A reliability evaluation method, device, equipment, and storage medium for a target system

Abstract

An embodiment of the present application provides a method, apparatus, device, and storage medium for evaluating the reliability of a target system. Among them, the method includes: obtaining a statistical data set, where each statistical data in the statistical data set is obtained by screening the management data of different systems according to the corresponding defect attribute words; the defect attribute words include: discovered defects and / or repaired defects; determining at least one intermediate system included in the target system and at least one subsystem included in the intermediate system; based on the statistical data set, using the Delphi method to determine the probability level of each subsystem in the target system; based on the probability level of at least one subsystem included in each intermediate system, determining the repair damage probability of the corresponding intermediate system; based on the repair damage probability of each intermediate system, determining the repair damage function of the corresponding intermediate system; based on the repair damage function of each intermediate system, determining the reliability of the target system.

Description

Technical Field

[0001] The present application relates to the field of public safety, and relates to, but is not limited to, a method, device, equipment, and storage medium for evaluating the reliability of a target system. Background Art

[0002] With the rapid development of urbanization construction, public safety has become increasingly important. For example, as of the end of 2020, the number of elevators in China has reached more than 7.8 million. While elevators provide convenience to people, safety accidents caused by elevator defects also occur from time to time. Among them, the total number of elevator accidents accounts for about 25% of the total number of special equipment accidents. Therefore, it is of great significance to find a scientific, reasonable, and effective method for evaluating the reliability of a target system.

[0003] In the existing research on the reliability of target systems, most methods are implemented based on methods such as artificial intelligence, fault trees, and neural networks. However, these methods have limitations of being complex and time-consuming in application, and the problem that the neural network model is prone to falling into local minima during the solution process. Therefore, the present application introduces the orthogonal defect classification method in software defect management into the research on the reliability of target systems. The orthogonal defect classification method is a bridge between qualitative analysis and quantitative analysis. Compared with general defect classification methods, it has lower costs and can reasonably, efficiently, and scientifically achieve accurate defect traceability, with strong measurability. Conducting reliability mathematical modeling on the statistical data obtained by the orthogonal defect classification method can effectively solve problems such as non-standard data statistics, complex reliability modeling, and inaccurate prediction, and derive a mathematical expression for the reliability parameter index based on Markov theory, analyze the factors affecting system performance, and provide guiding opinions for the optimization design work. Summary of the Invention

[0004] In view of this, embodiments of the present application provide a method, device, equipment, and storage medium for evaluating the reliability of a target system.

[0005] The technical solution of the embodiments of the present application is implemented as follows:

[0006] In a first aspect, an embodiment of the present application provides a method for evaluating the reliability of a target system. The method includes: obtaining a statistical data set, where each piece of statistical data in the statistical data set is obtained by screening the management data of different systems according to a corresponding defect attribute word; the defect attribute words include: discovered defect and / or repaired defect; determining at least one intermediate system included in the target system and at least one subsystem included in the intermediate system; based on the statistical data set, using the Delphi method to determine the probability level of each subsystem in the target system; based on the probability level of at least one subsystem included in each intermediate system, determining the repair damage probability of the corresponding intermediate system; based on the repair damage probability of each intermediate system, determining the repair damage function of the corresponding intermediate system; based on the repair damage function of each intermediate system, determining the reliability of the target system.

[0007] In a second aspect, an embodiment of the present application provides a device for evaluating the reliability of a target system. The device includes: a first acquisition module for obtaining a statistical data set, where each piece of statistical data in the statistical data set is obtained by screening the management data of different systems according to a corresponding defect attribute word; the defect attribute words include: discovered defect and / or repaired defect; a first determination module for determining at least one intermediate system included in the target system and at least one subsystem included in the intermediate system; a second determination module for, based on the statistical data set, using the Delphi method to determine the probability level of each subsystem in the target system; a third determination module for, based on the probability level of at least one subsystem included in each intermediate system, determining the repair damage probability of the corresponding intermediate system; a fourth determination module for, based on the repair damage probability of each intermediate system, determining the repair damage function of the corresponding intermediate system; a fifth determination module for, based on the repair damage function of each intermediate system, determining the reliability of the target system.

[0008] In a third aspect, an embodiment of the present application provides a computer device. The device includes: a memory and a processor. The memory stores a computer program that can run on the processor, and when the processor executes the computer program, it implements the steps in the above method.

[0009] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the steps in the above method.

[0010] As can be seen from the above, in the embodiments of the present application, by introducing the orthogonal defect classification method into the management data of different systems, accurate defect tracing can be reasonably, efficiently and scientifically realized, making the management data of different systems more accurate, and also laying a foundation for determining the probability levels of subsystems in the target system later; by using the Delphi method to evaluate each subsystem in the target system, the limitations in obtaining data samples by the orthogonal defect classification method can be more reasonably compensated, making the analysis results more objective; through the damage function, the impact of each intermediate system in the target system on the entire target system can be more intuitively judged, and corresponding optimization suggestions can be provided for the target system in a targeted manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 is a schematic flow chart of a method for evaluating the reliability of a target system provided by an embodiment of the present application;

[0012] Figure 2a is a statistical chart of objects of elevator defects in City H within one year provided by an embodiment of the present application;

[0013] Figure 2b is a statistical chart of types of elevator defects in City H within one year provided by an embodiment of the present application;

[0014] Figure 3 is a process chart of elevator orthogonal defect classification provided by an embodiment of the present application;

[0015] Figure 4 is a structural diagram of elevator operation provided by an embodiment of the present application;

[0016] Figure 5 is a reliability block diagram of an elevator system provided by an embodiment of the present application;

[0017] Figure 6 is a Markov state transition diagram provided by an embodiment of the present application;

[0018] Figure 7a is a schematic diagram of a triangular membership function of the elevator system failure probability level provided by an embodiment of the present application;

[0019] Figure 7b is a schematic diagram of a triangular membership function of the elevator system repair probability level provided by an embodiment of the present application;

[0020] Figure 8 is a structural division diagram of the elevator system of Elevator A provided by an embodiment of the present application;

[0021] Figure 9 is a schematic diagram of the composition structure of a device for evaluating the reliability of a target system provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0022] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the following will clearly and completely describe the technical solutions in the embodiments of this application with reference to the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are some, but not all, of the embodiments of this application. The following embodiments are used to illustrate this application, but not to limit the scope of this application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of this application without creative efforts belong to the scope of protection of this application.

[0023] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments. However, it can be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments, and can be combined with each other without conflict.

[0024] It should be noted that the terms "first / second / third" involved in the embodiments of this application are only used to distinguish similar objects and do not represent a specific order for the objects. It can be understood that "first / second / third" can be interchanged with a specific order or sequence when permitted, so that the embodiments of this application described here can be implemented in an order other than that illustrated or described here.

[0025] Those skilled in the art of this technology can understand that, unless otherwise defined, all terms (including technical terms and scientific terms) used here have the same meaning as the general understanding of those of ordinary skill in the art in the field to which the embodiments of this application belong. It should also be understood that terms such as those defined in a general dictionary should be understood to have a meaning consistent with the meaning in the context of the prior art, and will not be interpreted with an idealized or overly formal meaning unless specifically defined as here.

[0026] Before elaborating on the embodiments of this application, the nouns and terms involved in the embodiments of this application are described. The nouns and terms involved in the embodiments of this application are applicable to the following explanations:

[0027] The Delphi method, also known as the expert survey method, was initiated and implemented by the RAND Corporation in the United States in 1946. In essence, it is a feedback anonymous inquiry method. Its general process is to solicit the opinions of experts on the problem to be predicted, then organize, summarize, and statistically analyze them, and then anonymously feedback them to each expert, solicit opinions again, centralize them again, and feedback them until a consistent opinion is obtained.

[0028] The orthogonal defect classification method is a method for classifying defects. Essentially, it means classifying defects from multiple perspectives to describe them, and these attributes jointly point to the process that needs attention. This process of describing defects is similar to using the coordinates (x, y, z) in the orthogonal coordinate axes in the Cartesian coordinate system to describe a point. Orthogonal defect classification establishes a measurable causal relationship in the software development process by extracting key defect information.

[0029] Figure 1 The flowchart of a reliability evaluation method for a target system provided by an embodiment of the present application is as follows Figure 1 shown, and the method at least includes the following steps:

[0030] Step S110, obtain a statistical data set.

[0031] Here, each of the statistical data in the statistical data set is obtained by screening the management data of different systems according to the corresponding defect attribute words; the defect attribute words include: defect discovery and / or defect repair.

[0032] In the embodiment of the present application, a statistical data set in the elevator defect management platform in City H within one year is obtained. The data in the elevator defect management platform in City H within one year is described, classified, and statistically analyzed according to the elevator defect attribute words to obtain the defect activity (DA, Defect Activity), the event causing the defect (ECD, Event Causing Defect), and the effect of the defect (EOD, Effect Of Defects) in defect discovery, and the type of defect (TOD, Type Of Defect), the defect qualifier (DQ, Defect Qualifier), the source of the defect (SOD, Source Of Defects), the defective object (DO, Defective Object), and the history of the defect (HOD, History Of Defects) in defect repair, which are the statistical data of these eight orthogonal defect attribute words. Among the statistical data of the eight feasible orthogonal defect attribute words in the embodiment of the present application, the defective object and the type of defect are used as examples, as Figure 2a shown is the statistical chart of the defective objects of elevators in City H within one year, which statistically counts the number of times of defects occurring in different defective objects within one year; Figure 2b shown is the statistical chart of the types of elevator defects in City H within one year, which statistically counts the proportion of different types of elevator defects in all elevator defect types. For example, the proportion of mechanical defects is 59%, the proportion of electrical defects is 24%, and the proportion of other defects is 17%.

