Drilling and mining equipment management method and system based on RCM

Abstract

The invention relates to the technical field of drilling and mining equipment integrity management, in particular to an RCM-based drilling and mining equipment management method and system, and the method comprises the steps: collecting and analyzing basic information through a server, and then carrying out the important degree evaluation method research and risk quantitative evaluation technology research of drilling and mining key equipment; and finally, comprehensively and quantitatively evaluating the importance degree of each part in the drilling and production key moving equipment and the risk degree of a fault mode, and providing a scientific decision for the maintenance of the drilling and production key moving equipment in combination with the actual maintenance conditions and operation characteristics of the drilling and production key moving equipment. The system comprises an acquisition module, and a sensor device, a sensor detection module, a server, an importance evaluation module, a risk evaluation module and a maintenance decision module which are in communication connection in sequence. Through the management method and system, scientific maintenance of the drilling and mining equipment can be realized.

Description

Technical Field

[0001] The present invention relates to the technical field of integrity management of drilling and production moving equipment, and particularly to a management method and system for drilling and production moving equipment based on RCM. Background Art

[0002] At present, the moving equipment in oil and gas drilling and production equipment has the characteristics of complex structure, variable working conditions, and diverse failure modes. Moreover, with the large-scale popularization of complex drilling and production operations such as deep wells and ultra-deep wells, the degree of equipment refinement and system integration is getting higher and higher, and the moving equipment shows diversified development. During the oil and gas drilling and production process, once an important moving equipment fails, it will cause a complete unplanned shutdown at the operation site, resulting in significant production losses and high maintenance costs, and even causing safety accidents such as casualties. Through the statistics of the causes of major accidents in the petrochemical industry, the failures caused by moving equipment account for 41%. The moving equipment in oil and gas drilling and production in China still follows the means of increasing the maintenance frequency to prevent the occurrence of failures. However, after reaching a certain threshold, simply increasing the equipment maintenance frequency cannot effectively prevent the occurrence of internal failures of moving equipment. At the same time, due to the improvement of the refinement degree of moving equipment, frequent disassembly and repair of equipment will not only cause a sharp increase in maintenance costs, but also reduce the reliability of the equipment, and is very likely to cause new failures, resulting in the reduction of the equipment life. For this reason, the RCM maintenance system that has been widely used in other industries is introduced.

[0003] However, in the implementation process of the traditional RCM analysis method, there is a lack of a quantitative analysis model, no connection is established between the equipment characteristics and the operating environment, and no quantitative evaluation is carried out by combining multiple factors such as equipment characteristics, real-time operating status, and maintenance information. Its analysis process has high requirements for analysts, involves many professionals and departments, and requires the cooperation of users and participants to complete. There is a large amount of qualitative analysis in the analysis process, which requires a large amount of reliability and maintainability data support, and the analysis results vary greatly. As a result, the maintenance cost during the whole life cycle of the equipment is high, and it cannot operate reliably, controllably, continuously, and economically. Summary of the Invention

[0004] To solve the above technical problems, the present invention proposes a management method and system for drilling and production moving equipment based on RCM, which can realize scientific maintenance of drilling and production moving equipment.

[0005] The present invention is realized by adopting the following technical solutions: A management method for drilling and production moving equipment based on RCM includes the following steps: Step S 1 . Collect the maintenance status data of key drilling and production moving equipment and the fault data of sensor equipment, and transmit them to the server; Step S 2. The server receives maintenance status data and fault data, analyzes and identifies them, and then stores them classified. Step S 3 . Extract the classified data in the above server, determine the importance influencing factors of each component of the key drilling and production moving equipment, and use them as evaluation indicators. By comprehensively evaluating the evaluation indicators, quantitatively evaluate the importance of each component in the key drilling and production moving equipment in an all-round way; identify and classify the fault modes that occur in the key drilling and production moving equipment, quantitatively evaluate the importance of the fault modes, determine the influence degree of the fault modes on the safety of the key drilling and production moving equipment, and evaluate and predict the risk degree of the fault modes. Step S 4 . According to the importance of each component in the key drilling and production moving equipment, the risk degree of the fault modes, and the actual maintenance conditions and operation characteristics of the key drilling and production moving equipment, dynamically adjust the maintenance strategy and maintenance cycle.

