A method and system for evaluating the estimated reliability of a system in a non-working state

Abstract

The present invention relates to a method and system for evaluating the predicted reliability of a system in a non-working state. The method comprises: obtaining failure rate models of different electronic components; determining a reliability model according to the failure rate model; obtaining coupling relationships between different electronic components; and determining the reliability of the entire system according to the reliability model and the coupling relationship. The present invention can quickly and efficiently handle the predicted reliability evaluation work under different systems.

Description

Technical Field

[0001] The present invention relates to the field of reliability assessment, and in particular to a method and system for assessing the estimated reliability of a system in a non-working state. Background Art

[0002] In modern weapons and equipment evaluation and military confrontation, reliability assessment is extremely complex. There are various types of failure rates and degradation models. There are many models and data that need to be processed during the evaluation process. In order to achieve the effective application of various models and methods, facilitate the traceability of the evaluation process and reduce duplication of work, it has become a problem that system-level predictive reliability assessment needs to face.

[0003] Nowadays, it is uncommon to set failure rates in models for system reliability assessment, and there are no publications or reports on how to couple the individual reliabilities of these electronic components to obtain system-level reliability. Summary of the invention

[0004] The purpose of the present invention is to provide a method and system for evaluating the predicted reliability of a system in a non-working state, modeling failure rates and reliabilities of different levels and types, selecting different reliability models and combination relationships according to different systems and electronic components, and quickly and efficiently evaluating the system reliability.

[0005] To achieve the above object, the present invention provides the following solutions:

[0006] A method for evaluating the estimated reliability of a system in a non-operating state includes:

[0007] Obtain failure rate models of different electronic components, wherein the electronic components include switches, diodes, piezoelectric gyroscopes, batteries, and mechanical filters, and the failure rate models include switch model failure rate models, diode model failure rate models, piezoelectric gyroscope model failure rate models, battery model failure rate models, and mechanical filter model failure rate models;

[0008] Determining a reliability model according to the failure rate model, wherein the reliability model includes an exponential model, a lognormal distribution model, a Weibull model and a bathtub model;

[0009] Obtain the coupling relationship between different electronic components;

[0010] The reliability of the entire system is determined based on the reliability model and the coupling relationship.

[0011] Optionally, the switch model failure rate model is:

[0012] λ p =(λ b1 +λ b2 )πE π Q π L π CYC

[0013] In the formula, λ b1 is the basic failure rate of the switch drive mechanism, λ b2 is the basic failure rate of the switch active grounding, π E is the environmental factor, π Q is the mass coefficient, π L is the contact load factor, π CYC is the switching rate coefficient;

[0014] The diode model failure rate model is:

[0015]

[0016] In the formula, λ b is the basic failure rate, π E is the environmental factor, π Q is the mass coefficient, π r is the rated current coefficient, π A is the application coefficient, is the voltage stress coefficient, π c is the structural coefficient;

[0017] The failure rate model of the piezoelectric gyroscope model is:

[0018] λ p =(λ b1 +λ b2 )π C π A π k π E π L

[0019] In the formula, λ b1 is the basic failure rate of the piezoelectric gyro sensitive device, λ b2 Basic failure rate of the rear circuit of the piezoelectric gyroscope, π C Complexity coefficient, π k Structural coefficient, π E is the environmental factor, π A is the application coefficient, π L is the maturity coefficient;

[0020] The battery model failure rate model is:

[0021] λ p =λ b π E π Q

[0022] In the formula, λb is the basic failure rate, π E is the environmental factor, π Q is the quality coefficient;

[0023] The mechanical filter model failure rate model is:

[0024] λ p =λ b π E π Q π f

[0025] In the formula, λ b is the basic failure rate, π E is the environmental factor, π Q is the mass coefficient, π f is the frequency coefficient.

[0026] Optionally, the exponential model is The Weibull model is Among them, F(t) is the reliability of the reliability model, λ p is the failure rate of the failure rate model, t is the time starting from the ideal state of the component, that is, when the reliability is 1, and γ is the distribution shape parameter.

