A method for evaluating the operation management and risk prevention and control capabilities of unmanned stations in oil and gas pipelines

Abstract

The present application discloses a method for evaluating the operation management and risk prevention and control capabilities of an unmanned station of an oil and gas pipeline, the method comprising: acquiring first acquired data information by acquiring data on the oil and gas pipeline according to a data acquisition device; constructing a multidimensional evaluation model; inputting the first acquired data information into the multidimensional evaluation model for multidimensional evaluation to obtain first output information; generating a first multidimensional index score; normalizing the first multidimensional index score to obtain a second multidimensional index score; calling a preset grade calculation formula from a grade calculation module according to a first scoring instruction to perform grade calculation on the second multidimensional index score to obtain a multidimensional scoring grade; generating a first scoring grade according to the multidimensional scoring grade; and obtaining a first evaluation report. The method solves the technical problems in the prior art that the conditions for implementing unmanned station management in the oil and gas pipeline industry cannot be intelligently evaluated, and that the risks of unmanned station management cannot be effectively identified.

Description

Technical Field

[0001] The present application relates to the field of artificial intelligence, and in particular to a method for evaluating the operation management and risk prevention and control capabilities of unmanned stations in oil and gas pipelines. Background Art

[0002] With the continuous development of automation, informatization and intelligent technology of long-distance oil and gas pipelines, technological progress has continuously promoted the transformation of management models, from traditional duty mode and waiting mode to regionalized and unmanned station management mode. The unmanned station management mode is an inevitable choice to optimize the labor organization structure, achieve cost reduction and efficiency improvement, and promote the high-quality development of the oil and gas pipeline industry. With the in-depth promotion of the unmanned station management model, the station has undergone changes in software and hardware conditions, management interface, and personnel capability requirements. At the same time, risks will also come with it, making it possible for the station to have uncontrolled risks. Therefore, how to objectively, comprehensively and scientifically evaluate the current status of the ability of oil and gas pipeline stations to implement unmanned station management and identify the risks that will arise in the process of transforming oil and gas pipeline stations from traditional management mode to unmanned station management mode has become an important part of promoting the unmanned station management mode.

[0003] In the process of implementing the technical solution in the embodiments of the present application, the inventors of the present application found that the above technology has at least the following technical problems:

[0004] The existing technology is unable to conduct intelligent assessment of the conditions for implementing unmanned station management in the oil and gas pipeline industry, and there is also a technical problem that it is unable to effectively identify the risks of unmanned station management. Summary of the invention

[0005] The purpose of this application is to provide a method for evaluating the operation management and risk prevention and control capabilities of unmanned stations in oil and gas pipelines, so as to solve the technical problems in the prior art that the conditions for implementing unmanned station management in the oil and gas pipeline industry cannot be intelligently evaluated, and that the risks of unmanned station management cannot be effectively identified.

[0006] In view of the above problems, an embodiment of the present application provides a method for operation management and risk prevention and control capability evaluation of an unmanned station of an oil and gas pipeline.

[0007] In a first aspect, the present application provides an operation and risk prevention and control evaluation method for an unmanned station of an oil and gas pipeline, the method being implemented by an operation management and risk prevention and control capability evaluation system for an unmanned station of an oil and gas pipeline, wherein the method comprises: acquiring first acquired data information by acquiring data on the oil and gas pipeline according to the data acquisition device; constructing a multidimensional evaluation model, wherein each dimension in the multidimensional evaluation model has multiple indicators; inputting the first acquired data information into the multidimensional evaluation model for multidimensional evaluation, and acquiring first output information according to the multidimensional evaluation model, wherein the first output information is multidimensional evaluation information; generating a first multidimensional indicator score according to the multidimensional evaluation information; acquiring a second multidimensional indicator score by normalizing the first multidimensional indicator score; performing grade calculation on the second multidimensional indicator score by calling a preset grade calculation formula from a grade calculation module according to a first scoring instruction, and acquiring a multidimensional scoring grade; generating a first scoring grade according to the multidimensional scoring grade, wherein the first scoring grade is the lowest grade among the multidimensional scoring grades; and obtaining a first evaluation report according to the first scoring grade.

[0008] On the other hand, the present application also provides an oil and gas pipeline unmanned station operation management and risk prevention and control capability evaluation system, which is used to execute an oil and gas pipeline unmanned station operation and risk prevention and control evaluation method as described in the first aspect, wherein the system includes: a first acquisition unit: the first acquisition unit is used to collect data on the oil and gas pipeline according to a data acquisition device to obtain first collected data information; a first construction unit: the first construction unit is used to construct a multidimensional evaluation model, wherein each dimension in the multidimensional evaluation model has multiple indicators; a second acquisition unit: the second acquisition unit is used to input the first collected data information into the multidimensional evaluation model for multidimensional evaluation, and obtain first output information according to the multidimensional evaluation model, wherein the first output information is a multidimensional Evaluation information; a first generation unit: the first generation unit is used to generate a first multidimensional indicator score according to the multidimensional evaluation information; a third acquisition unit: the third acquisition unit is used to obtain a second multidimensional indicator score by normalizing the first multidimensional indicator score; a fourth acquisition unit: the fourth acquisition unit is used to call a preset grade calculation formula from a grade calculation module according to a first scoring instruction to perform grade calculation on the second multidimensional indicator score to obtain a multidimensional scoring grade; a second generation unit: the second generation unit is used to generate a first scoring grade according to the multidimensional scoring grade, wherein the first scoring grade is the lowest grade among the multidimensional scoring grades; a fifth acquisition unit: the fifth acquisition unit is used to obtain a first evaluation report according to the first scoring grade.

[0009] In a third aspect, an embodiment of the present application further provides an oil and gas pipeline unmanned station operation management and risk prevention and control capability evaluation system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method described in the first aspect when executing the program.

