Method for measuring failure bottom event index of aircraft electrical circuit network and computer equipment

Abstract

The application discloses a kind of aircraft electric circuit network failure bottom event index measurement method and computer equipment, the method comprises: identifying three kinds of core bottom events of aircraft electric circuit network failure;For each bottom event, determine the failure rate measurement method, cable failure is calculated by querying data manual method, structure is disconnected failure is calculated by finite element simulation combined with fatigue theory, and the failure rate measurement model is established by using accelerated test method to obtain degradation data for electric bonding corrosion failure;Electric bonding structure test pieces are manufactured using materials, processes and configurations equivalent to installed products;Accelerated testing is performed on the test pieces, and failure data under each stress step is obtained, characteristic life under each stress step is obtained by extrapolation through the life distribution model, and the acceleration coefficient is obtained by regression algorithm using the accelerated life model, and the MTBF and failure rate of the bonding assembly are calculated according to the acceleration coefficient.The application can greatly improve the precision and confidence of failure rate measurement.

Description

Technical Field

[0001] This invention belongs to the field of engineering technology, specifically relating to a method for calculating the failure event index of an aircraft electrical circuit network, a computer device, a computer-readable storage medium, and a computer program product. Background Technology

[0002] With the widespread application of composite materials in aircraft, their low electrical conductivity and high thermal sensitivity make them unsuitable for replacing traditional metal structures in achieving current return and electromagnetic protection functions. Therefore, additional metal components are needed to form a continuous electrical circuit network with the existing aircraft structure. As the core of the system, the reliability of the connection of the lap joint directly affects the operational safety of the aircraft's electrical system. However, this part is susceptible to multiple factors throughout its life cycle, such as vibration and shock, temperature and humidity cycles, corrosion from contact with dissimilar metals, and mechanical stress fatigue, facing the risk of failure such as physical connection disconnection and increased lap impedance. Furthermore, the complex parallel structure of the electrical circuit network further increases the complexity of fault evolution. At the same time, traditional multimeters are not accurate enough, and the four-wire method cannot accurately measure the true lap impedance due to current shunting. In addition, the lap joint components degrade slowly under normal stress, and conventional tests cannot obtain sufficient failure data within a reasonable period. Existing failure rate models are not fully adapted to its typical configuration and special failure mechanism, resulting in inaccurate calculation of the failure rate of the lap joint and difficulty in identifying weak points, which cannot provide a scientific quantitative basis for system design optimization, quality control, and operation and maintenance decisions. Summary of the Invention

[0003] The purpose of this invention is to provide a method for calculating the failure event index of an aircraft electrical circuit network, a computer device, a computer-readable storage medium, and a computer program product, which can significantly improve the accuracy and confidence of failure rate calculation.

[0004] To achieve the above objectives, one aspect of the present invention provides a method for calculating the failure event index of an aircraft electrical circuit network, comprising:

[0005] Step S1: Identify key components and their failure modes in the aircraft electrical circuit network, establish the correlation from failure mechanism to failure mode, identify key sensitive stresses through failure mechanism analysis, and identify three core bottom events of aircraft electrical circuit network failure through failure mode and effect analysis, including cable failure, structural disconnection failure, and electrical bridging corrosion failure.

[0006] Step S2: Determine the failure rate calculation method for each type of basic event. Cable failure is calculated by consulting the data manual. Structural disconnection failure is calculated by combining finite element simulation with fatigue theory and stress-strength interference model. Electrical lap corrosion failure is calculated by using accelerated testing to obtain degradation data to establish a failure rate calculation model and select a lifetime distribution model and an accelerated lifetime model.

[0007] Step S3: Use materials, processes and configurations equivalent to those of the installed product to manufacture an electrical lap structure test piece to simulate the mechanical connection and electrical contact state of the actual electrical circuit network;

[0008] Step S4: Determine the type of accelerated stress based on the sensitive stress analysis, determine the number of parameters to be determined based on the accelerated life model, set the number of stress steps and the number of samples based on the number of parameters to be determined, conduct accelerated tests on the test pieces, obtain failure data under each stress step, obtain the characteristic life under each stress step by extrapolation through the life distribution model, obtain the acceleration coefficient through the accelerated life model and regression algorithm, and calculate the MTBF and failure rate of the electrical circuit network connection components based on the acceleration coefficient.

[0009] Another aspect of the present invention provides a computer device including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method described above.

[0010] Another aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described above.

[0011] Another aspect of the present invention provides a computer program product including a computer program that, when executed by a processor, implements the steps of the method described above.

