Engine part reliability modeling method based on reliability unit

Abstract

The invention relates to an engine component reliability modeling method based on a reliability unit, which comprises the following steps: (1) carrying out engine body external field fault statistics: carrying out statistics on aero-engine fault data, and determining a reliability index distribution object; (2) engine reliability unit division is carried out, and the reliability units have physical independence and comprise structures with large safety influences; and (3) carrying out hierarchical division and reliability modeling on the whole engine system. And (4) based on the established hierarchical division relationship of the complete engine system, carrying out reliability distribution based on a cost function from left to right. According to the method, aero-engine part reliability modeling and system reliability distribution considering reliability improvement cost can be realized, and a method basis is provided for aero-engine reliability design.

Description

Technical Field

[0001] The invention belongs to the technical field of aerospace engines, and in particular relates to a reliability unit-based engine component reliability modeling method. Background Art

[0002] An aircraft engine is a complex mechanical system whose components are connected through assembly. Each component has multiple failure modes throughout its life cycle. The overall reliability indicators of aircraft engines include mean time between failures, idle stop rate, return rate, etc. In order to ensure that the engine can complete the scheduled flight mission stably and safely, it is necessary to establish a reliability model covering typical failure modes and form a reliability allocation method from the whole machine to the parts, so as to answer the requirements of the reliability indicators of the aircraft engine.

[0003] At present, there are mature reliability modeling methods for electronic product system reliability, including equal distribution method, improved electronic equipment consulting group distribution method, weight distribution method and extended score distribution method. The existing literature "Wang Qi et al., Reliability Modeling and Analysis of Coupled Cascading Failure Systems, Operations Research and Management, 2024, 33(01):90-94." considers the mutual influence of coupled systems and implements reliability modeling through continuous-time Markov processes. However, this method assumes that the life of the original parts obeys exponential distribution and is mainly used for electronic components in power systems. The life of mechanical systems usually obeys logarithmic ecological distribution and Weibull distribution, so this method is no longer used. The existing application "Reliability Modeling Method for Gun System Based on Copula and Multi-performance Degradation Data (CN202311362892.5)" uses multi-performance degradation data that contains more information than life data for reliability modeling, and uses Copula functions to describe the correlation between performance. However, this method uses Copula functions to describe the correlation between performance, which is complex to calculate for complex mechanical structures of engines, has low calculation efficiency, and is difficult to achieve efficient engineering applications. In summary, the existing reliability allocation and analysis methods are not suitable for the complex mechanical structure of aircraft engines. Summary of the invention

[0004] In order to overcome the shortcomings of the prior art, the present invention provides an engine component reliability modeling method based on reliability units, which innovatively introduces the concept of reliability units, allocates reliability to reliability units with physical independence, and realizes reliability allocation by combining a cost function model, thereby achieving effective allocation of reliability indicators. The invention can effectively support the reliability design of aviation and aerospace vehicles.

[0005] To achieve the above object, the present invention adopts the following technical solution: a reliability modeling method for engine components based on reliability units, comprising the following steps:

[0006] Step (1) Conducting statistics on external engine failures, including: collecting statistics on aircraft engine failure data and determining reliability index allocation objects;

[0007] Step (2) Carry out the division of aircraft engine reliability units; including: dividing into reliability units according to the faulty parts and locations, the reliability units have physical independence, and supplement the reliability units related to safety;

[0008] Step (3) Conducting hierarchical division and reliability modeling of the entire engine system, including: conducting hierarchical analysis of the aircraft engine system based on its functional characteristics;

[0009] Step (4) carries out reliability allocation based on the cost function; including: carrying out reliability allocation from left to right based on the established hierarchical division relationship of the engine system; the possibility index in the cost function is comprehensively evaluated using five influencing factors: importance, technology maturity, environmental severity, complexity, and detectability.

[0010] The advantages of the present invention compared with the prior art are:

[0011] (1) The present invention adds a reliability unit level based on the traditional system reliability model, further decomposing the reliability indicators of components into specific parts, so that the reliability indicators can be assessed.

[0012] (2) The present invention adds a reliability allocation method based on a cost function to the traditional system reliability allocation method, which can realize reliability allocation that takes into account the reliability improvement cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] FIG1 is a flow chart of a reliability modeling method for engine components based on a reliability unit of the present invention;

[0014] Figure 2 is a schematic diagram of a turbine blade / disk reliability unit;

[0015] FIG3 is a schematic diagram of the hierarchical division of the engine system;

[0016] Figure 4 shows the changing pattern of the possibility index. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical scheme and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. In addition, the technical features involved in each embodiment of the present invention described below can be combined with each other as long as they do not conflict with each other. To achieve the above-mentioned purpose, the present invention adopts the following technical scheme.

