Low-frequency power supply cabinet reliability prediction method and system based on fault physical model

Abstract

The invention discloses a low-frequency power supply cabinet reliability prediction method and system based on a fault physical model. The method comprises the following steps: analyzing common failure mechanisms of a low-frequency power supply cabinet; performing single-point fault distribution fitting of the low-frequency power supply cabinet based on the fault information; based on a single-point fault distribution fitting result, multi-point fault distribution fusion analysis is carried out, and module-level, equipment-level and system-level reliability evaluation of the low-frequency power supply cabinet is completed; and based on the module-level, equipment-level and system-level reliability evaluation results of the low-frequency power supply cabinet, constructing a low-frequency power supply cabinet reliability prediction model, and realizing multi-level reliability prediction of the low-frequency power supply cabinet. By constructing the optimal fault function of the fault mechanism, reliability evaluation of the low-frequency power supply cabinet is realized, reliability prediction of each level of the low-frequency power supply cabinet is further realized, a method for improving the reliability of the system is comprehensively determined, and the design and operation reliability of equipment is improved.

Description

Technical Field

[0001] The present application relates to the technical field of reliability engineering, and particularly relates to a reliability prediction method and system for a low-frequency power cabinet based on a physics-of-failure model. Background Art

[0002] A low-frequency power cabinet is a device used for distributing, controlling, and protecting electrical equipment in a low-voltage power system. It is mainly used for power transmission, control, protection, and monitoring of electrical equipment and lines in a low-voltage power system. It usually includes the following components: a power distribution cabinet main body, a power switch, control components, protection components, instruments, etc. Its main functions and roles include: distributing the electric energy from power sources such as generators and substations to various electrical equipment, and supplying power to different electrical equipment; controlling the equipment through control components, and real-time detecting and monitoring the system status through a monitoring system, etc.

[0003] In a nuclear power plant reactor, the low-frequency power cabinet is used for the normal startup and shutdown of the reactor, and for manually operating the control rods to be withdrawn from and inserted into the reactor core under various working conditions to change its reactivity. During the automatic regulation of the reactor power, the regulating rod groups of the rod control system receive the automatic rod speed signal and rod movement direction signal sent by the power regulation device, so as to realize the automatic tracking of the reactor power with the change of the load and maintain it at the required power level.

[0004] The low-frequency power cabinet is composed of a large number of circuit boards and electronic components of various types and quantities. If it fails due to the harsh environmental loads it bears, it will directly cause the control rods to be unable to complete their various functions, thereby affecting the safe operation of the reactor. Therefore, improving the reliability level of the low-frequency power cabinet is of crucial significance for ensuring the safety of the reactor. Conducting the reliability prediction of the low-frequency power cabinet in advance helps to realize the life tracking evaluation of the low-frequency power cabinet system and its key functional units, and design the maintenance decision-making scheme for the low-frequency power cabinet system and its key functional units.

[0005] Since most nuclear power plants are built in coastal and riverside areas, the air is humid and contains salts and chlorides, which has certain corrosiveness. Therefore, the environment where the low-frequency power cabinet is located is relatively complex, the possibility of failure increases significantly, and its health status assessment is also relatively complex. How to accurately and quickly realize the reliability prediction of the low-frequency power cabinet has become a difficult problem that needs to be solved urgently. Summary of the Invention

[0006] In order to quickly and accurately realize the reliability prediction of the low-frequency power cabinet, the present application proposes a reliability prediction method and system for a low-frequency power cabinet based on a physics-of-failure model. The present application realizes the reliability assessment of the low-frequency power cabinet by constructing an optimal failure function of the failure mechanism, and then realizes the reliability prediction at each level of the low-frequency power cabinet, comprehensively determines the method for improving the system reliability, and improves the design and operation reliability of the equipment.

[0007] On the one hand, the present application is implemented through the following technical solutions:

[0008] A reliability prediction method for a low-frequency power cabinet based on a physics-of-failure model, the method comprising:

[0009] Analyze the common failure mechanisms of the low-frequency power cabinet;

[0010] Perform single-point failure distribution fitting of the low-frequency power cabinet based on the failure information;

[0011] Based on the single-point failure distribution fitting results, carry out multi-point failure distribution fusion analysis to complete the reliability assessment of the low-frequency power cabinet at the module level, equipment level, and system level;

[0012] Based on the reliability assessment results of the low-frequency power cabinet at the module level, equipment level, and system level, construct a reliability prediction model for the low-frequency power cabinet to achieve multi-level reliability prediction of the low-frequency power cabinet.

[0013] In some embodiments, the common failure mechanisms of the low-frequency power cabinet include: solder joint fatigue failure, plated through-hole fatigue failure, vibration fatigue failure, and mechanical shock failure.