[0012] The method, computer equipment, computer-readable storage medium, and computer program product for calculating the failure event index of the aircraft electrical circuit network according to the above-described aspects of the present invention can significantly improve the accuracy and confidence of failure rate calculation. Attached Figure Description

[0013] To more clearly illustrate the technical solutions of the present invention, the accompanying drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort:

[0014] Figure 1 This is a flowchart of a method for calculating the failure event index of an aircraft electrical circuit network according to an embodiment of the present invention;

[0015] Figure 2 This is a schematic diagram of a method for calculating the failure event index of an aircraft electrical circuit network according to an embodiment of the present invention;

[0016] Figure 3 This is a structural diagram of a computer device according to an embodiment of the present invention. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0018] One embodiment of the present invention provides a method for calculating the failure event index of an aircraft electrical circuit network, such as... Figure 1 As shown, the method of this embodiment of the invention includes steps S1 to S4. The following is in conjunction with... Figure 2 The schematic diagram illustrates the various steps of the method in this embodiment of the invention.

[0019] Step S1, Failure Mode and Effects Analysis of Failure Events

[0020] The electrical circuit network's overlapping section includes conductive core components and supporting and protective structures such as metal channels and overlapping plates. Although the latter are not conductive, they are prone to failure due to adhesive creep, material aging, etc., leading to cable wear and other faults. Using Failure Mode and Effects Analysis (FMEA), combined with historical fault data, the composition characteristics of overlapping components, and material performance parameters, the failure mechanisms are clarified: First, a functional boundary diagram of the electrical circuit network is established to clarify the interface relationships and functional requirements between core components such as cables, terminals, and overlapping plates and external systems. Then, for key combinations such as cables and terminals, and single / double terminals and overlapping plates, potential functional deviations such as hard and soft faults are enumerated. Furthermore, the failure mechanisms corresponding to each fault mode, such as adhesive creep and metal corrosion, are analyzed to establish the correlation between micro-mechanisms and macro-faults. Through hierarchical impact analysis and quantitative assessment, the priority of fault handling and critical events are determined.

[0021] Step S2, Selection of failure rate calculation model

[0022] Based on the failure mode analysis conclusions, this study focuses on three core events: cable failure, structural disconnection failure, and electrical bridging corrosion failure, and constructs failure rate models. Cable failure is calculated using the data handbook method, specifically employing the maximum value method of dual-source data from the NPRD data handbook (Reliability Data Handbook for Non-Electronic Components) and the GJB 299D standard (Reliability Prediction Handbook for Electronic Equipment). Structural disconnection failure is solved using finite element simulation combined with fatigue theory and a stress-strength interference model. Electrical bridging corrosion failure rate is modeled based on accelerated degradation tests. Simultaneously, multi-dimensional verification is used to identify sensitive stresses such as temperature and humidity. Combining the failure rate variation characteristics throughout the component's life cycle, the mathematical characteristics and engineering applicability of exponential, Weibull, and log-normal distributions are compared. Based on the impedance degradation law of the bridging component, the optimal model is selected, laying the foundation for subsequent experiments and calculations.

[0023] Step S3, Test piece manufacturing

[0024] The test specimen for the electrical connection structure of the equivalent installed product is manufactured. It consists of aluminum conductors, metal brackets / channels, terminals, and dissimilar metal lap interfaces. It simulates the mechanical connection and electrical contact state of the actual electrical circuit network, constructs an electrochemical corrosion-sensitive unit, and uses the same grade of materials, surface treatment process, and fastening method. Test lines are reserved in the lap area to collect degradation data at regular intervals. The test specimen is designed with three typical configurations: single-terminal lap, double-terminal lap, and bracket and metal channel lap. Each is equipped with 0.5-1 meter ERN (Electrical Return Network) cables to form a complete circuit. The entire manufacturing and delivery process follows the quality management system, checks the completeness of documents and design compliance, and conducts sampling inspections. The initial contact resistance of the lap interface is required to be <0.25 mΩ. The materials, processes, and performance are guaranteed to be equivalent to the installed product, providing high-confidence physical sample support for subsequent accelerated testing and the establishment of corrosion failure rate prediction models.

[0025] Step S4: Design and calculation of the bottom-event failure rate verification experiment.