[0033] Step S120, determine at least one intermediate system included in the target system and at least one subsystem included in the intermediate system.

[0034] In some embodiments, the target system may be an elevator system; the intermediate system may be at least one of a car part, a landing part, a machine room part, and a hoistway and pit part; the subsystem may be at least one of a car system, a safety protection system, a door system, a traction system, a power drive system, an electrical control system, a guiding system, and a weight balance system.

[0035] In the embodiments of the present application, the data statistically counted by the elevator defect management platform in City H is selected as a case. The elevator in a certain community in City H is denoted as Elevator A, and the elevator system F0 of Elevator A is used as the target system; the car part F 11 , the landing part F 12 , the machine room part F 21 and the hoistway and pit part F 22 are used as the intermediate system; the car part F 11 includes: a car system X0 and a safety protection system X1; the landing part F 12 includes: a door system X2, the machine room part F 21 includes: a traction system X3, a power drive system X4, and an electrical control system X5, and the hoistway and pit part F 22 includes: a guiding system X6 and a weight balance system X7.

[0036] Step S130, based on the statistical data set, use the Delphi method to determine the probability levels of each subsystem in the target system.

[0037] In some embodiments, the probability levels may be a failure probability level and a repair probability level.

[0038] In the embodiments of the present application, based on the statistical data of eight orthogonal defect attribute words of elevators in City H within one year, experts score the failure probability levels of each subsystem X i in Elevator A, and obtain an evaluation table of the failure probability levels of each subsystem in Elevator A shown in Table 1; experts score the repair probability levels of each subsystem X i in Elevator A, and obtain an evaluation table of the repair probability levels of each subsystem in Elevator A shown in Table 2.

[0039] Table 1 Evaluation Table of Failure Probability Levels of Subsystems in Elevator A

[0040] Subsystem Expert 1 Expert 2 Expert 3 Expert 4 <![CDATA[X0]]> 4 6 7 6 <![CDATA[X1]]> 6 5 5 4 <![CDATA[X2]]> 6 8 6 7 <![CDATA[X3]]> 7 8 8 6 <![CDATA[X4]]> 9 8 7 8 <![CDATA[X5]]> 5 4 6 4 <![CDATA[X6]]> 3 5 4 3 <![CDATA[X7]]> 7 7 8 6

[0041] Table 2 Evaluation Table of Repair Probability Levels of Subsystems in Elevator A

[0042] Subsystem Expert 1 Expert 2 Expert 3 Expert 4 <![CDATA[X0]]> 5 7 4 6 <![CDATA[X1]]> 4 5 5 6 <![CDATA[X2]]> 3 4 3 4 <![CDATA[X3]]> 3 3 4 5 <![CDATA[X4]]> 2 3 3 4 <![CDATA[X5]]> 2 3 3 3 <![CDATA[X6]]> 3 2 2 3 <![CDATA[X7]]> 4 3 4 5

[0043] Among them, the car part F 11Including: car system X0 and safety protection system X1; landing section F 12 Including: door system X2, machine room section F 21 Including: traction system X3, electric drive system X4 and electrical control system X5, hoistway and pit section F 22 Including: guiding system X6 and weight balance system X7.

[0044] Step S140, based on the probability level of at least one subsystem included in each of the intermediate systems, determine the repair probability of the corresponding intermediate system.

[0045] In some embodiments, in step S140, the determining the repair probability of the corresponding intermediate system based on the probability level of at least one subsystem included in each of the intermediate systems includes: steps S141 to S144, where:

[0046] Step S141, based on the probability level of each subsystem, query a preset first relationship table to determine the repair parameter and triangular fuzzy set corresponding to the subsystem; the first relationship table is used to represent the corresponding relationship between the probability level and the repair parameter, triangular fuzzy set.

[0047] Here, the repair parameter may be the number of failures within a certain period of time, the time consumed for one repair.

[0048] In the embodiments of the present application, according to the fact that expert 4 in Table 1 gives a failure probability level of 8 for subsystem X4 in elevator A, query Table 3, the number of failures within 1 year corresponding to the failure probability level of 8 is 10, and the corresponding triangular fuzzy set is (0.7, 0.8, 0.9); according to this method, determine the number of failures within 1 year and the triangular fuzzy set corresponding to each failure probability level of subsystem X i in elevator A. Among them, the repair parameter is the number of failures within 1 year.

[0049] Table 3 Elevator System Failure Probability Level Table

[0050]

[0051]

[0052] Similarly, according to the fact that expert 4 in Table 2 gives a maintenance probability level of 6 for subsystem X0 in elevator A, query Table 4, the time consumed for one repair corresponding to the maintenance probability level of 6 is 50, and the corresponding triangular fuzzy set is (0.7, 0.9, 1); according to this method, determine the time consumed for one repair and the triangular fuzzy set corresponding to each maintenance probability level of subsystem X i in elevator A. Among them, the repair parameter is the time consumed for one repair.

[0053] Table 4 Maintenance Probability Level Table of Elevator System

[0054] Probability level Time consumed for one repair / h Linguistic variable Triangular fuzzy set 1 ≤0.5 Very easy (0，0，0.1) 2 1 Easy (0，0.1，0.3) 3 5 Relatively easy (0.1，0.3，0.5) 4 10 Average (0.3，0.5，0.7) 5 20 Relatively difficult (0.5，0.7，0.9) 6 50 Difficult (0.7，0.9，1) 7 ≥80 Very difficult (0.9，1，1)

[0055] Step S142, based on the damage parameters of the subsystem and the corresponding triangular fuzzy set, determine the triangular fuzzy probability of the corresponding subsystem;

[0056] In some embodiments, the j-th triangular fuzzy probability of the subsystem i is determined by formula (1).

[0057]

[0058] where j is the j-th probability level of the subsystem i, is the j-th triangular fuzzy probability of the subsystem i, P i j is the triangular fuzzy set corresponding to the j-th probability level of the subsystem i; if the damage parameter corresponding to the j-th probability level of the subsystem i is the number of failures within a certain period of time, then λ m is determined by formula (2); if the damage parameter corresponding to the j-th probability level of the subsystem i is the time consumed for one maintenance, then λ m is determined by formula (3).

[0059]

[0060]

[0061] In the embodiments of the present application, according to expert 4, the failure probability level of subsystem X4 of elevator A is 8, and the corresponding triangular fuzzy set is The number of failures in one year is 10, and according to formula (2), we get According to formula (1), calculate the triangular fuzzy probability of the failure probability of subsystem X4 given by expert 4 Calculated in this way, the triangular fuzzy probabilities of the failure probabilities of subsystem X4 of elevator A given by expert 1, expert 2, and expert 3 are respectively Similarly, the triangular fuzzy probability of each failure probability of subsystem X i is obtained

[0062] Similarly, according to expert 4, the maintenance probability level of subsystem X0 of elevator A is 6, and the corresponding triangular fuzzy set is The time consumed for one maintenance is 50, and according to formula (3), we get According to formula (1), calculate the triangular fuzzy probability of the maintenance probability of subsystem X0 given by expert 4 According to this method, the triangular fuzzy probabilities of the maintenance probabilities of Subsystem X0 of Elevator A by Expert 1, Expert 2, and Expert 3 are respectively Similarly, the triangular fuzzy probability of each maintenance probability of Subsystem X i is obtained.

[0063] Step S143: Based on the triangular fuzzy function theory, quantify the triangular fuzzy probability of the subsystem to obtain the damage probability of the corresponding subsystem.

[0064] Here, the damage probability of the subsystem can be understood as the precise probability corresponding to the triangular fuzzy probability of the subsystem.

[0065] In some embodiments, quantify the triangular fuzzy probability of each subsystem in the target system; obtain the triangular fuzzy probability of the subsystem i through Formula (4).

[0066]

[0067] Wherein, is the left fuzzy region, is the center of the fuzzy set, is the right fuzzy region, is the triangular fuzzy probability corresponding to the 1st to jth probability levels in the subsystem i, is the triangular fuzzy probability of the subsystem i.

[0068] Through Formula (5), quantify the triangular fuzzy probability of the subsystem i obtained by Formula (4) to obtain the damage probability of the corresponding subsystem i, wherein P i is the damage probability of the subsystem i, is the left fuzzy region in the triangular fuzzy probability, is the center of the fuzzy set in the triangular fuzzy probability, is the right fuzzy region in the triangular fuzzy probability.

[0069]

[0070] In the embodiments of the present application, calculating the failure probability of each subsystem X i specifically is that the triangular fuzzy probabilities of the failure probabilities of Subsystem X4 of Elevator A by Experts 1 to 4 are Obtain the triangular fuzzy probability of the failure probability of Subsystem X4 in Elevator A through the "arithmetic average method", that is, calculate the triangular fuzzy probability of the failure probability of Subsystem X4 in Elevator A according to Formula (4), and obtain Wherein, is the left fuzzy region, is the center of the fuzzy set, is the right fuzzy area; then use the "mean area method" to convert the triangular fuzzy probability of the failure probability of subsystem X4 of elevator A into a failure probability, that is, calculate the failure probability of subsystem X4 according to formula (5), and obtain where P4 is the failure probability of subsystem X4 in elevator A; calculate according to this method to obtain the failure probability of each subsystem X of elevator A as shown in Table 5 i of the failure probability.

