of gas pipelines.

[0004] To achieve the above object, the technical solution adopted by the present invention is as follows:

[0005] An analysis method for the influence of control defects in third-party construction accidents of gas pipelines, which specifically includes the following steps:

[0006] S1. Establish the third-party construction tasks and safety constraints of gas pipelines, construct the hierarchical structure of the STAMP model according to the preset functional requirements and safety objectives, and analyze in combination with the VSM model to identify control defects;

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

[0008] S3. Use the CRITIC weight method to process and calculate the coefficient of control defects in third-party construction accidents of gas pipelines obtained from Pearson correlation analysis to obtain the weight of control defects in third-party construction accidents of gas pipelines;

[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, "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;

[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 p-th evaluation index of the n-th sample;

[0024] S3-2. Perform normalization processing using standard deviation, and represent the index variability in the form of standard deviation:

[0025]

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

[0027] S3-3. The index conflict is represented by the correlation coefficient, and its formula is:

[0028]

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

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

[0031]

[0032] In the formula, C j represents the information amount of the j-th control defect;

[0033] S3-5. Calculate the weight of each control defect, and the calculation formula is:

[0034]

[0035] In the formula, W j represents the weight of the j-th control defect target.

[0036] Furthermore, step S4 specifically includes:

[0037] S4-1. Establish a causal relationship diagram between control defects according to the hierarchical structure of the STAMP model;

[0038] S4-2. According to the causal relationship diagram between control defects of third-party construction accidents of gas pipelines, establish a flow-stock diagram between effective control defects of third-party construction accidents of gas pipelines;

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

[0040] Correspondingly, the present invention also proposes an analysis system for the impact of control defects in third-party construction accidents of 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 the digital expression parameters of control defects in third-party construction accidents of gas pipelines;

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

[0043] The data analysis module is used to configure the coefficients of control defects in third-party construction accidents of gas pipelines and use the CRITIC weight method to calculate the control defect weights;

[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 third-party construction accidents of pipelines, and send the results to managers at all levels through a computer terminal, so that managers at all levels can formulate targeted prevention and improvement measures according to the results.

[0045] The beneficial effects of the present invention are as follows:

[0046] Based on the hierarchical division of the components of the pipeline protection system by the STAMP model, the present invention also conducts a functional division of the components of the pipeline protection system according to the VSM model, compensating for the deficiencies of the STAMP model in analyzing potential organizational controls. However, the accident analysis part has certain drawbacks of fuzziness and subjectivity. By combining the Pearson coefficient method and the CRITIC weight method, the objective attributes of the data itself are fully utilized for scientific evaluation, making up for the deficiency of subjectivity in the use of the model. Therefore, the Pearson-CRITIC method is used for quantitative analysis of control defects, focusing on analyzing the control defect weights. Combining the control defects and the accident occurrence process of third-party construction damage accidents of pipelines, a system dynamics model of third-party construction damage accidents of pipelines is constructed using the system dynamics theory. Taking the system safety level as the research object, the key control defects of third-party construction accidents of gas pipelines that have the greatest impact on the change of the system safety level are determined, providing a theoretical basis for effectively preventing, timely controlling, and eliminating third-party construction accidents of gas pipelines. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a schematic flow chart of the analysis method of the present invention;

[0048] Figure 2 This is the flow chart of the combination principle of the Pearson-CRITIC method of the present invention;

[0049] Figure 3 This is the structure diagram of the analysis system of the present invention;

[0050] Figure 4 This is the causal relationship diagram between the control defects of the third-party construction accidents of the gas pipeline of the present invention;

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

[0052] Figure 6 This is the correlation coefficient comparison table between the control defects in the simulation experiment of the present invention. Specific embodiments

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

[0054] As Figures 1-6 shown, the present invention proposes an analysis method for the impact of control defects in third-party construction accidents of gas pipelines. On the basis of hierarchically dividing the components of the pipeline protection system by the STAMP model, the functions of the components of the pipeline protection system are further divided according to the VSM model, making up for the deficiencies in the STAMP model when analyzing potential organizational controls. However, there are certain fuzzy and subjective drawbacks in the accident analysis part. By combining the Pearson coefficient method and the CRITIC weight method, the objective attributes of the data itself are fully utilized for scientific evaluation, making up for the deficiency of certain subjectivity in the use of the model. Therefore, the Pearson-CRITIC method is used for quantitative analysis of control defects, focusing on analyzing the control defect weights. Combining the control defects and the accident occurrence process of third-party construction damage accidents of pipelines, a system dynamics model of third-party construction damage accidents of pipelines is constructed using the system dynamics theory, and taking the system safety level as the research object, the key control defects of third-party construction accidents of gas pipelines that have the greatest impact on the change of the system safety level are determined, providing a theoretical basis for effectively preventing, timely controlling, and eliminating third-party construction accidents of gas pipelines. The method specifically includes the following steps:

