Reusable vehicle maintenance logic decision-making method based on FMEA and TOPSIS methods

Abstract

The invention discloses a reusable launch vehicle maintenance logic decision method based on FMEA and TOPSIS methods, and the method comprises the steps: carrying out the structural decomposition analysis of a reusable launch vehicle system, and determining a device which may have a fault; fMEA analysis is carried out on equipment which may have faults, an FMEA table is compiled, fault modes, fault reasons and fault influences of all the equipment are clarified, FMEA analysis results are analyzed, evaluation indexes are constructed for all the equipment, and the importance degree of all the equipment is determined; according to the importance degree of the equipment, calculating the importance degree sorting ratio of the equipment, dividing the equipment which possibly breaks down into three classes, and determining an equipment maintenance mode for each class of equipment by adopting a corresponding RCM logic decision process; and an entropy weight TOPSIS method is adopted to determine an optimal maintenance mode, so that the provided maintenance decision achieves economic benefit maximization on the basis of meeting related requirements of maintainability and reliability, and industrialization and large-scale development of related technologies in the future is facilitated.

Description

Technical Field

[0001] The invention relates to a reusable vehicle maintenance logic decision method based on FMEA and TOPSIS methods, and belongs to the field of reusable vehicle maintenance decision-making. Background Art

[0002] The reusable launch vehicle is a very large and complex system with a very complicated structure and very strict functional requirements. There are many coupling and interlacing of subsystems and subsystems. Due to the high cost and the requirement of long-term reusability, in principle, no failure is allowed in the launch vehicle system when it performs a mission on orbit. However, it is inevitable that failures will still occur during the on-orbit mission of the launch vehicle. Once a failure occurs, it will harm the normal operation of the launch vehicle, affect subsequent use, and seriously cause the mission to be unable to be performed. How to choose the appropriate method to diagnose the occurrence of the failure and evaluate the harmful impact of the failure, how to implement the repair and recovery of the failure, and how to complete the scheduled mission to the greatest extent when the failure is difficult to repair, etc., are the key foundations for substantially improving the on-orbit reliability of the reusable launch vehicle, ensuring the completion of the established mission, and reducing economic costs. It is also an inevitable requirement for related development in the future. High-precision, high-reliability, and long-life launch vehicles are the development direction proposed in line with market demand.

[0003] Fault diagnosis technology diagnoses the monitored system by selecting the corresponding method, and then gives a fault prediction. At present, fault diagnosis methods are widely used to guide the formulation of spacecraft maintenance plans. However, due to the complexity of the carrier system itself and the hidden nature of early fault characteristics, most of the commonly used diagnostic methods currently show a low fault diagnosis rate. In addition, the randomness of the operation process and the prediction error affect the prediction accuracy. In addition, the reuse of carriers is a new concept, and it is difficult to obtain sufficient repair experience support, so fault diagnosis methods are difficult to carry out. Summary of the invention

[0004] The technical problem solved by the present invention is: to overcome the shortcomings of the prior art, to provide a maintenance logic decision for a reusable carrier based on FMEA and TOPSIS methods, and to use a logic decision diagram to provide an optimal maintenance decision plan based on FMEA (Failure Mode and Effects Analysis) analysis and TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) analysis, so that the provided maintenance decision can achieve maximum economic benefits on the basis of meeting the requirements related to maintainability and reliability, and to contribute to the industrialization and large-scale development of related technologies in the future.

[0005] The technical solution of the present invention is: a maintenance logic decision method for reusable vehicles based on FMEA and TOPSIS method, wherein:

[0006] Conduct structural breakdown analysis of reusable launch vehicle systems to identify equipment that may fail;

[0007] Conduct FMEA analysis on equipment that may fail, compile FMEA tables, clarify the failure mode, cause, and impact of each device, analyze the results of FMEA analysis, build evaluation indicators for each device, and determine the importance of each device;

[0008] Calculate the equipment importance ranking ratio based on the importance of the equipment, divide the equipment that may fail into three categories, and use the corresponding RCM logic decision process to determine the maintenance method corresponding to each of the multiple failure modes for each type of equipment;

[0009] Decision-making indicators are constructed for maintenance methods, and a decision matrix is ​​constructed based on them. Each maintenance method under different decision indicators is evaluated according to economic benefits, and the benefit indicators of each maintenance method under different decision indicators are obtained. The entropy weight TOPSIS method is used to determine the importance weight of each benefit indicator. Combined with the benefit indicators and the indicator importance weights, the evaluation values ​​of various maintenance methods are calculated, and the optimal maintenance method for the equipment is selected.