[0010] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0011] 1. By collecting data from the oil and gas pipeline according to the data collection device, first collected data information is obtained; a multidimensional evaluation model is constructed, wherein each dimension in the multidimensional evaluation model has multiple indicators; the first collected data information is input into the multidimensional evaluation model for multidimensional evaluation, and first output information is obtained according to the multidimensional evaluation model, wherein the first output information is multidimensional evaluation information; a first multidimensional indicator score is generated according to the multidimensional evaluation information; a second multidimensional indicator score is obtained by normalizing the first multidimensional indicator score; a preset grade calculation formula is called from the grade calculation module according to the first scoring instruction to perform grade calculation on the second multidimensional indicator score to obtain a multidimensional scoring grade; a first scoring grade is generated according to the multidimensional scoring grade, wherein the first scoring grade is the lowest grade in the multidimensional scoring grade; a first evaluation report is obtained according to the first scoring grade. The method achieves the goal of intelligently evaluating the multi-party conditions for implementing unmanned station management of the oil and gas pipeline based on the real-time data collection results of the oil and gas pipeline, thereby determining the scoring level of the unmanned station management capability, and finally generating a personalized evaluation report, thereby promoting the technical effect of promoting unmanned station management of the oil and gas pipeline.

[0012] 2. Through the first auxiliary evaluation model, a multi-dimensional, multi-indicator intelligent evaluation is conducted on the operation and management of the oil and gas pipeline in the transition to an unmanned station, achieving the technical effect of intelligently identifying the comprehensive situation of unmanned station management. Further based on the evaluation results, the feasibility assessment of the implementation of unmanned station management in the oil and gas pipeline industry is revised, thereby improving the accuracy of the system evaluation results and achieving the technical effect of providing objective and effective theoretical guidance for the transition of the oil and gas pipeline to an unmanned station management mode.

[0013] 3. By discarding the indicator scores that do not reach the preset indicator score data in each dimension, the adverse impact of extreme data on the overall score results is avoided, achieving the technical effect of improving the accuracy of the evaluation.

[0014] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0016] Figure 1 This is a flow chart of a method for evaluating the operation management and risk prevention and control capabilities of an unmanned station of an oil and gas pipeline according to an embodiment of the present application;

[0017] Figure 2 A schematic diagram of a process for obtaining a second scoring level by correcting the first scoring level according to the second output information in a method for evaluating the operation management and risk prevention and control capabilities of an unmanned station of an oil and gas pipeline according to an embodiment of the present application;

[0018] Figure 3 This is a flow chart of obtaining the first output information in a method for operation management and risk prevention and control capability evaluation of an unmanned station of an oil and gas pipeline according to an embodiment of the present application;

[0019] Figure 4 A flowchart of sending the first assessment report to the first manager according to the first reminder information in a method for operation management and risk prevention and control capability evaluation of an unmanned station of an oil and gas pipeline according to an embodiment of the present application;

[0020] Figure 5 This is a structural diagram of an oil and gas pipeline unmanned station operation management and risk prevention and control capability evaluation system according to an embodiment of the present application;

[0021] Figure 6 It is a schematic diagram of the structure of an exemplary electronic device according to an embodiment of the present application.

[0022] Description of reference numerals:

[0023] A first obtaining unit 11 , a first constructing unit 12 , a second obtaining unit 13 , a first generating unit 14 , a third obtaining unit 15 , a fourth obtaining unit 16 , a second generating unit 17 , a fifth obtaining unit 18 , a bus 300 , a receiver 301 , a processor 302 , a transmitter 303 , a memory 304 , and a bus interface 305 . DETAILED DESCRIPTION

[0024] The embodiment of the present application provides an evaluation method for the operation management and risk prevention and control capabilities of unmanned stations in oil and gas pipelines, which solves the technical problems in the prior art that the conditions for implementing unmanned station management in the oil and gas pipeline industry cannot be intelligently evaluated, and the risks of unmanned station management cannot be effectively identified. It achieves the technical effect of intelligently evaluating the multiple conditions for implementing unmanned station management in oil and gas pipelines based on the real-time data collection results of the oil and gas pipelines, and then determining the scoring level of the unmanned station management capabilities, and finally generating a personalized evaluation report, thereby promoting the implementation of unmanned station management in oil and gas pipelines.

[0025] Below, the technical solutions in the embodiments of the present application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments of the present application. It should be understood that the present application is not limited to the example embodiments described herein. Based on the embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application. It should also be noted that, for the convenience of description, only the parts related to the present application are shown in the accompanying drawings, rather than all of them.

[0026] Application Overview

[0027] With the continuous development of automation, informatization and intelligent technology of long-distance oil and gas pipelines, technological progress has continuously promoted the transformation of management models, from traditional duty mode and waiting mode to regionalized and unmanned station management mode. The unmanned station management mode is an inevitable choice to optimize the labor organization structure, achieve cost reduction and efficiency improvement, and promote the high-quality development of the oil and gas pipeline industry. With the in-depth promotion of the unmanned station management model, the station has undergone changes in software and hardware conditions, management interface, and personnel capability requirements. At the same time, risks will also come with it, making it possible for the station to have uncontrolled risks. Therefore, how to objectively, comprehensively and scientifically evaluate the current status of the ability of oil and gas pipeline stations to implement unmanned station management and identify the risks that will arise in the process of transforming oil and gas pipeline stations from traditional management mode to unmanned station management mode has become an important part of promoting the unmanned station management mode.

[0028] The existing technology is unable to conduct intelligent assessment of the conditions for implementing unmanned station management in the oil and gas pipeline industry, and there is also a technical problem that it is unable to effectively identify the risks of unmanned station management.

[0029] In response to the above technical problems, the overall idea of ​​the technical solution provided by this application is as follows:

[0030] The present application provides an operation management and risk prevention and control capability evaluation method for an unmanned station of an oil and gas pipeline, and the method is applied to an operation management and risk prevention and control capability evaluation system for an unmanned station of an oil and gas pipeline, wherein the method comprises: acquiring first acquired data information by acquiring data on the oil and gas pipeline according to the data acquisition device; constructing a multidimensional evaluation model, wherein each dimension in the multidimensional evaluation model has multiple indicators; inputting the first acquired data information into the multidimensional evaluation model for multidimensional evaluation, and acquiring first output information according to the multidimensional evaluation model, wherein the first output information is multidimensional evaluation information; generating a first multidimensional indicator score according to the multidimensional evaluation information; acquiring a second multidimensional indicator score by normalizing the first multidimensional indicator score; performing grade calculation on the second multidimensional indicator score by calling a preset grade calculation formula from a grade calculation module according to a first scoring instruction, and acquiring a multidimensional scoring grade; generating a first scoring grade according to the multidimensional scoring grade, wherein the first scoring grade is the lowest grade among the multidimensional scoring grades; and obtaining a first evaluation report according to the first scoring grade.