[0006] The said Step S 3 In it, determine the importance influencing factors of each component of the key drilling and production moving equipment, and use them as evaluation indicators, specifically referring to: through fault tree analysis, find out various influencing factors that cause faults in the key drilling and production moving equipment, and determine the logical relationship between them; analyze the hierarchical relationship of each component of the key drilling and production moving equipment, and use the analytic hierarchy process to determine the relative importance of each component; use the grey relational analysis method to determine the relational relationship between the influencing factors of each component and the safety of the key drilling and production moving equipment, and use the importance influencing factors of each component as evaluation indicators.

[0007] The said Step S 3 In it, identify and classify the fault modes that occur in the key drilling and production moving equipment, and quantitatively evaluate the importance of the fault modes, determine the influence degree of the fault modes on the safety of the key drilling and production moving equipment, specifically referring to: through FMEA, identify and classify the fault modes that occur in the key drilling and production moving equipment, and according to the identified fault modes, use the grey relational analysis algorithm to quantitatively evaluate the importance of each fault mode, so as to determine the influence degree of the fault modes on the equipment safety.

[0008] Before identifying and classifying the fault modes that occur in the key drilling and production moving equipment through FMEA, it also includes preprocessing the data, including removing outliers, missing values and redundant data.

[0009] The said Step S 3 In it, evaluating and predicting the risk degree of the fault modes specifically refers to: using the support vector machine algorithm for modeling and prediction to judge the risk degree of the fault modes.

[0010] The said Step S 4Specifically, it refers to combining the importance of each component and the risk level of the failure mode in different ways, selecting the optimal maintenance strategy; adjusting the maintenance cycle and inspection interval according to the actual maintenance conditions and operation characteristics of the key drilling and production moving equipment, and finally establishing a decision optimization model based on the predicted failure trend and maintenance requirements to dynamically adjust the maintenance strategy and maintenance cycle.

[0011] The said step S 4 In this, the optimal maintenance strategy is selected through the decision tree algorithm; the maintenance cycle and inspection interval are adjusted through the reinforcement learning algorithm; the failure trend and maintenance requirements are predicted through the time series analysis method.

[0012] A management system for key drilling and production moving equipment based on RCM, including an acquisition module, and a sensor device, a sensor detection module, a server, an importance evaluation module, a risk evaluation module, and a maintenance decision module that are sequentially communicatively connected; the acquisition module is electrically connected to the server; The acquisition module is used to acquire the maintenance status data of the key drilling and production moving equipment and transmit it to the server; The sensor detection module is used to acquire the failure data and transmit it to the server when the sensor device fails; The server is used to receive the maintenance status data and the failure data, classify them into the maintenance status database, the historical failure database, and the running failure database in the server in sequence, and then transmit the classified data to the risk evaluation module and the importance evaluation module; The importance evaluation module is used to analyze the data transmitted by the server, determine the importance influencing factors of each component of the key drilling and production moving equipment, use them as evaluation indicators, comprehensively evaluate the evaluation indicators, quantitatively evaluate the importance of each component in the key drilling and production moving equipment in an all-round way, and establish an importance evaluation model for the key drilling and production moving equipment; The risk evaluation module is used to analyze the data transmitted by the server, identify and classify the failure modes that occur in the key drilling and production moving equipment, quantitatively evaluate the importance of the failure modes, determine the influence degree of the failure modes on the safety of the key drilling and production moving equipment, evaluate and predict the risk level of the failure modes, and establish a quantitative risk evaluation model for the failure modes; The maintenance decision module is used to dynamically adjust the maintenance strategy and the maintenance cycle according to the importance of each component in the key drilling and production moving equipment, the risk level of the failure mode, and the actual maintenance conditions and operation characteristics of the key drilling and production moving equipment.

[0013] It further includes a display terminal communicatively connected to the maintenance decision module.

[0014] It further includes a reading terminal electrically connected to the maintenance decision module, which is used for the staff to read the failure data and the historical failure data.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. The maintenance strategy of the present invention is determined according to the actual maintenance conditions and operation characteristics of key drilling and production moving equipment. At the same time, quantitative analysis of the maintenance strategy decision-making process is realized, forming a set of maintenance decision-making methods for key drilling and production moving equipment. This quantitative analysis method is more accurate and intuitive than the prior art and can better provide a basis for formulating maintenance strategies.

