Diesel engine common cause failure analysis method based on repairable dynamic fault tree

Abstract

The application discloses a diesel engine common cause failure analysis method based on a repairable dynamic fault tree, and proposes a common cause failure model for a modeling method of the repairable dynamic fault tree of a diesel engine system. By designing the deterministic common cause failure logic gate and the probabilistic common cause failure logic gate of the repairable dynamic fault tree, the instantaneous availability change curve of the diesel engine under the condition of considering the deterministic common cause failure and the probabilistic common cause failure can be obtained. The influence of the deterministic common cause failure and the probabilistic common cause failure on the reliability of the system is avoided, the deviation between the analysis result of the repairable dynamic fault tree and the actual situation is reduced, and the normal operation of the diesel engine is ensured. In addition, the application uses the multi-criteria compromise solution sequencing method to calculate the component importance of a complex system under the influence of the common cause failure of the repairable dynamic fault tree. The weak link of the diesel engine electronic control system is judged through comprehensive analysis, and the reliability of the diesel engine under the influence of the common cause failure can be accurately evaluated.

Description

Technical Field

[0001] This invention relates to the technical field of diesel engine failure analysis, and in particular to a method for common cause failure analysis of diesel engines based on repairable dynamic fault trees. Background Technology

[0002] Diesel engines are primarily used in the transportation industry and are the main power source for heavy-duty vehicles. Various factors are considered when selecting diesel engines for heavy-duty vehicles, including engine reliability and availability, engine maintenance and installation costs, and engine operating costs. However, the operating and maintenance costs of each diesel engine are particularly significant during vehicle operation. This is why transportation companies are committed to developing and improving engine performance to suit operations and optimize engine performance. Improving engine performance is key to ensuring optimal results during use, timely prediction of failures, and extending vehicle lifespan. Therefore, it is essential to focus on improving the reliability of vehicle engines.

[0003] The most effective way to improve the reliability of diesel engines is to incorporate reliability concepts into their design phase. This involves conducting appropriate reliability calculations and analyses to prevent problems before they occur (reducing manufacturing costs and improving overall product lifecycle reliability). Therefore, improving the reliability of diesel engine systems can prevent significant personal injury and economic losses caused by system reliability issues.

[0004] When performing repairable dynamic fault tree modeling for repairable systems like diesel engines, deterministic and probabilistic common-cause failures of components are not considered. For example, in real-world redundant systems, neglecting the impact of common-cause failures of redundant components on system reliability analysis will lead to discrepancies between the analysis results and the actual situation, rendering the analysis worthless.

[0005] In existing technologies, repairable dynamic fault tree (RTF) modeling for common-cause failure analysis in diesel engines typically uses OR logic gates to analyze redundant components. For example, Markov-based RTFs consider both failure rate and maintainability rate to calculate the instantaneous availability of the diesel engine system. However, RTFs that do not consider common-cause failures cannot calculate the impact of actual redundant component failures on system reliability, leading to discrepancies between the analysis results and actual conditions. Summary of the Invention

[0006] The purpose of this invention is to provide a diesel engine common cause failure analysis method based on repairable dynamic fault trees, which solves the problem that the reliability assessment of diesel engines is not accurate enough in the prior art when common cause failures are not considered. This method uses deterministic common cause failures and probabilistic common cause failures as theoretical models to perform diesel engine common cause failure analysis. It ensures that when repairable dynamic fault trees are used to analyze the reliability of diesel engine redundant systems, the error between the analysis and the actual system reliability analysis is reduced, thus providing a guarantee for the normal operation of diesel engines.

[0007] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0008] This invention provides a method for common cause failure analysis of diesel engines based on repairable dynamic fault trees, comprising the following steps:

[0009] S1. Analyze the principle and structure of the diesel engine system to identify the repairable top event of the dynamic fault tree;

[0010] S2. Select the common cause failure model based on the actual situation of the diesel engine system, and derive the quantitative calculation formula of the common cause failure logic gate using the Markov repairable system.

[0011] S3. Determine the failure rate and repair rate of each component in the diesel engine system: Determine the repair and failure logic relationship between components, use a direct algorithm and the derived common cause failure logic gate quantitative calculation formula to obtain the transient availability of the repairable dynamic fault tree top event;

[0012] S4. Use the downlink method to find the minimum cut sets of the repairable dynamic fault tree, and the probability importance of each minimum cut set;

[0013] S5. Calculate the importance of the repairable dynamic fault tree structure and use the multi-criteria compromise solution ranking method to calculate the repair importance of components.