[0018] The technical solution of the present invention is further described below in conjunction with the accompanying drawings.

[0019] like Figure 1 As shown, a reliability unit-based engine component reliability modeling method of the present invention comprises the following steps:

[0020] Step 1: Conduct statistics on external engine failures. Statistical aviation engine failure data to determine the reliability index allocation object. The present invention counts the failure data of multiple turboshaft engines for nearly 10 million flight hours, identifies the location and category of engine failures, and generally has the following characteristics:

[0021] ① Structures that frequently bear large alternating loads are prone to failure, such as high- and low-cycle composite fatigue failure and creep failure of turbine blades, and cracks caused by thermal cycles of flame tubes.

[0022] ② Connection structures that transmit large loads are prone to micro-fatigue and wear failures at contact points, such as tenon connection structures, gear structures, arc end tooth connection structures, spline connection structures, etc.

[0023] ③ Adjacent structures that have relative motion during operation are prone to gap enlargement, wear, collision and other faults when deformation occurs, such as blade tip collision, comb tooth seal, rotor and stator blade root edge plate and other structures;

[0024] ④ When non-metallic sealing parts such as rubber rings and lip oil seals are used in the structural design, oil leakage is prone to occur;

[0025] ⑤ The probability of failure of most structures of the engine body is extremely low, and it almost never occurs in the statistical results of field failures.

[0026] On this basis, common engine failures are classified into four categories, including parts themselves, connection structures, relative motion, and non-metallic seals.

[0027] Step 2: Carry out the division of engine reliability units. First, the reliability units are divided according to the faulty parts and locations. This reliability unit division method can meet the physical independence requirements. Taking the turbine blade / disk as an example, the reliability units are divided into three categories, namely, blade body, blade disk tenon connection, and disk body. Figure 2 As shown. At this time, the structure with extremely low failure rate is simplified and not used as a reliability unit, so as to ensure that the reliability model is simple and effective. Then, the reliability units related to safety are supplemented. The probability of failure of some structures is extremely low, but its impact on safety is large, so it needs to be supplemented as a reliability unit. For example, the rupture of the wheel body is a safety-related event, even if the probability of failure in the field is extremely low (airworthiness requires failure rate <10 -8 ), but is still supplemented as a reliability unit.

[0028] Step 3: Carry out hierarchical division and reliability modeling of the engine system. For complex aircraft engine systems, hierarchical analysis is performed based on their functional characteristics, such as Figure 3 As shown in the figure, it includes four levels: system level, subsystem level, component level, and reliability unit level. The reliability unit level is added on the basis of the traditional level. For the reliability unit level, a reliability model based on the series system is established.

[0029] Step 4: Carry out reliability allocation based on cost function. Figure 3 The established engine system hierarchical division relationship carries out reliability allocation from left to right. The present invention considers the reliability improvement cost and establishes a reliability optimization allocation method.

[0030] The optimization model shown in formula (1) is used to transform the reliability allocation problem into an optimization problem.

[0031] (1)

[0032] Among them, R s is the system reliability, R i is the reliability of the reliability unit, R s For each reliability unit R i Function H, R d is the system reliability index, n represents the number of reliability units, c i The cost function for each reliability unit has an exponential form.

[0033] (2)

[0034] in, and Respectively represent the current reliability result and the maximum achievable reliability of the i-th reliability unit, and the maximum achievable reliability Usually less than 100%. It is an index of the feasibility of improving reliability. The higher f is, the easier it is to improve reliability.

[0035] In formula (2), the cost function value of the reliability unit increases with the increase of the allocation reliability, and finally reaches the maximum achievable reliability when the allocation reliability reaches The cost function approaches infinity when the probability index is low. The increasing trend of the cost function is controlled by the probability index. The physical meaning of the probability index is: the ability of the reliability unit to improve the reliability compared with other reliability units in the component. The lower the probability index, the faster the cost function approaches infinity, which means that the reliability is more difficult to improve. Figure 4 shown.

[0036] The possibility index depends on multiple influencing factors, including the importance of the reliability unit, technical maturity, environmental severity, complexity, detectability and maintainability. The present invention uses a 10-point system to evaluate the influencing factors of the possibility index (Table 1), and then determines the possibility index f of the reliability unit by weighted average, which is expressed as:

[0037] (3)

[0038] Among them, a ij It represents the score of the jth influencing factor of the ith reliability unit, which varies between 0 and 10; m represents the number of influencing factors, and m=5 is taken in the present invention.