[0016] Through the technical solution of the present invention, the quantification, comprehensiveness, and scientific nature of the decision-making process can be achieved.

[0017] 2. The present invention improves the deficiencies of traditional RCM technology and conducts quantitative evaluation by combining multiple factors such as equipment characteristics, real-time operating status, and maintenance information. This multi-factor evaluation method is more comprehensive and objective than the prior art and can better provide a scientific basis for the maintenance of key drilling and production moving equipment.

[0018] 3. The technical solution of the present invention can also predict the fault trend and maintenance requirements, enabling this management method to have preventive maintenance means. Compared with traditional means such as daily inspections and regular hierarchical maintenance, the preventive maintenance means adopted by the present invention is more scientific and can provide a more scientific decision for the maintenance of key drilling and production moving equipment, which is more economical and reliable.

[0019] 4. Through the setting of structures such as the importance evaluation module and risk evaluation module in this management system, the server collects and analyzes basic information such as the current maintenance status, historical fault data, and operation data of key drilling and production moving equipment, and then conducts quantitative evaluation of the importance of key drilling and production moving equipment and the risk level of fault modes through the importance evaluation module and risk evaluation module. Finally, an importance evaluation model for key drilling and production moving equipment and a quantitative evaluation model for fault mode risks are established to provide a scientific decision for the maintenance of key drilling and production moving equipment.

[0020] 5. Through the setting of structures such as the reading terminal and display terminal in the present invention, when on-site maintenance personnel are on-site for maintenance, they can read the importance evaluation model of key drilling and production moving equipment, the quantitative evaluation model of fault mode risks, and the maintenance decision-making method of key drilling and production moving equipment by electrically connecting the reading terminal and the maintenance decision-making module, which provides convenience for front-line maintenance personnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The present invention will be further described in detail below in conjunction with the accompanying drawings of the specification and specific embodiments, where: Figure 1 is a schematic structural diagram of the present invention; Figure 2 is a schematic structural diagram of the sensor detection module in the present invention; Figure 3Schematic diagram of the server in the present invention; Figure 4 Schematic diagram of the importance evaluation module in the present invention; Figure 5 Schematic diagram of the risk evaluation module in the present invention; Figure 6 Schematic diagram of the maintenance decision-making module in the present invention; Markings in the figure: 1. Sensor device, 2. Sensor detection module, 201. Operation unit, 202. Detection unit, 203. Data transmission unit, 3. Server, 301. Receive data unit, 302. Store data unit, 303. Transmit data unit, 3021. Maintenance status database, 3022. Historical fault database, 3023. Operation fault database, 4. Acquisition module, 5. Reading terminal, 6. Importance evaluation module, 601. Importance influencing factor analysis unit, 602. Importance evaluation model establishment unit, 7. Risk evaluation module, 701. Risk identification unit, 702. Risk evaluation model establishment unit, 8. Maintenance decision-making module, 801. Receive information unit, 802. Data analysis and processing unit, 803. Transmit information unit, 9. Display terminal. Detailed implementation manners

[0022] Embodiment 1 As a basic implementation manner of the present invention, the present invention includes a management method for drilling and production moving equipment based on RCM, including the following steps: Step S 1 . Collect the maintenance status data of the key moving equipment for drilling and production and the fault data of the sensor device 1, and transmit them to the server 3.

[0023] Step S 2 . The server 3 receives the maintenance status data and the fault data, analyzes and identifies them, and stores them classified.

[0024] Step S 3 . Extract the classified data in the server 3 above, determine the importance influencing factors of each component of the key moving equipment for drilling and production, and use them as evaluation indicators. By comprehensively evaluating the evaluation indicators, quantitatively evaluate the importance of each component in the key moving equipment for drilling and production.

[0025] Identify and classify the fault modes that occur in the key moving equipment for drilling and production, quantitatively evaluate the importance of the fault modes, determine the influence degree of the fault modes on the safety of the key moving equipment for drilling and production, and evaluate and predict the risk degree of the fault modes.