[0014] S6. Based on the maintenance importance of the components, perform common cause failure analysis on the diesel engine system.

[0015] Further, step S1 includes:

[0016] S11. A diesel engine electronic control system is used to monitor the real-time operating status of the diesel engine oil;

[0017] S12. The diesel engine electronic control system is regarded as a unit connected in series with the diesel engine, and the fault of the diesel engine electronic control system is selected as the top event of the repairable dynamic fault tree.

[0018] Furthermore, in step S2, the quantitative calculation formula for the common-cause failure logic gate is derived using the Markov repairable system, including:

[0019] S21. Derive the quantitative calculation formula for deterministic common-cause failure logic gates;

[0020] S22. Derive the quantitative calculation formula for probabilistic common-cause failure logic gates.

[0021] Further, step S3 includes:

[0022] S31. Determine the repairability of each component in the diesel engine system: Establish the state transition matrix of the repairable component, and obtain the availability of the repairable component at time t from the state transition;

[0023] S32. Determine the failure rate of each component in the diesel engine system: Use a direct algorithm and the derived common-cause failure logic gate quantitative calculation formula to obtain the transient availability of the repairable dynamic fault tree top event.

[0024] Further, step S4 includes:

[0025] S41. The minimum cut set of the repairable dynamic fault tree is calculated using the static-dynamic transformation method by the following formula;

[0026]

[0027] In the above formula, l represents the number of basic events in the fault tree, and i represents the number of basic events x. i The number of vectors; j is the number of minimal cut sets; v j For x i The minimum cut set; φ(x) is the structure function of the repairable dynamic fault tree;

[0028] S42. Calculate the probability importance of each minimal cut set using the probability importance formula.

[0029] Probability Importance Formula:

[0030]

[0031] In the formula, I R (z) represents the probabilistic importance of component z; h(R) represents the reliability function of component z; R z Let z be the minimum path set of component z.

[0032] Further, in step S5, calculating the importance of the repairable dynamic fault tree structure includes:

[0033] Suppose the state of the b-th component X changes from 0 to 1, the corresponding state change of the diesel engine system is Q. b (X);

[0034] The structural importance of the component is:

[0035] In the formula, a represents the number of cut-order sets.

[0036] Furthermore, in step S5, the component maintenance importance is calculated using a multi-criteria compromise solution ranking method, including: setting v df The evaluation index is d, where d is the component ordinal number and f is the evaluation index ordinal number. The importance of the unit component v needs to be selected based on the actual situation of the diesel engine system. 1f Repair rate v 2f Repair costs v 3f Occurrence frequency v 4f As an evaluation index for the importance of maintenance; where v 3f and v 4f The indicator scores are obtained from expert ratings;

[0037] Substitute the structural importance of each component into the unit component importance;

[0038] Establish decision matrix D:

[0039]

[0040] In the above formula, v 11 ,v 12 ,...v df These are the evaluation indicators, corresponding to the f-th evaluation indicator in the component with index d.

[0041] v in the above formula df Standardize by substituting into the following formula:

[0042] p represents the number of components participating in the evaluation, and g represents the number of components participating in the evaluation.

[0043] Obtain the standardized decision matrix r df ;

[0044] Calculate the positive ideal solution r for each evaluation index. + and negative ideal solution r - :

[0045]

[0046]

[0047] F is the minimum ordinal value of the evaluation index, and F' is the maximum ordinal value of the evaluation index;

[0048] S d Given the absolute values ​​of the positive and negative ideal solutions, the distance ratio R between the positive and negative ideal solutions of each component is calculated using the following formula. d :

[0049]

[0050]

[0051] l represents the number of evaluation indicators, w df Let f be the weight of the centrality criterion for the evaluation index with ordinal number f in the d-th component;

[0052] Calculate the benefit ratio: v d For the decision mechanism coefficients of the majority criterion strategies of the d-th component;

[0053]

[0054] in,

[0055] Finally, based on the benefit ratio Q of each component d Rank the maintenance importance.

[0056] Compared with the prior art, the present invention has the following beneficial effects:

[0057] 1. This invention proposes a common-cause failure model for the repairable dynamic fault tree modeling method of diesel engine systems. By designing deterministic and probabilistic common-cause failure logic gates for the repairable dynamic fault tree, the instantaneous availability change curves of the diesel engine considering both deterministic and probabilistic common-cause failures can be obtained. This avoids neglecting the impact of deterministic and probabilistic common-cause failures on system reliability, reduces the deviation between the repairable dynamic fault tree analysis results and the actual situation, and provides assurance for the normal operation of the diesel engine.