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

[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, "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;

[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 p-th evaluation index of the n-th sample;

[0069] S3-2. Perform normalization using standard deviation to represent the variability of indicators in the form of standard deviation:

[0070]

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

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

[0073]

[0074] In the formula, R j represents the correlation coefficient of the j-th evaluation index; A control defect correlation coefficient graph is established with i and j as the horizontal and vertical coordinates, and r ij represents the correlation coefficient between the evaluation indicators i and j;

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

[0076]

[0077] In the formula, C j represents the information amount of the j-th control defect;

[0078] S3-5. Calculate the weight of each control defect, and the calculation formula is:

[0079]

[0080] In the formula, W j represents the weight of the j-th control defect target.

[0081] Step S4. According to the hierarchical structure and control defect weights, construct a system dynamics model, determine the key control defects of the third-party construction accident of the pipeline, and formulate targeted prevention and improvement measures. Specifically include:

[0082] S4-1. Establish a causal relationship diagram between control defects according to the hierarchical structure of the STAMP model;

[0083] S4-2. Based on the causal relationship diagram between the control defects of third-party construction accidents in gas pipelines, establish a flow-stock diagram between the effective control defects of third-party construction accidents in gas pipelines;

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

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

[0086] The data acquisition module is used to input the digital expression parameters of the control defects of third-party construction accidents in gas pipelines;

[0087] The data processing module is used to obtain the correlation coefficients between the control defects of third-party construction accidents in gas pipelines by using correlation analysis;

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

[0089] 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 third-party construction accidents in pipelines, and send the results to managers at all levels through a computer terminal, so that managers at all levels can formulate targeted prevention and improvement measures according to the results.

[0090] Simulation experiment:

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

[0092] Analyze the control defects of the 47 accident cases collected through the STAMP model and the VSM model, and based on the classification of control defects by the STAMP model and the classification of organizational factors by the VSM model, statistically sort out the above accident causes to obtain 30 control defects, and the specific factors are shown in Table 1.

[0093] Table 1

[0094]

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

[0096] After completing the correlation analysis between control defects, an original index database is established according to Table 1. The total number of samples is 47, and there are 30 evaluation indicators, forming an original index data matrix. Then, normalization processing is performed, and the data is "flattened" to a certain fixed interval [0, 1]. For the pipeline distribution not clearly defined by the construction party, its maximum value is 1 and the minimum value is 0. Substituting into the formula for calculation, we can get x^"=1". The calculation methods for the remaining control defects are the same. The control defects after normalization processing are renamed to distinguish them from the data before processing. The processed ones are named "MMS_ pipeline distribution not clearly defined by the construction party", and the same applies to the rest of the naming. According to the correlation coefficient and standard deviation, the index variability, index conflict, index information content, and objective weight are calculated, and the results are shown in Table 2.

[0097] Table 2

[0098]

[0099]

[0100] To establish the causal relationship between control defects based on the STAMP model hierarchy, first convert the control defects in Table 1 into noun forms, analyze the causal relationship between levels, and establish a system-level causal relationship diagram. The corresponding relationship between specific control defects and causal relationship elements is shown in Table 3 and Figure 4 as shown below.

[0101] Table 3

[0102]

[0103]

[0104] The gas safety operation system studies the impact of each level on system safety according to the STAMP model hierarchy, and is respectively 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 restraint of internal control and feedback in the system. The level of system safety can be regarded as determined by the levels of safety of the operation layer, the project management layer, and the social system layer. To determine the influencing factors of the level variables, auxiliary variables also need to be determined, as shown in Table 4.

[0105] Table 4

[0106]

[0107] To fully express the factors at each level affecting the system safety level and display the internal influencing factors of the safety level at each level, the system safety level is determined by the safety levels at each level, and the drawn flow-stock diagram is as Figure 5 shown below.