[0026] Step S 4. Dynamically adjust the maintenance strategy and maintenance cycle according to the importance of each component in the key drilling and production moving equipment, the risk level of the failure mode, and the actual maintenance conditions and operation characteristics of the key drilling and production moving equipment.

[0027] Embodiment 2 As a preferred embodiment of the present invention, the present invention includes a management method for drilling and production moving equipment based on RCM, comprising the following steps: Step S 1 . Collect the maintenance status data of the key drilling and production moving equipment and the failure data of the sensor device 1, and transmit them to the server 3.

[0028] Step S 2 . The server 3 receives the maintenance status data and the failure data, analyzes and identifies them, and then classifies and stores them.

[0029] Step S 3 . Extract the classified data in the above server 3, determine the importance influencing factors of each component of the key drilling and production moving equipment, and use them as evaluation indicators. Through comprehensive evaluation of the evaluation indicators, comprehensively and quantitatively evaluate the importance of each component in the key drilling and production moving equipment. Specifically, through fault tree analysis, find out various influencing factors that cause the failure of the key drilling and production moving equipment, and determine the logical relationship between them. Analyze the hierarchical relationship of each component of the key drilling and production moving equipment, and use the analytic hierarchy process to determine the relative importance of each component. Use the grey relational analysis method to determine the correlation relationship between the influencing factors of each component and the safety of the key drilling and production moving equipment, and use the importance influencing factors of each component as evaluation indicators. Through comprehensive evaluation of the evaluation indicators, comprehensively and quantitatively evaluate the importance of each component in the key drilling and production moving equipment.

[0030] Identify and classify the failure modes that occur in the key drilling and production moving equipment, quantitatively evaluate the importance of the failure modes, determine the impact degree of the failure modes on the safety of the key drilling and production moving equipment, and evaluate and predict the risk level of the failure modes. Specifically, through FMEA, identify and classify the failure modes that occur in the key drilling and production moving equipment. According to the identified failure modes, use the grey relational analysis algorithm to quantitatively evaluate the importance of each failure mode, so as to determine the impact degree of the failure modes on the equipment safety. Use the support vector machine algorithm for modeling and prediction to judge the risk level of the failure modes.

[0031] Step S 4 . Combine the importance of each component and the risk level of the failure mode in different combinations, select the optimal maintenance strategy; combine the actual maintenance conditions and operation characteristics of the key drilling and production moving equipment, adjust the maintenance cycle and inspection interval, and finally establish a decision optimization model according to the predicted failure trend and maintenance requirements, and dynamically adjust the maintenance strategy and maintenance cycle.

[0032] Example 3 As another preferred embodiment of the present invention, the present invention includes a management system for key drilling and production moving equipment based on RCM, which includes a collection module 4 and a sensor device 1, a sensor detection module 2, a server 3, an importance evaluation module 6, a risk evaluation module 7, and a maintenance decision-making module 8 that are communicatively connected in sequence. The collection module 4 is electrically connected to the server 3.

[0033] The collection module 4 is used to collect the maintenance status data of the key drilling and production moving equipment and transmit it to the server 3.

[0034] The sensor detection module 2 is used to collect fault data and transmit it to the server 3 when the sensor device 1 fails.

[0035] The server 3 is used to receive the maintenance status data and the fault data, classify them into the maintenance status database 3021, the historical fault database 3022, and the running fault database 3023 in the server 3 in sequence, and then transmit the classified data to the risk evaluation module 7 and the importance evaluation module 6.

[0036] The importance evaluation module 6 is used to analyze the data transmitted by the server 3, determine the importance influencing factors of each component of the key drilling and production moving equipment, and use them as evaluation indicators. By comprehensively evaluating the evaluation indicators, the importance of each component in the key drilling and production moving equipment is quantitatively evaluated, and an importance evaluation model for the key drilling and production moving equipment is established.

[0037] The risk evaluation module 7 is used to analyze the data transmitted by the server 3, identify and classify the fault modes that occur in the key drilling and production moving equipment, quantitatively evaluate the importance of the fault modes, determine the influence degree of the fault modes on the safety of the key drilling and production moving equipment, evaluate and predict the risk degree of the fault modes, and establish a quantitative risk evaluation model for the fault modes.