[0031] After introducing the basic principles of the present application, various non-limiting implementation methods of the present application will be specifically described below in conjunction with the drawings in the specification.

[0032] Embodiment 1

[0033] Please refer to the attached Figure 1 The embodiment of the present application provides an oil and gas pipeline unmanned station operation management and risk prevention and control capability evaluation method, wherein the method is applied to an oil and gas pipeline unmanned station operation management and risk prevention and control capability evaluation system, the system is communicatively connected with a data acquisition device, and the method specifically includes the following steps:

[0034] Step S100: collecting data on the oil and gas pipeline according to the data collection device to obtain first collected data information;

[0035] Specifically, the method for evaluating the operation management and risk prevention and control capabilities of unmanned stations of oil and gas pipelines is applied to the evaluation system for the operation management and risk prevention and control capabilities of unmanned stations of oil and gas pipelines. Based on the real-time data collection results of the oil and gas pipelines, the multiple conditions for implementing unmanned station management of the oil and gas pipelines can be intelligently evaluated, and then the scoring level of the unmanned station management capabilities can be determined, and finally a personalized evaluation report can be generated, thereby promoting the implementation of the unmanned station management mode of the oil and gas pipelines. The oil and gas pipelines include oil pipelines and gas pipelines. The oil pipelines are composed of oil pipes and their accessories, and are equipped with corresponding oil pump units according to the needs of the process flow, and are designed and installed into a complete pipeline system; the gas pipeline refers to a pipeline mainly used for transporting natural gas, liquefied petroleum gas, and artificial coal gas. The data acquisition device refers to the data that can collect the relevant data of the oil and gas pipelines transporting oil and gas and the relevant condition data of the unmanned station management of the oil and gas pipelines in real time, that is, the first collected data information. Among them, the first collected data information includes relevant data information in the dimensions of basic realization, capacity maintenance, risk prevention and control, consequence reduction, emergency management and disposal of unmanned station management of oil and gas pipelines. In addition, since the data acquisition device is communicatively connected to the oil and gas pipeline unmanned station operation and risk prevention and control evaluation system, the collected data can be transmitted to the system in real time.

[0036] Through the data acquisition device, the technical effect of comprehensively and accurately understanding the relevant condition data of unmanned station management of oil and gas pipelines is achieved, laying a data foundation for the subsequent evaluation of the feasibility of implementing the unmanned station management mode for the corresponding oil and gas pipelines.

[0037] Step S200: constructing a multidimensional evaluation model, wherein each dimension in the multidimensional evaluation model has multiple indicators;

[0038] Specifically, the multidimensional evaluation model is embedded in the oil and gas pipeline unmanned station operation and risk prevention and control evaluation system, and is used to intelligently evaluate the feasibility of the oil and gas pipeline unmanned station management mode. The evaluation dimensions of the multidimensional evaluation model include the basic realization of unmanned station management of oil and gas pipelines, capacity maintenance, risk prevention and control, consequence mitigation, emergency management and disposal, and each dimension in the multidimensional evaluation model has multiple evaluation indicators. For example, the assessment and evaluation of the basic implementation dimension of unmanned station management of oil and gas pipelines includes aspects such as process flow, key equipment and instruments, basic process control systems, auxiliary systems, alarm management, organizational and system updates and changes; the assessment and evaluation of the capability maintenance dimension of unmanned station management of oil and gas pipelines includes aspects such as reliability, availability, maintainability, etc.; the assessment and evaluation of the risk prevention and control dimension of unmanned station management of oil and gas pipelines includes aspects such as functional safety of unmanned stations, information security and key risk management; the assessment and evaluation of the consequence mitigation dimension of unmanned station management of oil and gas pipelines includes aspects such as fire and gas systems, release systems, and fire protection systems; the assessment and evaluation of the emergency management and disposal dimension of unmanned station management of oil and gas pipelines includes aspects such as emergency plans, emergency drills, emergency disposal capabilities, disposal plans, and emergency guarantees.

[0039] Through the multidimensional evaluation model, various aspects of unmanned station management of oil and gas pipelines are evaluated, and then multi-dimensional evaluation results of the implementation of unmanned station management of oil and gas pipelines are obtained, achieving the technical effect of all-round and full-coverage comprehensive evaluation, and improving the accuracy and effectiveness of intelligent evaluation results.

[0040] Step S300: inputting the first collected data information into the multidimensional evaluation model for multidimensional evaluation, and obtaining first output information according to the multidimensional evaluation model, wherein the first output information is multidimensional evaluation information;

[0041] Specifically, the relevant data of oil and gas transported by the oil and gas pipelines and the relevant condition data of unmanned station management of the oil and gas pipelines collected in real time by the data acquisition device are input into the multidimensional evaluation model, and the corresponding first output information is obtained through the intelligent multidimensional evaluation of the multidimensional evaluation model. Among them, the first output information is the feasibility evaluation results of unmanned stations in multiple dimensions, including the basic realization of unmanned station management of oil and gas pipelines, capacity maintenance, risk prevention and control, consequence reduction, emergency management and disposal. Through the multidimensional evaluation model, the feasibility of unmanned station management of oil and gas pipelines is comprehensively evaluated in an all-round and comprehensive manner, thereby improving the accuracy and effectiveness of intelligent evaluation results.