[0027] Optionally, the coupling relationship includes a series coupling relationship, a parallel coupling relationship and a hybrid coupling relationship.

[0028] A system for evaluating the estimated reliability of a system in a non-operating state comprises:

[0029] A failure rate model acquisition module is used to acquire failure rate models of different electronic components, wherein the electronic components include switches, diodes, piezoelectric gyroscopes, batteries and mechanical filters, and the failure rate models include switch model failure rate models, diode model failure rate models, piezoelectric gyroscope model failure rate models, battery model failure rate models and mechanical filter model failure rate models;

[0030] A reliability model determination module, used to determine a reliability model according to the failure rate model, wherein the reliability model includes an exponential model, a lognormal distribution model, a Weibull model and a bathtub model;

[0031] A coupling relationship acquisition module is used to acquire the coupling relationship between different electronic components;

[0032] The reliability determination module is used to determine the reliability of the entire system according to the reliability model and the coupling relationship.

[0033] Optionally, the switch model failure rate model is:

[0034] λp =(λ b1 +λ b2 )π E π Q π L π CYC

[0035] In the formula, λ b1 is the basic failure rate of the switch drive mechanism, λ b2 is the basic failure rate of the switch active grounding, π E is the environmental factor, π Q is the mass coefficient, π L is the contact load factor, π CYC is the switching rate coefficient;

[0036] The diode model failure rate model is:

[0037]

[0038] In the formula, λ b is the basic failure rate, π E is the environmental factor, π Q is the mass coefficient, π r is the rated current coefficient, π A is the application coefficient, is the voltage stress coefficient, π c is the structural coefficient;

[0039] The failure rate model of the piezoelectric gyroscope model is:

[0040] λ p =(λ b1 +λ b2 )π C π A π k π E π L

[0041] In the formula, λ b1 is the basic failure rate of the piezoelectric gyro sensitive device, λ b2 Basic failure rate of the rear circuit of the piezoelectric gyroscope, π C Complexity coefficient, π k Structural coefficient, π E is the environmental factor, π A is the application coefficient, π L is the maturity coefficient;

[0042] The battery model failure rate model is:

[0043] λ p =λ p π E πQ

[0044] In the formula, λ b is the basic failure rate, π E is the environmental factor, π Q is the quality coefficient;

[0045] The mechanical filter model failure rate model is:

[0046] λ p =λ b π E π Q π f

[0047] In the formula, λ b is the basic failure rate, π E is the environmental factor, π Q is the mass coefficient, π f is the frequency coefficient.

[0048] Optionally, the exponential model is The Weibull model is Among them, F(t) is the reliability of the reliability model, λ p is the failure rate of the failure rate model, t is the time starting from the ideal state of the component, that is, when the reliability is 1, and γ is the distribution shape parameter.

[0049] Optionally, the coupling relationship includes a series coupling relationship, a parallel coupling relationship and a hybrid coupling relationship.

[0050] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0051] The present invention relates to a method and system for evaluating the estimated reliability of a system in a non-working state. The method comprises: obtaining failure rate models of different electronic components; determining a reliability model according to the failure rate model; obtaining coupling relationships between different electronic components; and determining the reliability of the entire system according to the reliability model and the coupling relationship. It can be seen that the present invention can select different failure rate models and reliability models according to different types of electronic components, and quickly and efficiently cope with the estimated reliability evaluation work under different systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0053] Figure 1 It is a flow chart of the estimated reliability evaluation method of the system in the non-working state of the present invention;

[0054] Figure 2 It is a flow chart of the algorithm for predicting the reliability of the electronic system of special equipment in non-working state;

[0055] Figure 3 It is a typical schematic diagram of system reliability model;

[0056] Figure 4 It is the reliability block diagram of the series system;

[0057] Figure 5 It is the reliability block diagram of the parallel system;

[0058] Figure 6 It is a schematic diagram of the reliability change curve;

[0059] Figure 7 It is a schematic diagram of the hybrid model;

[0060] Figure 8 is a schematic diagram of the equivalent model;

[0061] Fig. 9 It is a structural diagram of the estimated reliability assessment system of the present invention in a non-working state. DETAILED DESCRIPTION

[0062] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0063] The purpose of the present invention is to provide a method and system for evaluating the predicted reliability of a system in a non-working state, modeling failure rates and reliabilities of different levels and types, selecting different reliability models and combination relationships according to different systems and electronic components, and quickly and efficiently evaluating the system reliability.