[0038] The maintenance decision-making module 8 is used to dynamically adjust the maintenance strategy and the maintenance cycle according to the importance of each component in the key drilling and production moving equipment, the risk degree of the fault mode, and the actual maintenance conditions and operation characteristics of the key drilling and production moving equipment.

[0039] Example 4 As the best embodiment of the present invention, the present invention includes a management system for key drilling and production moving equipment based on RCM, referring to the attached drawings of the specification Figure 1, including a collection module 4, a display terminal 9, a reading terminal 5, and a sensor device 1, a sensor detection module 2, a server 3, an importance evaluation module 6, a risk evaluation module 7, and a maintenance decision-making module 8 that are communicatively connected in sequence. The collection module 4 is electrically connected to the server 3; the display terminal 9 is communicatively connected to the maintenance decision-making module 8, and the reading terminal 5 is electrically connected to the maintenance decision-making module 8.

[0040] The collection module 4 is used to collect the maintenance status data of key drilling and production moving equipment such as drilling rigs, derricks, and mud pumps, and transmit it to the server 3.

[0041] Refer to the attached Figure 2 , the sensor detection module 2 may include an operation unit 201, a detection unit 202, and a data transmission unit 203. The operation unit 201 is used for the normal operation of the sensor device 1; when a failure occurs, the detection unit 202 transmits the detected failure data to the server 3 through the data transmission unit 203.

[0042] Refer to the attached Figure 3 , the server 3 may include a data receiving unit 301, a data storage unit 302, and a data transmission unit 303. The data storage unit 302 includes a maintenance status database 3021, a historical failure database 3022, and an operation failure database 3023. The server 3 collects the data sent by the collection module 4 and the sensor detection module 2 through the data receiving unit 301, and classifies the collected data into the maintenance status database 3021, the historical failure database 3022, and the operation failure database 3023 in sequence through the data storage unit 302, completing the collection and analysis of basic information such as the maintenance status, historical failure data, and operation data of key drilling and production moving equipment. The data transmission unit 303 transmits the classified data to the risk evaluation module 7 and the importance evaluation module 6.

[0043] Refer to the attached Figure 4 , the importance evaluation module 6 includes an importance influencing factor analysis unit 601 and an importance evaluation model establishment unit 602. Through the importance influencing factor analysis unit 601, the data content in the server 3 is analyzed to obtain an importance evaluation method for key drilling and production moving equipment, and thus, according to this importance evaluation method for key drilling and production moving equipment, the importance evaluation model establishment unit 602 establishes an importance evaluation model for key drilling and production moving equipment.

[0044] Refer to the attached Figure 5The risk assessment module 7 includes an equipment risk identification unit 701 and a risk assessment model establishment unit 702. The equipment risk identification unit 701 identifies the risks of key drilling and production equipment through FEMA technology, forms a study on risk quantitative assessment technology, and then establishes a failure mode risk quantitative assessment model through the risk assessment model establishment unit 702.

[0045] Refer to the instruction manual Figure 6 The maintenance decision module 8 includes an information receiving unit 801, a data analysis and processing unit 802, and an information transmission unit 803. The information is received by the information receiving unit 801. The data analysis and processing unit 802 analyzes and processes the information, and dynamically adjusts the maintenance strategy and maintenance cycle according to the importance of each component in the key drilling and production equipment, the risk level of the failure mode, and the actual maintenance conditions and operation characteristics of the key drilling and production equipment. The information transmission unit 803 transmits the processed information to the display terminal 9.

[0046] By setting up structures such as the reading terminal 5 and the display terminal 9, when front-line personnel perform on-site maintenance, they can read the importance of key drilling and production dynamic equipment, the quantitative evaluation model of failure mode risk, and the maintenance decision method of key drilling and production dynamic equipment by electrically connecting the reading terminal 5 and the maintenance decision module 8, thereby providing convenience for front-line maintenance personnel.