[0042] Step S400: generating a first multidimensional indicator score according to the multidimensional evaluation information;

[0043] Step S500: obtaining a second multidimensional indicator score by normalizing the first multidimensional indicator score;

[0044] Specifically, the first multidimensional index score includes all evaluation index results corresponding to various dimensions such as the basic implementation of unmanned station management of oil and gas pipelines, capacity maintenance, risk prevention and control, consequence mitigation, emergency management and disposal. Since each dimension corresponds to multiple different evaluation indicators, and there are large differences in the numerical value and unit of each indicator evaluation result, the first multidimensional index score result is normalized, and all the indicator evaluation results after processing are the second multidimensional index score. Among them, the normalization process is a way to simplify the calculation. There are two forms of normalization methods: one is to convert the number into a decimal between (0, 1), and the other is to convert the dimensional expression into a dimensionless expression, which is mainly proposed for the convenience of data processing. Mapping the data to the range of 0 to 1 for processing is more convenient and fast. Through the normalization process, the complexity of subsequent data processing is reduced, and the technical effect of improving the efficiency of system operation is achieved.

[0045] Step S600: according to the first scoring instruction, calling a preset grade calculation formula from the grade calculation module to perform grade calculation on the second multidimensional indicator score to obtain a multidimensional scoring grade;

[0046] Specifically, after the oil and gas pipeline unmanned station operation and risk prevention and control evaluation system normalizes the output results of the multidimensional evaluation model, it automatically issues a first scoring instruction for calling the preset grade calculation formula from the grade calculation module, and performing grade calculation on the second multidimensional indicator score to obtain the multidimensional score grade corresponding to the second multidimensional indicator score. The grade calculation module is also embedded in the oil and gas pipeline unmanned station operation and risk prevention and control evaluation system, and internally stores the feasibility grade calculation formula for the oil and gas pipeline unmanned station management, that is, the preset grade calculation formula.

[0047] The multi-dimensional scoring level refers to the system grading the unmanned station management of oil and gas pipelines with different scores after intelligent calculation based on the preset grade calculation formula. For example, the comprehensive multi-dimensional scoring results are divided into five levels, among which, the multi-dimensional score ≤60 is divided into the first level, at this time the unmanned station lacks the basic conditions for realizing the unmanned mode and it is difficult to support the unmanned mode; the multi-dimensional score of 60-70 is divided into the second level, at this time the unmanned station only has some basic conditions for realizing the unmanned mode, and under the existing technical and management conditions, it cannot meet the requirements of the unmanned mode, and continuous technical transformation and management upgrades are required; the multi-dimensional score of 70-80 is divided into the third level, at this time the unmanned station can partially meet the requirements of the unmanned mode, the basic realization of the unmanned mode, and the ability to maintain , risk prevention and control, consequence mitigation, emergency response and other capabilities still need to be further improved, some basic conditions need to be continuously improved, and there is still much room for improvement compared with the unmanned mode; the multi-dimensional score of 80 to 90 is divided into four levels. At this time, the unmanned station can basically meet the requirements of the unmanned mode, the basic realization of the unmanned mode, the capability maintenance, risk prevention and control, consequence mitigation, emergency response and other capabilities are at a high level, and the basic conditions for realizing the unmanned mode are met, but some indicators still need further improvement; the multi-dimensional score of 90 to 100 is divided into five levels. At this time, the unmanned station can realize the unmanned mode, the basic realization of the unmanned mode, the capability maintenance, risk prevention and control, consequence mitigation, emergency response and other capabilities tend to be perfect, and it has extremely high unmanned mode capabilities.

[0048] Through the first scoring instruction, the system automatically calls the preset grade calculation formula in the grade calculation module, and obtains the multi-dimensional scoring grade after calculation, thereby clarifying the feasibility of the operation and management of the unmanned station of the corresponding oil and gas pipeline, and achieving the technical effect of intelligently assessing the feasibility grade based on data.

[0049] Step S700: generating a first rating level according to the multi-dimensional rating levels, wherein the first rating level is the lowest level in the multi-dimensional rating levels;

[0050] Step S800: Obtain a first evaluation report according to the first scoring level.

[0051] Specifically, a first scoring level is generated according to the multi-dimensional scoring level. Among them, according to the short board impact evaluation method, the first scoring level is the lowest level in the multi-dimensional scoring level. For example, for a certain oil and gas transmission station, after multi-dimensional evaluation, combined with weight calculation, it is determined that the basic implementation of its unmanned station management is rated as level four, the ability of unmanned station management is maintained as level three, the risk prevention and control of unmanned station management is rated as level four, the consequence mitigation of unmanned station management is rated as level four, and the emergency management and disposal of unmanned station management is rated as level five. Then the final comprehensive rating of the oil and gas transmission station is level three. Finally, for the first scoring level, the system returns the first evaluation report accordingly.

[0052] Based on the real-time data collection results of oil and gas pipelines, an intelligent evaluation is conducted on the various conditions for the implementation of unmanned station management of oil and gas pipelines, and then the scoring level of the unmanned station management capability is determined, and finally a personalized evaluation report is generated, thereby achieving the technical effect of promoting the implementation of unmanned station management of oil and gas pipelines.

[0053] Furthermore, step S600 in the embodiment of the present application further includes:

[0054] Step S610: The preset level calculation formula is:

[0055] Z = ∑(Y × α)

[0056] Among them, Z is the weighted sum of all dimensions; Y is the weighted sum of the scores of each dimension; α is the dimension weight.

[0057] Specifically, first calculate the score results of each indicator in each dimension. The calculation formula is as follows:

[0058] X = ∑(W × γ)

[0059] Among them, W is the score of each indicator, and γ is the weight of each indicator.

[0060] Further, the scoring results of each dimension are calculated using the following formula:

[0061] Y = ∑(X × β)

[0062] Among them, Y is the weighted sum of the scores of each dimension, and β is the weight of each dimension.

[0063] Finally, the preset grade calculation formula can be used to calculate the comprehensive score Z of the unmanned station operation management of the oil and gas pipeline after comprehensively considering all dimensions and all dimensions corresponding to each indicator. Through data calculation based on multiple indicators, the technical effect of intuitively and accurately obtaining the feasibility evaluation of the unmanned station operation management of the oil and gas pipeline is achieved.

[0064] Further, as attached Figure 2As shown, step S700 of the embodiment of the present application also includes:

[0065] Step S710: constructing a first auxiliary evaluation model;

[0066] Step S720: collecting data from the unmanned station according to the data collection device to obtain second data collection information;

[0067] Step S730: inputting the second data collection information into the first auxiliary evaluation model, and obtaining second output information according to the first auxiliary evaluation model, wherein the second output information is auxiliary multi-dimensional evaluation information;

[0068] Step S740: modify the first scoring level according to the second output information to obtain a second scoring level.