[0064] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0065] Figure 1 FIG. 1 is a flow chart of the estimated reliability evaluation method of the system in a non-operating state of the present invention. Figure 1 As shown, a method for evaluating the estimated reliability of a system in a non-working state includes:

[0066] Step 101: Obtain failure rate models of different electronic components, wherein the electronic components include switches, diodes, piezoelectric gyroscopes, batteries, and mechanical filters, and the failure rate models include switch model failure rate models, diode model failure rate models, piezoelectric gyroscope model failure rate models, battery model failure rate models, and mechanical filter model failure rate models.

[0067] The switch model failure rate model is:

[0068] λ p =(λ b1 +λ b2 )π E π Q π L π CYC

[0069] In the formula, λ b1 is the basic failure rate of the switch drive mechanism, λ b2 is the basic failure rate of the switch active grounding, π E is the environmental factor, π Q is the mass coefficient, π L is the contact load factor, π CYC is the switching rate coefficient;

[0070] The diode model failure rate model is:

[0071]

[0072] In the formula, λ b is the basic failure rate, π E is the environmental factor, π Q is the mass coefficient, π r is the rated current coefficient, π A is the application coefficient, is the voltage stress coefficient, π c is the structural coefficient;

[0073] The failure rate model of the piezoelectric gyroscope model is:

[0074] λ p =(λ b1 +λ b2 )π C π A π k π E π L

[0075] In the formula, λ b1 is the basic failure rate of the piezoelectric gyro sensitive device, λ b2 Basic failure rate of the rear circuit of the piezoelectric gyroscope, π C Complexity coefficient, πk Structural coefficient, π E is the environmental factor, π A is the application coefficient, π L is the maturity coefficient;

[0076] The battery model failure rate model is:

[0077] λ p =λ p π E π Q

[0078] In the formula, λ b is the basic failure rate, π E is the environmental factor, π Q is the quality coefficient;

[0079] The mechanical filter model failure rate model is:

[0080] λ p =λ b π E π Q π f

[0081] In the formula, λ b is the basic failure rate, π E is the environmental factor, π Q is the mass coefficient, π f is the frequency coefficient.

[0082] Step 102: Determine a reliability model based on the failure rate model, wherein the reliability model includes an exponential model, a lognormal distribution model, a Weibull model, and a bathtub model.

[0083] The failure rate model of electronic components is selected based on experience or historical data, and the output of the failure rate model of electronic components is used as the input of the reliability model to obtain the reliability function of each subsystem that changes with time.

[0084] The exponential model is The Weibull model is Among them, F(t) is the reliability of the reliability model, λ P is the failure rate of the failure rate model, t is the time from the ideal state of the component, that is, the reliability is 1, γ is the distribution shape parameter, when γ = 1, the density function is an exponential density function, when γ = 2, the density function is a Rayleigh distribution, and selecting γ as a suitable value can be close to the normal distribution. γ is a parameter of the Weibull distribution.

[0085] Figure 2This is a flow chart of the algorithm for predicting the reliability of the electronic system of special equipment in the non-working state. Figure 2 The components in are electronic components.

[0086] Step 103: Acquire coupling relationships between different electronic components, where the coupling relationships include series coupling relationships, parallel coupling relationships, and hybrid coupling relationships.

[0087] The first step is to obtain the failure rate of a single component (the mean time between failures and the failure rate, i.e., the failure rate, are inversely proportional). The component is the aforementioned electronic component, and the failure rate is used as a parameter input for the reliability model. The subsequent series-parallel system is the series-parallel reliability model. The failure rate is the initial component parameter, and the last step is to obtain a reliability function that changes over time, which includes the failure rate parameter.