[0047] Based on the above management system, this embodiment also proposes a drilling and mining equipment management method based on RCM, including the following steps: Step S 1 The acquisition module 4 is used to collect the maintenance status data of the key dynamic equipment of drilling and production, and transmits it to the server 3. The sensor detection module 2 is used to detect the sensor device 1. When the detection unit 202 of the sensor detection module 2 detects a fault, the fault data of the detected sensor device 1 is transmitted to the server 3 through the data transmission unit 203.

[0048] Step S 2 The server 3 receives the data transmitted by the sensor detection module 2 and the acquisition module 4 through the receiving data unit 301, establishes the RCM basic information data architecture of the key dynamic equipment of drilling and production, and then analyzes and identifies the data, and stores them in the maintenance status database 3021, the historical fault database 3022 and the operation fault database 3023 in the storage data unit 302 in turn, and then transmits the classified data to the risk assessment module 7 and the importance assessment module 6 through the transmission data unit 303.

[0049] Step S 3. The importance evaluation module 6 receives the transmitted data architecture, and generates an importance evaluation method for key drilling and production moving equipment and establishes an importance evaluation model for key drilling and production moving equipment by combining methods such as fault tree, analytic hierarchy process, and grey relational analysis algorithm through the importance influencing factor analysis unit 601 and the importance evaluation model 602 establishment unit.

[0050] Specifically, by receiving data related to key drilling and production moving equipment, including performance parameters, fault information, maintenance records, etc. of each component of the equipment, a fault tree is then constructed, with the main faults of the equipment as the top event, and then decomposed layer by layer until the basic events. Through the analysis of the fault tree, various factors leading to equipment faults can be found, and their logical relationships can be determined. Then, the hierarchical relationships of each component of the key drilling and production moving equipment are analyzed, and the analytic hierarchy process method is used to determine the relative importance of each component. Finally, the grey relational analysis method is used to study the correlation between influencing factors such as the fault repair time, repair cost, and repair difficulty of each component and the equipment safety. Through this method, the influence degree of these factors on equipment safety can be determined. Based on the above analysis, the importance influencing factors of each component of the equipment can be used as evaluation indicators, and these indicators can include: the influence degree of component safety, component repair time, component repair cost, and component repair difficulty. Establish an importance evaluation model for key drilling and production moving equipment, comprehensively evaluate these indicators, and a comprehensive evaluation of the importance of each component of the key drilling and production moving equipment can be realized, achieving quantification in the evaluation and screening process of important functional components.

[0051] The risk evaluation module 7 receives the transmitted data and generates a quantitative risk evaluation technical method for key drilling and production moving equipment by using FEMA technology through the equipment risk identification unit 701, and establishes a quantitative evaluation model for the fault mode risk of key drilling and production moving equipment through the risk evaluation model establishment unit 702.

[0052] Specifically, first, the operation data of key drilling and production moving equipment are received, including the working parameters of the equipment, status monitoring data, fault information, etc. These data can be obtained through sensors, monitoring systems, fault diagnosis systems, etc. The collected data are preprocessed, including cleaning, sorting, and summarizing, to remove outliers, missing values, and redundant data, ensuring the accuracy and consistency of the data. The FMEA technology is used to identify and classify the possible fault modes of the key drilling and production moving equipment. According to the identified fault modes, the grey relational analysis algorithm is used to quantitatively evaluate the importance of each fault mode. Grey relational analysis can reveal the degree of association between each fault mode and the overall performance of the equipment, thereby determining its impact on the equipment safety. Then, the support vector machine algorithm is used to model and predict the results of the importance analysis. The support vector machine algorithm is a powerful machine learning algorithm that can be used to establish a quantitative evaluation model for the risk of fault modes and predict the future risk trend based on historical data. Subsequently, the established model is verified and optimized through actual operation data to improve the accuracy and reliability of the model. Optimization can be carried out by adjusting model parameters, increasing the feature dimension, etc. Then, according to the established quantitative evaluation model for the risk of fault modes, the risk of the key drilling and production moving equipment is evaluated and predicted. According to the evaluation results, corresponding preventive measures, maintenance strategies, or safety control plans can be taken to reduce the equipment operation risk and improve the safety and reliability of the equipment.