[0058] 2. This invention uses a multi-criteria compromise solution ranking method to calculate the component importance of a complex system under the influence of common-cause failures for common-cause failure events in repairable dynamic fault trees. It considers the impact of common-cause failure components on system reliability, providing quantitative information on the impact of common-cause failures for system improvement. By comprehensively analyzing and identifying the weak points in the diesel engine electronic control system, it can accurately assess the reliability of the diesel engine under the influence of common-cause failures. Attached Figure Description

[0059] Figure 1 This is a flowchart of the diesel engine common cause failure analysis method based on repairable dynamic fault tree of the present invention;

[0060] Figure 2 This is a flowchart illustrating the implementation of the diesel engine common cause failure analysis method based on repairable dynamic fault tree according to the present invention.

[0061] Figure 3 The deterministic common-cause failure logic gate of this invention is transformed into a Markov model diagram.

[0062] Figure 4 This invention transforms the probabilistic common-factor logic gate into a Markov model diagram.

[0063] Figure 5 This is a schematic diagram of the diesel engine electronic control system in this embodiment.

[0064] Figure 6 Deterministic common cause modeling and explicit deterministic common cause modeling for repairable dynamic fault trees of electronic control systems.

[0065] Figure 7 This study provides probabilistic common cause modeling and explicit probabilistic common cause modeling for repairable dynamic fault trees in electronic control systems.

[0066] Figure 8 The availability variation curves for the repairable dynamic fault tree of the electronic control system, excluding common cause failures, deterministic common cause failures, and probabilistic common cause failures.

[0067] Figure 9 This is a minimal cut set maintenance importance graph. Detailed Implementation

[0068] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.

[0069] In the description of this invention, it should be noted that the terms "upper," "lower," "inner," "outer," "front end," "rear end," "both ends," "one end," and "the other end," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0070] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installed," "equipped with," "connected," etc., should be interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium; it can be a connection within two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0071] Reference Figure 1 As shown, this invention provides a diesel engine common cause failure analysis method based on a repairable dynamic fault tree, including the following specific steps S1 to S6; the principle is as follows: Figure 2 As shown.

[0072] S1. Analyze the principle and structure of the diesel engine system to determine the repairable dynamic fault tree top event; that is, confirm the failure logic characteristics of the diesel engine system and determine the failure criteria of the diesel engine system; step S1 specifically includes:

[0073] S11. A diesel engine electronic control system is used to monitor the real-time operating status of the diesel engine oil;

[0074] The diesel engine electronic control system is a device that monitors the operating status of the diesel engine. During operation, the electronic control system can monitor changes in the diesel engine's operation in real time, provide timely feedback on any issues that arise, and take appropriate measures accordingly. This diesel engine electronic control system includes one start signal, one control signal, one foot pedal signal, one intercom device, one power supply, one backup power supply, one controller, one sensor system, one actuator, and one fuel cut-off solenoid valve.

[0075] S12. The diesel engine electronic control system is regarded as a unit connected in series with the diesel engine, and the fault of the diesel engine electronic control system is selected as the top event of the repairable dynamic fault tree.

[0076] In addition to assisting the operation of the diesel engine, the diesel engine electronic control system also plays a role in monitoring the real-time status of the diesel engine and adjusting the diesel engine power source in a timely manner. Therefore, in the modeling, the diesel engine electronic control system is treated as a series unit, and "diesel engine electronic control system failure" is selected as the top event.

[0077] S2. Based on the actual situation of the diesel engine system, select a common cause failure model and derive a quantitative calculation formula for the common cause failure logic gate using a Markov repairable system; specifically including:

[0078] S21. Select the common cause failure model based on the actual situation of the diesel engine system;

[0079] First assume (CC1, CC2, ..., CC) n The probability of a common cause (P1, P2, ..., P) occurring is called the triggering event; n x represents the probability that a related basic event is forced to occur when the triggering event occurs; n is a positive integer. t X is the probability of a component failing independently. IF This represents the probability of a component failure occurring. The formula for calculating probabilistic common-cause failure at the component level is:

[0080] X IF = (CC1·P1+CC2·P2+…+CC) n ·P n )+x t (1)

[0081] If (CC1, CC2, ..., CC) nIf all values ​​are 1, then the common cause failure model is a deterministic common cause failure model; otherwise, it is a probabilistic common cause failure model.