[0088] The series coupling relationship, parallel coupling relationship and hybrid coupling relationship are used to obtain the series system model, parallel system model and hybrid system model respectively. Figure 3 Schematic diagram of a typical system reliability model.

[0089] 1. Series system model

[0090] A system in which the failure of any of the units that make up the system will lead to the failure of the entire system is called a series system. A series system is one of the most common and simplest models. Figure 4 Reliability block diagram of the series system.

[0091] Mathematical model of series system:

[0092]

[0093] Where n is the total number of component units that make up the system, i is the number of the component unit, R s (t) is the reliability of the system.

[0094] When the life distribution of each unit is exponential distribution, that is:

[0095]

[0096] R i (t) is the reliability of the component unit numbered i, λ i is the failure rate of component unit numbered i.

[0097] The reliability of the system is:

[0098]

[0099] System failure rate λ s is the failure rate of each unit λ i sum:

[0100]

[0101] The mean time between failures of the system:

[0102]

[0103] It can be seen that when the life of each unit in the series system is exponentially distributed, the life of the system is also exponentially distributed. It can be seen that the system reliability is the product of the reliability of each unit. When the reliability of each unit is less than 1, the more units there are, the smaller the system reliability and the smaller the MTBF value.

[0104] 2. Parallel system model

[0105] A system that fails only when all the units that make up the system fail is called a parallel system. The parallel system is the simplest redundant system. In terms of completing the function, only one unit is needed to complete it. Setting multiple units in parallel is to improve the mission reliability of the system. However, the basic reliability of the system decreases, and the maintenance and guarantee requirements increase.

[0106]

[0107] From the above formula we can see:

[0108] (i) Reliability in parallel is equal to unreliability in series, and there is a duality between them;

[0109] (ii) The more parallel units there are, the higher the system reliability. i (t) is a value less than 1, so their continuous product becomes smaller and smaller, thus:

[0110] Getting bigger and bigger.

[0111] When the life distribution of each unit is exponential distribution, the reliability of the parallel system is:

[0112]

[0113] The mean time between failures of the system:

[0114]

[0115] For the most commonly used two-unit parallel system:

[0116]

[0117]

[0118]

[0119] It can be seen from the formula that although λ1 ,λ 2 are all constants, but the failure rate λ of the parallel system s (t) is no longer a constant.

[0120] For a parallel system of n identical units:

[0121] R s (t) = 1-(1-e λt )″

[0122]

[0123] The relationship between the parallel system reliability function and the parallel unit is as follows: Figure 5 As shown, the system reliability is significantly improved compared with a single unit without reserve, especially when n=2, the reliability is significantly improved. When there are too many parallel units, the reliability improvement speed is greatly slowed down. Figure 5 Reliability block diagram of parallel system. Figure 6 It is a schematic diagram of the reliability change curve.

[0124] 3. Hybrid system model

[0125] Engineering systems are not simply series or parallel, but also mixed models of series and parallel or parallel and series. To facilitate engineering calculations, the equivalent model method can be used. The reliability of the system can be calculated using the basic formulas of the series system and the parallel system. This is more practical for systems that are not very complex. Figure 7 Schematic diagram of the hybrid model. Figure 8 Schematic diagram of the equivalent model.

[0126] The calculation method of equivalent combination is as follows:

[0127] Connect units 1, 2, and 3 in series to form S 1 , units 4 and 5 are connected in series to form S 2 ; Units 6 and 7 are connected in parallel to form S 3 ; Then S 1 , S 2 Parallel connection into S 4 , and finally S 4 , S 3 The series connection is the reliability of the hybrid system.

[0128] Calculating the series part and the parallel part gives:

[0129]

[0130]

[0131]

[0132]

[0133] The reliability of the whole system R s for:

[0134]

[0135] For the hybrid model, the reliability of the parallel-series system is higher than that of the series-parallel system. Because in the parallel-series system, each unit in each parallel segment is a backup for each other. When one unit fails, it does not affect a parallel unit. In the series-parallel system, if one unit fails, a branch in the parallel connection will fail. Therefore, the parallel-series reserve is mainly used for protection against open circuit faults, while the series-parallel connection is mainly used for protection against short circuit faults.