[0053] Step S 4 . The importance evaluation module 6 and the risk evaluation module 7 transmit the generated information to the maintenance decision-making module 8. The maintenance decision-making module 8 receives the information through the information receiving unit 801 and analyzes and processes it through the data analysis unit to form a maintenance decision-making method for the key drilling and production moving equipment. Subsequently, the processing result is transmitted to the display terminal 9 through the information transmission unit 803.

[0054] Specifically, according to the analysis results of the importance evaluation module 6 and the risk evaluation module 7, the decision tree algorithm is used to classify and make decisions on the maintenance strategies of each component. The decision tree algorithm can select the optimal maintenance strategy according to different combinations of importance and risk levels. Then, combined with the actual maintenance conditions and operation characteristics, the reinforcement learning algorithm is used to dynamically optimize the regular maintenance cycle and the hidden danger inspection interval. The reinforcement learning algorithm can learn the optimal maintenance decision strategy through interaction with the environment, so as to adjust the maintenance cycle and inspection interval to meet the actual needs. Subsequently, the time series analysis method is used to analyze the historical operation data and fault data of the equipment, revealing its changing trend and periodic law over time. Time series analysis can predict future fault trends and maintenance requirements, providing guidance for preventive maintenance. Based on the above analysis results, a decision optimization model is established. This decision optimization model can dynamically adjust the maintenance strategy and maintenance cycle according to factors such as the actual operation status, importance, and risk level of the equipment, realizing the quantitative analysis of the maintenance decision-making process. Through the output results of the decision optimization model, a set of maintenance decision-making methods for key drilling and production moving equipment is formed. This method can automatically generate the optimal maintenance plan and adjustment plan according to the actual operation data and fault information, providing decision support for the maintenance and management of the equipment.

[0055] Step S 5 . The display terminal 9 displays the importance evaluation method of the key drilling and production moving equipment, the importance evaluation model of the key drilling and production moving equipment, the risk quantitative evaluation technical method of the key drilling and production moving equipment, the fault mode risk quantitative evaluation model of the key drilling and production moving equipment, and the maintenance decision-making method of the key drilling and production moving equipment.

[0056] Step S 6 . When front-line personnel perform maintenance, by reading the terminal 5 which is electrically connected to the maintenance decision module 8, the fault data and the maintenance decision-making method can be read on the equipment body.

[0057] In summary, after reading the present invention document, various other corresponding transformation schemes made by ordinary technicians in the art without creative mental labor according to the technical solutions and technical concepts of the present invention all fall within the scope protected by the present invention.

Claims

1. A management method for drilling and production moving equipment based on RCM, Characterized in that: It includes the following steps: Step S 1 . Collect the maintenance status data of key drilling and production equipment and the fault data of the sensor device (1), and transmit them to the server (3); Step S 2 . The server (3) receives the maintenance status data and the fault data, analyzes and identifies them, and then stores them classified; Step S 3 . Extract the classified data in the above-mentioned server (3), determine the influencing factors of the importance of each component of the key drilling and production moving equipment, and use them as evaluation indicators. Through comprehensive evaluation of the evaluation indicators, comprehensively and quantitatively evaluate the importance of each component in the key drilling and production moving equipment; identify and classify the fault modes that occur in the key drilling and production moving equipment, quantitatively evaluate the importance of the fault modes, determine the influence degree of the fault modes on the safety of the key drilling and production moving equipment, and evaluate and predict the risk degree of the fault modes; Step S 4 . Dynamically adjust the maintenance strategy and maintenance cycle according to the importance of each component in the key drilling and production moving equipment, the risk level of the failure mode, and the actual maintenance conditions and operation characteristics of the key drilling and production moving equipment.

2. The management method for drilling and production moving equipment based on RCM according to claim 1, Characterized in that: The described step S 3 Determine the importance influencing factors of each component of the key drilling and production moving equipment, and use them as evaluation indicators, specifically referring to: through fault tree analysis, find out various influencing factors that cause failures of the key drilling and production moving equipment, and determine the logical relationships between them; analyze the hierarchical relationships of each component of the key drilling and production moving equipment, and use the analytic hierarchy process to determine the relative importance of each component; use the grey relational analysis method to determine the relational relationship between the influencing factors of each component and the safety of the key drilling and production moving equipment, and use the importance influencing factors of each component as evaluation indicators.