[0010] Preferably, when constructing evaluation indicators for each device and determining the importance of each device, the risk priority number RPN method is used for evaluation, specifically:

[0011] The scoring method is used to score the three risk factors of each device, namely, the severity of failure (S), the frequency of occurrence (O), and the difficulty of detection (D), from 1 to 10, and the importance of the equipment is obtained by weighted integration.

[0012] Preferably, the device importance ranking ratio α is calculated according to the importance of the device, and the devices that may fail are divided into three categories, specifically:

[0013]

[0014] Where: C k represents the importance of the kth device, C kmax Indicates the maximum value of the equipment importance among all the equipment that may fail;

[0015] When the importance ranking ratio α is between 60% and 100%, the corresponding equipment is critical equipment, i.e., Class III equipment;

[0016] When the importance ranking ratio α is between 20% and 60%, the corresponding equipment is important equipment, i.e., Class II equipment;

[0017] When the importance ranking ratio α is between 0% and 20%, the corresponding equipment is general equipment, that is, Class I equipment.

[0018] Preferably, the RCM logic decision process for determining the equipment maintenance method for Class III equipment is as follows:

[0019] First, determine whether regular maintenance is effective. If so, use regular maintenance. If regular maintenance is ineffective, determine whether the fault has hidden consequences.

[0020] If there are no hidden failure consequences, determine whether the preventive maintenance cost of the equipment is greater than the post-failure maintenance cost. If so, perform post-failure maintenance. If not, further determine whether there is a suitable unit status tracking technology. If there is a suitable unit status tracking technology, perform maintenance based on the equipment unit operating status. If there is no suitable unit status tracking technology, analyze whether the unit meets the requirements for scheduled overhaul. If so, perform regular overhaul. If not, scrap it regularly.

[0021] If the fault has hidden consequences, determine whether the hidden consequences can be detected:

[0022] If the hidden consequences can be detected, then determine whether there is appropriate unit status tracking technology. If there is appropriate unit status tracking technology, then repair based on the equipment unit operating status. If there is no appropriate unit status tracking technology, then analyze whether the unit meets the requirements for scheduled overhaul. If so, then overhaul regularly. If not, then scrap it regularly.

[0023] If the hidden consequences cannot be detected, determine whether the cost of preventive maintenance of the equipment is greater than the cost of subsequent maintenance. If so, repair it after failure. If not, further determine whether there is appropriate unit status tracking technology. If there is appropriate unit status tracking technology, repair it based on the operating status of the equipment unit. If there is no appropriate unit status tracking technology, analyze whether the unit meets the requirements for scheduled disassembly and repair. If so, disassemble and repair it regularly. If not, scrap it regularly.

[0024] Preferably, the RCM logic decision process for determining the equipment maintenance method for Class II equipment is as follows:

[0025] First, determine whether regular maintenance is effective. If so, use regular maintenance. If regular maintenance is ineffective, determine whether the fault has hidden consequences.

[0026] If the failure does not have hidden consequences, determine whether the preventive maintenance cost of the equipment is greater than the post-failure maintenance cost. If so, perform post-failure maintenance. If not, further determine whether there is appropriate unit status tracking technology. If there is appropriate unit status tracking technology, perform maintenance based on the operation of the equipment unit. If the operation status of the equipment unit cannot be detected, analyze whether the unit meets the requirements for scheduled overhaul. If so, perform regular overhaul. If not, scrap the unit regularly.

[0027] If the fault has hidden consequences, determine whether the hidden consequences can be detected:

[0028] If the hidden consequences can be detected, repair after failure;

[0029] If the hidden consequences cannot be detected, determine whether the cost of preventive maintenance of the equipment is greater than the cost of subsequent maintenance. If so, repair it after failure. If not, scrap it regularly.

[0030] Preferably, the RCM logic decision process for Class I equipment to determine the equipment maintenance method is as follows:

[0031] First, determine whether regular maintenance is effective. If so, use regular maintenance. If regular maintenance is ineffective, determine whether the fault has hidden consequences.