[0136] Step 104: Determine the reliability of the entire system according to the reliability model and the coupling relationship.

[0137] By repeatedly applying the series-parallel hybrid model, the reliability functions of each subsystem are integrated into a reliability prediction function for the system level, and the predicted reliability of the system-level electronic class in the non-working state is obtained. The multi-level series-parallel hybrid structure under this system can be expressed as:

[0138]

[0139]

[0140]

[0141] R 混k =R 串k R 并k

[0142] The above formula determines the reliability mapping of the series-parallel hybrid coupling relationship from the component to the system. In this way, the reliability of the component can be mapped to the reliability of the system.

[0143] Fig. 9 FIG. 1 is a structural diagram of the estimated reliability evaluation system of the system in the non-operating state of the present invention. Fig. 9 As shown, a system for evaluating the estimated reliability of a system in a non-working state includes:

[0144] The failure rate model acquisition module 201 is used to acquire failure rate models of different electronic components, wherein the electronic components include switches, diodes, piezoelectric gyroscopes, batteries and mechanical filters, and the failure rate models include switch model failure rate models, diode model failure rate models, piezoelectric gyroscope model failure rate models, battery model failure rate models and mechanical filter model failure rate models.

[0145] The reliability model determination module 202 is used to determine a reliability model according to the failure rate model, wherein the reliability model includes an exponential model, a lognormal distribution model, a Weibull model and a bathtub model.

[0146] The coupling relationship acquisition module 203 is used to acquire the coupling relationship between different electronic components, where the coupling relationship includes a series coupling relationship, a parallel coupling relationship and a hybrid coupling relationship.

[0147] The reliability determination module 204 is used to determine the reliability of the entire system according to the reliability model and the coupling relationship.

[0148] The switch model failure rate model is:

[0149] λ p =(λ b1 +λ b2 )π E π Q π L π CYC

[0150] In the formula, λ b1 is the basic failure rate of the switch drive mechanism, λ b2 is the basic failure rate of the switch active grounding, π E is the environmental factor, π Q is the mass coefficient, π L is the contact load factor, π CYC is the switching rate coefficient;

[0151] The diode model failure rate model is:

[0152]

[0153] In the formula, λ b is the basic failure rate, π E is the environmental factor, π Q is the mass coefficient, π r is the rated current coefficient, π A is the application coefficient, is the voltage stress coefficient, π c is the structural coefficient;

[0154] The failure rate model of the piezoelectric gyroscope model is:

[0155] λ p =(λ b1 +λ b2 )π C π A π k π E π L

[0156] In the formula, λ b1 is the basic failure rate of the piezoelectric gyro sensitive device, λ b2 Basic failure rate of the rear circuit of the piezoelectric gyroscope, π C Complexity coefficient, π k Structural coefficient, π E is the environmental factor, π A is the application coefficient, π L is the maturity coefficient;

[0157] The battery model failure rate model is:

[0158] λ p =λ b π E π Q

[0159] In the formula, λ b is the basic failure rate, π E is the environmental factor, π Q is the quality coefficient;

[0160] The mechanical filter model failure rate model is:

[0161] λ p =λ b π E π Q π f

[0162] In the formula, λ b is the basic failure rate, π E is the environmental factor, π Q is the mass coefficient, π f is the frequency coefficient.

[0163] The exponential model is The Weibull model is Among them, F(t) is the reliability of the reliability model, λ p is the failure rate of the failure rate model, t is the time from the ideal state of the component, that is, the reliability is 1, γ is the distribution shape parameter, when γ = 1, the density function is an exponential density function, when γ = 2, the density function is a Rayleigh distribution, and selecting γ as a suitable value can be close to the normal distribution. γ is a parameter of the Weibull distribution.

[0164] This embodiment is described by taking the estimated reliability evaluation of the control system as an example.