[0082] S22. Derivation of the quantitative calculation formula for deterministic common-cause failure logic gates; such as Figure 3 The diagram shown is a conversion of the deterministic common-cause failure logic gate into a Markov model.

[0083] Based on the deterministic common-cause failure characteristics of diesel engines, a β model is adopted. The β model assumes that two failure modes exist in the system components: one is the independent failure λ of the component. A One type is deterministic common-cause failure λ C Both failure modes lead to component failure, but in a repairable system like a diesel engine, each failure mode also has a corresponding repair rate, such as... Figure 6 As shown. The β model is generally determined through comprehensive expert evaluation, for example, to ensure the scientific validity of the data. During implementation, the β factor evaluation is conducted by a panel of at least three experts who provide a comprehensive score.

[0084] The formula for calculating the β model factor is as follows:

[0085]

[0086] in

[0087] λ B =λ A +λ C

[0088] In the above formula, λ B Let λ be the probability of complete component failure. A For the component-independent failure rate, λ C This represents the common-cause failure rate.

[0089] In the following formula, μ A For input independent failure x t The maintenance rate of (t), λ A For input independent failure x t The failure rate of (t). μ C To input the maintenance rate of deterministic common-cause failure ccf(t), λ C Let C(t) be the failure rate of the deterministic common-cause failure (ccf(t)). Let C(t) be the normal state probability of the common-cause gate output event at time t. From the deterministic common-cause failure logic, the state transition matrix of the deterministic common-cause failure logic gate for a repairable dynamic fault tree is:

[0090]

[0091] 1) List of Quantitative Calculation Rules

[0092] like Figure 3 As shown, where μ A Δt is the input event x t (t) is determined by the maintenance rate μ within the time interval Δt. A The probability of causing a system state transition, λ A Δt is the input event x t (t) is determined by the failure rate λ within the time interval Δt. A The probability of causing a system state transition. μ B Δt represents the time interval during which the input event ccf(t) is determined by the maintenance rate μ. B The probability of causing a system state transition, λ B Δt is the input event ccf(t) within time Δt, determined by the failure rate λ. B The possibility of causing a system state transition. For example... Figure 3 As shown in the table below, 0 corresponds to rule 1, 1 corresponds to rule 2, 2 corresponds to rule 3, and so on.

[0093] Input event x into the deterministic common-cause failure logic gate. t The output event y(t) and the output event y(t) have two states: state 0 is the normal working state, and state 1 is the fault state. Based on x... t The relationship between the inputs and outputs of C(t), ccf(t), and C(t) yields a list of quantitative operational rules for the deterministic common factor gate, as shown in Table 1.

[0094] Table 1: List of Quantitative Calculation Rules for Deterministic Common Factorization

[0095]

[0096]

[0097] 2) Quantitative calculation formula for deterministic common-cause failure logic gates

[0098] As can be seen from the state transition matrix, the quantitative calculation formula for deterministic common-cause failure logic gates is as follows:

[0099]

[0100] C(t) is the deterministic common-cause failure probability, and s1 and s2 are the two non-negative real roots of the above equation, derived from the quadratic equation. It can be known that...

[0101] S23. Derivation of the quantitative calculation formula for probabilistic common-cause failure logic gates; such as Figure 4 The diagram shown is a representation of the transformation of a probabilistic common-cause logic gate into a Markov model.

[0102] In real-world systems, deterministic common-cause failures can lead to the failure of different components with varying probabilities. This behavior is called probabilistic common-cause failure. A system can be affected by probabilistic common-cause failures from multiple different systems, denoted as CC1, CC2, ..., CC2. n Each CC i This will affect the components, assuming component A has a failure probability of P. iA P iA =Pr(Component A Fault / CC) i (occurred). Among them, CC i The probability of occurrence is PCC i PCC i and P iA All hypothetical input parameters are derived from comprehensive expert evaluation. This embodiment selects an explicit modeling method, such as... Figure 7 As shown, this paper proposes a method for repairing dynamic fault trees for probabilistic common-cause failures by combining existing probabilistic common-cause failure theory with Markov models and applying the model to repairable dynamic fault trees.