[0026] (1) Accelerated degradation test design: In view of the slow degradation of electrical circuit network components under normal stress, in order to obtain effective degradation data within a reasonable period without changing the inherent failure mechanism, the constant stress accelerated degradation test method was selected for research. Compared with step and sequential stress tests, this method has the advantages of no interference with the failure mechanism, mature statistical theory, and feasible engineering implementation. Based on the previous sensitive stress analysis and corresponding accelerated model, the number of unknown parameters was determined. According to the parameter estimation principle, the number of stress steps was set to be greater than the number of unknown parameters plus one. In combination with the parameter solution requirements of the lifetime distribution model, in order to improve the fitting accuracy and statistical confidence, ten test samples were configured for each stress step. (2) Data acquisition and lifetime extrapolation: Throughout the test, the performance parameters of the samples were measured periodically to collect degradation trajectory data. First, the inherent resistance of the test lead was measured by the short-circuit calibration method as a correction benchmark. Then, under the stable conditions of each stress step, the resistance of each overlap position was measured by a calibration resistance tester. The environmental and circuit parameters were recorded simultaneously. The actual component resistance was obtained by subtracting the lead resistance from the measured data. The degradation trajectory dataset was constructed by longitudinal comparison. To address the issue that the overlapping part may not actually fail, and considering the law that impedance increases with aging, a random and deterministic degradation model is used to fit the full life cycle curve. The optimal model is selected by the goodness-of-fit index. Then, the model and the preset failure threshold are combined to solve the time point when the sample reaches the critical state, and the pseudo-failure lifetime of each sample is obtained. (3) Based on the pseudo-failure lifetime data under multiple stress levels, the maximum likelihood estimation method is first used to complete the estimation of the lifetime distribution characteristic parameters. The goodness-of-fit is verified by Anderson-Darling and chi-square tests. If it fails, the data quality is checked, the distribution model is re-evaluated, and the consistency of the failure mechanism is verified. Then, the characteristic lifetime of each stress group is obtained from the lifetime distribution model. The acceleration model is transformed into an equation form. The unknown parameters of the acceleration factor are solved by regression algorithm in combination with each stress condition to determine the acceleration coefficient. Finally, the working profile temperature cycle is converted into the number of cycles of the known characteristic lifetime stress using the acceleration coefficient. Combined with the correspondence between the civil aircraft cycle time and the number of cycles, the MTBF (Mean Time Between Failures) of the electrical circuit network overlapping component is calculated, and then the failure rate is calculated.

[0027] As described above, the method of this invention is guided by the overall idea of ​​calculating the failure baseline of electrical circuit networks. With the advancement of failure mode and effects analysis (FMEA), it gradually meets the failure baseline testing requirements for overlapping structures, striving to guide design in a data-driven manner and ensure the effective implementation of electrical circuit network optimization and fault prevention measures. First, key components and their failure modes in the electrical circuit network are identified, including current transmission functional components and physical support structures. A thorough analysis is conducted to establish the characterization correlation from failure mechanism to failure mode, and a quantitative evaluation is used to determine the priority of treatment. Second, based on the failure mechanism analysis results, key sensitive stresses such as temperature, humidity, and vibration are identified through failure physics theory derivation and engineering experience verification. Combined with the component performance degradation law, a lifetime distribution model is determined. Next, considering the slow degradation of components under normal stress, a constant stress accelerated degradation test method is adopted. The number of stress steps and sample quantity are designed according to the acceleration scheme and lifetime model. Then, performance degradation data is collected through the test platform, and the degradation model is used for fitting analysis. A pseudo-failure lifetime is extrapolated by combining a preset failure threshold. Finally, based on failure data at multiple stress levels, lifetime distribution fitting and accelerated model parameter solving are performed. The stress cycles under the working profile are converted into the number of cycles under normal stress using the acceleration coefficient. Finally, the MTBF and failure rate of the component are calculated, realizing accurate prediction of reliability indicators from test data to actual use conditions, and providing a scientific basis for the reliability of electrical circuit networks.

[0028] Electrical lap joints, as the cornerstone of the integrity and safety of aircraft electrical circuits, provide a reliable low-impedance path for return current, preventing interference or corrosion caused by current traveling through unexpected paths. They also establish effective discharge channels for static electricity and lightning currents, protecting the safe operation of sensitive electronic equipment. However, their performance degradation is highly insidious; the slow increase in lap resistance is difficult to detect in the early stages, but when the resistance exceeds a critical value, it can suddenly trigger serious safety problems such as abnormal potentials, equipment malfunctions, localized overheating, or even arcing. These components are typically made of various composite materials connected by fasteners and lap strips. Their failure involves complex processes involving multiple mechanisms such as electrochemical corrosion, fretting wear, and stress relaxation under sensitive stresses such as temperature, humidity, and vibration. Furthermore, the design requirement for components to have the same lifespan as the aircraft presents a fundamental contradiction with the model development cycle. Therefore, under the premise of ensuring that the failure mechanism remains unchanged, accelerated degradation testing rapidly reproduces the degradation process in the laboratory by applying enhanced stress, providing a feasible way to calculate the failure event index of the electrical circuit network within a limited time. This solves the problem that the slow degradation of the aircraft electrical circuit network splice components under normal stress makes it difficult to calculate the failure rate.