[0014] In some embodiments, the specific process of the single-point failure distribution fitting includes:

[0015] Use a stress simulation method for analysis to obtain the mean time to failure of key components and their components / units, and obtain a probability density histogram after counting the frequencies;

[0016] Fit a probability density curve according to the probability density histogram;

[0017] Determine the failure distribution according to the probability density curve; the failure distribution is a normal distribution, a lognormal distribution, an exponential distribution, or a Weibull distribution.

[0018] In some embodiments, the multi-point failure distribution fusion analysis process specifically includes:

[0019] Perform Monte Carlo random sampling based on the failure distribution function, and select the sampling time with the minimum failure time as the failure time sample according to the competing failure principle;

[0020] Perform distribution fitting on the failure time samples, and determine the optimal distribution fitting result as the optimal failure distribution function according to the AIC information criterion;

[0021] Based on the optimal distribution function, carry out reliability assessment at the module level, equipment level, and system level.

[0022] In some embodiments, the method uses a reliability block diagram model as a reliability prediction model, wherein the reliability block diagram model describes the logical relationship between unit functions and system functions based on the functional correlation between system components;

[0023] The method performs reliability analysis and evaluation on the key equipment based on the physical failure modes of the key components of the low-frequency power supply cabinet, and conducts reliability prediction from the bottom up.

[0024] In some implementations, the reliability prediction model construction process specifically includes:

[0025] Analyze the functions of the low-frequency power supply cabinet based on the module-level, device-level, and system-level reliability evaluation results, and construct a functional schematic diagram of the low-frequency power supply cabinet;

[0026] Conduct series-parallel analysis based on the functional principle diagram of the low-frequency power supply cabinet to construct a reliability block diagram of the low-frequency power supply cabinet;

[0027] The total reliability of the low-frequency power supply cabinet system is calculated using the model functions involved in the low-frequency power supply cabinet reliability block diagram.

[0028] In some implementations, the reliability block diagram model mainly includes:

[0029] The reliability calculation function of the series reliability block diagram model is:

[0030] R 串 (t)=R1(t)×R2(t)×…×R n (t)

[0031] Among them, R 串 (t) is the overall reliability of the series system, R i (t), i = 1, 2, 3, ..., n represents the reliability of the i-th node;

[0032] And / or, the parallel reliability block diagram model, its reliability calculation function is:

[0033]

[0034] Among them, R 并 (t) is the overall reliability of the parallel system, R i (t),i=1,2,3,...,n represents the reliability of the ith series path;

[0035] And / or, K / N redundant reliability block diagram model, its reliability calculation function is:

[0036]

[0037] Among them, R K / N (t) is the reliability of the K / N redundant system, and R(t) is the reliability of a single node.

[0038] On the other hand, the present application also proposes a reliability prediction system for a low-frequency power supply cabinet based on a physics-of-failure model, and the system includes:

[0039] A failure mechanism analysis module, which is configured to analyze common failure mechanisms of the low-frequency power supply cabinet;

[0040] A single-point failure distribution fitting module, which is configured to perform single-point failure distribution fitting of the low-frequency power supply cabinet based on failure information;

[0041] A multi-point failure distribution fusion module, which is configured to carry out multi-point failure distribution fusion analysis based on the single-point failure distribution fitting result to complete reliability evaluation at the module level, equipment level, and system level of the low-frequency power supply cabinet;

[0042] And a reliability calculation module, which is configured to construct a reliability prediction model for the low-frequency power supply cabinet based on the reliability evaluation results at the module level, equipment level, and system level of the low-frequency power supply cabinet to achieve multi-level reliability prediction of the low-frequency power supply cabinet.

[0043] In some embodiments, the single-point failure distribution fitting module further includes:

[0044] A failure information acquisition unit, which is configured to analyze by using a stress simulation method to obtain the mean time to failure of each component of the low-frequency power supply cabinet equipment and unit;

[0045] An information processing unit, which is configured to obtain a probability density histogram after counting the frequencies according to the mean time to failure;

[0046] And a first fitting unit, which is configured to fit a probability density curve according to the probability density histogram and determine the failure distribution according to the probability density curve.

[0047] In some embodiments, the multi-point failure distribution fusion module further includes:

[0048] A sampling unit, which is configured to perform Monte Carlo random sampling based on the failure distribution function and select the sampling time with the minimum failure time as the failure time sample according to the competing failure principle;

[0049] a second fitting unit, the second fitting unit being configured to: perform distribution fitting on the fault time samples, and determine an optimal distribution fitting result as an optimal fault distribution function according to an AIC information criterion;

[0050] a module-level evaluation unit, the module-level evaluation unit being configured to: perform module-level reliability evaluation based on the module-level optimal fault distribution function output by the second fitting unit;

[0051] a device-level evaluation unit, the device-level evaluation unit being configured to: perform device-level reliability evaluation based on the device-level optimal fault distribution function output by the second fitting unit;

[0052] and a system-level evaluation unit, wherein the system-level evaluation unit is configured to: perform system-level reliability evaluation according to the system-level optimal fault distribution function output by the second fitting unit.