[0103] Based on the characteristics of repairable dynamic fault trees, a probabilistic common-cause explicit modeling method is adopted. (cc1,cc2,…,cc n The probability of a common cause occurring is called a triggering event. Therefore, the formula for calculating probabilistic common cause failures at the component level is:

[0104] X IF =(cc1·q1+cc2·q2+…+cc n ·q n )+x t (1)

[0105] In the following formula, μ1 represents the input-independent failure x t The maintenance rate of (t), x t For input independent failure x t The failure rate of cc1(t). μ2 is the repair rate of the input probabilistic common-cause failure cc1(t), where cc1 is the failure rate of the input probabilistic common-cause failure cc1(t). q1 is the occurrence rate of the triggering event, and μ3 is the repair rate corresponding to q1. q1(t) is the failure state probability of the output event of the probabilistic common-cause gate at time t. The state transition matrix corresponding to the probabilistic common-cause failure is as follows:

[0106]

[0107] 1) List of Quantitative Calculation Rules

[0108] Where μ1Δt is the input event x t (t) is the probability of a system state transition caused by the maintenance rate μ1 within a time interval Δt, where λ1Δt is the input event x.t (t) The probability of a system state transition caused by the failure rate λ1 within a time interval Δt. μ c Δt represents the time interval during which the input event cc1(t) is determined by the maintenance rate μ. c The probability of causing a system state transition is given by cc1Δt, which is the probability that the input event cc1(t) will cause a system state transition due to the failure rate cc1 within the time interval Δt.

[0109] μ3Δt represents the probability that the input event q1(t) will cause a system state transition due to the maintenance rate μ3 within the time interval Δt, and q1Δt represents the probability that the input event q1(t) will cause a system state transition due to the failure rate q1 within the time interval Δt.

[0110] Input event x into a probabilistic common factor gate t The functions x, cc1(t), q1(t), and output event y(t) have two states: state 0 is the normal working state, and state 1 is the fault state. Based on x... t The relationship between the inputs and outputs of y(t), cc1(t), q1(t), and y(t) yields a list of quantitative operational rules for the probabilistic common factor gate, as shown in Table 2.

[0111] Table 2: List of Quantitative Calculation Rules for Probability Common Factor Gates

[0112]

[0113] 2) Quantitative calculation formula for probabilistic common-cause failure logic gates

[0114] Based on the state matrix of the probabilistic common-cause failure logic gate, the following set of differential equations can be obtained.

[0115]

[0116] P0(t), P1(t), P2(t), P3(t), and P4(t) represent the five solutions to the system of equations; P'0(t), P'1(t), P'2(t), P'3(t), and P'4(t) are the derivatives of P0(t), P1(t), P2(t), P3(t), and P4(t), respectively.

[0117] Solving the above system of equations yields the following quantitative calculation formula for probabilistic common-cause failure logic gates:

[0118]

[0119] S3. Determine the failure rate and repair rate of each component in the diesel engine system: Determine the repair and failure logic relationship between components, use a direct algorithm and the derived common cause failure logic gate quantitative calculation formula to obtain the transient availability of the repairable dynamic fault tree top event;

[0120] That is: establish the state transition matrix of the repairable component, obtain the availability of the repairable component at time t from the state transition, and use a direct algorithm and the derived formula for the common cause failure logic gate to calculate the transient availability of the repairable dynamic fault tree top event (i.e., the success probability of the diesel engine electronic control system); step S3 specifically includes:

[0121] S31. Determine the repairability of each component in the diesel engine system: Establish the state transition matrix of the repairable component, and obtain the availability of the repairable component at time t from the state transition;

[0122] Assume that components in a complex repairable system have only two states: a normal, usable state and a failed state, λ. E and μ E If so, the available state and the failed state of the repairable component are 0 and 1 respectively.

[0123] The state transition matrix of the repairable component is as follows:

[0124]

[0125] According to Markov's theorem for repairable systems, the state matrix of a repairable component can be transformed into:

[0126]

[0127] Where P0′(t) and P1′(t) are the derivatives of P0(t) and P1(t), respectively. P0(t) and P1(t) represent the two solutions to the system of equations.

[0128] By performing an L-transform on both sides of the above formula, we can obtain the system of equations:

[0129]

[0130] Given (P0(0), P1(0)) = (1, 0), we can solve for:

[0131]

[0132] Given the initial conditions, the availability A(t) of the repairable component at time t is:

[0133]

[0134] S32. The transient availability of the repairable dynamic fault tree top event is obtained by using a direct algorithm and a quantitative calculation formula derived from the common cause failure logic gate.