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

[0109] The specific formulas for the horizontal variables are as follows:

[0110] System safety level = Social system layer safety level + Project management layer safety level + Operation layer safety level;

[0111] Social system layer safety level = Database construction + Supervision and inspection + Knowledge publicity + Linkage mechanism;

[0112] Project management layer safety level = Safety officer allocation + Safety training and education + Safety culture + Safety supervision + Emergency handling + Management system and procedures + Hidden danger investigation system;

[0113] Operation layer safety level = Safety awareness + On-site operation;

[0114] The relationship formula between the auxiliary variables can be obtained by multiplying the control defect weight affecting a certain variable by the correlation coefficient between the two. For example, the allocation of safety officers is affected by the safety investment. Therefore, the value of the safety officer allocation is equal to the weight of the safety investment, 3.27, multiplied by the correlation coefficient between the safety officer allocation and the safety investment, 0.125. The main formulas for the remaining auxiliary variables are as follows:

[0115] Safety culture = Knowledge publicity * 0.48;

[0116] Pipeline protection plan = Communication with the pipeline company * 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 position awareness + Pipeline protection plan * 0.139;

[0119] Safety officer allocation = Safety investment * 0.125;

[0120] Communication with the pipeline company = Linkage channel * 0.501;

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

[0122] Input the flow stock diagram and the control defect weights into the Vensim platform to obtain the simulated value of the system safety level, as shown in Table 5.

[0123] Table 5

[0124]

[0125] Through the above analysis, it can be obtained that the establishment of the linkage mechanism has the greatest impact on the system security level. Finally, according to the level of the control defect in the hierarchical structure, the reason why the linkage mechanism between enterprises, although not having the highest weight, has the greatest impact on the system security level and is regarded as a key control defect is explained.

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

[0127] Therefore, in reality, establishing and improving the linkage mechanism can enable the gas safety management department to establish a connection 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 issuing the construction permit can remind or notify the construction unit to contact the gas company. At the same time, the construction project information will also be notified to the gas company, and the contact result between the construction unit and the gas company will be reviewed.

[0128] Obviously, the embodiments described above are only a part of the embodiments of this application, rather than all embodiments. The drawings of this application give preferred embodiments, but do not limit the patent scope of this application. This application can be implemented in many different forms. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosed content of this application more thorough and comprehensive. Although this application has been described in detail with reference to the foregoing embodiments, for those skilled in the art, they can still modify the technical solutions recorded in the foregoing specific embodiments, or perform equivalent replacements for some of the technical features. Any equivalent structure directly or indirectly using the content of this application's specification and drawings in other related technical fields is equally within the scope of the patent protection of this application.

Claims

1. Analysis method for the influence of control defects in third-party construction accidents of gas pipelines, characterized in that: 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 formulate targeted prevention and improvement measures; 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 a hierarchical structure of the VSM model, divided into social system subsystem, safety decision subsystem, control subsystem, coordination subsystem and construction subsystem, to identify control defects in third-party construction accidents of gas pipelines; 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: where r represents the Pearson correlation coefficient, n represents the sample size of the data, X i , Y i is the i-th corresponding sample, representing the specific cause of the accident; represents the sample mean, and S X , S Y represents the sample standard deviation; 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.

2. The analysis method for the influence of the control defect of the third-party construction accident on the gas pipeline according to claim 1, characterized in that: 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 p-th evaluation index of the n-th 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 j-th evaluation index, and X ij represents the value of the i-th sample on the j-th evaluation index, and S j represents the standard deviation of the j-th index; S3-3. The conflict of indicators is expressed by the correlation coefficient, and the formula is: where R j represents the correlation coefficient of the j-th evaluation index; a control defect correlation coefficient graph is established with i and j as the horizontal and vertical coordinates, and r ij represents the correlation coefficient of the evaluation index between i and j; S3-4. Calculate the information amount of each control defect. The calculation formula is: where C j represents the amount of information of the j-th 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.

3. The analysis method for the influence of third-party construction accident control defects of gas pipelines as described in claim 1 is implemented based on an analysis system for the influence of third-party construction accident control defects of gas pipelines, and is characterized in that: 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 the digital expression parameters of the control defects of third-party construction accidents in gas pipelines; The data processing module is used to obtain the correlation coefficients between the control defects of third-party construction accidents in gas pipelines by using correlation analysis; The data analysis module is used to configure the coefficients of the control defects of third-party construction accidents in gas pipelines and use the CRITIC weight method to calculate the control defect weights; 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 third-party construction accidents in pipelines, and send the results to managers at all levels through a computer terminal, so that managers at all levels can formulate targeted prevention and improvement measures according to the results.

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