[0165] 1. Construct a control system based on a tree structure, and set the correlation coefficient of the failure rate model of electronic components according to different types and experience of electronic components;

[0166] 2. Select different fusion models for the subsystems in the pilot control system, such as series and parallel models;

[0167] 3. Select reliability models for different electronic components and subsystems. For example, select the exponential model for the positive overload switch, and make corresponding settings for other subsystems;

[0168] 4. Finally, set the initial ideal state time and the safety threshold of system reliability, perform calculations, and obtain the estimated reliability change curve of the control system and its electronic components and subsystems over time.

[0169] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0170] The principles and implementation methods of the present invention are described in this article using specific examples. The description of the above embodiments is only used to help understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A method for evaluating the estimated reliability of a system in a non-working state, characterized in that: include: Obtain failure rate models of different electronic components, wherein the electronic components include switches, diodes, piezoelectric gyroscopes, batteries, and mechanical filters, and the failure rate models include switch model failure rate models, diode model failure rate models, piezoelectric gyroscope model failure rate models, battery model failure rate models, and mechanical filter model failure rate models; Determining a reliability model according to the failure rate model, wherein the reliability model includes an exponential model, a lognormal distribution model, a Weibull model and a bathtub model; Obtain the coupling relationship between different electronic components; Determining the reliability of the entire system according to the reliability model and the coupling relationship; According to the coupling relationship, a series system model, a parallel system model and a hybrid system model are obtained respectively; The series system model is: Where n is the total number of component units that make up the system, i is the number of the component unit, R s (t) is the reliability of the system; The parallel system model is: Where n is the total number of component units that make up the system, i is the number of the component unit, R s (t) is the reliability of the system; The equivalent combination calculation method of the hybrid system model is as follows: Connect units 1, 2, and 3 in series to form S1, connect units 4 and 5 in series to form S2, connect units 6 and 7 in parallel to form S3, then connect S1 and S2 in parallel to form S4, and finally connect S4 and S3 in series to obtain the reliability of the hybrid system. Calculating the series part and the parallel part gives: R s1 =R1R2R3 R s2 =R4R5 <h2 style=";text-align:left;direction:ltr">R<h2 style=";text-align:left;direction:ltr"> s3 <h2 style=";text-align:left;direction:ltr"> =R6+R7-R6R7 R s4 =R s1 +R s2 -R s1 R s2 The reliability of the whole system R s For: R s =R s4 R s3 .

2. The method for evaluating the estimated reliability of a system in a non-working state according to claim 1, characterized in that: The switch model failure rate model is: l p =(λ b1 +λ b2 )p E p Q p L p CYC In the formula, λ b1 is the basic failure rate of the switch drive mechanism, λ b2 is the basic failure rate of the switch active grounding, π E is the environmental factor, π Q is the mass coefficient, π L is the contact load factor, π CYC is the switching rate coefficient; The diode model failure rate model is: In the formula, λ b is the basic failure rate, π E is the environmental factor, π Q is the mass coefficient, π r is the rated current coefficient, π A is the application coefficient, is the voltage stress coefficient, π c is the structural coefficient; The failure rate model of the piezoelectric gyroscope model is: l p =(λ b1 +λ b2 )p C p A p k p E p L In the formula, λ b1 is the basic failure rate of the piezoelectric gyro sensitive device, λ b2 Basic failure rate of the rear circuit of the piezoelectric gyroscope, π C Complexity coefficient, π k Structural coefficient, π E is the environmental factor, π A is the application coefficient, π L is the maturity coefficient; The battery model failure rate model is: l p =λ b p E p Q In the formula, λ b is the basic failure rate, π E is the environmental factor, π Q is the quality coefficient; The mechanical filter model failure rate model is: l p =λ b p E p Q p f In the formula, λ b is the basic failure rate, π E is the environmental factor, π Q is the mass coefficient, π f is the frequency coefficient.

3. The method for evaluating the estimated reliability of a system in a non-working state according to claim 1, characterized in that: The exponential model is The Weibull model is Among them, F(t) is the reliability of the reliability model, λ p is the failure rate of the failure rate model, t is the time starting from the ideal state of the component, that is, when the reliability is 1, and γ is the distribution shape parameter.

