Methods for reliability analysis of a technical system

Abstract

Methods for determining the reliability of a technical system using fault tree analysis, comprising the following steps: S1 - Defining basic events of fault tree analysis; S2 - for each basic event, defining a fuzzy linguistic variable and a set of membership functions; S3 - at least partially based on real-time embedded software, defines a minimal cutting set for linguistic fault tree analysis; S4 - at least partially based on the minimum intersection theorem, determining the reliability of the technical system. Furthermore, the invention relates to a control unit, vehicle system, a computer program product and a computer-readable medium for executing the method.

Description

[0001] The present invention relates to a method for the reliability analysis of a technical system. The invention further relates to a control unit, a vehicle system, a computer program product, and a computer-readable medium for executing the method. State of the art

[0002] Fault Tree Analysis (FTA) is a standardized method for assessing the overall reliability of a non-redundant technical system composed of numerous functional units. For this analysis, the technical system is modeled as a tree-like logical chain of causative events or basic events that can culminate in an undesired event (system failure). "Tree-like" means that, for example, system failure occurs when a specific logical chain of events is true, and these events can, in turn, be logical chains of subordinate events. The basic events encompass malfunctions of individual functional units.

[0003] In conventional fault tree analysis, failure probabilities are considered as exact values, i.e., as single estimates or fixed values. However, it can sometimes be difficult to estimate an exact failure rate of components, for example, if sufficient data is lacking or the characteristics of the events are vague. This can be particularly critical during the design phase, when the details of the components may not yet be finalized and therefore an exact failure rate is unknown.

[0004] It is an object of the invention to provide an alternative or improved method for the reliability analysis of a technical system, as well as a control unit of a technical system, a computer program product for carrying out the method, and a computer-readable medium. Disclosure of the invention

[0005] The object of the invention is solved by means of a method according to claim 1, by a control unit according to claim 8, by a vehicle system according to claim 9, by a computer program product according to claim 10, and by a computer-readable medium according to claim 11. Advantageous further developments, additional features and / or advantages of the invention will become apparent from the dependent claims and the following description.

[0006] According to a first aspect, the present disclosure discloses a method for determining the reliability of a technical system using fault tree analysis, comprising the steps: S1 - Defining basic events of fault tree analysis; S2 - for each basic event, defining a fuzzy linguistic variable and a set of membership functions; S3 - at least partially based on real-time embedded software, defines a minimal cutting set for linguistic fault tree analysis; S4 - at least partially based on the minimum intersection theorem, determining the reliability of the technical system.

[0007] Step S3 may include determining a set of identifiable system errors.

[0008] Step S4 may include determining the degrees of possibility of the identified system errors.

[0009] Step S4 may include summing the degrees of possibility of the identified system failures.

[0010] Step S1 can include the acquisition of sensor data corresponding to the basic events.

[0011] The procedure may include the following step: S5 - During the operation of the technical system, transmitting information regarding the reliability of the technical system to a user of the technical system, preferably by visual, acoustic, and / or haptic means.

[0012] The procedure may include the following step: S6 - During the operation of the technical system, recording and / or storing the reliability of the technical system.

[0013] According to another aspect, the present disclosure discloses a control unit of a technical system that is configured to perform the procedure described above.

[0014] According to a further aspect, the present disclosure discloses a vehicle system comprising: a control unit described above; a sensor system comprising at least one sensor unit which is configured to detect measured quantities of at least one operating quantity of the vehicle system and to transmit them to the control unit.

[0015] According to another aspect, the present disclosure discloses a computer program product for carrying out the above-described method, if the computer program product is executed by a control unit of a vehicle system or is stored on a computer-readable data carrier.

[0016] According to another aspect, the present disclosure discloses a computer-readable medium on which a computer program product as defined above is stored. Brief description of the characters

[0017] The invention is explained in more detail below with reference to exemplary embodiments and the accompanying schematic drawing, which is not to scale. The figures (Fig.) in the drawing are merely examples and show: Fig. 1. An example of a technical system; Fig. 2 a schematic representation of a fault tree analysis; Fig. 3 a schematic representation of a linguistic variable; Fig. 4 a schematic flowchart of a procedure for determining the reliability of a technical system;

[0018] Based on the Fig. Sections 1 to 4 below schematically describe the structure and operation of a method for the reliability analysis of a technical system. The technical system 1 can be a vehicle system, such as a brake control system, which performs functions like an electronic stability program (ESP) or an anti-lock braking system (ABS).

[0019] The monitoring of the technical system 1 is usually carried out by a large number of sensors arranged at different points in the technical system 1, which transmit sensor data to a control unit of the technical system 1.

[0020] In the Fig. In the embodiment shown in Figure 1, the technical system 1 is an ESP module, at which sensor data are determined by sensor units not shown at the locations shown by reference symbols A to E and transmitted to a control unit.