[0032] If the failure does not have hidden consequences, determine whether the preventive maintenance cost of the equipment is greater than the post-failure maintenance cost. If so, perform post-failure maintenance. If not, further determine whether there is appropriate unit status tracking technology. If there is appropriate unit status tracking technology, perform maintenance based on the equipment unit operating status. If the equipment unit operating status cannot be detected, analyze whether the unit meets the scheduled overhaul requirements. If so, perform regular overhaul. If not, scrap the unit regularly.

[0033] If the fault has hidden consequences, determine whether the hidden consequences can be detected:

[0034] If the hidden consequences can be detected, repair after failure;

[0035] If the hidden consequences cannot be detected, they will be scrapped regularly.

[0036] Preferably, the decision indicators constructed for the maintenance method include: mission loss, maintenance cost, maintenance difficulty, detectability, downtime, failure rate, failure function impact, and failure safety impact.

[0037] Preferably, a decision matrix is ​​constructed to evaluate the maintenance methods according to their economic benefits, and obtain the benefit indicators of each maintenance method, specifically:

[0038] Define a maintenance method for a certain equipment that contains m types of failure modes, and score the maintenance methods according to n decision indicators; use numbers from 1 to 10 to judge the degree of scoring, and the larger the value, the higher the degree of the corresponding indicator;

[0039] Let the score of the i-th maintenance method of the equipment based on the j-th decision indicator be x ij , 1≤i≤m, 1≤j≤n;

[0040] Then the decision matrix X is constructed as:

[0041]

[0042] where x ij represents the score value of the jth indicator under the i-th fault mode, X' j represents the score set of multiple maintenance methods under the jth indicator, X i is the scoring set of the i-th maintenance method;

[0043] The maintenance decision index of the failure mode is evaluated according to economic benefits, and the standard transformation formula is:

[0044]

[0045] Among them, r ij represents the benefit index corresponding to the jth decision index under the i-th maintenance mode; maxX' j represents the maintenance method with the highest score under the jth decision indicator, minX' j It represents the maintenance method with the lowest score under the j-th decision indicator; i represents one of the numbers 1 to m among the m failure modes, and j represents one of the numbers 1 to n among the n decision indicators.

[0046] Preferably, the method of determining the importance weight of each benefit-type indicator using the entropy weight TOPSIS method is:

[0047] Find the benefit index r of the i-th maintenance method of the equipment under the j-th decision index ij The characteristic weight p ij :

[0048]

[0049] Find the entropy value e of the j-th decision indicator j :

[0050]

[0051] Calculate the difference coefficient h of the j-th decision indicator j :

[0052]

[0053] Calculate the weight value ω using the entropy weight method j :

[0054]

[0055] Preferably, the objective formula of the optimal maintenance method under the jth decision indicator is:

[0056]

[0057] The objective formula of the worst maintenance method under the jth decision indicator is:

[0058]

[0059] The distance between each maintenance mode and the optimal maintenance mode target and the worst maintenance mode target is calculated using the equation:

[0060] The formula for the optimal maintenance method target distance is:

[0061]

[0062] The formula for the target distance of the worst maintenance method is:

[0063]

[0064] The TOPSIS evaluation value is determined according to the positive and negative bull's-eye distance formula, which represents the evaluation value ET of each maintenance method:

[0065]

[0066] The maintenance method with the largest evaluation value ET is selected as the optimal maintenance method for the equipment.

[0067] Compared with the prior art, the present invention has the following advantages:

[0068] The present invention adopts FMEA to conduct failure mode analysis and impact analysis on each subsystem and component that constitutes the carrier product, providing a systematic and detailed process for the subsequent identification and evaluation of the importance of the equipment, which has a wider applicability than the existing technology; the TOPSIS method is used to determine the weights of relevant indicators, avoiding the influence of subjective assignment and model assumptions on the results. The maintenance plan evaluation system formed optimizes the fault diagnosis effect, improves the prediction accuracy, and is conducive to the generation of the optimal maintenance plan for the carrier with high maintainability, high reliability and long life, reducing the failure losses during use and operation at a lower cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 This is the overall idea diagram of the present invention;

[0070] Figure 2 It is a logic decision flow chart of the maintenance mode of Class III equipment of the present invention;

[0071] Figure 3 It is a logic decision flow chart of the maintenance mode of Class II equipment of the present invention;

[0072] Figure 4 This is a logical decision flow chart of the maintenance method of Class I equipment of the present invention. DETAILED DESCRIPTION

[0073] The present invention combines FMEA theory and TOPSIS model, proposes a maintenance logic decision method for reusable vehicle based on FMEA and TOPSIS method, and performs maintenance decision work for reusable vehicle based on the logic decision model under FMEA and TOPSIS analysis.