[0039] Table 1 Influencing factors of possibility index

[0040]

Claims

1. A reliability modeling method for engine components based on reliability units, characterized in that: The steps include: Step (1) Conducting statistics on external engine failures, including: collecting statistics on aircraft engine failure data and determining reliability index allocation objects; Step (2) Carry out the division of aircraft engine reliability units; including: dividing into reliability units according to the faulty parts and locations, the reliability units have physical independence, and supplement the reliability units related to safety; Step (3) Conducting hierarchical division and reliability modeling of the entire engine system, including: conducting hierarchical analysis of the aircraft engine system based on its functional characteristics; Step (4) carries out reliability allocation based on the cost function; including: carrying out reliability allocation from left to right based on the established hierarchical division relationship of the engine system; the possibility index in the cost function is comprehensively evaluated using five influencing factors: importance, technology maturity, environmental severity, complexity, and detectability.

2. The reliability modeling method for engine components based on reliability unit according to claim 1, characterized in that: The step (1) classifies engine failures into four categories, including parts failures, connection structure failures, relative motion failures, and non-metallic sealing failures.

3. The reliability modeling method of engine components based on reliability unit according to claim 2, characterized in that: In step (2), the reliability unit related to safety includes a reliability unit with a very low probability of structural failure and a great impact on safety. The probability of failure is very low, that is, the probability of failure is specifically <10 -8 .

4. The reliability modeling method for engine components based on reliability unit according to claim 3, characterized in that: In step (3), the aircraft engine system includes four levels: system level, subsystem level, component level, and reliability unit level.

5. The reliability modeling method for engine components based on reliability unit according to claim 4, characterized in that: The specific steps of step (4) are: In step (4), the specific process of the reliability allocation method based on the cost function is as follows: The optimization model shown in formula (1) is used to transform the reliability allocation problem into an optimization problem; (1) Among them, R s is the system reliability, R i is the reliability of the reliability unit, R s is the system reliability, expressed as each reliability unit R i Function H, R d is the system reliability index, n represents the number of reliability units, and They represent the current reliability result and the maximum achievable reliability of the i-th reliability unit, respectively, and c i Represents the cost function of each reliability unit, which has an exponential form: (2) Among them, the maximum achievable reliability Less than 100%, It is an indicator of the possibility of improving reliability; In formula (2), the cost function value of the reliability unit increases with the increase of the allocation reliability, and finally reaches the maximum achievable reliability when the allocation reliability reaches When , the cost function approaches infinity, and the increasing trend of the cost function is controlled by the possibility index. The physical meaning of the possibility index is: the ability of the reliability unit to improve the reliability compared with other reliability units in the component.

6. The reliability modeling method for engine components based on reliability unit according to claim 5, characterized in that: The possibility index in step (4) depends on five influencing factors: importance, technical maturity, environmental severity, complexity, and detectability. The influencing factors of the possibility index are evaluated using a 10-point system, and then the possibility index f of the reliability unit is determined by weighted average, expressed as: (3) Among them, a ij It represents the score of the jth influencing factor of the i-th reliability unit, which varies between 0 and 10. m represents the number of influencing factors, and m=5.

7. The reliability modeling method for engine components based on reliability unit according to claim 6, characterized in that: The influencing factors of the possibility index in step (4) are evaluated using a 10-point system, and the evaluation rules are as follows: ① Importance: The smaller the number of reliability unit failures that cause system failure, the higher the importance score. The minimum number of reliability unit failures is 10 points and the maximum is 0 points. ②Technology maturity: The higher the technology maturity, the higher the technology maturity score. The technology maturity of the reliability unit in a mature engine is high, but if new materials and new processes are adopted, the technology maturity is low. The highest technology maturity is 10 points and the lowest is 0 points. ③ Environmental severity: The higher the degree of standardization, the higher the standardization score; the stricter the environment in which the reliability unit is located, the higher the environmental severity; the highest environmental severity is 10 points and the lowest is 0 points; ④ Complexity: The higher the complexity, the more likely the structure is to fail, and the higher the complexity score; the highest complexity score is 10 points, and the lowest is 0 points; ⑤ Detectability: The worse the detectability, the higher the maintainability score; the highest detectability is 10 points and the worst is 0 points.

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