[0053] In some embodiments, the reliability calculation module further includes:

[0054] A block diagram construction unit, wherein the block diagram construction unit is configured to: analyze the function of the low-frequency power supply cabinet according to the module-level, device-level, and system-level reliability evaluation results of the low-frequency power supply cabinet, construct a low-frequency power supply cabinet functional schematic diagram, and then perform series-parallel analysis based on the low-frequency power supply cabinet functional schematic diagram to construct a reliability block diagram of the low-frequency power supply cabinet;

[0055] And, a calculation unit, wherein the calculation unit is configured to calculate the total system reliability through the model function involved in the low-frequency power supply cabinet reliability block diagram.

[0056] In some implementations, the reliability block diagram model mainly includes:

[0057] The reliability calculation function of the series reliability block diagram model is:

[0058] R 串 (t)=R1(t)×R2(t)×…×R n (t)

[0059] Among them, R 串 (t) is the overall reliability of the series system, R i (t), i = 1, 2, 3, ..., n represents the reliability of the i-th node;

[0060] And / or, the parallel reliability block diagram model, its reliability calculation function is:

[0061]

[0062] Among them, R 并(t) is the overall reliability of the parallel system, R i (t), where i = 1, 2, 3,..., n represents the reliability of the i-th series path;

[0063] And / or, a K / N redundant reliability block diagram model, whose reliability calculation function is:

[0064]

[0065] Among them, R K / N (t) is the reliability of the K / N redundant system, and R(t) is the reliability of a single node.

[0066] A reliability prediction method and system for a low-frequency power supply cabinet based on a physics of failure model proposed in this application. By constructing an optimal failure function for the failure mechanism, the reliability assessment of the low-frequency power supply cabinet is realized, and then the reliability prediction at all levels of the low-frequency power supply cabinet is achieved. The method for improving the system reliability is comprehensively determined to improve the design and operation reliability of the equipment;

[0067] A reliability prediction method and system for a low-frequency power supply cabinet based on a physics of failure model proposed in this application. Uncertainty and randomness are considered in the physics of failure model. Through Monte Carlo simulation, the adaptability of uncertainty factors such as parameter dispersion and dynamic changes in load to reliability prediction can be solved, and the randomization of the failure mechanism model is realized, making the prediction results more real and accurate;

[0068] A reliability prediction method and system for a low-frequency power supply cabinet based on a physics of failure model proposed in this application. The reliability block diagram model is used as the reliability prediction model. The block diagram architecture is relatively simple and can comprehensively show the sequential structure between the various components of the system, facilitating the solution of relevant parameters such as the reliability and MTTF of the system. Description of the Drawings

[0069] The drawings described herein are used to provide a further understanding of the embodiments of the present application, form a part of the present application, and do not limit the embodiments of the present application. In the drawings:

[0070] Figure 1 is the method flow chart of the embodiment of the present application;

[0071] Figure 2 is the system principle block diagram of the embodiment of the present application;

[0072] Figure 3 is an example of the working task profile of the low-frequency power supply cabinet; among them, (a) is the temperature cycle profile; (b) is the random vibration PSD spectrum; (c) is the mechanical shock excitation;

[0073] Figure 4 is the DC unit PCBA simulation model of the low-frequency power supply cabinet;

[0074] Figure 5 It is the fitting result diagram of the fatigue failure distribution of the through-holes plated on the DC unit PCBA;

[0075] Figure 6 It is the functional schematic diagram of the low-frequency power supply cabinet;

[0076] Figure 7 It is the reliability block diagram model of the low-frequency power supply cabinet system;

[0077] Figure 8 It is the reliability result diagram of the low-frequency power supply cabinet system. Specific implementation manners

[0078] To make the objectives, technical solutions and advantages of the present application clearer and more understandable, the present application will be further described in detail below in conjunction with embodiments and the accompanying drawings. The illustrative implementation manners and descriptions of the present application are only used to explain the present application and are not intended to limit the present application.

[0079] Embodiment 1:

[0080] In view of the problems such as the harsh operating environment of the current low-frequency power supply cabinet and the urgent need to improve the reliability level, this embodiment proposes a reliability prediction method for the low-frequency power supply cabinet based on the physics-of-failure model. The implementation principle of the method proposed in this embodiment is as follows: First, determine the key components, core elements, etc. of the low-frequency power supply cabinet, analyze their common failure modes and failure mechanisms, and comprehensively analyze the mutual influence among various failure mechanisms; Then, based on the obtained failure information, perform fitting of the single-point failure distribution of the low-frequency power supply cabinet, and then construct the single-point failure distribution function of the low-frequency power supply cabinet devices; Next, carry out multi-point failure distribution fusion, based on the single-point failure, calculate the failure distributions at the module level, equipment level, and system level in sequence to achieve reliability assessment; Finally, construct a reliability prediction model for the low-frequency power supply cabinet to achieve reliability prediction at all levels of the low-frequency power supply cabinet.