[0074] The overall idea is Figure 1 As shown, the specific method is described as:

[0075] Step 1: Confirm the analysis object, that is, the equipment that may fail;

[0076] Structural decomposition analysis refers to decomposing a system according to certain principles, decomposing the system into equipment, and then decomposing the equipment into individual components. When decomposing a system, the granularity of the decomposition is often determined based on the actual situation. To determine the maintenance items to be performed on the reusable vehicle, it is first necessary to clarify the structural composition. Here, you can refer to relevant design data or reliability block diagrams to perform structural decomposition. Important functional units refer to system components that will affect the system's mission and safety reliability, or have major consequences when equipment fails. According to the results of the structural decomposition, referring to the characteristics of unimportant units, units with less impact can be eliminated to determine the final objects that need to be studied.

[0077] Step 2: Equipment importance evaluation based on FMEA analysis

[0078] Failure Mode and Effect Analysis, or "Potential Failure Mode and Effect Analysis", is abbreviated as FMEA. FMEA is a systematic activity that analyzes the subsystems and parts that make up the product and each process of the process in the product design stage and process design stage, finds all potential failure modes, and analyzes their possible consequences, so as to take necessary measures in advance to improve the quality and reliability of the product.

[0079] Perform FMEA analysis on the research object in Step 1, compile FMEA tables, and clarify the failure mode, cause, and impact of each device or subsystem stand-alone device (research object). The format of the FMEA table is shown in Table 1.

[0080] Table 1FMEA table format

[0081] Serial number Device Name Failure Mode Failure Impact Cause Compensatory measures Responsible person / completion date

[0082] After the equipment to be analyzed and the FMEA work are established, the results of the FMEA analysis are analyzed, evaluation indicators are constructed for the analyzed equipment, and the importance of each equipment is established, so as to facilitate the analysis of equipment of different importance by adopting different logical decision-making methods. The present invention adopts the risk priority number RPN method for evaluation. Analyze the equipment failure risk of the system and evaluate the risk factor score. Score the three risk factors of the severity of failure of each equipment (severity S), the frequency of occurrence (frequency O), and the difficulty of discovery (detection D), and use numbers 1 to 10 to judge the degree of failure. The larger the value, the higher the severity, the more frequent the occurrence, and the less likely it is to be discovered. Get the risk factor evaluation summary table. The larger the equipment risk priority value, the more important it is in the maintenance decision. The three risk factors are weighted and integrated to obtain the importance of the equipment. The equipment importance scoring table is shown in Table 2.

[0083] Table 2 Equipment importance rating table

[0084] Serial number Equipment / Subsystem Severity S Frequency Detection degree D Equipment importance

[0085] Step 3: Failure mode logic decision

[0086] The equipment importance ranking ratio refers to the arrangement of equipment importance values ​​from high to low. The highest value ranking ratio is 100%, and the importance ranking ratios of the remaining equipment are their importance values ​​relative to the highest value.

[0087] The percentage of the device importance value.

[0088]

[0089] α represents the ranking ratio of equipment importance,

[0090] C k represents the importance of the kth device,

[0091] C kmax Indicates the maximum importance of all devices that may fail.

[0092] According to the evaluation results of equipment importance, the equipment level is classified, and the equipment is divided into categories III, II, and I according to the equipment importance ranking ratio. The classification standards are shown in Table 3.

[0093] Table 3 Equipment classification based on importance evaluation

[0094]

[0095] Different logical decision-making processes are used for different levels of equipment. The specific logical decision-making and analysis processes for the three levels of equipment are as follows: Figure 2 , Figure 3 , Figure 4 shown.

[0096] (1) The RCM logic decision process for determining the equipment maintenance method for Class III equipment is as follows:

[0097] First, determine whether regular maintenance is effective. If so, use regular maintenance. If regular maintenance is ineffective, determine whether the fault has hidden consequences.