[0071] Table 5 Failure Probability of Subsystems of Elevator A

[0072] Subsystem <![CDATA[Failure probability / h -1 > Subsystem <![CDATA[Failure probability / h -1 > <![CDATA[X0]]> <![CDATA[1.311×10 -4 > <![CDATA[X4]]> <![CDATA[1.1×10 -3 > <![CDATA[X1]]> <![CDATA[2.9431×10 -5 > <![CDATA[X5]]> <![CDATA[2.408×10 -5 > <![CDATA[X2]]> <![CDATA[3.5852×10 -4 > <![CDATA[X6]]> <![CDATA[7.7055×10 -6 > <![CDATA[X3]]> <![CDATA[5.7078×10 -4 > <![CDATA[X7]]> <![CDATA[4.4057×10 -4 >

[0073] Calculate the repair probability of each subsystem X i specifically, the triangular fuzzy probabilities of the repair probabilities of subsystem X0 of elevator A by experts 1 to 4 are Obtain the triangular fuzzy probability of the repair probability of subsystem X0 in elevator A through the "arithmetic mean method", that is, calculate the triangular fuzzy probability of the repair probability of subsystem X0 in elevator A according to formula (4), and obtain where is the left fuzzy area,[[]] is the center of the fuzzy set,[[]] is the right fuzzy area; then use the "mean area method" to convert the triangular fuzzy probability of the repair probability of subsystem X0 of elevator A into a repair probability, that is, calculate the repair probability of subsystem X0 according to formula (5), and obtain where P0 is the repair probability of subsystem X0 in elevator A, calculate according to this method to obtain the repair probability of each subsystem X of elevator A as shown in Table 6 i of the repair probability.

[0074] Table 6 Repair Probability of Subsystems of Elevator A

[0075] Subsystem <![CDATA[Failure probability / h -1 > Subsystem <![CDATA[Failure probability / h -1 > <![CDATA[X0]]> 0.0287 <![CDATA[X4]]> 0.0738 <![CDATA[X1]]> 0.0344 <![CDATA[X5]]> 0.0763 <![CDATA[X2]]> 0.0550 <![CDATA[X6]]> 0.0925 <![CDATA[X3]]> 0.0513 <![CDATA[X7]]> 0.0488

[0076] In some embodiments, calculating the triangular fuzzy probability of each subsystem can also be calculated by programming in MATLAB software in combination with formula (1), formula (2), formula (3) and formula (4). For example, taking the calculation of the triangular fuzzy probability corresponding to the repair probability of subsystem X0 of elevator A as an example, according to each subsystem X of elevator A iThe time consumed for one repair and the triangular fuzzy set of each subsystem of Elevator A are used to calculate the triangular fuzzy probability of each subsystem of Elevator A. Referring to Table 2, it can be seen that the scoring results of Experts 1, 2, 3, and 4 for X0 are 5, 7, 4, and 6 respectively. MATLAB software programming is carried out as follows: According to the triangular fuzzy sets in Table 4, let: A1 = [0, 0, 0.1], A2 = [0, 0.1, 0.3], A3 = [0.1, 0.3, 0.5], A4 = [0.3, 0.5, 0.7], A5 = [0.5, 0.7, 0.9], A6 = [0.7, 0.9, 1], A7 = [0.9, 1, 1]; According to the time consumed for one repair in Table 4, let: B1 = 1 / 0.5, B2 = 1 / 1, B3 = 1 / 5, B4 = 1 / 10, B5 = 1 / 20, B6 = 1 / 50, B7 = 1 / 80 according to formula (3); Taking B1 as an example, 1 / 0.5 means that it takes 0.5 h for one repair.

[0077] Calculate the triangular fuzzy probability of X0 according to formula (1) and formula (4). The triangular fuzzy probability of X0 is Wherein, is the triangular fuzzy probability of X0.

[0078] Step S144: Based on the damage probability of the subsystem, determine the damage probability of the corresponding intermediate system according to the reliability series system formula.

[0079] In some embodiments, the damage probability includes the repair probability and the failure probability. Step S144, the determining the damage probability of the corresponding intermediate system based on the damage probability of the subsystem according to the reliability series system formula includes: when the damage probability of the subsystem is the failure probability, determining the failure probability of the corresponding intermediate system through formula (6);

[0080] λ i = λ1 + … + λ n Formula (6).

[0081] When the damage probability of the subsystem is the repair probability, determining the repair probability of the corresponding intermediate system through formula (7);

[0082]

[0083] Wherein, λ and μ are the failure probability and the repair probability respectively.

[0084] In the embodiments of the present application, the failure probability λ 11 of the car part F is calculated through formula (6), and λ 11 is obtained, and λ 11= λ0 + λ1, where λ0 and λ1 are the failure probabilities of the car system and the safety protection system respectively; the failure probabilities of the landing part F 12 , the machine room part F 21 , the hoistway and pit part F 22 are λ 12 , λ 21 , λ 22 respectively.

[0085] Similarly, the repair probability μ 11 of the car part F 11 is calculated through formula (7), and it is obtained that where λ0 and λ1 are the failure probabilities of the car system and the safety protection system respectively, and μ0 and μ1 are the repair probabilities of the car system and the safety protection system respectively; the repair probabilities of the landing part F 12 , the machine room part F 21 , the hoistway and pit part F 22 are μ 12 , μ 21 , μ 22 respectively.

[0086] Step S150, based on the repair and damage probability of each of the intermediate systems, determine the repair and damage function corresponding to the intermediate system.

[0087] In some embodiments, the repair and damage function includes a reliability function and a maintainability function. The determining the repair and damage function corresponding to the intermediate system based on the repair and damage probability of each of the intermediate systems includes: when the repair and damage probability of the intermediate system is the failure probability λ, determining the reliability function of the intermediate system through formula (8);

[0088]

[0089] when the repair and damage probability of the intermediate system is the repair probability μ, determining the maintainability function of the intermediate system through formula (9);

[0090]

[0091] where t represents time.

[0092] In the embodiments of the present application, the reliability function R 11 of the car part F 11 (t) is calculated through formula (8), and it is obtained that where λ 11 is the failure probability of the car part F 11 ; the failure probabilities of the landing part F 12 , the machine room part F 21, Hoistway and Pit Part F 22 The reliability functions are respectively R 12 (t), R 21 (t), R 22 (t); where t represents time.

[0093] Similarly, the maintainability function M 11 of the car part F 11 (t) is calculated through formula (9), and it is obtained that where μ 11 is the maintenance probability of the car part F 11 ; calculating according to this method, the maintainability functions of the landing part F 12 , the machine room part F 21 , and the hoistway and pit part F 22 are respectively M 12 (t), M 21 (t), M 22 (t); where t represents time.

[0094] Step S160, determine the reliability of the target system based on the damage functions of each of the intermediate systems.

[0095] Using MATLAB software to simulate and analyze the reliability functions and maintenance functions of the car part F 11 , the landing part F 12 , the machine room part F 21 , and the hoistway and pit part F 22 , analyze the influence of the reliability functions and maintenance functions of each part of the elevator on the elevator system, optimize the elevator system, and propose corresponding improvement measures.

[0096] In some possible embodiments, the defect attribute words include: discovering defects and / or repairing defects; step S110 further includes: step S111 and step S112.

[0097] Step S111, obtain the management data of different systems within a certain period of time.

[0098] In the embodiment of the present application, firstly, the relevant data of the elevator on the elevator defect management platform in H City within one year is obtained, and the obtained data is preliminarily screened and counted. Because the data in the elevator defect management platform only roughly describes the defects of the elevator, most of them are not very standardized, such as: the elevator air outlet is cold, the elevator door gap is blocked, etc., and the defect handling personnel have inconsistent descriptions of the defect type, components, causes, conceptual terms, etc., all of which lead to poor standardization and usability of the collected data. Therefore, it is necessary to remove some irrelevant data, screen and optimize some situations where the corresponding term descriptions are not standardized, data is missing, etc., in order to improve the accuracy of elevator reliability analysis. The preliminary screening and statistical principles of fault data in the elevator defect management platform are as follows:

[0099] (1) If the elevator equipment fails due to human error, it should not be recorded as an equipment defect. For example, if an elevator door is hit by a human, causing a door defect.

[0100] (2) After the elevator equipment has been repaired by maintenance personnel, if the same fault occurs again within one day after the repair, it should be recorded as one fault.

[0101] (3) If the elevator equipment has multiple sudden defects and failures on the same day and the elevator is restarted to resume work, after investigation by relevant personnel, if the cause of the failure is the same, it will be recorded as one failure; if the cause is different, it will be recorded as multiple failures.

[0102] (4) Operational failures of the elevator caused by external interference should not be counted as the number of failures.

[0103] Step S112 , filtering and counting the management data according to the found defects and repaired defects respectively, to obtain a statistical data set, wherein the statistical data set includes statistical data corresponding to the found defects and / or statistical data corresponding to the repaired defects.

[0104] The defect discovery includes at least one of defect activities, defect triggering events and defect impacts; and the defect repair includes at least one of defect types, defect qualifiers, defect sources, defect objects and defect history.

[0105] In the embodiment of the present application, elevator defect attribute words are defined as two categories: defect discovery attribute and defect repair attribute according to the orthogonal defect classification method. Figure 3 The figure below shows the elevator orthogonal defect classification process. Detected defects include DA, ECD, and EOF, while repaired defects include TOD, DQ, SOD, DO, and HOD. Defect detection provides feedback for the elevator verification process, while repair provides guidance for optimized elevator design. Together, repair and detection constitute the elevator defect management system.

[0106] In some possible embodiments, when the target system includes more than two functional layer systems, each of the functional layer systems includes at least one intermediate system, and each of the intermediate systems includes at least one subsystem; step S150 further includes steps S151 to S154.

[0107] Step S151, determining the repair probability of the corresponding functional layer system based on the repair probability of at least one intermediate system included in each functional layer system.

[0108] In the embodiments of the present application, the failure probability λ1 of the elevator body F1 is calculated by formula (6), and it is obtained that λ1 = λ 11 +λ 12 , where λ 11 and λ 12 are the failure probabilities of the car part F 11 and the landing part F 12 respectively; similarly, the failure probability λ2 of the elevator exterior F2 is calculated according to this method.