[0021] In the state of the art, for example a fault tree analysis (FTA) can be carried out to assess the reliability of the technical system 1. Fig. Figure 2 schematically illustrates the generally known procedure in this context. At the apex of the fault tree topology 1' is a top event 11. Top event 11 represents an undesired event, for example, the total failure of the technical system 1. Top event 11 is identified, for example, within the framework of a hazard analysis and is defined by so-called "requirements" that describe the requirements for the reliability of the technical system 1. According to Fig. 2. Five basic events A' to E' are shown as examples, relating to the in Fig. The fault tree analysis refers to the locations in the technical system 1 shown in Figure 1, which are represented by sensors, and describes potential technical problems at these locations. For example, the basic events A' to E' could involve the leakage of brake fluid through seals located at the corresponding locations A to E. This can occur with varying probabilities and can be monitored by sensors located at locations A to E that measure the brake fluid pressure. If, for example, it is determined that a maximum permissible brake fluid pressure is exceeded at location B, the fault tree analysis assumes that the undesired basic event of brake fluid leakage has occurred at location B.Connections between the basic events A' to E' are represented by logical AND operators and / or OR operators 12, where the arrangement of the basic events and the operators in the figure is merely exemplary and in a real fault tree topology usually has several nested levels.

[0022] The parameters affecting the redundant technical system 1 are highly uncertain: The system components considered in the software processing chain exhibit uncertain dependencies and correlations. To address these uncertainties, it would be appropriate to apply fuzzy logic-based mathematical and data processing structures. Purely homological results (i.e., those obtained without fuzzy methods) are incapable of representing the essential boundary conditions of real-world system operation.

[0023] The inventors have found that in certain chassis control applications, simple binary logic rules implemented in the control unit are superior to many machine and neural learning algorithms, both in terms of the accuracy and generalizability of the predictions.

[0024] In some applications, fuzzy logic rules have proven to be more accurate. However, the classic fuzzy fault tree cannot be used for real-time testing of embedded systems. The main reason for this is the convergence of the fuzzy membership functions, which occurs as a consequence of their heterogeneity, and their absence when determining the minimum cutting set, that is, the sequence of basic events leading to the top event.

[0025] In known fuzzy FTAs, the basic events are characterized by a single fuzzy membership function. This leads to problems in determining system reliability and does not allow for embedded real-time applications. The method proposed here uses a linguistic FTA and a set of membership functions, which accelerates the reliability determination. However, the system for evaluating the linguistic FTA and the embedded algorithm must be structured completely differently than in known fuzzy FTAs.

[0026] Therefore, a new FTA method is presented here, in which a series of fuzzy membership functions describe the uncertainty and reliability of all basic events in the fault tree. To decide which logical system to use, it is proposed to introduce linguistic variables for a linguistic FTA. Based on the FTA approach, the simplest possible description of the sensor data can thus be used without compromising accuracy and reliability.

[0027] In general, a fuzzy system is a system whose variables (or at least some of them) span states that are fuzzy rather than real. These fuzzy numbers can include linguistic terms like "very small," "medium," and so on, depending on their interpretation within a specific context. In this case, the variables are called "linguistic variables." Each linguistic variable is defined by a basic variable whose values ​​are real numbers within a certain range. A basic variable is a variable in the usual sense, for example, any physical variable such as temperature, pressure, electric current, or magnetic flux, or any other numerical variable such as interest rate, blood count, age, or power.In the case of a linguistic variable, linguistic concepts that represent approximate values ​​of a basic variable that is important for a particular application are captured by approximate fuzzy numbers.

[0028] Each linguistic variable comprises the following elements: - a name that should reflect the meaning of the basic variables involved; - a basic variable with its range of values ​​(a closed interval of real numbers); - a set of linguistic terms that refer to values ​​of the basic variables; - a semantic rule that assigns meaning to each linguistic term - namely a corresponding fuzzy number defined on the domain of basic variables.

[0029] An example of a linguistic variable is in Fig. 3 is shown. The linguistic variable is defined at 32. In the example of the Fig. 3 is its name “performance”, which reflects the meaning of the associated basic variable – a variable that expresses the performance (plotted on the abscissa 37 as a percentage) of a goal-oriented unit in a specific context using real numbers in the interval [0,100], for example, a person, a machine, an organization, or a method. Linguistic values ​​or states 31 of the linguistic variables are as in Fig. 3 is shown at reference marker 40 “very small”, at 41 “small”, at 42 “medium”, at 43 “large”, and at 44 “very large”. Each of these linguistic terms is assigned one of the trapezoidal fuzzy membership functions 35 by a semantic rule, as shown at reference marker 34.

[0030] A method is proposed here that incorporates a range of fuzzy membership functions for linguistic variables in FTA analysis. The underlying technical problem can, for example, involve the analysis of the... Fig. The technical system shown in Figure 1 and its associated fuzzy fault tree are used to determine its reliability. The proposed method allows for the determination of reliability in real time.

[0031] Due to the different membership functions (trapezoidal, triangular, Gaussian, etc.), the inclusion of logical AND and OR, the determination of the minimum intersection set in the fuzzy FTA method, and the ordering of possible variations, convergence problems can arise. One goal of the proposed method is to determine the optimal reliability of a redundant system in an embedded manner in real time.