[0029] The following uses an aircraft electrical circuit network as an example to further explain in detail the process of calculating the failure event index using the method of the present invention.

[0030] Step S1: Analysis of influencing factors of basic event failure modes in electrical circuit networks

[0031] The electrical circuit network's overlapping sections not only include the core components for current transmission but also their physical support and protection structures, such as metal channels, overlapping plates, and fasteners. While these support structures do not directly participate in conductivity, they are susceptible to failure mechanisms such as adhesive creep, insulation aging, metal component corrosion, and mechanical stress fatigue, which can lead to cable wear, short circuits, or loose connections. To identify weak points in the circuit network and determine their decisive impact on system reliability, failure mode and effects analysis (FMEA) methods are used, combined with historical failure data, overlapping component characteristics, and material performance parameters, to identify potential failure modes induced under operating conditions, thereby determining the failure mechanisms.

[0032] Specifically, the process begins by establishing a functional boundary diagram of the system to clarify the interface relationships between components such as cables, terminals, lap joints, metal channels, and fasteners, and external systems such as the main power supply, avionics, and fuselage structure, thus obtaining the functional requirements of the electrical lap joint system. Based on this, for combinations of cables and terminals, single / double terminals and lap joints, and lap joints and metal channels, possible functional deviations are enumerated. These failure modes include hard failures resulting in complete functional loss, as well as soft failures where performance parameters gradually deviate from the design range. For each failure mode, the failure mechanism is analyzed, establishing a characterization correlation from microscopic mechanisms to macroscopic failures. For example, a lap joint resistance exceeding the minimum impedance requirement can be attributed to processes such as interface compound formation due to electrochemical corrosion, surface degradation caused by fretting wear, or contact pressure attenuation due to stress relaxation. Then, the impact of each failure mode on different levels of the system is analyzed, starting with the local impact of the failure on the component itself, then analyzing its interference with the function of the next-level subsystem, and subsequently determining its comprehensive impact on the overall system's operational safety. Finally, a quantitative assessment is used to determine the priority order for handling failure modes.

[0033] Step S2: Selection of the calculation model for the failure rate of the electrical circuit network bottom event

[0034] Step S21: Select a low-event failure rate model

[0035] A systematic analysis of the failure rate model for bottom-event failures in electrical circuit networks was conducted. Based on the failure mode and effects analysis (FMEA) conclusions, the top event, "loss of the reference voltage of the common voltage base," is related to bottom-event failures such as cable disconnection, metal bracket disconnection, metal cable tray disconnection, electrical bridging disconnection, and electrical bridging corrosion. Its failure rate follows an additive principle. Considering that the failure rate of dissimilar metal contact corrosion at electrical bridging joints is significantly higher than that of corrosion of independent metal components, the model is effectively simplified by ignoring corrosion terms for metal brackets and cable trays. The predicted model is constructed focusing on the following three aspects:

[0036] (1) Cable failure: The maximum value method of dual-source data from NPRD data manual and GJB 299D standard is adopted. Foreign data are obtained directly from tables based on quality level and environmental category. Domestic data are calculated based on the environment of unmanned areas without environmental control for transport aircraft and UAVs. The maximum value of the two is taken to ensure that the predicted value is both accurate and conservative.

[0037] (2) Failure of metal brackets, cable trays and electrical connections: Based on the structural strength failure mechanism, the stress distribution is obtained by applying random vibration and impact excitation using finite element simulation (FEA), coupled with the strength distribution determined by material grade and process data, and the failure rate is calculated by fatigue theory and stress-strength interference model.

[0038] (3) Electro-lap corrosion failure: To address the electrochemical corrosion degradation mechanism caused by critical sensitive stress, accelerated degradation test methods were used to obtain degradation data and establish a failure rate calculation model. For details, please refer to the test design scheme.

[0039] Finally, by weighting and summing the failure rates of the three types of bottom events, the comprehensive failure rate of the top event can be obtained, providing a quantitative basis for the analysis of system safety and reliability.