[0109] λ i = λ1 + … + λ n Formula (6);

[0110] The repair probability μ1 of the elevator body F1 is calculated by formula (7), and it is obtained that where λ 11 and λ 12 are the failure probabilities of the car part F 11 and the landing part F 12 respectively, μ 11 and μ 12 are the repair probabilities of the car part F 11 and the landing part F 12 respectively; similarly, the repair probability μ2 of the elevator exterior F2 is calculated according to this method.

[0111]

[0112] Where λ and μ are the failure probability and the repair probability respectively.

[0113] Step S152, based on the repair probability of each functional layer system, determining the functional layer system corresponding to the steady-state availability function with the largest slope from the more than two functional layer systems.

[0114] In some embodiments, in step S152, determining the functional layer system corresponding to the steady-state availability function with the maximum slope from the two or more functional layer systems based on the repair probability of each functional layer system includes: step S1521, based on Markov theory, determining the function of the steady-state availability corresponding to each repair probability according to the repair probability of each functional layer system; step S1522, determining the functional layer system corresponding to the steady-state availability function with the maximum slope based on the function of the steady-state availability corresponding to each repair probability.

[0115] In the embodiments of the present application, Figure 4 The shown elevator operation structure diagram includes a machine room 41, a hoistway 42, a car 43, a landing 44, and a pit 45. The machine room 41 includes a speed governor 411, a motor and a power supply system 412, and a traction machine 413. The landing 44 includes a landing door 441. The car 43 includes electrical switches 431 such as end station protection device limit and position limit, and a car 432. The pit 45 includes car guide rails 451, a trailing cable 452, a buffer 453, and a counterweight device 454.

[0116] The Figure 4 shown elevator operation structure diagram is classified and simplified to obtain Figure 5 the reliability block diagram of the shown elevator system, as Figure 5 shown. The elevator system includes a car part F 11 , a landing part F 12 , a machine room part F 21 , and a hoistway and pit part F 22 . Among them, the car part F 11 includes a car system X0 and a safety protection system X1. The landing part F 12 includes a door system X2. The machine room part F 21 includes a traction system X3, an electric drive system X4, and an electrical control system X5. The hoistway and pit part F 22 includes a guiding system X6 and a weight balance system X7. When any one of the subsystems in the elevator system fails, it will cause the failure of the entire system. Therefore, these components can be regarded as a series system.

[0117] Based on the above analysis, a Markov state transition diagram of the elevator system is made through Markov theory, as Figure 6 shown. Define a stochastic process The stochastic process has a total of 4 different states, namely State 1: both the elevator body F1 and the elevator exterior F2 are in normal states; State 2: the elevator body F1 is in a normal state while the elevator exterior F2 is in a faulty state; State 3: the elevator body F1 is in a faulty state while the elevator exterior F2 is in a normal state; State 4: both the elevator body F1 and the elevator exterior F2 are in faulty states. λ1 is the failure probability of the elevator body F1, λ2 is the failure probability of the elevator exterior F2, μ1 is the repair probability of the elevator body F1, μ2 is the repair probability of the elevator exterior F2, and t represents time. Taking the transition from State 1 to State 2 as an example, when the elevator exterior F2 in State 1 fails to obtain State 2, the transition from State 1 to State 2 is λ2Δt; taking the transition from State 2 to State 1 as an example, when the fault of the elevator exterior F2 in State 2 is repaired to obtain State 1, the transition from State 1 to State 2 is μ2Δt. Figure 6 The other states are obtained in the same way and will not be elaborated here.

[0118] According to Figure 6 the formula (10) for the Markov state transition matrix Q of the A elevator system is obtained.

[0119]

[0120] Among them, λ1 and λ2 are the failure probabilities of the elevator body F1 and the elevator exterior F2 respectively; μ1 and μ2 are the repair probabilities of the elevator body F1 and the elevator exterior F2 respectively.

[0121] The transient reliability calculation formula of the elevator system is derived. Let P i (t) be the probability that the system is in state i (i = 1, 2, 3, 4) at time t, and P i (t) = {P1(t), P2(t), P3(t), P4(t)} be the state distribution vector of the system at time t, and P i ’(t) be the derivative of P i (t). The vector P i ’(t) = {P1’(t), P2’(t), P3’(t), P4’(t)} is the matrix composed of P i ’(t). From the state equation P i (t)Q = P i ’(t) of the Markov process, formula (11) can be obtained. After performing Laplace transform on it, formula (12) is obtained. Among them, P i * (s) is the vector obtained after Laplace transform of P i (t), and s is the variable obtained after Laplace transform of t. Then, by performing inverse transform on formula (12), P1(t), P2(t), P3(t), and P4(t) (i.e., the probabilities of being in states 1, 2, 3, and 4 at time t) can be obtained.

[0122]

[0123]

[0124] Since the system can only work properly when it is in state 1, through derivation, the transient availability of Elevator A system is formula (13);

[0125]

[0126] Among them, L -1 is the inverse Laplace transform, and P1(t) is the transient availability when the system is in state 1.

[0127] Through formula (12), P1(t), P2(t), P3(t) and P4(t) can be obtained. At this time, according to the probabilities P1(t), P2(t), P3(t) and P4(t) of each state occurring, the probabilities of the elevator body F1 and the elevator exterior F2 being normal or faulty can be judged macroscopically. When t approaches infinity, the transient availability of each state at this time becomes the steady-state availability, which is represented by P i (i = 1, 2, 3, 4). Let P = {P1, P2, P3, P4} be the distribution vector of the steady-state probabilities. According to the steady-state equation P·Q = 0 of the Markov process, the steady-state probability equations of the elevator system are formula (14), and the steady-state probabilities of each state of the system can be obtained according to formula (14).

[0128]

[0129] And through derivation, formula (15) is obtained. Through formula (15), the steady-state availability of Elevator A system is analyzed. For example, taking λ1 as a variable and substituting the values of λ2, μ1 and μ2, the function of the failure rate λ1 of the elevator body F1 on the steady-state availability of the elevator system is obtained; taking λ2 as a variable and substituting the values of λ1, μ1 and μ2, the function of the failure rate λ2 of the elevator exterior F2 on the steady-state availability of the elevator system is obtained; and so on, the function of the repair rate μ1 of the elevator body F1 on the steady-state availability of the elevator system and the function of the repair rate μ2 of the elevator exterior F2 on the steady-state availability of the elevator system are obtained.

[0130]

[0131] Step S153, determine the functional layer system corresponding to the steady-state availability function with the largest slope as the target functional layer system.

[0132] In the embodiment of the present application, by comparing the slopes of the four functions obtained in step S152, the functional layer system corresponding to the function with the largest slope is determined as the target functional layer system.

[0133] If λ1 is taken as a variable and the slope of the function of the failure rate λ1 of the elevator body F1 with respect to the steady-state availability of the elevator system is the largest, then the elevator body is determined as the target functional layer system.

[0134] Step S154: Determine the repair and damage function of the corresponding intermediate system through the repair and damage probabilities of each intermediate system corresponding to the target functional layer system.

[0135] In the embodiment of the present application, if the slope of the function of the failure rate λ1 of the elevator body F1 with respect to the steady-state availability of the elevator system is the largest or the slope of the function of the repair rate μ1 of the elevator body F1 with respect to the steady-state availability of the elevator system is the largest, then the target functional layer system is the elevator body F1, and the intermediate systems corresponding to the elevator body F1 are the car part F 11 and the landing part F 12 ; Substitute the failure probabilities and repair probabilities of the car part F 11 and the landing part F 12 into and respectively to determine the reliability functions and maintainability functions of the car part F 11 and the landing part F 12 , which are R 11 (t), R 12 (t), M 11 (t), M 12 (t) respectively.

[0136] If the slope of the function of the failure rate λ2 of the elevator exterior F2 with respect to the steady-state availability of the elevator system is the largest or the slope of the function of the repair rate μ2 of the elevator exterior F2 with respect to the steady-state availability of the elevator system is the largest, then the target functional layer system is the elevator exterior F2, and the intermediate systems corresponding to the elevator exterior F2 are the machine room part F 21 and the hoistway and pit part F 22 ; Substitute the failure probabilities and repair probabilities of the machine room part F 21 and the hoistway and pit part F 22 into and respectively to determine the reliability functions and maintainability functions of the machine room part F 21 and the hoistway and pit part F 22 , which are R 21 (t), R 22 (t), M 21 (t), M 22 (t) respectively.

[0137] In some possible embodiments, step S141 further includes: defining a first relationship table. Using the Delphi method to define linguistic variables and determining the corresponding relationship between the linguistic variables and the triangular fuzzy sets; dividing the repair parameters into probability levels according to the linguistic variables to obtain the corresponding relationship between the linguistic variables, the repair parameters, and the probability levels; and determining the corresponding relationship between the probability levels, the repair parameters, the linguistic variables, and the triangular fuzzy sets as the first relationship table.

[0138] In the embodiments of the present application, for example, when defining the elevator system failure probability level table, the Delphi method is used to define the linguistic variables of the number of failures of the elevator system within one year, which are 10 linguistic variables from very rare to inevitable. A triangular fuzzy set is introduced, and the corresponding relationship between each linguistic variable and the triangular fuzzy set is, for example, the triangular fuzzy set corresponding to "very rare" is (0, 0, 0.1); the number of failures within one year is divided according to the linguistic variables into 10 levels. For example, probability level 1 is that the number of failures within one year ≤ 0.005, and its corresponding linguistic variable is "very rare"; the corresponding relationship between level 1, the number of failures within one year ≤ 0.005, "very rare", and the triangular fuzzy set (0, 0, 0.1) is obtained, and so on, to obtain the elevator system failure probability level table shown in Table 3. Table 3 shows the corresponding relationship between each failure probability level, the number of failures within one year, and the triangular fuzzy set.