[0098] If there are no hidden failure consequences, determine whether the preventive maintenance cost of the equipment is greater than the post-failure maintenance cost. If so, perform post-failure maintenance. If not, further determine whether there is a suitable unit status tracking technology. If there is a suitable unit status tracking technology, perform maintenance based on the equipment unit operating status. If there is no suitable unit status tracking technology, analyze whether the unit meets the requirements for scheduled overhaul. If so, perform regular overhaul. If not, scrap it regularly.

[0099] If the fault has hidden consequences, determine whether the hidden consequences can be detected:

[0100] If the hidden consequences can be detected, then determine whether there is appropriate unit status tracking technology. If there is appropriate unit status tracking technology, then repair based on the equipment unit operating status. If there is no appropriate unit status tracking technology, then analyze whether the unit meets the requirements for scheduled overhaul. If so, then overhaul regularly. If not, then scrap it regularly.

[0101] If the hidden consequences cannot be detected, determine whether the cost of preventive maintenance of the equipment is greater than the cost of subsequent maintenance. If so, repair it after failure. If not, further determine whether there is appropriate unit status tracking technology. If there is appropriate unit status tracking technology, repair it based on the operating status of the equipment unit. If there is no appropriate unit status tracking technology, analyze whether the unit meets the requirements for scheduled disassembly and repair. If so, disassemble and repair it regularly. If not, scrap it regularly.

[0102] (2) The specific RCM logic decision process for determining the equipment maintenance method for Class II equipment is as follows:

[0103] First, determine whether regular maintenance is effective. If so, use regular maintenance. If regular maintenance is ineffective, determine whether the fault has hidden consequences.

[0104] If the failure does not have hidden consequences, determine whether the preventive maintenance cost of the equipment is greater than the post-failure maintenance cost. If so, perform post-failure maintenance. If not, further determine whether there is appropriate unit status tracking technology. If there is appropriate unit status tracking technology, perform maintenance based on the operation of the equipment unit. If the operation status of the equipment unit cannot be detected, analyze whether the unit meets the requirements for scheduled overhaul. If so, perform regular overhaul. If not, scrap the unit regularly.

[0105] If the fault has hidden consequences, determine whether the hidden consequences can be detected:

[0106] If the hidden consequences can be detected, repair after failure;

[0107] If the hidden consequences cannot be detected, determine whether the cost of preventive maintenance of the equipment is greater than the cost of subsequent maintenance. If so, repair it after failure. If not, scrap it regularly.

[0108] (3) The specific RCM logic decision process for determining the equipment maintenance method for Class I equipment is as follows:

[0109] First, determine whether regular maintenance is effective. If so, use regular maintenance. If regular maintenance is ineffective, determine whether the fault has hidden consequences.

[0110] If the failure does not have hidden consequences, determine whether the preventive maintenance cost of the equipment is greater than the post-failure maintenance cost. If so, perform post-failure maintenance. If not, further determine whether there is appropriate unit status tracking technology. If there is appropriate unit status tracking technology, perform maintenance based on the equipment unit operating status. If the equipment unit operating status cannot be detected, analyze whether the unit meets the scheduled overhaul requirements. If so, perform regular overhaul. If not, scrap the unit regularly.

[0111] If the fault has hidden consequences, determine whether the hidden consequences can be detected:

[0112] If the hidden consequences can be detected, repair after failure;

[0113] If the hidden consequences cannot be detected, they will be scrapped regularly.

[0114] The difference between the three levels of equipment lies in the subsequent links with invisible consequences. The higher the level, the more complicated the question and answer links are and the more diverse the maintenance methods are.

[0115] Through the qualitative analysis of RCM logic decision, the maintenance plans corresponding to m failure modes of suborbital vehicle equipment were determined.

[0116] Step 4: Comprehensively evaluate the equipment units based on TOPSIS to determine the best maintenance method.

[0117] Step 1: Construct evaluation indicators

[0118] After discussion by experts, an evaluation system including n indicators was determined. The present invention constructs n=8 evaluation indicators for suborbital vehicles as shown in Table 4.

[0119] Table 4 Maintenance method decision indicators

[0120]

[0121] Step 2: Build a decision matrix

[0122] The maintenance method of m failure modes contained in a certain equipment is to score the failure modes according to n indicators, and also use numbers 1 to 10 to judge their degree. The larger the number, the higher the degree of the corresponding indicator.