[0040] The failure of any basic event can cause the failure of the event "loss of the reference voltage function of the common voltage reference of the electrical circuit network". The basic events are related by OR. The failure rate calculation model of the event "loss of the reference voltage function of the common voltage reference of the electrical circuit network" is as follows:

[0041]

[0042] The failure rate calculation models for the metal bracket, metal cable tray, and electrical connection are as follows:

[0043]

[0044]

[0045]

[0046] The failure rate of dissimilar metal contact corrosion at electrical joints is much higher than that of individual metal supports or metal cable trays. Therefore, when calculating the failure rate of "the electrical circuit network losing its reference voltage due to the loss of a common voltage reference," the failure rate of metal supports and metal cable trays can be ignored. The failure rate model for "the electrical circuit network losing its reference voltage due to the loss of a common voltage reference" is summarized as follows:

[0047]

[0048] Step S22: Determine the lifetime distribution model of the overlapping components

[0049] Based on previous failure mechanism analysis results, and through multi-dimensional verification including failure physics theory derivation, industry standards, historical failure reports, and existing engineering experience, temperature, humidity, and vibration were identified as key sensitive stresses. Since electrical circuit network components may experience multiple stages throughout their life cycle, such as early failure, random failure, and wear-out failure, their failure rate is not constant. To accurately describe the statistical distribution characteristics of the lifetime of lap joint components, the mathematical properties and engineering applicability of lifetime distribution models such as the exponential distribution, Weibull distribution, and log-normal distribution were systematically evaluated, as shown in Table 1. Combining the impedance variation patterns presented by the performance degradation data of lap joint components, the optimal lifetime distribution model was determined.

[0050] Table 1 Comparison of Commonly Used Lifetime Distribution Models

[0051]

[0052] Step S23: Determine the accelerated life model

[0053] According to the low-event failure rate calculation model, there is no mature prediction method for the failure of the electrical bridging section; the failure rate needs to be calculated experimentally. The increased impedance of the electrical bridging section is related to corrosion effects, and the sensitive stresses are temperature and humidity. According to GB / T 17215.9311-2017 / IEC62059-31-1:2008 "Reliability of Electrical Measuring Equipment – ​​Part 311: Temperature and Humidity Accelerated Reliability Testing", the Peck temperature-humidity model is used for temperature and humidity accelerated life testing, and the Peck acceleration factor is:

[0054]

[0055] in, The percentage of relative humidity under operating conditions. This represents the percentage of relative humidity under stress conditions. Temperature in K under operating conditions. Let K be the temperature under stress, where k is the Boltzmann constant (8.617 × 10⁻⁶). ), Activation energy expressed in electron volts ( Typical values ​​in the range of 0.3 to 1.5 =0.9), where n is a constant. and n are the two coefficients of the model.

[0056] Step S3, Test piece manufacturing

[0057] To meet project requirements, this study focuses on the failure mechanism and failure rate calculation of electrical lap joints, and involves the fabrication of test specimens for electrical lap joint structures. The test specimens consist of aluminum conductors, metal support / trough structures, terminals, and dissimilar metal lap joint interfaces. By simulating the mechanical connection and electrical contact between terminals and lap joint structures in an actual electrical circuit network, representative electrochemical corrosion-sensitive units are constructed. The test specimens are manufactured using the same material grades, surface treatment processes, and fastening methods as the installed products to ensure corrosion behavior is equivalent to actual operating conditions. Test lines are connected to lap joint areas with different configurations to facilitate the timely collection of degradation data during accelerated testing, providing data support for establishing a predictive model for electrical lap joint corrosion failure rates.

[0058] Specifically, three typical configurations are used to cover major application scenarios: single-terminal overlap, double-terminal overlap, and bracket-to-metal channel overlap. Each test piece is equipped with 0.5 to 1 meter ERN cable to form a complete circuit. The entire manufacturing and delivery process is conducted under a quality management system, focusing on verifying the completeness of documents, design compliance (such as machining accuracy and oxide film thickness), and sampling for performance testing. It is mandatory that the initial contact resistance of the overlap interface is less than the theoretical resistance value, ensuring from the source that each test piece is equivalent to the installed product in terms of materials, processes, and performance. This provides reliable and authoritative physical sample support for obtaining high-confidence accelerated testing results and failure rate models.

[0059] Step S4: Design and calculation of the failure rate verification test for the bottom event of the electrical circuit network.