[0139] For example, when defining the elevator system repair probability level table, the Delphi method is used to define the linguistic variables of the time consumed for one repair of the elevator system, which are 7 linguistic variables from very easy to very difficult. A triangular fuzzy set is introduced, and the corresponding relationship between each linguistic variable and the triangular fuzzy set is, for example, the triangular fuzzy set corresponding to "very easy" is (0, 0, 0.1); the time consumed for one repair is divided according to the linguistic variables into 7 levels. For example, probability level 1 is that the time consumed for one repair is 0.5h, and its corresponding linguistic variable is "very easy". The corresponding relationship between level 1, the time consumed for one repair of 0.5h, "very easy", and the triangular fuzzy set (0, 0, 0.1) is obtained, and so on, to obtain the elevator system repair probability level table shown in Table 4. Table 4 shows the corresponding relationship between each repair probability level, the time consumed for one repair, and the triangular fuzzy set.

[0140] In some possible embodiments, the method further includes: defining the defect attribute words of the target system, and defining the defect attribute words of the target system into two categories: discovered defect attributes and repaired defect attributes. Among them, discovered defects include: defect activities, defect triggering events, and defect impacts, and repaired defects include defect types, defect qualifiers, defect sources, defect objects, and defect histories.

[0141] In the embodiments of the present application, elevator defect attribute words are defined into two major categories: discovered defect attributes and repaired defect attributes. For example, Figure 3 As shown in the figure, it is the process diagram of elevator orthogonal defect classification. Among them, discovered defects include: defect activities, defect triggering events, and defect impacts. Repaired defects include defect types, defect qualifiers, defect sources, defect objects, and defect histories. The explanations of each defect attribute word are as follows:

[0142] Defect activities: How the elevator defect is discovered and how the activities of the elevator are manifested when the defect appears. For example: the elevator makes a noise, the button does not respond, the elevator suddenly stops, the elevator speed is fast / slow, the elevator shakes, etc.

[0143] Defect triggering events: It refers to the consequences that will occur after the elevator defect is triggered. For example, it will cause: overshoot accident, undershoot accident, shearing accident, entrapment accident, etc.

[0144] Defect impacts: It refers to the impacts that the elevator defect may cause, such as casualties, property losses, and environmental damage. The defect is mainly measured from three aspects: severity, possibility, and detectability.

[0145] Defect types: The main defect types of the elevator are mechanical defects, electrical defects, and other defects.

[0146] Defect sources: It refers to the origin of the elevator defect, which mainly consists of mechanical lubrication, mechanical fatigue, mechanical wear, logic control system, safety circuit system, door lock circuit system, and other sources.

[0147] Defect objects: It refers to the description of the entity to be repaired, which mainly includes eight major parts: traction system, guiding system, car system, door system, weight balance system, electric drive system, electrical control system, and safety protection system.

[0148] Defect qualifiers: It refers to additional supplementary descriptions of elevator defect attributes. For example: fast / slow speed, high / low temperature, obvious / subtle defect.

[0149] Defect histories: It refers to the history of elevator defect repair, which can be newly discovered in previous project designs, generated during use, and newly introduced during the repaired process.

[0150] In some possible embodiments, the triangular fuzzy function theory includes the decomposition theorem and the extension principle of the fuzzy function. The decomposition theorem is used to connect fuzzy mathematics and mathematics, and the extension principle extends ordinary mathematical methods to fuzzy mathematics.

[0151] In some possible embodiments, the method further includes: The method of constructing the triangular fuzzy function models of different systems through the triangular fuzzy sets of different systems is as follows:

[0152] The triangular fuzzy set is as follows: where is the center of the fuzzy set, is the left fuzzy region, is the right fuzzy region, is the membership degree; the triangular fuzzy function models of different systems are determined by formula (16).

[0153]

[0154] In the embodiment of the present application, the Delphi method is used to define the language variable of the number of faults in the elevator system within 1 year, and the fault probability level is divided into 10 levels according to the language variable from very rare to inevitable. In order to associate the expert's judgment result on the event occurrence probability with the fuzzy set, a triangular fuzzy set is introduced. According to formula (16), the triangular membership function schematic diagram of the elevator system fault probability level as shown in Figure 7a is obtained, Figure 7a which shows the value of the triangular fuzzy set corresponding to the fault probability level. For example, using the Delphi method, the language variable corresponding to the number of faults within 1 year being 0.01 is rare, and the probability level corresponding to rare is defined as 2. According to Figure 7a it is obtained that the triangular fuzzy set corresponding to the probability level 2 is (0, 0.1, 0.2); and so on, the corresponding relationship between the probability level, the number of faults within 1 year, the language variable, and the triangular fuzzy set as shown in Table 3 is obtained.

[0155] The Delphi method is used to define the language variable of the time consumed for one repair of the elevator system, and the repair probability level is divided into 7 levels according to the language variable from very easy to very difficult. In order to associate the expert's judgment result on the event occurrence probability with the fuzzy set, a triangular fuzzy set is introduced. According to formula (16), the triangular membership function schematic diagram of the elevator system repair probability level as shown in Figure 7b is obtained, Figure 7b which shows the value of the triangular fuzzy set of the repair probability level. For example, using the Delphi method, the language variable corresponding to the time consumed for one repair being 1 is very easy, and the probability level corresponding to very easy is 1. According to Figure 7b it is obtained that the triangular fuzzy set corresponding to the probability level 1 is (0, 0, 0.1); and so on, the corresponding relationship between the probability level, the time consumed for one repair, the language variable, and the triangular fuzzy set as shown in Table 4 is obtained.

[0156] The above method will be described below in conjunction with a specific embodiment. However, it should be noted that this specific embodiment is only for better explaining the present application and does not constitute an improper limitation of the present application. The data statistically collected by the elevator defect management platform in City H is selected as a case, and the elevator in a certain community in City H is denoted as Elevator A. The method includes:

[0157] Step S210, defining elevator defect attribute words.

[0158] According to the orthogonal defect classification method, the elevator defect attribute words are defined into two categories: discovered defect attributes and repaired defect attributes. As Figure 3 shown, it is the process diagram of elevator orthogonal defect classification. Among them, discovered defects include: defect activities, triggering events of defects, and impacts of defects; repaired defects include types of defects, qualifiers of defects, sources of defects, objects of defects, and histories of defects.

[0159] Step S220, dividing the elevator system by the Delphi method.

[0160] As Figure 8 shown, the elevator system F0 of Elevator A is divided into the elevator body F1 and the elevator exterior F2 by the Delphi method.

[0161] The elevator body F1 includes: the car part F 11 and the landing part F 12 ; among them, the car part F 11 includes: the car system X0 and the safety protection system X1; the landing part F 12 includes: the door system X2.

[0162] The elevator exterior F2 includes: the machine room part F 21 and the hoistway and pit part F 22 . Among them, the machine room part F 21 includes: the traction system X3, the electric drive system X4, and the electrical control system X5. The hoistway and pit part F 22 includes: the guiding system X6 and the weight balance system X7.

[0163] Step S230, using the orthogonal defect classification method to screen, statistically analyze, and classify the relevant data of the elevator defect management platform.

[0164] The relevant data of the elevators in City H within one year obtained from the elevator defect management platform are obtained. First, the data in the elevator platform are screened to remove some unimportant data, and some situations such as non-standard descriptions of corresponding terms and data missing are screened and optimized to improve the accuracy of elevator reliability analysis.

[0165] Then, describe, classify, and count the filtered results according to the eight orthogonal defect attributes of elevator defects, namely defect activities, defect triggering events, defect impacts, defect types, defect qualifiers, defect sources, defect objects, and defect history. Among the statistical data of the eight feasible orthogonal defect attributes, examples are given based on the defect object and defect type, such as Figure 2a shows the statistical chart of the defect objects of elevators in City H within one year, which counts the number of defects occurring in different defect objects within one year; Figure 2b shows the statistical chart of the defect types of elevators in City H within one year, which counts the proportion of different defect types of elevators among all elevator defect types.

[0166] Step S240: Construct a triangular fuzzy function model for the failure probability level and the repair probability level.

[0167] The method for constructing the triangular fuzzy function model of the elevator system is as follows: First, assume that the fuzzy set of the possibility of a certain event f i occurring a failure is: where is the center of the fuzzy set, is the left fuzzy region, is the right fuzzy region, is the membership degree. The triangular fuzzy function model of the elevator system is determined by formula (16).

[0168]

[0169] Step S250: Define the linguistic variables and fuzzy sets for the failure probability level and the repair probability level.

[0170] Define the linguistic variables and fuzzy sets for the failure probability level of the elevator system, and the linguistic variables and fuzzy sets for the repair probability level of the elevator system. Define the linguistic variable for the number of failures of the elevator system within 1 year, and divide the failure probability level into 10 levels from very rare to inevitable according to the linguistic variable. Then, according to Step S240, make a triangular membership function graph of the failure probability level of the elevator system as shown in Figure 7a which shows the value range of the triangular fuzzy set corresponding to the failure probability level, and obtains the corresponding relationship between the probability level, the number of failures within 1 year, the linguistic variable, and the triangular fuzzy set as shown in Table 3; Use the Delphi method to define the linguistic variable for the time consumed for one repair of the elevator system, and divide the repair probability level into 7 levels from very easy to very difficult according to the linguistic variable. Then, according to Step S240, make a triangular membership function graph of the repair probability level of the elevator system as shown in Figure 7a which shows the value range of the triangular fuzzy set corresponding to the repair probability level, and obtains the corresponding relationship between the probability level, the time consumed for one repair, the linguistic variable, and the triangular fuzzy set as shown in Table 4; Make a triangular membership function graph of the repair probability level of the elevator system as shown in Figure 7b which shows the value range of the triangular fuzzy set corresponding to the repair probability level, and obtains the corresponding relationship between the probability level, the time consumed for one repair, the linguistic variable, and the triangular fuzzy set as shown in Table 5; Figure 7bThe value range of the triangular fuzzy set corresponding to the maintenance probability level is shown, and the corresponding relationship between the probability level, the time consumed for one maintenance, the linguistic variable, and the triangular fuzzy set as shown in Table 4 is obtained.