[0032] The proposed procedure has the following advantages: 1. The given basic event can be characterized by more than a single fuzzy distribution; 2. The redundancy and optimum of linguistic fault trees, as well as the degree of system reliability, can be determined more effectively than with known methods; 3. The method allows for real-time embedding based on a series of membership functions.

[0033] Let Ψ be a linguistic variable that, in the case of the in Fig. The technical system shown in 1 is represented by the following triplet: Ψ=(δ,ℝM×N,L)

[0034] The following applies: - δ is a simple variable representing a matrix and corresponding to a segment y defined in a reference space ℝ. This means that this variable contains the error limits of the given error of the system; - ℝ M×N= {x|x = [d ij ], 1 ≤ i ≤ M,1 ≤ j ≤ N} is the set of all failure matrix values ​​(basic events) that δ can take; - L = (L1, L2,..., L m , ..., L M} is a finite set consisting of fuzzy sets L m consists, that is, the set of different identifiable errors that characterize the variable δ and define its range of values ​​in ℝ M×N define. This is therefore realized through the series of fuzzy membership functions for a basic event.

[0035] L m is a fuzzy set defined a priori by a set of membership functions µ that assign a function to each element x ∈ ℝ M×N the degree µ Lm (x) assign to which x corresponds to L m belongs (in a range [0,1]): μLm(x):ℝM×N→[0,1];

[0036] This can either be written in the form of an ordered pair: Lm={(μLm(x));x∈ℝM×N}={(μLm([dij]),[dij];[dij]∈ℝM×N,);∈ℝM×N,1≤i≤M,1≤j≤N},

[0037] Or in additive continuous notation: Lm=∫xμLm(x)x=∫[dij]μLm([dij])[dij]

[0038] The identification decision is determined using fuzzy elementary statements, such as: "(The point matrix) δ is (with respect to system failure) L m “

[0039] Such a statement is an a posteriori description that vaguely describes the system error used to segment y and the degree of membership of the variable δ to the error L. m indicates.

[0040] If you consider every system error L m assigns a distribution of possibilities to a fuzzy elementary statement as follows: ∀x∈ℝM×N,πδ,Lm(x)=μLm(x);

[0041] Then an identification decision can be made after determining the degree of possibility π. δ,Lm (x) calculated with the δ for each system error L m This can be achieved by directly applying uncertainty-based fusion techniques to the matrix point values ​​of the variable δ.

[0042] Taking into account that each valuation value is a ij Since the matrix δ represents a language probability value, these values ​​can be normalized to represent possibility values ​​x. ij to be considered: xij=dijmaxk∈[1,M]dkj

[0043] In this way, the degree of possibility π can be δ,Lm (x) for each system failure L m calculated and specified by merging all possible values ​​into δ.

[0044] During the linguistic FTA process, the elements of the fuzzy FTA system are significantly modified. Regarding Fig.Section 4 below describes a schematic flowchart of the procedure. 1. S1 → Fault tree analysis based on a given system problem, defining basic events “B, C, D, E” 2. S2 → For each basic event, define a fuzzy linguistic variable and a set of membership functions. 3. S3 → Based on real-time embedded software, define a minimal cutting set for linguistic fault tree analysis. 4. S4 → Output of optimal reliability in a real-time embedded environment, based on the minimum intersection set of linguistic variables.

[0045] The invention is not limited to the described and illustrated embodiments. Rather, it also encompasses all further developments by skilled craftsmen within the scope of the invention defined by the claims. In addition to the described and illustrated embodiments, further embodiments are conceivable, which may include further modifications and combinations of features.

Claims

[1] Method for determining the reliability of a technical system using fault tree analysis, comprising the steps: S1 - Defining basic events of fault tree analysis; S2 - for each basic event, defining a fuzzy linguistic variable and a set of membership functions; S3 - at least partially based on real-time embedded software, defines a minimal cutting set for linguistic fault tree analysis; S4 - at least partially based on the minimum intersection theorem, determining the reliability of the technical system. [2] Method according to claim 1, characterized by , that step S3 includes determining a set of identifiable system errors. [3] Method according to claim 2, characterized by , that step S4 includes determining the degrees of possibility of the identified system errors. [4] Method according to claim 3, characterized by, that step S4 includes summing the degrees of possibility of the identified system errors. [5] Method according to claim 4, characterized by , that in step S1 corresponding sensor data is recorded with the basic events. [6] Method according to any one of claims 1 to 5, comprising the step: S5 - During the operation of the technical system, transmitting information regarding the reliability of the technical system to a user of the technical system, preferably by visual, acoustic, and / or haptic means. [7] Method according to any one of claims 1 to 6, comprising the step: S6 - During operation of the technical system, recording and / or storing the reliability of the technical system. [8] Control unit of a technical system configured to perform the method according to any one of claims 1 to 7. [9] Vehicle system comprising: a control unit according to claim 8; a sensor system, comprising at least one sensor unit, which is designed to capture measured values ​​of at least one operating parameter of the vehicle system and transmit them to the control unit. [10] Computer program product for carrying out the method according to one of claims 1 to 7, if the computer program product is executed by a control unit of a vehicle system or is stored on a computer-readable data carrier. [11] Computer-readable medium on which a computer program product according to claim 10 is stored.

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