[0081] As Figure 1 shown, the method proposed in this embodiment specifically includes the following steps:

[0082] Step 100, analyze the common failure mechanisms of the low-frequency power supply cabinet.

[0083] In this step 100, the failure mechanism analysis process specifically includes: According to the design principle of the low-frequency power supply cabinet, combined with the equipment usage environment and common faults, determine the key components of the low-frequency power supply cabinet and their main failure locations, analyze the failure modes and failure mechanisms of electromechanical products, take the key components of the low-frequency power supply cabinet and the main mechanisms causing their failures as the key objects for subsequent analysis, and provide a theoretical basis for the subsequent steps by analyzing the failure information of each failure mechanism. Common failure mechanisms of the low-frequency power supply cabinet include: solder joint fatigue failure, plated via hole fatigue failure, vibration fatigue failure, and mechanical shock failure, etc.

[0084] Step 200, perform single-point failure distribution fitting for the low-frequency power supply cabinet based on the failure information.

[0085] In this step 200, the single-point failure distribution fitting process specifically includes:

[0086] After determining the key components of the low-frequency power supply cabinet and the failure information of the key components, based on the failure information, perform distribution fitting for each failure mechanism to obtain the single-point failure distribution of each failure mechanism. Common failure distributions include normal distribution, lognormal distribution, exponential distribution, and Weibull distribution, etc. Fit the failure information data of each failure mechanism with the above distribution functions. Use the AIC information criterion to select the obtained distribution functions, screen out the optimal failure distribution function. Specifically, based on the failure information data, obtain multiple single-point failure distributions, including normal distribution, lognormal distribution, exponential distribution, and Weibull distribution, etc. Calculate the AIC functions of these distributions to obtain the optimal failure distribution function. The smaller the AIC value, the more suitable the marginal probability distribution function is for the characteristics of the simulation data. Its mathematical expression is as follows:

[0087]

[0088] Among them, g(x) is the probability density function, and k is the number of parameters in the distribution function.

[0089] Specifically, methods such as stress simulation can be used for analysis to obtain the mean time to failure of each component of the equipment and unit, obtain the probability density histogram after counting the frequencies, fit the probability density curve based on the probability density histogram, and determine the failure distribution according to the probability density curve.

[0090] Step 300, based on the single-point failure distribution fitting results, carry out multi-point failure distribution fusion analysis to complete the reliability assessment at the module level, equipment level, and system level of the low-frequency power supply cabinet.

[0091] In this step 300, the multi-point failure distribution fusion analysis process specifically includes:

[0092] Step 301: Conduct Monte Carlo random sampling based on the failure distribution function, and select the sampling time with the minimum failure time as the failure time (TTF) sample according to the competing failure principle.

[0093] Step 302: Perform distribution fitting on the failure time samples, and determine the optimal distribution fitting result as the optimal failure distribution function according to the AIC information criterion.

[0094] Step 303: Conduct module-level reliability assessment based on the optimal failure distribution function; repeat the above Steps 301 and 302 to complete equipment-level and system-level reliability assessments in sequence. That is, when conducting module-level reliability assessment, the failure distribution function adopted in Step 301 is the module-level failure distribution function, and the module-level optimal failure distribution function obtained by fitting in Step 302; when conducting equipment-level reliability assessment, the failure distribution function adopted in Step 301 is the equipment-level failure distribution function obtained by fusion, and the equipment-level optimal failure distribution function obtained by fitting in Step 302; when conducting system-level reliability assessment, the failure distribution function adopted in Step 301 is the system-level failure distribution function obtained by fusion, and the system-level optimal failure distribution function obtained by fitting in Step 302. It can be understood that during the process of conducting equipment-level and system-level reliability assessments, the module-level assessment results serve as the initial input for the equipment level, and the equipment-level assessment results serve as the initial input for the system level, and the equipment-level and system-level assessment results are obtained through iteration.

[0095] Step 400: Based on the module-level, equipment-level, and system-level reliability assessment results, construct a reliability prediction model for the low-frequency power cabinet to achieve multi-level reliability prediction of the low-frequency power cabinet.

[0096] Since the reliability block diagram model has the advantages of a relatively simple block diagram structure drawn, which can comprehensively display the sequential structure among the various components of the system, this embodiment adopts the reliability block diagram model as the basic structure of the reliability prediction model. Its basic idea is to describe the logical relationship between the unit function and the system function according to the functional correlation between the system component units. The reliability analysis and assessment of the key equipment can be carried out according to the failure physics mode of the key components of the low-frequency power cabinet, and then the reliability prediction can be carried out from bottom to top. In this Step 400, the specific process of constructing the reliability prediction model for the low-frequency power cabinet includes:

[0097] Step 401: According to the module-level, equipment-level, and system-level reliability assessment results, analyze the functions of the low-frequency power cabinet, construct a functional schematic diagram of the low-frequency power cabinet, and then conduct series-parallel analysis based on the functional principle of the module to construct a reliability block diagram.