[0069] Specifically, the first auxiliary evaluation model is used to intelligently evaluate the risk situation during the operation and management of the unmanned station. Similarly, the data acquisition device is used to perform real-time data acquisition on the relevant conditions of the unmanned station, and all collected data constitute the second data acquisition information. Furthermore, the second data acquisition information is input into the first auxiliary evaluation model, and the second output information is obtained according to the first auxiliary evaluation model. Among them, the second output information is a multi-dimensional evaluation result of evaluating the risk situation of the unmanned station operation and management of the oil and gas pipeline. Finally, the first scoring level is corrected and adjusted based on the second output information, and the corrected scoring level is the second scoring level.

[0070] Through the first auxiliary evaluation model, a multi-dimensional, multi-indicator intelligent evaluation is conducted on the operation and management of the oil and gas pipeline in the transition to an unmanned station, achieving the technical effect of intelligently identifying the comprehensive situation of unmanned station management. Further based on the evaluation results, the feasibility assessment of the implementation of unmanned station management in the oil and gas pipeline industry is revised, thereby improving the accuracy of the system evaluation results and achieving the technical effect of providing objective and effective theoretical guidance for the transition of oil and gas pipelines to an unmanned station management mode.

[0071] Further, as attached Figure 3 As shown, step S300 of the embodiment of the present application also includes:

[0072] Step S310: the multidimensional evaluation model includes a plurality of sub-evaluation models;

[0073] Step S320: Obtaining a first mapping data feature by performing model feature analysis on the multiple sub-evaluation models;

[0074] Step S330: classifying the first collected data information according to the first mapping data feature to obtain first classified data information;

[0075] Step S340: input the first classified data information as input information into the multiple sub-assessment models of the multidimensional assessment model for assessment to obtain the first output information.

[0076] Specifically, the multidimensional evaluation model includes a plurality of sub-evaluation models, which are used to evaluate the different types of data collected by the data acquisition device respectively. By performing model feature analysis on the plurality of sub-evaluation models, a first mapping data feature is obtained, and the first collected data information is further classified according to the first mapping data feature to obtain the first classified data information corresponding to the first collected data information. Finally, the first classified data information is input as input information into the plurality of sub-evaluation models of the multidimensional evaluation model, and after intelligent evaluation of each sub-evaluation model, an evaluation result of the first collected data information is obtained, which is the first output information. By setting a plurality of sub-evaluation models in the multidimensional evaluation model, a technical effect of performing targeted data evaluation on different data information and improving the accuracy of data evaluation results is achieved.

[0077] Furthermore, step S400 in the embodiment of the present application further includes:

[0078] Step S410: Obtaining first dimension evaluation information according to the multi-dimensional evaluation information;

[0079] Step S420: obtaining a plurality of indicator evaluation information corresponding to the first dimension according to the first dimension evaluation information;

[0080] Step S430: Obtaining indicator scoring data corresponding to the first indicator according to the plurality of indicator evaluation information;

[0081] Step S440: Obtain N indicator scoring data that are greater than or equal to preset indicator scoring data;

[0082] Step S450: Using the N indicator scoring data as the indicator scoring of the first dimension in the first multi-dimensional indicator scoring.

[0083] Specifically, the multidimensional evaluation information includes multiple dimensional evaluations of unmanned station operation management for oil and gas pipelines. The first dimensional evaluation information refers to the evaluation result of any dimension in the multidimensional evaluation information. Based on the first dimensional evaluation information, the evaluation information of multiple indicators corresponding to the first dimension can be determined. Then, multiple indicator scoring data corresponding to the first indicator can be obtained according to the multiple indicator evaluation information. Finally, N indicator scoring data that meet the preset indicator scoring data are selected as the indicator scoring of the first dimension in the first multidimensional indicator scoring. Among them, the preset indicator scoring data refers to the minimum standard of each indicator data in each dimension pre-set by the system based on multi-party analysis. For example, in the dimension of the ability to maintain unmanned station management for oil and gas pipelines, the reliability index data is 9, the availability index data is 7, and the maintainability index data is 5. The system preset indicator scoring data is 6. Then, since the maintainability index data is lower than the preset indicator scoring data, it is not used as the evaluation indicator of this dimension. Only the reliability index and availability index scoring data 9 and 7 are used as the indicator scoring of the ability to maintain the dimension of unmanned station management for oil and gas pipelines.

[0084] By discarding the indicator scores that do not reach the preset indicator score data in each dimension, the adverse impact of extreme data on the overall score results is avoided, achieving the technical effect of improving the accuracy of the evaluation.

[0085] Further, as attached Figure 4 As shown, the embodiment of the present application also includes step S900:

[0086] Step S910: Obtaining a first risk coefficient according to the multi-dimensional scoring level;

[0087] Step S920: determining whether the first risk factor is within a preset risk threshold;

[0088] Step S930: if the first risk factor is within the preset risk threshold, obtaining first reminder information;

[0089] Step S940: Send the first evaluation report to the first manager according to the first reminder information.

[0090] Specifically, the first risk coefficient refers to the risk coefficient assessment result of any dimension in the multi-dimensional scoring level. It is further determined whether the first risk coefficient is within the preset risk threshold. When the first risk coefficient is within the preset risk threshold, a first reminder message is obtained. Among them, the preset risk threshold refers to the data range of each dimension when the system is abnormal based on multi-party comprehensive analysis. The system automatically sends the first assessment report to the relevant management personnel according to the first reminder message. By intelligently judging the risk situation of each dimension in turn, the relevant person in charge will be reminded immediately once an abnormality occurs, so as to buy time for the relevant person in charge to formulate emergency measures, and achieve the technical effect of accurate monitoring, timely reminders, and avoidance of major risk problems.

[0091] Furthermore, step S910 of the embodiment of the present application further includes:

[0092] Step S911: Obtain a first preset rating level;

[0093] Step S912: obtaining M dimensional rating levels that are smaller than the first preset rating level by judging the first preset rating level and the multi-dimensional rating level;

[0094] Step S913: Obtain M rating level differences according to the M dimension rating levels;

[0095] Step S914: inputting the M rating level differences as input information into a risk assessment model, wherein the risk assessment model is obtained by data training until convergence;

[0096] Step S915: Obtain the first risk coefficient according to the risk assessment model.