[0060] Step S41, Accelerated Degradation Experiment Design

[0061] To address the slow degradation of electrical circuit network components under normal stress, accelerated degradation testing is employed. This method increases stress levels to accelerate performance degradation, effectively speeding up the component's performance degradation process while ensuring that its inherent failure mechanism remains unchanged. Accelerated degradation tests include constant stress accelerated degradation testing, step stress accelerated degradation testing, and sequential stress accelerated degradation testing. Based on the complexity of the electrical circuit network component's structure and function and reliability requirements, the constant stress accelerated degradation testing method is used to calculate the failure rate. This method, by conducting tests under constant high stress levels, can effectively accelerate the performance degradation process while ensuring that the component's failure mechanism remains unchanged, thereby obtaining sufficient degradation data within a reasonable testing period to support reliability assessment. Compared with the complexity of data processing in the step stress accelerated degradation test and the special requirements of the sequential stress test for dedicated control equipment, the constant stress test method has the following advantages: (1) Its stress loading method follows the principle of consistency of failure mechanism, effectively avoiding the interference of stress path dependence on degradation mechanism; (2) The statistical processing theory of this method is mature and perfect, which can ensure the accurate estimation of lifetime distribution parameters and acceleration factors; (3) The test scheme has high engineering feasibility under existing equipment conditions.

[0062] Based on the preliminary sensitive stress analysis to determine the type of accelerating stress, and combined with the corresponding accelerated life model, the number of undetermined parameters in the model's theoretical formula is determined. For example, in the selected Peck temperature-humidity model, and n are two coefficients of the model that need to be determined. Based on the mathematical principles of parameter estimation, the number of stress level steps must meet the basic requirement of being greater than the number of unknown parameters in the model plus one; therefore, the number of stress steps is determined. Based on the number of unknown characteristic parameters included in the lifetime distribution model, and the basic requirement of at least three samples for solution in parameter estimation theory, to improve fitting accuracy and statistical confidence, the number of samples for each step is determined to be ten.

[0063] Step S42, Data Acquisition and Lifetime Extrapolation

[0064] During the experiment, performance parameters of each sample were measured periodically, and degradation trajectory data were collected. Specifically, a benchmark test was first performed before the experiment. The inherent resistance value of the test lead was accurately measured and recorded using the short-circuit calibration method as a reference for subsequent data correction. Under stable test conditions at each stress level, the resistance values ​​at locations such as single terminal-lap joint, double terminal-lap joint, and lap joint-metal structure were measured periodically using a calibrated resistance meter, and the corresponding environmental parameters and circuit status were recorded simultaneously. All measured resistance data were subtracted from the lead reference resistance to obtain the true component resistance. By comparing the measured resistance data with the benchmark data before the experiment and the measured values ​​over time, a performance degradation trajectory dataset was constructed.

[0065] For degradation data acquired at various stress levels, since the overlapping sections may fail, a full life-cycle curve needs to be fitted using existing experimental data. Specifically, based on the law that impedance performance parameters gradually increase with aging, stochastic degradation models and deterministic degradation models are used for fitting analysis. The stochastic degradation model considers individual differences and measurement uncertainties, describing the variability of the degradation path through a stochastic process; the deterministic degradation model establishes a parameterized mathematical function relationship based on the physical failure mechanism. By comparing the goodness-of-fit indices of different models, the model that best represents the actual degradation law is selected as the final modeling model. After determining the optimal degradation model, combined with a pre-set failure threshold, the fitted degradation trajectory function and the failure threshold equation are solved simultaneously to obtain the time point when each sample reaches the critical state, thus obtaining the pseudo-failure lifetime of each sample.

[0066] Step S43, Accelerate lifetime fitting failure rate calculation

[0067] Based on failure data from multiple stress levels, a statistical method is used to fit the lifetime distribution. First, the maximum likelihood estimation method is used for parameter estimation. This method, based on probability and statistics theory, obtains the optimal estimates of characteristic parameters in the lifetime distribution by constructing a likelihood function and finding its extreme values. After parameter estimation, a goodness-of-fit test is conducted to evaluate the rationality of the distribution hypothesis, using methods such as the Anderson-Darling test and the chi-square test. During the test, the test statistic is compared with the corresponding critical value. If the test statistic is less than the critical value, the distribution hypothesis is accepted. If the goodness-of-fit test fails, the completeness and accuracy of the experimental data acquisition need to be checked, and it needs to be confirmed whether the measurement system error is within a reasonable range. Second, the appropriateness of the lifetime distribution model selection should be reassessed, and alternative models such as the log-normal distribution should be considered. Finally, the consistency of the failure mechanism should be analyzed in depth, and it should be verified whether the accelerated test conditions induce additional failure modes.