[0123] The score given to the maintenance method of the i-th failure mode of the equipment according to the j-th indicator is x ij , 1≤i≤m, 1≤j≤n.

[0124] Then the decision matrix X is constructed as:

[0125]

[0126] where x ij represents the score value of the jth indicator under the maintenance method of the i-th failure mode; X' j The score set of the maintenance methods of various failure modes under the jth indicator is X, and the score set of the maintenance method of the i-th failure mode is X i ,

[0127] The original decision matrix is ​​dimensionless processed to obtain a normalized decision matrix, and the normalized decision matrix is ​​used to cover the original decision matrix X;

[0128] The maintenance methods of failure modes under different decision indicators are evaluated according to economic benefits, and the corresponding benefit indicators are obtained. The standard transformation formula is:

[0129]

[0130] Among them, r ij It represents the benefit index corresponding to the jth index under the maintenance mode of the i-th failure mode. maxX' j represents the maintenance method of the fault mode with the highest score under the jth indicator, minX' j represents the maintenance method of the lowest-scoring fault mode under the jth indicator; i represents a number from 1 to m among the m fault modes, j represents a number from 1 to n among the n indicators, and x ijRepresents the score value of the jth indicator of the i-th failure mode.

[0131] If it is a cost indicator, the standard transformation formula is:

[0132]

[0133] Because the evaluation matrix of the present invention is a benefit-type indicator, a benefit-type transformation formula is selected to obtain the equipment economic benefit standard evaluation matrix N:

[0134]

[0135] Where N i Represents the i-th economic benefit evaluation set of equipment.

[0136] Step 3: Determine the weight of maintenance decision evaluation indicators

[0137] In order to obtain the i-th economic benefit evaluation set N of equipment i The entropy weight TOPSIS method is used to determine the weight of the indicator importance (the weight of the maintenance decision evaluation indicator). The entropy weight TOPSIS method is a commonly used multi-attribute decision-making method. Its main idea is to introduce the entropy weight method on the basis of the TOPSIS method, and determine its weight by calculating the information entropy of each attribute, thereby improving the reliability and accuracy of the decision results. In the traditional TOPSIS method, the attribute weight is usually obtained by subjective assignment by experts or calculated by mathematical models. The entropy weight law calculates the information entropy of each attribute and quantifies the importance of each attribute as its contribution to the decision result, thereby avoiding the influence of subjective assignment and model assumptions on the result. The entropy weight method is used to determine the weight of the indicator as follows:

[0138] Find the characteristic weight p of the benefit index of the maintenance method of the i-th failure mode of the equipment under the j-th decision index ij :

[0139]

[0140] Find the entropy value e of the jth decision indicator j :

[0141]

[0142] Calculate the difference coefficient h of the j-th decision indicator j :

[0143]

[0144] Calculate the weight value ω using the entropy weight method j :

[0145]

[0146] The fourth step is to calculate the evaluation value of each maintenance method and make a decision on the optimal maintenance method for the equipment.

[0147] According to the results of the above steps, the evaluation value can be calculated for the evaluation object through TOPSIS target decision. The specific steps are as follows:

[0148] First we can get the positive and negative targets as follows:

[0149] The objective formula of the optimal maintenance method under the jth index is:

[0150]

[0151] The objective formula of the worst maintenance method under the jth index is:

[0152]

[0153] The distance between each evaluation object (maintenance method) and the optimal maintenance method target and the worst maintenance method target is calculated using the equation:

[0154] The formula for the optimal maintenance method target distance is:

[0155]

[0156] The formula for the target distance of the worst maintenance method is:

[0157]

[0158] The TOPSIS evaluation value is determined according to the positive and negative bull's-eye distance formula, which represents the evaluation value of each maintenance method. We define this calculated value as the ET value.

[0159]

[0160] This value is used to make the optimal maintenance method decision, and the maintenance method with the largest weight evaluation value ET is selected as the optimal maintenance method for the equipment.

[0161] The contents not described in detail in the specification of the present invention belong to the prior art known to the professional and technical personnel in this field.