[0097] Specifically, the first preset scoring level refers to the scoring levels of each dimension pre-set by the system based on a comprehensive analysis of the requirements of the unmanned station and the actual conditions of the oil and gas pipeline. By comparing and judging the first preset scoring level and the multi-dimensional scoring level, M dimensional scoring levels that are less than the first preset scoring level are obtained, and the M scoring level differences corresponding to the M dimensional scoring levels are further calculated, and the M scoring level differences are input into the risk assessment model as input information, and the first risk coefficient is obtained intelligently according to the risk assessment model. Through the risk assessment model, the dimensional scores of the first preset scoring level can be accurately identified, achieving the technical effect of improving the prediction of the risk level of unmanned station management of oil and gas pipelines through highly individualized assessment measures.

[0098] In summary, the method for operation management and risk prevention and control capability evaluation of an unmanned station of an oil and gas pipeline provided in the embodiment of the present application has the following technical effects:

[0099] 1. By collecting data from the oil and gas pipeline according to the data collection device, first collected data information is obtained; a multidimensional evaluation model is constructed, wherein each dimension in the multidimensional evaluation model has multiple indicators; the first collected data information is input into the multidimensional evaluation model for multidimensional evaluation, and first output information is obtained according to the multidimensional evaluation model, wherein the first output information is multidimensional evaluation information; a first multidimensional indicator score is generated according to the multidimensional evaluation information; a second multidimensional indicator score is obtained by normalizing the first multidimensional indicator score; a preset grade calculation formula is called from the grade calculation module according to the first scoring instruction to perform grade calculation on the second multidimensional indicator score to obtain a multidimensional scoring grade; a first scoring grade is generated according to the multidimensional scoring grade, wherein the first scoring grade is the lowest grade in the multidimensional scoring grade; a first evaluation report is obtained according to the first scoring grade. The method achieves the goal of intelligently evaluating the multi-party conditions for implementing unmanned station management of the oil and gas pipeline based on the real-time data collection results of the oil and gas pipeline, thereby determining the scoring level of the unmanned station management capability, and finally generating a personalized evaluation report, thereby promoting the technical effect of promoting unmanned station management of the oil and gas pipeline.

[0100] 2. Through the first auxiliary evaluation model, a multi-dimensional, multi-indicator intelligent evaluation is conducted on the operation and management of the oil and gas pipeline in the transition to an unmanned station, achieving the technical effect of intelligently identifying the comprehensive situation of unmanned station management. Further based on the evaluation results, the feasibility assessment of the implementation of unmanned station management in the oil and gas pipeline industry is revised, thereby improving the accuracy of the system evaluation results and achieving the technical effect of providing objective and effective theoretical guidance for the transition of the oil and gas pipeline to an unmanned station management mode.

[0101] 3. By discarding the indicator scores that do not reach the preset indicator score data in each dimension, the adverse impact of extreme data on the overall score results is avoided, achieving the technical effect of improving the accuracy of the evaluation.

[0102] Embodiment 2

[0103] Based on the same inventive concept as the method for evaluating the operation management and risk prevention and control capability of an unmanned station of an oil and gas pipeline in the aforementioned embodiment, the present invention also provides an evaluation system for the operation management and risk prevention and control capability of an unmanned station of an oil and gas pipeline, see the attached Figure 5 , the system comprising:

[0104] A first obtaining unit 11, the first obtaining unit 11 is used to collect data from the oil and gas pipeline according to the data collection device to obtain first collected data information;

[0105] A first construction unit 12, wherein the first construction unit 12 is used to construct a multi-dimensional evaluation model, wherein each dimension in the multi-dimensional evaluation model has multiple indicators;

[0106] A second obtaining unit 13, the second obtaining unit 13 is used to input the first collected data information into the multidimensional evaluation model for multidimensional evaluation, and obtain first output information according to the multidimensional evaluation model, wherein the first output information is multidimensional evaluation information;

[0107] A first generating unit 14, the first generating unit 14 is used to generate a first multidimensional indicator score according to the multidimensional evaluation information;

[0108] A third obtaining unit 15, wherein the third obtaining unit 15 is used to obtain a second multidimensional indicator score by normalizing the first multidimensional indicator score;

[0109] A fourth obtaining unit 16, the fourth obtaining unit 16 is used to call a preset grade calculation formula from the grade calculation module according to the first scoring instruction to perform grade calculation on the second multidimensional indicator score to obtain a multidimensional scoring grade;

[0110] A second generating unit 17, the second generating unit 17 is used to generate a first scoring level according to the multi-dimensional scoring level, wherein the first scoring level is the lowest level in the multi-dimensional scoring level;

[0111] The fifth obtaining unit 18 is configured to obtain a first evaluation report according to the first scoring level.

[0112] Furthermore, the system also includes:

[0113] The first setting unit is used to preset the level calculation formula as Z=∑(Y×α), wherein Z is the weighted sum of all dimensions; Y is the weighted sum of the scores of each dimension; and α is the dimension weight.

[0114] Furthermore, the system also includes:

[0115] a second construction unit, the second construction unit being used to construct a first auxiliary evaluation model;

[0116] a sixth obtaining unit, the sixth obtaining unit being configured to perform data collection on the unmanned station according to the data collection device to obtain second data collection information;

[0117] a seventh obtaining unit, the seventh obtaining unit being used to input the second data acquisition information into the first auxiliary evaluation model, and obtain second output information according to the first auxiliary evaluation model, wherein the second output information is auxiliary multi-dimensional evaluation information;

[0118] An eighth obtaining unit, wherein the eighth obtaining unit is used to modify the first scoring level according to the second output information to obtain a second scoring level.