[0171] Step S260: Based on the statistical data of the orthogonal defect attribute words, use the Delphi method to determine the failure probability level and the maintenance probability level of each subsystem.

[0172] Since the data samples obtained by the orthogonal defect classification method are very limited, there are also problems such as missing data records, and the data obtained by the orthogonal defect classification method does not exactly correspond to the failure probability and maintenance probability of the elevator. Therefore, based on the eight elevator orthogonal defect statistical data obtained, experts pre-evaluate each subsystem X in Elevator A i and score the failure probability level of each subsystem X in Elevator A based on 10 failure probability levels i to obtain the failure probability level evaluation table of each subsystem in Elevator A as shown in Table 1; score each subsystem of the elevator based on 7 maintenance probability levels to obtain the maintenance probability level evaluation table of each subsystem in Elevator A as shown in Table 2.

[0173] Step S270: Based on the fuzzy function theory, determine the failure probability and the maintenance probability of each subsystem through the failure probability level and the maintenance probability of each subsystem.

[0174] One probability level corresponds to one λ m and the failure probability level or the maintenance probability level that the j-th expert gives to subsystem X i occurring within one year can be expressed by the corresponding fuzzy probability using formula (1). λ m is determined by formula (2) or formula (3).

[0175]

[0176] where j is the j-th probability level of the subsystem X i , is the j-th triangular fuzzy probability of the subsystem X i , is the triangular fuzzy set corresponding to the j-th probability level of the subsystem X i .

[0177]

[0178]

[0179] According to Table 1, the failure probability level that expert 4 gives to subsystem X4 of Elevator A is 8. Looking up Table 3, the triangular fuzzy set corresponding to the failure probability level 8 The number of failures in one year is 10. According to formula (2), we get According to formula (1), calculate the triangular fuzzy probability of the failure probability given by expert 4 to subsystem X4 Calculated in this way, the triangular fuzzy probabilities of the failure probabilities of subsystem X4 of elevator A given by expert 1, expert 2, and expert 3 are respectively Similarly, the triangular fuzzy probability of each failure probability of subsystem X i is obtained

[0180] Similarly, according to Table 2, the maintenance probability level given by expert 4 to subsystem X0 of elevator A is 6. Look up the triangular fuzzy set corresponding to maintenance probability level 6 in Table 4 The time consumed for one maintenance is 50. According to formula (3), we get According to formula (1), calculate the triangular fuzzy probability of the maintenance probability given by expert 4 to subsystem X0 Calculated in this way, the triangular fuzzy probabilities of the maintenance probabilities of subsystem X0 of elevator A given by expert 1, expert 2, and expert 3 are respectively Similarly, the triangular fuzzy probability of each maintenance probability of subsystem X i is obtained

[0181] Using the "arithmetic average method", the triangular fuzzy probability can be quantified, specifically as formula (4).

[0182]

[0183] where is the left fuzzy region is the center of the fuzzy set is the right fuzzy region is the triangular fuzzy probability corresponding to the 1st to jth probability levels in subsystem i is the triangular fuzzy probability of subsystem i

[0184] Through formula (5), the triangular fuzzy probability of subsystem i obtained by formula (4) is quantitatively processed to obtain the repair and damage probability corresponding to subsystem i. Where P i is the repair and damage probability of subsystem i is the left fuzzy region in the triangular fuzzy probability is the center of the fuzzy set in the triangular fuzzy probability is the right fuzzy region in the triangular fuzzy probability

[0185]

[0186] Specific calculation is as follows: Calculate each subsystem X iThe specific failure probability is that the triangular fuzzy probabilities of the failure probability of subsystem X4 of Elevator A by Experts 1 to 4 are The triangular fuzzy probability of the failure probability of subsystem X4 in Elevator A is obtained by the "arithmetic average method", that is, the triangular fuzzy probability of the failure probability of subsystem X4 in Elevator A is calculated according to formula (4), and it is obtained that where is the left fuzzy region, is the center of the fuzzy set, is the right fuzzy region; then the triangular fuzzy probability of the failure probability of subsystem X4 of Elevator A is converted into the failure probability by the "mean area method", that is, the failure probability of subsystem X4 is calculated according to formula (5), and it is obtained that where P4 is the failure probability of subsystem X4 in Elevator A; according to this method, the failure probabilities of each subsystem X of Elevator A as shown in Table 5 are calculated i of the failure probability.

[0187] Calculate the repair probability of each subsystem X i The specific repair probability is that the triangular fuzzy probabilities of the repair probability of subsystem X0 of Elevator A by Experts 1 to 4 are The triangular fuzzy probability of the repair probability of subsystem X0 in Elevator A is obtained by the "arithmetic average method", that is, the triangular fuzzy probability of the repair probability of subsystem X0 in Elevator A is calculated according to formula (4), and it is obtained that where is the left fuzzy region, is the center of the fuzzy set, is the right fuzzy region; then the triangular fuzzy probability of the repair probability of subsystem X0 of Elevator A is converted into the repair probability by the "mean area method", that is, the repair probability of subsystem X0 is calculated according to formula (5), and it is obtained that where P0 is the repair probability of subsystem X0 in Elevator A, and according to this method, the repair probabilities of each subsystem X of Elevator A as shown in Table 6 are calculated i of the repair probability.

[0188] where P in is the repair and damage probability of the subsystem X i . Then the failure probabilities and repair probabilities of each subsystem X of the elevator can be obtained i of the failure probability and repair probability.

[0189] Step S280, determine the failure probabilities and repair probabilities of the target layer system and the intermediate system based on the failure probabilities and repair probabilities of each subsystem.

[0190] When the failure probabilities and repair probabilities of each subsystem X i are obtained, since the subsystems are independent of each other, such as Figure 5As shown in the elevator operation structure diagram, which constructs the elevator reliability block diagram, when any subsystem in the elevator system fails, it will cause the failure of the entire system. Therefore, these components can be regarded as a series system.

[0191] According to the reliability series formulas (6) and (7), calculate the repair probability and failure probability of the intermediate system and the target layer system.

[0192] λ i = λ1 + … + λ n Formula (6);

[0193]

[0194] Among them, λ and μ are the failure probability and repair probability respectively.

[0195] Calculate the failure probability λ 11 of the car part F 11 through formula (6), and obtain λ 11 = λ0 + λ1, where λ0 and λ1 are the failure probabilities of the car system and the safety protection system respectively; calculate the failure probabilities λ 12 of the landing part F 21 of the machine room part F 22 of the hoistway and pit part F 12 、λ 21 、λ 22 in the same way.

[0196] Similarly, taking the repair probability μ 11 of the car part F 11 determined by formula (7) as an example, obtain Among them, λ0 and λ1 are the failure probabilities of the car system and the safety protection system respectively, and μ0 and μ1 are the repair probabilities of the car system and the safety protection system respectively; calculate the repair probabilities μ 12 of the landing part F 21 of the machine room part F 22 of the hoistway and pit part F 12 、μ 21 、μ 22 in the same way.

[0197] Then, according to the reliability series formula, obtain the failure probability and repair rate of calculating the elevator body F1 and the elevator exterior F2. Calculate the failure probability λ1 of the elevator body F1 through formula (6), and obtain λ1 = λ 11 + λ 12 , where λ 11 and λ 12 are the failure probabilities of the car part and the landing part respectively; calculate the failure probability λ2 of the elevator exterior F2 in the same way.

[0198] Calculate the maintenance probability μ1 of the elevator body F1 through formula (7), and obtain where μ 11 and μ 12 are the maintenance probabilities of the car part and the landing part respectively; calculate the maintenance probability μ2 of the elevator exterior F2 according to this method.

[0199] Step S290: Use Markov theory to establish the Markov state transition diagram and Markov transition matrix of the elevator system, and derive the mathematical expressions of its transient and steady-state related parameters.

[0200] According to Figure 4 the shown elevator operation structure diagram, divide the elevator system structure to obtain Figure 5 the shown reliability block diagram of the elevator system.

[0201] Define a stochastic process This stochastic process has a total of 4 different states, namely State 1: Both the elevator body and the elevator exterior are in normal state; State 2: The elevator body is in normal state and the elevator exterior is in fault state; State 3: The elevator body is in fault state and the elevator exterior is in normal state; State 4: Both the elevator body and the exterior are in fault state.

[0202] Based on the above analysis, make the Markov state transition diagram of the elevator system through Markov theory, as shown in Figure 6 shown, and obtain formula (10) the Markov state transition matrix Q of the elevator system.

[0203]

[0204] where λ1 and λ2 are the failure probabilities of the elevator body F1 and the elevator exterior F2 respectively; μ1 and μ2 are the maintenance probabilities of the elevator body F1 and the elevator exterior F2 respectively.

[0205] Derive the transient reliability calculation formula of the elevator system. Let P i (t) be the probability that the system is in state i (i = 1, 2, 3, 4) at time t, and P i (t) = {P1(t), P2(t), P3(t), P4(t)} be the state distribution vector of the system at time t, and P i ’(t) be the derivative of P i (t), and the vector P i ’(t) = {P1’(t), P2’(t), P3’(t), P4’(t)} be the matrix composed of P i ’(t). From the state equation P i (t)Q = P i’(t) gives formula (11), and its Laplace transform yields formula (12), where P i * (s) is the vector obtained by the Laplace transform of P i (t), and s is the variable obtained by the Laplace transform of t. Then, performing the inverse transform on formula (12) allows us to find P1(t), P2(t), P3(t), and P4(t) (i.e., the probabilities of being in states 1, 2, 3, and 4 at time t).