Claims

1. A maintenance logic decision method for reusable vehicles based on FMEA and TOPSIS method, characterized in that include: Conduct structural breakdown analysis of reusable launch vehicle systems to identify equipment that may fail; Conduct FMEA analysis on equipment that may fail, compile FMEA tables, clarify the failure mode, cause, and impact of each device, analyze the results of FMEA analysis, build evaluation indicators for each device, and determine the importance of each device; Calculate the equipment importance ranking ratio based on the importance of the equipment, divide the equipment that may fail into three categories, and use the corresponding RCM logic decision process to determine the maintenance method corresponding to each of the multiple failure modes for each type of equipment; Decision-making indicators are constructed for maintenance methods, and a decision matrix is ​​constructed based on them. Each maintenance method under different decision indicators is evaluated according to economic benefits, and the benefit indicators of each maintenance method under different decision indicators are obtained. The entropy weight TOPSIS method is used to determine the importance weight of each benefit indicator. Combined with the benefit indicators and the indicator importance weights, the evaluation values ​​of various maintenance methods are calculated, and the optimal maintenance method for the equipment is selected.

2. The maintenance logic decision method for reusable vehicle based on FMEA and TOPSIS method according to claim 1, characterized in that: When constructing evaluation indicators for each device and determining the importance of each device, the risk priority number RPN method is used for evaluation. Specifically: The scoring method is used to score the three risk factors of each device, namely, the severity of failure (S), the frequency of occurrence (O), and the difficulty of detection (D), from 1 to 10, and the importance of the equipment is obtained by weighted integration.

3. The maintenance logic decision method for reusable vehicle based on FMEA and TOPSIS method according to claim 1, characterized in that: The equipment importance ranking ratio α is calculated based on the importance of the equipment, and the equipment that may fail is divided into three categories, specifically: Where: C k represents the importance of the kth device, C kmax Indicates the maximum value of the equipment importance among all the equipment that may fail; When the importance ranking ratio α is between 60% and 100%, the corresponding equipment is critical equipment, i.e., Class III equipment; When the importance ranking ratio α is between 20% and 60%, the corresponding equipment is important equipment, i.e., Class II equipment; When the importance ranking ratio α is between 0% and 20%, the corresponding equipment is general equipment, that is, Class I equipment.

4. The maintenance logic decision method for reusable vehicle based on FMEA and TOPSIS method according to claim 3, characterized in that: The specific RCM logic decision process for determining the equipment maintenance method for Class III equipment is as follows: First, determine whether regular maintenance is effective. If so, use regular maintenance. If regular maintenance is ineffective, determine whether the fault has hidden consequences. If there are no hidden failure consequences, determine whether the preventive maintenance cost of the equipment is greater than the post-failure maintenance cost. If so, perform post-failure maintenance. If not, further determine whether there is a suitable unit status tracking technology. If there is a suitable unit status tracking technology, perform maintenance based on the equipment unit operating status. If there is no suitable unit status tracking technology, analyze whether the unit meets the requirements for scheduled overhaul. If so, perform regular overhaul. If not, scrap it regularly. If the fault has hidden consequences, determine whether the hidden consequences can be detected: If the hidden consequences can be detected, then determine whether there is appropriate unit status tracking technology. If there is appropriate unit status tracking technology, then repair based on the equipment unit operating status. If there is no appropriate unit status tracking technology, then analyze whether the unit meets the requirements for scheduled overhaul. If so, then overhaul regularly. If not, then scrap it regularly. If the hidden consequences cannot be detected, determine whether the cost of preventive maintenance of the equipment is greater than the cost of subsequent maintenance. If so, repair it after failure. If not, further determine whether there is appropriate unit status tracking technology. If there is appropriate unit status tracking technology, repair it based on the operating status of the equipment unit. If there is no appropriate unit status tracking technology, analyze whether the unit meets the requirements for scheduled disassembly and repair. If so, disassemble and repair it regularly. If not, scrap it regularly.

5. The maintenance logic decision method for reusable vehicle based on FMEA and TOPSIS method according to claim 3, characterized in that: The specific RCM logic decision process for determining the equipment maintenance method for Class II equipment is as follows: First, determine whether regular maintenance is effective. If so, use regular maintenance. If regular maintenance is ineffective, determine whether the fault has hidden consequences. If the failure does not have hidden consequences, determine whether the preventive maintenance cost of the equipment is greater than the post-failure maintenance cost. If so, perform post-failure maintenance. If not, further determine whether there is appropriate unit status tracking technology. If there is appropriate unit status tracking technology, perform maintenance based on the operation of the equipment unit. If the operation status of the equipment unit cannot be detected, analyze whether the unit meets the requirements for scheduled overhaul. If so, perform regular overhaul. If not, scrap the unit regularly. If the fault has hidden consequences, determine whether the hidden consequences can be detected: If the hidden consequences can be detected, repair after failure; If the hidden consequences cannot be detected, determine whether the cost of preventive maintenance of the equipment is greater than the cost of subsequent maintenance. If so, repair it after failure. If not, scrap it regularly.