[0119] Furthermore, the system also includes:

[0120] a second setting unit, wherein the second setting unit is used for the multidimensional evaluation model to include a plurality of sub-evaluation models;

[0121] a ninth obtaining unit, the ninth obtaining unit being configured to obtain a first mapping data feature by performing a model feature analysis on the plurality of sub-evaluation models;

[0122] a tenth obtaining unit, configured to classify the first collected data information according to the first mapping data feature to obtain first classified data information;

[0123] An eleventh obtaining unit is used to input the first classified data information as input information into the multiple sub-assessment models of the multidimensional assessment model for assessment, so as to obtain the first output information.

[0124] Furthermore, the system also includes:

[0125] a twelfth obtaining unit, the twelfth obtaining unit being configured to obtain first dimensional evaluation information according to the multi-dimensional evaluation information;

[0126] a thirteenth obtaining unit, the thirteenth obtaining unit being configured to obtain a plurality of indicator evaluation information corresponding to the first dimension according to the first dimension evaluation information;

[0127] a fourteenth obtaining unit, the fourteenth obtaining unit being configured to obtain indicator scoring data corresponding to the first indicator according to the plurality of indicator evaluation information;

[0128] A fifteenth obtaining unit, the fifteenth obtaining unit is used to obtain N indicator scoring data that is greater than or equal to the preset indicator scoring data;

[0129] A third setting unit, wherein the third setting unit is used to use the N indicator scoring data as the indicator scoring of the first dimension in the first multi-dimensional indicator scoring.

[0130] Furthermore, the system also includes:

[0131] A sixteenth obtaining unit, the sixteenth obtaining unit being used to obtain a first risk coefficient according to the multi-dimensional scoring level;

[0132] A first judgment unit, the first judgment unit is used to judge whether the first risk coefficient is within a preset risk threshold;

[0133] a seventeenth obtaining unit, the seventeenth obtaining unit being configured to obtain first reminder information if the first risk coefficient is within the preset risk threshold;

[0134] A first sending unit, wherein the first sending unit is used to send the first evaluation report to a first manager according to the first reminder information.

[0135] Furthermore, the system also includes:

[0136] An eighteenth obtaining unit, the eighteenth obtaining unit being used to obtain a first preset scoring level;

[0137] A nineteenth obtaining unit, the nineteenth obtaining unit being configured to obtain M dimensional scoring levels that are smaller than the first preset scoring level by judging the first preset scoring level and the multi-dimensional scoring level;

[0138] A twentieth obtaining unit, the twentieth obtaining unit being used to obtain M rating level differences according to the M dimension rating levels;

[0139] A fourth setting unit, the fourth setting unit is used to input the M scoring level differences as input information into a risk assessment model, the risk assessment model is obtained by data training until convergence;

[0140] A twenty-first obtaining unit, the twenty-first obtaining unit is used to obtain the first risk coefficient according to the risk assessment model.

[0141] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. Figure 1 The method and specific examples of operation management and risk prevention and control capability evaluation of an unmanned station of an oil and gas pipeline in Example 1 are also applicable to the operation management and risk prevention and control capability evaluation system of an unmanned station of an oil and gas pipeline in this embodiment. Through the above detailed description of the operation management and risk prevention and control capability evaluation method of an unmanned station of an oil and gas pipeline, those skilled in the art can clearly know the operation management and risk prevention and control capability evaluation system of an unmanned station of an oil and gas pipeline in this embodiment, so for the sake of brevity of the specification, it will not be described in detail here. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description.

[0142] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

[0143] Exemplary Electronic Devices

[0144] Reference below Figure 6 To describe the electronic device of the embodiment of the present application.

[0145] Figure 6 The figure shows a schematic structural diagram of an electronic device according to an embodiment of the present application.

[0146] Based on the inventive concept of a method for evaluating the operation management and risk prevention and control capabilities of an unmanned station for an oil and gas pipeline in the aforementioned embodiment, the present invention also provides a system for evaluating the operation management and risk prevention and control capabilities of an unmanned station for an oil and gas pipeline, on which a computer program is stored. When the program is executed by a processor, the steps of any method of the method for evaluating the operation management and risk prevention and control capabilities of an unmanned station for an oil and gas pipeline described above are implemented.

[0147] Among them, Figure 6 In the embodiment of the present invention, a bus architecture (represented by bus 300) is shown, which may include any number of interconnected buses and bridges, and bus 300 links various circuits including one or more processors represented by processor 302 and memory represented by memory 304. Bus 300 may also link various other circuits such as peripherals, voltage regulators, and power management circuits, which are well known in the art and are not further described herein. Bus interface 305 provides an interface between bus 300 and receiver 301 and transmitter 303. Receiver 301 and transmitter 303 may be the same element, namely a transceiver, which provides a unit for communicating with various other devices over a transmission medium.

[0148] The processor 302 is responsible for managing the bus 300 and general processing, while the memory 304 may be used to store data used by the processor 302 when performing operations.

[0149] The present application provides an operation management and risk prevention and control capability evaluation method for an unmanned station of an oil and gas pipeline, and the method is applied to an operation management and risk prevention and control capability evaluation system for an unmanned station of an oil and gas pipeline, wherein the method comprises: acquiring first acquired data information by acquiring data on the oil and gas pipeline according to the data acquisition device; constructing a multidimensional evaluation model, wherein each dimension in the multidimensional evaluation model has multiple indicators; inputting the first acquired data information into the multidimensional evaluation model for multidimensional evaluation, and acquiring first output information according to the multidimensional evaluation model, wherein the first output information is multidimensional evaluation information; generating a first multidimensional indicator score according to the multidimensional evaluation information; acquiring a second multidimensional indicator score by normalizing the first multidimensional indicator score; performing grade calculation on the second multidimensional indicator score by calling a preset grade calculation formula from a grade calculation module according to a first scoring instruction, and acquiring a multidimensional scoring grade; generating a first scoring grade according to the multidimensional scoring grade, wherein the first scoring grade is the lowest grade among the multidimensional scoring grades; and obtaining a first evaluation report according to the first scoring grade. It solves the technical problems in the existing technology that the conditions for implementing unmanned station management in the oil and gas pipeline industry cannot be intelligently evaluated, and the risks of unmanned station management cannot be effectively identified. It achieves the technical effect of intelligently evaluating the multiple conditions for implementing unmanned station management in the oil and gas pipeline based on the real-time data collection results of the oil and gas pipeline, and then determines the scoring level of the unmanned station management capability, and finally generates a personalized evaluation report, thereby promoting the technical effect of promoting unmanned station management in the oil and gas pipeline.