[0206]

[0207]

[0208] Since the system can only operate normally when it is in state 1, through derivation, the transient availability formula (13) of the A elevator system is obtained:

[0209]

[0210] where, L -1 is the inverse Laplace transform, and P1(t) is the transient availability when the system is in state 1.

[0211] From formula (12), P1(t), P2(t), P3(t), and P4(t) can be obtained. At this time, based on the probabilities P1(t), P2(t), P3(t), and P4(t) of each state occurring, the probabilities of the elevator body F1 and the elevator exterior F2 being normal or faulty can be macroscopically judged. When t approaches infinity, the transient availability of each state at this time becomes the steady-state availability, denoted by P i (i = 1, 2, 3, 4). Let P = {P1, P2, P3, P4} be the distribution vector of the steady-state probabilities. According to the steady-state equation P·Q = 0 of the Markov process, the steady-state probability equations of the elevator system are formula (14), and the steady-state probabilities of each state of the system can be obtained according to formula (14).

[0212]

[0213] And through derivation, formula (15) is obtained. By analyzing the steady-state availability of the A elevator system using formula (15), for example, taking λ1 as the variable and substituting the values of λ2, μ1, and μ2, the function of the failure rate λ1 of the elevator body F1 on the steady-state availability of the elevator system is obtained; taking λ2 as the variable and substituting the values of λ1, μ1, and μ2, the function of the failure rate λ2 of the elevator exterior F2 on the steady-state availability of the elevator system is obtained; and so on to obtain the function of the repair rate μ1 of the elevator body F1 on the steady-state availability of the elevator system and the function of the repair rate μ2 of the elevator exterior F2 on the steady-state availability of the elevator system.

[0214]

[0215] Step S300: Analyze the impact of the failure rate and repair rate of each subsystem of the elevator on the elevator system, and optimize them.

[0216] Compare the slopes of the four functions obtained in step S290, and determine the target functional layer system as the functional layer system corresponding to the function with the largest slope.

[0217] If the slope of the function of the failure rate λ1 of the elevator body F1 with respect to the steady-state availability of the elevator system is the largest or the slope of the function of the repair rate μ1 of the elevator body F1 with respect to the steady-state availability of the elevator system is the largest, then the target functional layer system is the elevator body F1, and the intermediate system corresponding to the elevator body F1 is the car part F 11 and the landing part F 12 ; Substitute the failure probabilities of the car part F 11 and the landing part F 12 into formula (8), and substitute the repair probabilities into formula (9) to determine the reliability functions and maintainability functions of the car part F 11 and the landing part F 12 , which are R 11 (t), R 12 (t), M 11 (t), M 12 (t).

[0218]

[0219]

[0220] where t represents time.

[0221] If the slope of the function of the failure rate λ2 of the elevator exterior F2 with respect to the steady-state availability of the elevator system is the largest or the slope of the function of the repair rate μ2 of the elevator exterior F2 with respect to the steady-state availability of the elevator system is the largest, then the target functional layer system is the elevator exterior F2, and the intermediate system corresponding to the elevator exterior F2 is the machine room part F 21 and the hoistway and pit part F 22 ; Substitute the failure probabilities of the machine room part F 21 and the hoistway and pit part F 22 into formula (8), and substitute the repair probabilities into formula (9) to determine the reliability functions and maintainability functions of the machine room part F 21 and the hoistway and pit part F 22 , which are R 21 (t), R 22 (t), M 21 (t), M 22 (t).

[0222] Use MATLAB software to calculate the reliability and maintainability of the intermediate system corresponding to the target functional layer system of the elevator, simulate and analyze the influence of the reliability function and maintainability function of the intermediate system on the elevator system, determine which intermediate system has the greatest impact on the overall elevator, optimize it, and propose corresponding improvement measures. For example, if it is found that the car part has a greater impact on the elevator, the car part can be regularly inspected and maintained, or high-reliability car components can be replaced.

[0223] Through the above calculation method, the influence of the reliability function and maintainability function of each subsystem on the elevator system can also be analyzed and calculated as needed, which will not be elaborated here.

[0224] Based on the foregoing embodiments, the embodiments of the present application further provide a reliability evaluation device for a target system. The device includes each module included and each sub-module included in each module, which can be implemented by a processor in the target system; of course, it can also be implemented by specific logic circuits; during implementation, the processor can be a central processing unit (CPU), a micro processing unit (MPU), a digital signal processor (DSP), or a field programmable gate array (FPGA), etc.

[0225] Based on the foregoing embodiments, the embodiments of the present application further provide a reliability evaluation device for a target system, as Figure 9 shown. The device 90 includes:

[0226] A first acquisition module 91, configured to acquire a statistical data set, where each statistical data in the statistical data set is obtained by screening the management data of different systems according to the corresponding defect attribute words; the defect attribute words include: defect discovery and / or defect repair;

[0227] A first determination module 92, configured to determine at least one intermediate system included in the target system and at least one subsystem included in the intermediate system;

[0228] A second determination module 93, configured to determine the probability level of each subsystem in the target system by using the Delphi method based on the statistical data set;

[0229] A third determination module 94, configured to determine the repair probability of the corresponding intermediate system based on the probability level of at least one subsystem included in each intermediate system;

[0230] The fourth determination module 95 is configured to determine a damage function corresponding to each of the intermediate systems based on the damage probability of each of the intermediate systems;

[0231] The fifth determination module 96 is configured to determine the reliability of the target system based on the damage function of each of the intermediate systems.

[0232] In some possible embodiments, the defect attribute words include: defect discovery and / or defect repair; the apparatus further includes: a second acquisition module, configured to acquire management data of different systems within a certain time period; a statistics module, configured to screen and statistically process the management data according to the defect discovery and defect repair respectively, to obtain a statistical data set, where the statistical data set includes statistical data corresponding to the defect discovery and / or statistical data corresponding to the defect repair; the defect discovery includes at least one of defect activities, defect triggering events, and defect impacts; the defect repair includes at least one of the type of the defect, the qualifier of the defect, the source of the defect, the object of the defect, and the history of the defect.

[0233] In some possible embodiments, the damage function includes a reliability function and a maintainability function, and the fourth determination module includes: a first determination sub-module, configured to, when the damage probability of the intermediate system is a failure probability λ, determine the reliability function of the intermediate system; where t represents time; a second determination sub-module, configured to, when the damage probability of the intermediate system is a maintenance probability μ, determine the maintainability function of the intermediate system.

[0234] In some possible embodiments, when the target system includes more than two functional layer systems, each of the functional layer systems includes at least one intermediate system, and each of the intermediate systems includes at least one subsystem; the apparatus further includes:

[0235] a sixth determination module, configured to determine a damage probability corresponding to each functional layer system based on the damage probability of at least one intermediate system included in each functional layer system; a seventh determination module, configured to determine, from the more than two functional layer systems, the functional layer system corresponding to the steady-state availability function with the largest slope based on the damage probability of each functional layer system; an eighth determination module, configured to determine the functional layer system corresponding to the steady-state availability function with the largest slope as the target functional layer system; a ninth determination module, configured to determine a damage function corresponding to the corresponding intermediate system through the damage probability of each intermediate system corresponding to the target functional layer system.

[0236] In some possible embodiments, the seventh determination module includes: a third determination sub-module, configured to determine, based on the Markov theory and according to the repair probability of each function layer system, a function of the steady-state availability corresponding to each repair probability; a fourth determination sub-module, configured to determine, based on the function of the steady-state availability corresponding to each repair probability, the function layer system corresponding to the steady-state availability function with the largest slope.

[0237] In some possible embodiments, the third determination module includes: a fifth determination sub-module, configured to query a preset first relationship table based on the probability level of each subsystem, and determine the repair parameter and the triangular fuzzy set corresponding to the subsystem; the first relationship table is used to represent the corresponding relationship between the probability level and the repair parameter and the triangular fuzzy set; a sixth determination sub-module, configured to determine the triangular fuzzy probability of the corresponding subsystem based on the repair parameter and the corresponding triangular fuzzy set of the subsystem; a quantification module, configured to perform a quantification process on the triangular fuzzy probability of the subsystem based on the triangular fuzzy function theory to obtain the repair probability of the corresponding subsystem; a seventh determination sub-module, configured to determine the repair probability of the corresponding intermediate system according to the reliability series system formula based on the repair probability of the subsystem.

[0238] In some possible embodiments, the repair probability includes a maintenance probability and a failure probability. The seventh determination sub-module includes: a first determination unit, configured to, when the repair probability of the subsystem is a failure probability, determine the failure probability of the corresponding intermediate system through λ i = λ1 + … + λ n ; a second determination unit, configured to, when the repair probability of the subsystem is a maintenance probability, determine the maintenance probability of the corresponding intermediate system through .

[0239] It should be noted here that: the description of the above device embodiments is similar to the description of the above method embodiments and has similar beneficial effects to those of the method embodiments. For the technical details not disclosed in the device embodiments of the present application, please refer to the description of the method embodiments of the present application for understanding.

[0240] It should be noted that in the embodiments of the present application, if the above method is implemented in the form of software functional modules and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the embodiments of the present application, in essence, or the part that contributes to the related technology, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device to execute all or part of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROMs), magnetic disks, or optical discs that can store program codes. In this way, the embodiments of the present application are not limited to any specific combination of hardware and software.

[0241] Correspondingly, the embodiments of the present application provide a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps in the method provided in the above embodiments are implemented.