[0098] Step 402: Calculate the overall reliability of the system through the model functions (series, parallel, and / or reliability calculation functions such as K / N, etc.) involved in the reliability block diagram. That is, calculate the overall reliability of the system according to the reliability calculation formula corresponding to the series-parallel structure in the reliability block diagram.

[0099] Common failure distribution types and their failure density functions include: normal distribution, lognormal distribution, exponential distribution, Weibull distribution, etc. Their failure density functions all have corresponding expressions, so Monte Carlo sampling, distribution fitting, etc. can be carried out based on this.

[0100] Specifically, the reliability block diagram model can be mainly divided into the following three types:

[0101] (1) Series reliability block diagram model, which refers to a system formed by connecting one by one from the physical starting point (starting node) to the physical ending point (ending node). A series system has two obvious characteristics: one is that there is no branch; the other is that if any physical node or the connection between nodes fails, the entire system fails. The reliability calculation method is:

[0102] R 串 (t) = R1(t) × R2(t) × … × R n (t)

[0103] Among them, R 串 (t) is the overall reliability of the series system, and R i (t), i = 1, 2, 3,..., n represents the reliability of the i-th node, where n is the number of nodes in the series system.

[0104] (2) Parallel reliability block diagram model, which refers to a system formed by multiple series paths connected in parallel from the physical node (starting node) to the physical ending point (ending node). A parallel system has four significant characteristics: one is that the system is composed of multiple series paths connected in parallel; the second is that each series path has no redundant branches; the third is that each series path can independently achieve the specified functions of the system; the fourth is that the disconnection of any (not all) series paths will not affect the realization of the functions of the entire system. The reliability calculation method is:

[0105]

[0106] Among them, R 并 (t) is the overall reliability of the parallel system, and R i (t), i = 1, 2, 3,..., n represents the reliability of the i-th series path, where n is the number of series paths in the parallel system.

[0107] (3) K / N redundancy model, which means that the system can work properly only when at least K out of N identical and independent nodes are free from failure. The reliability calculation method is as follows:

[0108]

[0109] Among them, R K / N (t) is the reliability of the K / N redundancy system, and R(t) is the reliability of a single node.

[0110] In this embodiment, by constructing an optimal fault model of the fault mechanism, reliability evaluation results at multiple levels are obtained, and combined with the reliability block diagram, the construction of the fault physics model is realized, and then the reliability prediction of the low-frequency power cabinet is completed.

[0111] Based on the same technical concept as above, this embodiment also proposes a reliability prediction system for a low-frequency power cabinet based on a fault physics model, as Figure 2 shown. This system includes:

[0112] Failure mechanism analysis module, which is configured to analyze the common failure mechanisms of the low-frequency power cabinet. The common failure mechanisms of the low-frequency power cabinet include: solder joint fatigue failure, plated via hole fatigue failure, vibration fatigue failure, and mechanical shock failure, etc.

[0113] Single-point fault distribution fitting module, which is configured to perform single-point fault distribution fitting of the low-frequency power cabinet based on fault information.

[0114] Multi-point fault distribution fusion module, which is configured to carry out multi-point fault distribution fusion analysis based on the single-point fault distribution fitting result, and complete the reliability evaluation at the module level, equipment level, and system level of the low-frequency power cabinet.

[0115] And a reliability calculation module, which is configured to construct a reliability prediction model of the low-frequency power cabinet based on the reliability evaluation results at the module level, equipment level, and system level, and realize multi-level reliability prediction of the low-frequency power cabinet.

[0116] Furthermore, the single-point fault distribution fitting module further includes:

[0117] Fault information acquisition unit, which is configured to analyze by means of stress simulation and other methods to obtain the mean time to failure of each component of the low-frequency power cabinet equipment and unit, that is, fault information.

[0118] Information processing unit, which is configured to obtain a probability density histogram after counting the frequencies according to the mean time to failure.

[0119] And, a first fitting unit configured to: fit a probability density curve according to a probability density histogram, and determine a failure distribution according to the probability density curve.

[0120] Furthermore, the multi-point failure distribution fusion module further includes:

[0121] A sampling unit configured to: perform Monte Carlo random sampling based on a failure distribution function, and select the sampling time with the minimum failure time as the failure time (TTF) sample according to the competing failure principle.

[0122] A second fitting unit configured to: perform distribution fitting on the failure time samples, and determine the optimal distribution fitting result as the optimal failure distribution function according to the AIC information criterion.

[0123] A module-level evaluation unit configured to: conduct module-level reliability evaluation according to the module-level optimal failure distribution function output by the second fitting unit.