6. The maintenance logic decision method for reusable vehicle based on FMEA and TOPSIS method according to claim 3, characterized in that: The specific RCM logic decision process for determining the equipment maintenance method for Class I equipment is as follows: First, determine whether regular maintenance is effective. If so, use regular maintenance. If regular maintenance is ineffective, determine whether the fault has hidden consequences. If the failure does not have hidden consequences, determine whether the preventive maintenance cost of the equipment is greater than the post-failure maintenance cost. If so, perform post-failure maintenance. If not, further determine whether there is appropriate unit status tracking technology. If there is appropriate unit status tracking technology, perform maintenance based on the equipment unit operating status. If the equipment unit operating status cannot be detected, analyze whether the unit meets the scheduled overhaul requirements. If so, perform regular overhaul. If not, scrap the unit regularly. If the fault has hidden consequences, determine whether the hidden consequences can be detected: If the hidden consequences can be detected, repair after failure; If the hidden consequences cannot be detected, they will be scrapped regularly.

7. The maintenance logic decision method for reusable vehicle based on FMEA and TOPSIS method according to claim 1, characterized in that: The decision indicators constructed for the maintenance method include: mission loss, maintenance cost, maintenance difficulty, detectability, downtime, failure rate, failure function impact, and failure safety impact.

8. The maintenance logic decision method for reusable vehicle based on FMEA and TOPSIS method according to claim 1, characterized in that: A decision matrix is ​​constructed to evaluate the maintenance methods according to their economic benefits, and the benefit indicators of each maintenance method are obtained, which are as follows: Define a maintenance method for a certain equipment that contains m types of failure modes, and score the maintenance methods according to n decision indicators; use numbers from 1 to 10 to judge the degree of scoring, and the larger the value, the higher the degree of the corresponding indicator; Let the score of the i-th maintenance method of the equipment based on the j-th decision indicator be x ij , 1≤i≤m, 1≤j≤n; Then the decision matrix X is constructed as: where x ij represents the score value of the jth indicator under the i-th fault mode, X' j represents the score set of multiple maintenance methods under the jth indicator, X i is the scoring set of the i-th maintenance method; The maintenance decision index of the failure mode is evaluated according to economic benefits, and the standard transformation formula is: Among them, r ij represents the benefit index corresponding to the jth decision index under the i-th maintenance mode; maxX' j represents the maintenance method with the highest score under the jth decision indicator, minX' j It represents the maintenance method with the lowest score under the j-th decision indicator; i represents one of the numbers 1 to m among the m failure modes, and j represents one of the numbers 1 to n among the n decision indicators.

9. The maintenance logic decision method for reusable vehicle based on FMEA and TOPSIS method according to claim 8, characterized in that: The method of using the entropy weight TOPSIS method to determine the importance weight of each benefit-type indicator is as follows: Find the benefit index r of the i-th maintenance method of the equipment under the j-th decision index ij The characteristic weight p ij : Find the entropy value e of the j-th decision indicator j : Calculate the difference coefficient h of the j-th decision indicator j : Calculate the weight value ω using the entropy weight method j :

10. The maintenance logic decision method for reusable vehicle based on FMEA and TOPSIS method according to claim 1, characterized in that: The objective formula of the optimal maintenance method under the jth decision index is: The objective formula of the worst maintenance method under the jth decision indicator is: The distance between each maintenance mode and the optimal maintenance mode target and the worst maintenance mode target is calculated using the equation: The formula for the optimal maintenance method target distance is: The formula for the target distance of the worst maintenance method is: The TOPSIS evaluation value is determined according to the positive and negative bull's-eye distance formula, which represents the evaluation value ET of each maintenance method: The maintenance method with the largest evaluation value ET is selected as the optimal maintenance method for the equipment.

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