[0135] Assume the probability of the unit output working normally is A(t), and the probability of shutdown is... There are n bottom event units under the top event, and the failure logic of the bottom event units is OR (or logic). The probability that the top event works normally at time t is P(t) = A1(t)·A2(t)·...·A n (t). Then there are n bottom event units under the top event, and the failure logic of the bottom event units is AND (AND logic). The probability of the top event being in a shutdown state at time t is...

[0136] S4. Use the downlink method to find the minimum cut sets of the repairable dynamic fault tree, and the probability importance of each minimum cut set; this step S4 specifically includes:

[0137] S41. Use the minimum cut set algorithm to find the minimum cut set that can repair the dynamic fault tree;

[0138] The minimum cut set algorithm for fault trees calculates the set of all combinations of failure events in the fault tree. This includes methods such as static-dynamic transformation, uplink / downlink transformation, binary decision graph transformation, timing operator method, and topological sorting. The static-dynamic transformation method is typically chosen and calculated using the following formula:

[0139]

[0140] In the above formula, l represents the number of basic events in the fault tree, and i represents the number of basic events x. i The number of vectors; j is the number of minimal cut sets; v j For x i The minimum cut set; φ(x) is the structure function of the repairable dynamic fault tree;

[0141] S42. Quantify the importance of each component in a repairable dynamic fault tree using component importance theory;

[0142] The component importance in a fault tree quantifies the importance of each component in the system, including: probabilistic importance, structural importance, backpropagation (BP) importance, and forward complication (CP) importance. Probabilistic importance is typically chosen and calculated using the following formula:

[0143] Probability Importance Formula:

[0144]

[0145] In the formula, I R (z) represents the probabilistic importance of component z; h(R) represents the reliability function of component z; R z Let z be the minimum path set of component z.

[0146] By calculating the component importance using a repairable dynamic fault tree, the significance of each component to the failure of the entire system can be obtained. Ranking the component importance facilitates the identification of weaknesses in the system's reliability design and allows for the proposal of targeted compensation measures, thereby supporting the development of reliability improvement strategies.

[0147] S5. Calculate the importance of the repairable dynamic fault tree structure, and calculate the repair importance of components using a multi-criteria compromise solution ranking method; specifically including:

[0148] S51. Calculate the importance of the repairable dynamic fault tree structure:

[0149] Suppose the state of the b-th component X changes from 0 to 1, the corresponding state change of the diesel engine system is Q. b (X);

[0150] The structural importance of the component is:

[0151] In the above formula, 'a' represents the number of cut-order sets.

[0152] S52. Calculate the maintenance importance of components using the multi-criteria compromise solution ranking method;

[0153] The importance level (v) of the unit component needs to be selected based on the actual situation of the system unit. 1f Repair rate v 2f Repair costs v 3f Occurrence frequency v 4f As an evaluation index for the importance of maintenance; where v 3f and v 4f The indicator score is obtained from expert scores, and the weights of the scores are assigned based on expert experience. The structural importance of each component obtained in step S51 is substituted into the unit component importance score.

[0154] Establish the decision matrix D.

[0155]

[0156] In the above formula, v 11 ,v 12 ,...v df These are the evaluation indicators, corresponding to the f-th evaluation indicator in the component with serial number d.

[0157] The decision matrix D is standardized using the following formula.

[0158]

[0159] In the above formula, p is the number of components participating in the evaluation, and g is the number of components participating in the evaluation.

[0160] Obtain the standardized decision matrix r df ;

[0161] Calculate the positive ideal solution r for each evaluation index. + and negative ideal solution r - .

[0162]

[0163] In the above formula, F is the minimum ordinal value of the evaluation index, and F' is the maximum ordinal value of the evaluation index.

[0164] S d Given the absolute values ​​of the positive and negative ideal solutions, the distance ratio R between the positive and negative ideal solutions of each component is calculated using the following formula. d :

[0165]

[0166] In the above formula, l represents the number of evaluation indicators, and w df Let f be the weight of the centrality criterion for the evaluation index with ordinal number f in the d-th component.

[0167] The benefit ratio is calculated using the following formula: v d Let be the decision mechanism coefficient of the "majority criterion" strategy for the d-th component.

[0168]

[0169] in,

[0170] Finally, based on the benefit ratio Q of each component d Rank the maintenance importance.

[0171] S6. Based on the maintenance importance of the aforementioned components, common-cause failure analysis of the diesel engine system is performed. This identifies the weak component units of the diesel engine system, contributing to the improvement of the reliability of the diesel engine system throughout its entire life cycle.