[0124] An equipment-level evaluation unit configured to: conduct equipment-level reliability evaluation according to the equipment-level optimal failure distribution function output by the second fitting unit.

[0125] And, a system-level evaluation unit configured to: conduct system-level reliability evaluation according to the system-level optimal failure distribution function output by the second fitting unit.

[0126] Furthermore, the reliability calculation module further includes:

[0127] A block diagram construction unit configured to: analyze the functions of the low-frequency power cabinet according to the module-level, equipment-level, and system-level reliability evaluation results, construct a functional schematic diagram of the low-frequency power cabinet, and then conduct series-parallel analysis based on the functional principles of the modules to construct a reliability block diagram;

[0128] And a calculation unit configured to: calculate the total system reliability through the model functions involved in the reliability block diagram. That is, calculate the total system reliability according to the model functions (reliability calculation formulas) involved in the reliability block diagram. The specific technical formulas are as described in step 400 above and will not be elaborated here.

[0129] Embodiment 2:

[0130] This embodiment uses the method and system proposed in the above embodiment to predict the reliability of a certain example. Among them, this embodiment selects a certain low-frequency power cabinet as the research object, and takes the DC unit PCBA as an example. The specific implementation process is as follows:

[0131] S1. Analyze the common failure mechanisms of the low-frequency power supply cabinet. As a power supply device, the low-frequency power supply cabinet necessarily has solder joints for electrical, thermal, and mechanical connections between the substrates or circuit boards, so solder joint fatigue failure is likely to occur. As a complex electronic device, the low-frequency power supply cabinet also contains structures such as multi-layer printed circuit boards. The vias between each layer of circuit boards are prone to strain, resulting in fatigue failure of the plated-through holes. Considering that vibration is more likely to occur in the environment where the low-frequency power supply cabinet is located, vibration fatigue and mechanical shock failure are also relatively common. In summary, the common failure mechanisms of the low-frequency power supply cabinet include: solder joint fatigue failure, plated-through hole fatigue failure, vibration fatigue, and mechanical shock failure.

[0132] S2. Based on the fault information, perform the single-point fault distribution fitting of the low-frequency power supply cabinet.

[0133] Taking the DC unit PCBA as an example, perform the single-point fault distribution fitting of this component. Its mission profile is as Figure 3 shown, and the established simulation model of the DC unit PCBA is as Figure 4 shown.

[0134] Taking the plated-through hole fatigue failure of the DC unit PCBA as an example, perform the fault distribution fitting of this failure mechanism. According to Figure 4 the established simulation model, carry out stress simulation analysis, obtain the mean time to failure of each component in the DC unit PCBA, obtain the probability density histogram after counting the frequencies, and then fit the probability density curve, as Figure 5 shown. It can be seen from Figure 5 that this fault distribution follows a normal distribution.

[0135] S3. Perform multi-point fault distribution fusion to achieve reliability assessment at the module level, equipment level, and system level of the low-frequency power supply cabinet.

[0136] Repeat the steps of S2 for other failure mechanisms of the DC unit PCBA, and obtain its reliability analysis table as shown in Table 1.

[0137] Table 1

[0138]

[0139]

[0140] Repeat the above process to obtain the reliability analysis structures of other modules, which can be used for subsequent establishment of the reliability block diagram model of the low-frequency power supply cabinet, system reliability prediction, etc.

[0141] S4. Construct a reliability prediction model for the low-frequency power supply cabinet to achieve reliability prediction.

[0142] Construct the functional schematic diagram of the low-frequency power supply cabinet as Figure 6 shown, based on Figure 6The established reliability block diagram model of the low-frequency power supply cabinet system is as follows Figure 7 shown. Among them, the low-frequency power supply device, the function control box, the main transformer chassis, and the exhaust fan are in a series model. The low-frequency power supply device includes an input / output unit, a low-frequency signal unit, an isolation drive unit, a protection monitoring unit, a main circuit unit, a main circuit rectification unit, and an indication unit. Among them, the isolation drive unit and the protection monitoring unit receive the pulse signals transmitted by the low-frequency signal unit and transmit the IGBT signals to the main circuit unit and the main circuit rectification unit. Therefore, they are in a parallel model, and the input / output unit, the low-frequency signal unit, the main circuit unit, the main circuit rectification unit, and the indication unit are in a series structure. The function control box includes an input / output unit, a DC unit, a rod speed unit plug-in, a group D automatic / manual unit plug-in, a shutdown unit plug-in, and a reverse plug-in unit plug-in. Among them, the input / output unit and the DC unit are in a series structure. The rod speed unit plug-in, the group D automatic / manual unit plug-in, the shutdown unit plug-in, and the reverse plug-in unit plug-in receive the electrical energy transmitted by the DC unit and output corresponding signals respectively. Therefore, they are constructed in a parallel structure. The main transformer chassis includes a main transformer, a 380V switch, and a low-voltage conversion switch, which is in a series structure, and three 380V switches are used in parallel.