[0068] Then, the characteristic lifetimes corresponding to multiple stress groups are obtained through the lifetime distribution model. The acceleration model is converted into an equation form. Based on the lifetime distribution characteristics obtained under each stress step and combined with the corresponding stress conditions, the Weibull distribution of the five stress groups can be fitted from the failure data of the previous five levels, obtaining the characteristic lifetimes corresponding to the five stress groups, denoted as N1, N2, N3, N4, and N5. These are substituted into the acceleration factor formula, and the converted acceleration equation is fitted and solved using a regression algorithm to obtain the unknown parameters of the acceleration factor and determine the acceleration coefficient. Finally, the temperature cycle under the working profile is converted into the number of stress cycles for any known characteristic lifetime using the acceleration coefficient. Based on the correspondence between the civil aircraft cycle time and the number of cycles, the MTBF of the electrical circuit network connection components is calculated, and the failure rate is obtained. The failure rate is the reciprocal of the MTBF.

[0069] The method for calculating the failure event index of aircraft electrical circuit networks according to embodiments of the present invention has the following beneficial effects:

[0070] This invention is guided by the overall approach of calculating the failure events of electrical circuit networks. Through Failure Mode and Effects Analysis (FMEA), it accurately identifies core failure events and combines multi-source technologies to customize dedicated failure rate calculation models for different types of failure events. Coupled with test specimens equivalent to installed products and covering typical configurations, along with scientific accelerated degradation testing and data fitting methods, it significantly improves the accuracy and confidence of failure rate calculations. Furthermore, it possesses strong engineering practicality; the simplified and reasonable model is adaptable to mainstream application scenarios, and the testing and data processing methods are mature and easy to operate, directly providing quantitative evidence for system reliability analysis. It can also accurately locate weak points, supporting aircraft electrical circuit network design optimization, quality control, and maintenance decisions, facilitating full lifecycle reliability management and reducing maintenance costs. Simultaneously, it breaks through the limitations of traditional measurement, constructing a complete technical system. Its core ideas can be extended to similar complex interconnected structure products, possessing both innovation and broad applicability.

[0071] The calculation method of this invention constructs a failure rate calculation system of "failure analysis - model customization - experimental verification". Targeting the parallel structure characteristics of aircraft electrical circuit networks and special failure mechanisms such as dissimilar metal contact corrosion, it identifies core underlying events through failure mode and effect analysis, customizes calculation schemes for each type of underlying event, obtains data through accelerated degradation tests, and matches life models to achieve accurate quantification of different failure types, breaking through the bottleneck of insufficient calculation accuracy of traditional methods.

[0072] The calculation method of this invention provides a specific fault mode identification and failure rate model construction method for aircraft electrical circuit networks. Specifically, it includes a fault mode and impact analysis process through system functional boundary definition, key combination configuration fault enumeration, and micro-mechanism and macro-fault correlation analysis, as well as a simplified modeling logic that focuses on core bottom events and ignores secondary influencing factors. It also covers customized calculation schemes such as dual-source data fusion calculation for cable failure, finite element simulation and fatigue theory combination for structural disconnection, and accelerated model application for electrical bridging corrosion, ensuring that the model is both consistent with actual working conditions and has engineering feasibility.

[0073] The calculation method of this invention is adapted to the experimental design and data processing method of aircraft electrical circuit network characteristics. It includes the use of test piece manufacturing standards with materials, processes and configurations (single / double terminal overlap, bracket and metal groove overlap) equivalent to the installed products, scientifically setting constant stress accelerated degradation test scheme with stress steps and sample quantity, and a full-process data processing method including pre-test short-circuit calibration, accurate data acquisition during the test, post-test multi-model fitting and selection, and pseudo-failure lifetime solution. It effectively solves the problems of long test cycle and insufficient data caused by slow component degradation under normal stress, and ensures the reliability and confidence of the calculation results.

[0074] The above describes the application of the method of the present invention in aircraft electrical circuit networks, and it can also be applied to industries with similar scenarios such as aviation, aerospace, automobiles, and rail transportation.

[0075] Embodiments of the present invention also provide a computer device, which may be a server, and its internal structure diagram may be as follows: Figure 3 As shown. The computer device includes a processor, memory, and a network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores operating parameter data for various components. The network interface communicates with external terminals via a network connection. When executed by the processor, the computer program implements the steps of the method according to embodiments of the present invention.

[0076] Those skilled in the art will understand that Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0077] Embodiments of the present invention also provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method of the embodiments of the present invention.

[0078] Embodiments of the present invention also provide a computer program product, including a computer program that, when executed by a processor, implements the steps of the method of the embodiments of the present invention.