[0172] In this embodiment, MATLAB 2019b is used as the simulation software to simulate the reliability assessment of the diesel engine electronic control system when considering both dynamic maintenance and fault characteristics. The deterministic common cause failure logic gate and probabilistic common cause failure logic gate of the repairable dynamic fault tree of the present invention are compared with the repairable dynamic fault tree that does not consider common cause failures, and the availability quantitative analysis value of the diesel engine electronic control system based on the repairable dynamic fault tree model is output.

[0173] This embodiment assumes that the diesel engine electronic control system and components operate in two states: fault and normal, and that the component failure rate and repair rate follow an exponential distribution. For example... Figure 5 The diagram shown is a schematic of the diesel engine electronic control system. The components include: start signal x1, control signal x2, foot pedal signal x3, intercom device x4, power supply x5, backup power supply x6, controller x7, sensor system x8, actuator x9, and fuel cut-off solenoid valve x1. 10 Its failure rate (10) -3 / h -1The values ​​were 0.082, 0.07, 0.05, 0.064, 0.04, 0.04, 0.05, 0.01, 0.022, and 0.07, respectively, with a repair rate ( / h). -1 The values ​​are 1.3, 1.5, 0.8, 0.5, 0.6, 0.6, 1.5, 0.85, 0.96 and 0.8 respectively.

[0174] In the deterministic common-cause failure model, the β factor is assumed to be 0.2, and the corresponding virtual maintenance rate μ is set to 0.2. In the probabilistic common-cause failure model, C1 and P1 are set to 0.02 and 0.5, respectively, and their equivalent maintenance rates μ1 and μ2 are set to 0.2 and 0.5, respectively.

[0175] Minimal cut set of RDFTA without considering CCF:

[0176] K1={x1},K2={x2},K3={x3},K4={x4},K5={x7},K6={x8},K7={x9},K8={x 10},K9={x5,x6},K 10 ={x8,x9,x 10}

[0177] Consider the minimum cut set of the RDFTA of CCF:

[0178] K1={x1},K2={x2},K3={x3},K4={x4},K5={x7},K6={x8},K7={x9},K8={x 10},K9={C,x5},K 10 ={x8,x9,x 10}

[0179] Consider the minimum cut set of the RDFTA of PCCF:

[0180] K1={x1},K2={x2},K3={x3},K4={x4},K5={x7},K6={x8},K7={x9},K8={x 10},K9={x6,x5},K 10 ={CC1,P1}K 11 ={CC1,P1},K 12 ={x8,x9,x 10}

[0181] Figure 8The data shows that the availability of the electronic control system (ECU) is higher when deterministic common-cause failure is not considered than when deterministic common-cause failure is considered. This indicates that deterministic common-cause failure has a significant impact on the reliability of diesel engine ECUs. However, considering the realities of complex systems, when deterministic common-cause failure does not completely lead to system failure, the availability when considering probabilistic common-cause failure is higher than that when considering deterministic common-cause failure, but lower than that when deterministic common-cause failure is not considered. Figure 8 The analysis results show that probabilistic common-cause failure is more consistent with the actual situation of complex repairable systems.

[0182] Figure 9 The maintenance importance of diesel engine electronic control system components is presented for consideration of deterministic common-cause failures, deterministic common-cause failures, and probabilistic common-cause failures. The figure shows the maintenance importance of redundant components, with C1 and P1 having the highest maintenance importance in the probabilistic common-cause failure model. This concludes that in redundant systems, the impact of probabilistic common-cause failures on system reliability should be considered, reducing the deviation between the results of repairable dynamic fault tree analysis and actual conditions.

[0183] The simulation results above clearly show that the diesel engine common cause failure analysis method based on repairable dynamic fault tree proposed in this invention can quickly and accurately calculate the availability and maintenance importance of the common cause failure of redundant systems, which is more in line with the reliability analysis of redundant systems in actual situations.

[0184] In summary, the diesel engine common cause failure analysis method based on repairable dynamic fault tree of the present invention has high accuracy and strong universality, and can accurately assess the reliability of diesel engines under the influence of common cause failure.