3. The management method for drilling and production moving equipment based on RCM according to claim 1 or 2, Characterized in that: The said step S 3 identifies and classifies the failure modes that occur in the key drilling and production moving equipment, quantitatively evaluates the importance of the failure modes, and determines the degree of influence of the failure modes on the safety of the key drilling and production moving equipment. Specifically, it means: identifying and classifying the failure modes that occur in the key drilling and production moving equipment through FMEA, and based on the identified failure modes, using the grey relational analysis algorithm to quantitatively evaluate the importance of each failure mode, so as to determine the degree of influence of the failure modes on the equipment safety.

4. The management method for drilling and production moving equipment based on RCM according to claim 3, Characterized in that: Before identifying and classifying the failure modes of key drilling and production moving equipment through FMEA, it also includes preprocessing the data, including removing outliers, missing values, and redundant data from the data.

5. The management method for drilling and production moving equipment based on RCM according to claim 3, Characterized in that: The described step S 3 The evaluation and prediction of the risk level of the failure mode specifically refer to: using the support vector machine algorithm for modeling and prediction to determine the risk level of the failure mode.

6. The management method for drilling and production moving equipment based on RCM according to claim 3, Characterized in that: The said step S 4 Specifically, it means: making different combinations of the importance degrees of each component and the risk levels of the failure modes, and selecting the optimal maintenance strategy; adjusting the maintenance cycle and inspection interval in combination with the actual maintenance conditions and operation characteristics of the key drilling and production moving equipment, and finally establishing a decision optimization model based on the predicted failure trend and maintenance requirements to dynamically adjust the maintenance strategy and maintenance cycle.

7. The management method for drilling and production moving equipment based on RCM according to claim 6, Characterized in that: The step S 4 selects an optimal maintenance strategy through a decision tree algorithm; adjusts the maintenance cycle and inspection interval through a reinforcement learning algorithm; and predicts the fault trend and maintenance requirements through a time series analysis method.

8. A management system for key drilling and production moving equipment based on RCM, Characterized in that: It includes a collection module (4) and a sensor device (1), a sensor detection module (2), a server (3), a criticality evaluation module (6), a risk evaluation module (7), and a maintenance decision-making module (8) that are sequentially communicatively connected; the collection module (4) is electrically connected to the server (3); The collection module (4) is used to collect the maintenance status data of key drilling and production moving equipment and transmit it to the server (3); The sensor detection module (2) is used to collect failure data and transmit it to the server (3) when the sensor device (1) fails; The server (3) is used to receive the maintenance status data and failure data, classify them into the maintenance status database (3021), historical failure database (3022), and operating failure database (3023) in the server (3) in sequence, and then transport the classified data to the risk evaluation module (7) and the criticality evaluation module (6); The criticality evaluation module (6) is used to analyze the data transmitted by the server (3), determine the criticality influencing factors of each component of the key drilling and production moving equipment, and use them as evaluation indicators. By comprehensively evaluating the evaluation indicators, quantitatively evaluate the criticality of each component in the key drilling and production moving equipment in an all-round way, and establish a criticality evaluation model for the key drilling and production moving equipment; The risk evaluation module (7) is used to analyze the data transmitted by the server (3), identify and classify the failure modes of the key drilling and production moving equipment, quantitatively evaluate the criticality of the failure modes, determine the influence degree of the failure modes on the safety of the key drilling and production moving equipment, evaluate and predict the risk degree of the failure modes, and establish a quantitative risk evaluation model for the failure modes; The maintenance decision-making module (8) is used to dynamically adjust the maintenance strategy and maintenance cycle according to the criticality of each component in the key drilling and production moving equipment, the risk degree of the failure modes, and the actual maintenance conditions and operation characteristics of the key drilling and production moving equipment.

9. The management system for key drilling and production moving equipment based on RCM according to claim 8, Characterized in that: It further includes a display terminal (9) communicatively connected to the maintenance decision-making module (8).

10. A management system for key drilling and production moving equipment based on RCM according to claim 8, characterized in that: it further includes a reading terminal (5) electrically connected to the maintenance decision-making module (8) for staff to read fault data and historical fault data.

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