[0242] In the embodiments of the present application, a chip can also be provided. The chip includes a processor, and the processor can call and run a computer program from a memory to implement the steps in any of the above methods. The chip can also include a memory. Among them, the processor can call and run a computer program from the memory to implement the steps in any of the above methods. Among them, the memory can be an independent device separate from the processor or integrated in the processor.

[0243] It should be pointed out here that the descriptions of the above storage medium and device embodiments are similar to the descriptions of the above method embodiments and have beneficial effects similar to those of the method embodiments. For the technical details not disclosed in the storage medium and device embodiments of the present application, please refer to the descriptions of the method embodiments of the present application for understanding.

[0244] Correspondingly, in the embodiments of the present application, a computer device is also provided for implementing a reliability evaluation method for a target system described in the above method embodiments. The device includes a computer storage medium, and the computer storage medium stores a computer program. The computer program includes instructions that can be executed by at least one processor. When the instructions are executed by the at least one processor, the method in the embodiments of the present application is implemented.

[0245] It should be noted here that the descriptions of the above-mentioned device, computer storage medium, chip, computer program product, and computer program embodiment are similar to those of the above-mentioned method embodiment and have similar beneficial effects to the method embodiment. For the technical details not disclosed in a computer device, computer-readable storage medium, chip, computer program product, and computer program embodiment of the present application, please refer to the description of the method embodiment of the present application for understanding. The above-mentioned device, chip, or processor may include any one or more of the following integrations: Application Specific Integrated Circuit (ASIC), Digital Signal Processor (DSP), Digital Signal Processing Device (DSPD), Programmable Logic Device (PLD), Field Programmable Gate Array (FPGA), Central Processing Unit (CPU), Graphics Processing Unit (GPU), neural-network processing units (NPU), controller, microcontroller, microprocessor, programmable logic device, discrete gate or transistor logic device, discrete hardware component. Those of ordinary skill in the art can understand that all or part of the steps of implementing the above-mentioned method embodiment can be completed by hardware related to program instructions. The foregoing program can be stored in a computer storage medium. When the program is executed, it executes the steps including the above-mentioned method embodiment; and the foregoing storage medium includes: mobile storage device, read-only memory, magnetic disk, or optical disc and other various media that can store program codes. Alternatively, if the above-mentioned integrated unit of the present application is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer storage medium.

[0246] Based on such an understanding, the technical solution of the embodiment of the present application, in essence or the part that contributes to the related technology, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions to enable a computer device (which may be a personal computer, server, etc.) to execute all or part of the methods described in the embodiments of the present application. The foregoing storage medium includes: mobile storage device, ROM, magnetic disk, or optical disc and other various media that can store program codes.

[0247] It should be understood that the "one embodiment" or "an embodiment" mentioned throughout the specification means that the specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present application. Therefore, the appearances of "in one embodiment" or "in an embodiment" throughout the specification do not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner. It should be understood that in various embodiments of the present application, the magnitudes of the serial numbers of the above processes do not mean the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application. The serial numbers of the embodiments of the present application are only for description and do not represent the advantages or disadvantages of the embodiments.

[0248] It should be noted that in this article, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including a..." does not exclude the existence of additional identical elements in the process, method, article or device including the element.

[0249] In several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored, or not executed. In addition, the coupling, direct coupling or communication connection between the components shown or discussed with each other can be through some interfaces. The indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0250] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units; they can be located in one place or distributed to multiple network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiments of the present application.

[0251] In addition, each functional unit in the embodiments of the present application can be all integrated in one processing unit, or each unit can be separately used as a unit, or two or more units can be integrated in one unit; the above integrated units can be implemented in the form of hardware, or in the form of hardware plus software functional units.

[0252] Alternatively, if the above integrated units of the present application are implemented in the form of software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the embodiments of the present application, in essence or the part that contributes to the related art, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing the automatic test line of the device to execute all or part of the methods described in the various embodiments of the present application. The foregoing storage medium includes: various media that can store program codes such as removable storage devices, ROMs, magnetic disks, or optical discs.

[0253] The methods disclosed in several method embodiments provided by the present application can be arbitrarily combined without conflict to obtain new method embodiments.

[0254] The features disclosed in several method or device embodiments provided by the present application can be arbitrarily combined without conflict to obtain new method embodiments or device embodiments.

[0255] The above is only the implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should all be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A reliability evaluation method for a target system, characterized in that, The method includes: Obtaining a set of statistical data, where each piece of statistical data in the set of statistical data is obtained by screening the management data of different systems according to the corresponding defect attribute words; the defect attribute words include: defect discovery and / or defect repair; Determining at least one intermediate system included in the target system and at least one subsystem included in the intermediate system; Based on the set of statistical data, using the Delphi method to determine the probability level of each subsystem in the target system; Based on the probability level of each subsystem, querying a preset first relationship table to determine the repair loss parameter and triangular fuzzy set corresponding to the subsystem; the first relationship table is used to represent the corresponding relationship between the probability level, the repair loss parameter, and the triangular fuzzy set; Based on the repair loss parameter of the subsystem and the corresponding triangular fuzzy set, determining the triangular fuzzy probability of the corresponding subsystem; Based on the triangular fuzzy function theory, quantifying the triangular fuzzy probability of the subsystem to obtain the repair loss probability of the corresponding subsystem; Based on the repair loss probability of the subsystem, determining the repair loss probability of the corresponding intermediate system based on the reliability series system formula; the repair loss probability includes the maintenance probability μ and the failure probability λ; When the repair probability of the intermediate system is the failure probability λ, determine the reliability function of the intermediate system through And when the repair probability of the intermediate system is the maintenance probability μ, determine the maintainability function of the intermediate system through where t represents time; the reliability function and the maintainability function are repair functions. Based on the repair loss function of each intermediate system, determining the reliability of the target system.

2. The method according to claim 1, wherein The defect attribute words include: defect discovery and / or defect repair; the method further includes: Obtaining the management data of different systems within a certain period of time; Respectively screening and counting the management data according to the defect discovery and defect repair to obtain a set of statistical data, the set of statistical data including the statistical data corresponding to the defect discovery and / or the statistical data corresponding to the defect repair; The defect discovery includes at least one of defect activities, defect triggering events, and defect impacts; the defect repair includes at least one of the type of defect, qualifier of defect, source of defect, object of defect, and history of defect.

3. The method according to claim 1 or 2, characterized in that, When the target system includes more than two functional layer systems, each functional layer system includes at least one intermediate system, and each intermediate system includes at least one subsystem; The method further includes: Based on the repair loss probability of at least one intermediate system included in each functional layer system, determining the repair loss probability of the corresponding functional layer system; Based on the repair loss probability of each functional layer system, determining, from the more than two functional layer systems, the functional layer system corresponding to the steady-state availability function with the largest slope; Determining the functional layer system corresponding to the steady-state availability function with the largest slope as the target functional layer system; Through the repair loss probability of each intermediate system corresponding to the target functional layer system, determining the repair loss function of the corresponding intermediate system.

4. The method according to claim 3, wherein The determining, from the more than two functional layer systems, the functional layer system corresponding to the steady-state availability function with the largest slope based on the repair loss probability of each functional layer system includes: Based on Markov theory, according to the repair loss probability of each functional layer system, determining the function of the steady-state availability corresponding to each repair loss probability; Based on the function of the steady-state availability corresponding to each repair loss probability, determining the functional layer system corresponding to the steady-state availability function with the largest slope.

5. The method according to claim 1, wherein Based on the damage probability of the subsystem, determine the damage probability of the corresponding intermediate system based on the reliability series system formula, including: When the repair probability of the subsystem is the failure probability, through λ i = λ1 + ··· + λ n Determine the failure probability of the corresponding intermediate system; When the repair probability of the subsystem is the maintenance probability, by determine the maintenance probability of the corresponding intermediate system.

6. A reliability evaluation device for a target system, characterized in that, The device includes: A first acquisition module, configured to acquire a statistical data set, where each statistical data in the statistical data set is obtained by screening the management data of different systems according to the corresponding defect attribute words; the defect attribute words include: defect discovery and / or defect repair; A first determination module, configured to determine at least one intermediate system included in the target system and at least one subsystem included in the intermediate system; A second determination module, configured to determine the probability level of each subsystem in the target system by using the Delphi method based on the statistical data set; A fifth determination sub-module, based on the probability level of each subsystem, query a preset first relationship table to determine the damage parameter and the triangular fuzzy set of the corresponding subsystem; the first relationship table is used to represent the corresponding relationship between the probability level and the damage parameter, and the triangular fuzzy set; A sixth determination sub-module, configured to determine the triangular fuzzy probability of the corresponding subsystem based on the damage parameter and the corresponding triangular fuzzy set of the subsystem; A quantification module, configured to perform a quantification process on the triangular fuzzy probability of the subsystem based on the triangular fuzzy function theory to obtain the damage probability of the corresponding subsystem; A seventh determination sub-module, configured to determine the damage probability of the corresponding intermediate system based on the reliability series system formula based on the damage probability of the subsystem; the damage probability includes the maintenance probability and the failure probability; A first determination sub-module, configured to, when the repair probability of the intermediate system is the failure probability λ, determine the reliability function of the intermediate system through ; and a second determination sub-module, configured to, when the repair probability of the intermediate system is the repair probability μ, determine the maintainability function of the intermediate system through ; where t represents time; the reliability function and the maintainability function are repair loss functions. A fifth determination module, configured to determine the reliability of the target system based on the damage function of each intermediate system.

7. A computer device, characterized in that, Including: A memory and a processor, the memory stores a computer program that can run on the processor, and when the processor executes the computer program, the steps in the method according to any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, the steps in the method according to any one of claims 1 to 5 are implemented.

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