[0185] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A diesel engine common cause failure analysis method based on a repairable dynamic fault tree, characterized by, Includes the following steps: S1. Analyze the principle and structure of the diesel engine system to identify the repairable top event of the dynamic fault tree; S2. Select the common cause failure model based on the actual situation of the diesel engine system, and derive the quantitative calculation formula of the common cause failure logic gate using the Markov repairable system. S3. Determine the failure rate and repair rate of each component in the diesel engine system: Determine the repair and failure logic relationship between components, use a direct algorithm and the derived common cause failure logic gate quantitative calculation formula to obtain the transient availability of the repairable dynamic fault tree top event; S4. Use the downlink method to find the minimum cut sets of the repairable dynamic fault tree, and the probability importance of each minimum cut set; S5. Calculate the importance of the repairable dynamic fault tree structure and use the multi-criteria compromise solution ranking method to calculate the repair importance of components. S6. Based on the maintenance importance of the components, perform common cause failure analysis on the diesel engine system; In step S2, selecting a common cause failure model based on the actual situation of the diesel engine system specifically includes: First assume The probability of a common cause occurring is called a triggering event; This represents the probability that a related basic event is forced to occur when the triggering event occurs; n takes the value of a positive integer. The probability of a component failing independently. This represents the probability of component failure occurring; the formula for calculating probabilistic common-cause failure at the component level is: （1） If If both are 1, the common cause failure model is selected as a deterministic common cause failure model, otherwise as a probabilistic common cause failure model. Step S3 includes: S31. Determine the repairability of each component in the diesel engine system: Establish the state transition matrix of the repairable component, and obtain the availability of the repairable component at time t from the state transition; S32. Determine the failure rate of each component in the diesel engine system: Use a direct algorithm and the derived common-cause failure logic gate quantitative calculation formula to obtain the transient availability of the repairable dynamic fault tree top event; In step S5, the importance of the repairable dynamic fault tree structure is calculated, including: Suppose the state of the b-th component X changes from 0 to 1, the corresponding state change of the diesel engine system is as follows: ； The structural importance of the component is then: In the formula, a represents the number of cut-order sets; In step S5, the component maintenance importance is calculated using a multi-criteria compromise solution ranking method, including: setting... Here, d is the component ordinal number, and f is the evaluation index ordinal number; The importance of unit components needs to be selected based on the actual situation of the diesel engine system. Repair rate Repair costs Frequency of occurrence As an evaluation indicator of the importance of maintenance; among which and The indicator scores are obtained from expert ratings; Substitute the structural importance of each component into the unit component importance; Establish decision matrix D: In the above formula, These are the evaluation indicators, corresponding to the f-th evaluation indicator in component number d; The above formula is brought into the following formula for normalization: The above formula is brought into the following formula for normalization: p is the number of components involved in the evaluation, and g is the number of participants involved in the evaluation. obtaining a normalized decision matrix ; calculating the positive ideal solution of each evaluation index and the negative ideal solution : F is the minimum value of the evaluation index ordinal number, is the maximum value of the evaluation index ordinal number; The distance ratio of the positive and negative ideal solutions of each component is calculated by the following formula : l is the number of evaluation indexes, is the weight of the centrality criterion of the evaluation index with the sequence number f in the dth component. Compute benefit ratio: Decision mechanism coefficient for the most criterion strategy of the dth component; wherein ; Finally, the importance of each component is ranked according to the benefit-to-cost ratio for repair.

2. The diesel common cause failure analysis method based on the repairable dynamic fault tree according to claim 1, characterized in that, Step S1 includes: S11. A diesel engine electronic control system is used to monitor the real-time operating status of the diesel engine oil; S12. The diesel engine electronic control system is regarded as a unit connected in series with the diesel engine, and the fault of the diesel engine electronic control system is selected as the top event of the repairable dynamic fault tree.

3. The diesel common cause failure analysis method based on the repairable dynamic fault tree according to claim 2, characterized in that, In step S2, the quantitative calculation formula for the common-cause failure logic gate is derived using the Markov repairable system, including: S21. Derive the quantitative calculation formula for deterministic common-cause failure logic gates; S22. Derive the quantitative calculation formula for probabilistic common-cause failure logic gates.

4. The diesel common cause failure analysis method based on the repairable dynamic fault tree according to claim 1, characterized in that, Step S4 includes: S41. The minimum cut set of the repairable dynamic fault tree is calculated using the static-dynamic transformation method by the following formula; In the above formula, l represents the number of basic events in the fault tree, and i represents the number of basic events. The number of vectors; j is the number of minimal cut sets; for The minimum cut set; A structure function for repairable dynamic fault trees; S42. Calculate the probability importance of each minimal cut set using the probability importance formula. Probability Importance Formula: In the formula, Let be the probabilistic importance of component z; h(R) is the reliability function of component z; Let z be the minimum path set of component z.

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