[0143] Based on the above analysis, the system-level reliability prediction of the low-frequency power supply cabinet is carried out. In the low-frequency power supply cabinet system, the module reliability analysis results of the DC unit, the group D automatic / manual unit plug-in, the rod speed unit plug-in, the protection monitoring unit, the low-frequency signal unit, the reverse plug-in unit plug-in, the isolation drive unit, and the shutdown unit plug-in are obtained through S3 calculation. The reliability of the input / output unit, the main circuit unit, the main circuit rectification unit, the indication unit, the main transformer, the 380V switch, the low-voltage conversion switch, and the exhaust fan is relatively high. The failure rate of the product is at a relatively low level and basically remains stable. It can be approximately considered that the failure rate is a constant. Therefore, it is considered that the failures of the above units follow an exponential distribution, and its failure rate function is a constant value, that is: λ(t) = λ

[0144] The reliability function is obtained as:

[0145] R(t) = e -λt

[0146] According to literature research and manual query, the failure rate λ = 0.05 of this type of unit is selected, and thus the reliability of the above units can be obtained. Then, based on the reliability block diagram model and using the model function, the reliability of the low-frequency power supply cabinet system changing with time is as follows Figure 8 shown.

[0147] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0148] The present application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one or more of the flows Figure 1 or blocks.

[0149] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in Figure 1 one or more of the flows Figure 1 or blocks.

[0150] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in Figure 1 one or more of the flows Figure 1 or blocks.

[0151] The specific embodiments described above further elaborate on the purpose, technical solution, and beneficial effects of the present application. It should be understood that the above description is only the specific embodiments of the present application and is not used to limit the protection scope of the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. A reliability prediction method for a low-frequency power supply cabinet based on a physics-of-failure model, characterized in that, The method includes: Analyzing the common failure mechanisms of the low-frequency power supply cabinet; Performing single-point failure distribution fitting of the low-frequency power supply cabinet based on the fault information; Based on the single-point failure distribution fitting results, conducting multi-point failure distribution fusion analysis to complete the reliability assessment of the low-frequency power supply cabinet at the module level, equipment level, and system level; Based on the reliability assessment results of the low-frequency power supply cabinet at the module level, equipment level, and system level, constructing a reliability prediction model for the low-frequency power supply cabinet to achieve multi-level reliability prediction of the low-frequency power supply cabinet.

2. The reliability prediction method of a low-frequency power cabinet based on a fault physics model according to claim 1, wherein The common failure mechanisms of the low-frequency power supply cabinet include: solder joint fatigue failure, plated via hole fatigue failure, vibration fatigue failure, and mechanical shock failure.

3. A reliability prediction method for a low-frequency power cabinet based on a fault physics model according to claim 1, characterized in that The specific process of the single-point failure distribution fitting includes: Using the stress simulation method for analysis, obtaining the mean time to failure of key components and their components / units, and obtaining the probability density histogram after counting the frequencies; Fitting a probability density curve according to the probability density histogram; Determining the failure distribution according to the probability density curve; the failure distribution is a normal distribution, a lognormal distribution, an exponential distribution, or a Weibull distribution.

4. A reliability prediction method for a low-frequency power cabinet based on a physics-of-failure model according to claim 1, characterized in that, The multi-point failure distribution fusion analysis process specifically includes: Performing Monte Carlo random sampling based on the failure distribution function, and selecting the sampling time with the minimum failure time as the failure time sample according to the competing failure principle; Performing distribution fitting on the failure time sample, and determining the optimal distribution fitting result as the optimal failure distribution function according to the AIC information criterion; Based on the optimal distribution function, conducting reliability assessments at the module level, equipment level, and system level.

5. A reliability prediction method for a low-frequency power cabinet based on a physics-of-failure model according to claim 1, characterized in that, The method uses a reliability block diagram model as the reliability prediction model, and the reliability block diagram model describes the logical relationship between the unit function and the system function according to the functional correlation between the system component units; The method conducts reliability analysis and assessment on the key equipment based on the failure physics mode of the key components of the low-frequency power supply cabinet, and conducts reliability prediction from bottom to top.

6. The reliability prediction method for a low-frequency power cabinet based on a physics-of-failure model according to claim 5, wherein The specific process of the reliability prediction model framework includes: According to the reliability assessment results of the low-frequency power supply cabinet at the module level, equipment level, and system level, analyzing the functions of the low-frequency power supply cabinet and constructing a functional schematic diagram of the low-frequency power supply cabinet; Conducting series-parallel analysis according to the functional schematic diagram of the low-frequency power supply cabinet to construct the reliability block diagram of the low-frequency power supply cabinet; Using the model functions involved in the reliability block diagram of the low-frequency power supply cabinet to calculate the total reliability of the low-frequency power supply cabinet system.