4. The method for evaluating the estimated reliability of a system in a non-working state according to claim 1, characterized in that: The coupling relationship includes a series coupling relationship, a parallel coupling relationship and a hybrid coupling relationship.

5. A system for evaluating the estimated reliability of a system in a non-operating state, characterized in that: include: A failure rate model acquisition module is used to acquire failure rate models of different electronic components, wherein the electronic components include switches, diodes, piezoelectric gyroscopes, batteries and mechanical filters, and the failure rate models include switch model failure rate models, diode model failure rate models, piezoelectric gyroscope model failure rate models, battery model failure rate models and mechanical filter model failure rate models; A reliability model determination module, used to determine a reliability model according to the failure rate model, wherein the reliability model includes an exponential model, a lognormal distribution model, a Weibull model and a bathtub model; A coupling relationship acquisition module is used to acquire the coupling relationship between different electronic components; A reliability determination module, used to determine the reliability of the entire system according to the reliability model and the coupling relationship; According to the coupling relationship, a series system model, a parallel system model and a hybrid system model are obtained respectively; The series system model is: Where n is the total number of component units that make up the system, i is the number of the component unit, R s (t) is the reliability of the system, R i (t) is the reliability of the module numbered i; The parallel system model is: Where n is the total number of component units that make up the system, i is the number of the component unit, R s (t) is the reliability of the system, R i (t) is the reliability of the module numbered i; The equivalent combination calculation method of the hybrid system model is as follows: Connect units 1, 2, and 3 in series to form S1, connect units 4 and 5 in series to form S2, connect units 6 and 7 in parallel to form S3, then connect S1 and S2 in parallel to form S4, and finally connect S4 and S3 in series to obtain the reliability of the hybrid system. Calculating the series part and the parallel part gives: R s1 =R1R2R3 R s2 =R4R5 <h2 style=";text-align:left;direction:ltr">R<h2 style=";text-align:left;direction:ltr"> s3 <h2 style=";text-align:left;direction:ltr"> =R6+R7-R6R7 R s4 =R s1 +R s2 -R s1 R s2 The reliability of the whole system R s For: R s =R s4 R s3 .

6. The estimated reliability assessment system for a system in a non-operating state according to claim 5, characterized in that: The switch model failure rate model is: l p =(λ b1 +λ b2 )p E p Q p L p CYC In the formula, λ b1 is the basic failure rate of the switch drive mechanism, λ b2 is the basic failure rate of the switch active grounding, π E is the environmental factor, π Q is the mass coefficient, π L is the contact load factor, π CYC is the switching rate coefficient; The diode model failure rate model is: In the formula, λ b is the basic failure rate, π E is the environmental factor, π Q is the mass coefficient, π r is the rated current coefficient, π A is the application coefficient, is the voltage stress coefficient, π c is the structural coefficient; The failure rate model of the piezoelectric gyroscope model is: l p =(λ b1 +λ b2 )p C p A p k p E p L In the formula, λ b1 is the basic failure rate of the piezoelectric gyro sensitive device, λ b2 Basic failure rate of the rear circuit of the piezoelectric gyroscope, π C Complexity coefficient, π k Structural coefficient, π E is the environmental factor, π A is the application coefficient, π L is the maturity coefficient; The battery model failure rate model is: l p =λ b p E p Q In the formula, λ b is the basic failure rate, π E is the environmental factor, π Q is the quality coefficient; The mechanical filter model failure rate model is: l p =λ b p E p Q p f In the formula, λ b is the basic failure rate, π E is the environmental factor, π Q is the mass coefficient, π f is the frequency coefficient.

7. The estimated reliability assessment system for a system in a non-operating state according to claim 5, characterized in that: The exponential model is The Weibull model is Among them, F(t) is the reliability of the reliability model, λ p is the failure rate of the failure rate model, t is the time starting from the ideal state of the component, that is, when the reliability is 1, and γ is the distribution shape parameter.

8. The estimated reliability assessment system for a system in a non-operating state according to claim 5, characterized in that: The coupling relationship includes a series coupling relationship, a parallel coupling relationship and a hybrid coupling relationship.

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