[0150] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, devices, or computer program products. Therefore, the present application may adopt a complete software embodiment, a complete hardware embodiment, or a combination of software and hardware embodiments. In addition, the present application is in the form of a computer program product that can be implemented on one or more computer-usable storage media containing computer-usable program codes. The computer-usable storage medium includes, but is not limited to, various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), disk storage, compact disc read-only memories (CD-ROM), optical memories, etc.

[0151] The present invention is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products of the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A system that specifies the functions of a box or multiple boxes.

[0152] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a product including an instruction system, which is implemented in the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0153] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps of the functions specified in a box or multiple boxes. Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they are aware of the basic creative concepts. Therefore, the attached claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0154] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for evaluating the operation management and risk prevention and control capabilities of unmanned stations in oil and gas pipelines, wherein: The method is applied to an oil and gas pipeline unmanned station operation management and risk prevention and control capability evaluation system, the system is communicatively connected with a data acquisition device, and the method includes: Collecting data from the oil and gas pipeline according to the data collection device to obtain first collected data information; Constructing a multidimensional evaluation model, wherein each dimension in the multidimensional evaluation model has multiple indicators; Inputting the first collected data information into the multidimensional evaluation model for multidimensional evaluation, and obtaining first output information according to the multidimensional evaluation model, wherein the first output information is multidimensional evaluation information; Generating a first multidimensional indicator score according to the multidimensional evaluation information; By normalizing the first multidimensional indicator score, a second multidimensional indicator score is obtained; According to the first scoring instruction, a preset grade calculation formula is called from the grade calculation module to perform grade calculation on the second multidimensional indicator score to obtain a multidimensional scoring grade; Generate a first rating level according to the multi-dimensional rating levels, wherein the first rating level is the lowest level in the multi-dimensional rating levels; Obtaining a first evaluation report according to the first scoring level; Constructing the first auxiliary assessment model; Collecting data from the unmanned station according to the data collection device to obtain second data collection information; Inputting the second data collection information into the first auxiliary evaluation model, and obtaining second output information according to the first auxiliary evaluation model, wherein the second output information is auxiliary multi-dimensional evaluation information; Modify the first scoring level according to the second output information to obtain a second scoring level; Wherein, generating a first multidimensional indicator score according to the multidimensional evaluation information, the method further comprises: Obtaining first dimension evaluation information according to the multi-dimensional evaluation information; According to the first dimension evaluation information, obtaining multiple indicator evaluation information corresponding to the first dimension; Obtaining indicator scoring data corresponding to the first indicator according to the plurality of indicator evaluation information; Obtain N indicator scoring data that is greater than or equal to the preset indicator scoring data; The N indicator scoring data are used as the indicator scoring of the first dimension in the first multidimensional indicator scoring.

2. The method of claim 1, wherein: The preset level calculation formula is Z = Σ(Y×α) Among them, Z is the weighted sum of all dimensions; Y is the weighted sum of the scores of each dimension; α is the dimension weight.

3. The method of claim 1, wherein: The inputting the first collected data information into the multidimensional evaluation model for multidimensional evaluation, and obtaining first output information according to the multidimensional evaluation model, the method further includes: The multidimensional assessment model includes a plurality of sub-assessment models; Obtaining a first mapping data feature by performing model feature analysis on the multiple sub-evaluation models; Classify the first collected data information according to the first mapping data feature to obtain first classified data information; The first classified data information is input as input information into the multiple sub-assessment models of the multi-dimensional assessment model for assessment to obtain the first output information.

4. The method of claim 1, wherein: The method further comprises: According to the multi-dimensional scoring level, a first risk coefficient is obtained; Determining whether the first risk factor is within a preset risk threshold; If the first risk factor is within the preset risk threshold, obtaining first reminder information; The first evaluation report is sent to a first manager according to the first reminder information.

5. The method of claim 4, wherein: The method further comprises: obtaining a first risk coefficient according to the multi-dimensional scoring level; Obtaining the first preset rating level; By judging the first preset scoring level and the multi-dimensional scoring level, M dimensional scoring levels that are smaller than the first preset scoring level are obtained; According to the M dimension rating levels, M rating level differences are obtained; Inputting the M rating level differences as input information into a risk assessment model, wherein the risk assessment model is obtained by data training until convergence; According to the risk assessment model, the first risk coefficient is obtained.

6. An oil and gas pipeline unmanned station operation management and risk prevention and control capability evaluation system, characterized in that: The system is used to implement the method for operation management and risk prevention and control capability evaluation of an unmanned station of an oil and gas pipeline according to any one of claims 1 to 5, and the system comprises: First acquisition unit: The first acquisition unit is used to collect data from the oil and gas pipeline according to the data acquisition device to obtain first collected data information; First construction unit: The first construction unit is used to construct a multidimensional evaluation model, wherein each dimension in the multidimensional evaluation model has multiple indicators; Second obtaining unit: The second obtaining unit is used to input the first collected data information into the multidimensional evaluation model for multidimensional evaluation, and obtain first output information according to the multidimensional evaluation model, wherein the first output information is multidimensional evaluation information; First generating unit: The first generating unit is used to generate a first multidimensional indicator score according to the multidimensional evaluation information; A third obtaining unit: the third obtaining unit is used to obtain a second multidimensional indicator score by normalizing the first multidimensional indicator score; Fourth obtaining unit: the fourth obtaining unit is used to call a preset grade calculation formula from the grade calculation module according to the first scoring instruction to perform grade calculation on the second multidimensional indicator score to obtain a multidimensional scoring grade; Second generating unit: The second generating unit is used to generate a first scoring level according to the multi-dimensional scoring level, wherein the first scoring level is the lowest level in the multi-dimensional scoring level; Fifth obtaining unit: The fifth obtaining unit is used to obtain a first evaluation report according to the first scoring level.

7. An oil and gas pipeline unmanned station operation management and risk prevention and control capability evaluation system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the method according to any one of claims 1 to 5 are implemented.

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