7. A reliability prediction method for a low-frequency power supply cabinet based on a physics-of-failure model according to claim 6, characterized in that The reliability block diagram model mainly includes: A series-type reliability block diagram model, whose reliability calculation function is: R 串 (t) = R1(t) × R2(t) × … × R n (t) where, R 串 (t) is the overall reliability of the series system, and R i (t), i = 1, 2, 3, ..., n represents the reliability of the i-th node; And / or, a parallel-type reliability block diagram model, whose reliability calculation function is: Among them, R 并 (t) is the overall reliability of the parallel system, and R i (t), where i = 1, 2, 3,..., n represents the reliability of the i-th series path; And / or, a K / N redundant-type reliability block diagram model, whose reliability calculation function is: Among them, R K / N (t) is the reliability of the K / N redundancy system, and R(t) is the reliability of a single node.

8. A reliability prediction system for a low-frequency power supply cabinet based on a physics-of-failure model, characterized in that The system includes: A failure mechanism analysis module configured to analyze the common failure mechanisms of the low-frequency power supply cabinet; A single-point failure distribution fitting module configured to perform single-point failure distribution fitting of the low-frequency power supply cabinet based on the fault information; The multi-point fault distribution fusion module, the multi-point fault distribution fusion module is configured to: based on the single-point fault distribution fitting result, carry out multi-point fault distribution fusion analysis, and complete the reliability assessment of the low-frequency power cabinet at the module level, equipment level, and system level; And, the reliability calculation module, the reliability calculation module is configured to: based on the reliability assessment results of the low-frequency power cabinet at the module level, equipment level, and system level, construct a reliability prediction model for the low-frequency power cabinet, and realize the multi-level reliability prediction of the low-frequency power cabinet.

9. The reliability prediction system of a low-frequency power cabinet based on a physics-of-failure model according to claim 8, characterized in that, The single-point fault distribution fitting module further includes: The fault information acquisition unit, the fault information acquisition unit is configured to: analyze by using the stress simulation method to obtain the mean time to failure of each component of the low-frequency power cabinet equipment and unit; The information processing unit, the information processing unit is configured to: according to the mean time to failure, obtain the probability density histogram after counting the frequencies; And, the first fitting unit, the first fitting unit is configured to: fit the probability density curve according to the probability density histogram, and determine the fault distribution according to the probability density curve.

10. A reliability prediction system for a low-frequency power cabinet based on a fault physics model according to claim 8, characterized in that, The multi-point fault distribution fusion module further includes: The sampling unit, the sampling unit is configured to: perform Monte Carlo random sampling based on the fault distribution function, and select the sampling time with the minimum fault time as the fault time sample according to the competing failure principle; The second fitting unit, the second fitting unit is configured to: perform distribution fitting on the fault time sample, and determine the optimal distribution fitting result as the optimal fault distribution function according to the AIC information criterion; The module-level evaluation unit, the module-level evaluation unit is configured to: carry out module-level reliability evaluation according to the module-level optimal fault distribution function output by the second fitting unit; The equipment-level evaluation unit, the equipment-level evaluation unit is configured to: carry out equipment-level reliability evaluation according to the equipment-level optimal fault distribution function output by the second fitting unit; And, the system-level evaluation unit, the system-level evaluation unit is configured to: carry out system-level reliability evaluation according to the system-level optimal fault distribution function output by the second fitting unit.

11. A reliability prediction system for a low-frequency power cabinet based on a fault physics model according to claim 8, characterized in that, The reliability calculation module further includes: The block diagram construction unit, the block diagram construction unit is configured to: analyze the functions of the low-frequency power cabinet according to the reliability assessment results of the low-frequency power cabinet at the module level, equipment level, and system level, construct a functional schematic diagram of the low-frequency power cabinet, and then perform series-parallel analysis according to the functional schematic diagram of the low-frequency power cabinet to construct the reliability block diagram of the low-frequency power cabinet; And, the calculation unit, the calculation unit is configured to: calculate the total system reliability through the model functions involved in the reliability block diagram of the low-frequency power cabinet.

12. A reliability prediction system for a low-frequency power cabinet based on a fault physics model according to claim 10, characterized in that, The reliability block diagram model mainly includes: The series-type reliability block diagram model, and its reliability calculation function is: R 串 R(t) = R1(t) × R2(t) × … × R n (t) Among them, R 串 (t) is the overall reliability of the series system, and R i (t), where i = 1, 2, 3,..., n represents the reliability of the i-th node; And / or, the parallel-type reliability block diagram model, and its reliability calculation function is: Among them, R 并 (t) is the overall reliability of the parallel system, and R i (t), i = 1, 2, 3,..., n represents the reliability of the i-th series path; And / or, the K / N redundant-type reliability block diagram model, and its reliability calculation function is: where R K / N (t) is the reliability of the K / N redundancy system, and R(t) is the reliability of a single node.

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