[0079] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A method for calculating the failure event index of an aircraft electrical circuit network, characterized in that, include: Step S1: Identify key components and their failure modes in the aircraft electrical circuit network, establish the correlation from failure mechanism to failure mode, identify key sensitive stresses through failure mechanism analysis, and identify three core bottom events of aircraft electrical circuit network failure through failure mode and effect analysis, including cable failure, structural disconnection failure, and electrical bridging corrosion failure. Step S2: Determine the failure rate calculation method for each type of basic event. Cable failure is calculated by consulting the data manual. Structural disconnection failure is calculated by combining finite element simulation with fatigue theory and stress-strength interference model. Electrical lap corrosion failure is calculated by using accelerated testing to obtain degradation data to establish a failure rate calculation model and select a lifetime distribution model and an accelerated lifetime model. Step S3: Use materials, processes and configurations equivalent to those of the installed product to manufacture an electrical lap structure test piece to simulate the mechanical connection and electrical contact state of the actual electrical circuit network; Step S4: Determine the type of accelerated stress based on the sensitive stress analysis, determine the number of parameters to be determined based on the accelerated life model, set the number of stress steps and the number of samples based on the number of parameters to be determined, conduct accelerated tests on the test pieces, obtain failure data under each stress step, extrapolate the characteristic life under each stress step through the life distribution model, obtain the acceleration coefficient through the regression algorithm using the accelerated life model, and calculate the MTBF and failure rate of the electrical circuit network connection components based on the acceleration coefficient. In step S4, the accelerated life model is transformed into an acceleration equation. Based on the characteristic life under each stress step, the acceleration equation is fitted and solved by a regression algorithm in combination with the corresponding stress conditions to obtain the unknown parameters of the acceleration factor and determine the acceleration coefficient. The temperature cycle under the working profile is converted into the number of stress cycles with known characteristic life using the acceleration coefficient. Combining the correspondence between cycle time and cycle number, the MTBF of the electrical circuit network connection component is calculated, and then the failure rate is obtained.

2. The method as described in claim 1, characterized in that, In step S2, the Peck temperature-humidity model is determined as the accelerated life model, and the acceleration factor AF is: in, The percentage of relative humidity under operating conditions. This represents the percentage of relative humidity under stress conditions. Temperature in K under operating conditions. Let K be the temperature under stress, where k is the Boltzmann constant. Let be the activation energy expressed in electron volts, and n be a constant.

3. The method as described in claim 1 or 2, characterized in that, The electrical lap joint structure test piece consists of aluminum conductors, metal brackets and cable trays, terminals, and dissimilar metal lap joint interfaces. By simulating the mechanical connection and electrical contact state between terminals and lap joint structures in an actual electrical circuit network, it constructs an electrochemical corrosion sensitive unit. Test lines are reserved in the lap joint area to collect degradation data at regular intervals. The test piece is designed with three typical configurations: single-terminal lap joint, double-terminal lap joint, and bracket and metal tray lap joint. Each matching ERN cable forms a complete circuit.

4. The method as described in claim 1 or 2, characterized in that, In step S4, before the test, the inherent resistance of the test lead is determined by the short-circuit calibration method as a correction benchmark. Then, under the stable conditions of each stress step, the resistance at each overlap position is measured using a resistance tester. The actual component resistance is obtained by subtracting the lead resistance from the measured data. By comparing the measured data with the benchmark data before the test and the measured values ​​in the longitudinal direction, a performance degradation trajectory dataset is constructed.

5. The method as described in claim 4, characterized in that, For the degradation data obtained under various stress levels, random degradation models and deterministic degradation models were used for fitting. By comparing the goodness-of-fit indices of different models, the model that best represents the actual degradation law was selected as the optimal degradation model. Combined with a pre-set failure threshold, the degradation trajectory function obtained by fitting was solved simultaneously with the failure threshold equation to obtain the time point when each sample reached the critical state, thus obtaining the pseudo-failure lifetime of each sample.

6. The method as described in claim 1 or 2, characterized in that, In step S2, based on the failure mechanism analysis results, temperature, humidity, and vibration are identified as key sensitive stresses through multi-dimensional verification. By evaluating the mathematical characteristics and engineering applicability of multiple lifetime distribution models and combining the impedance change law presented by the performance degradation data of the lap joint components, the optimal lifetime distribution model is determined.

7. The method as described in claim 6, characterized in that, In step S4, based on failure data of multiple stress levels, the maximum likelihood estimation method is used to estimate the characteristic parameters of the lifetime distribution. The goodness-of-fit test is used to evaluate the rationality of the distribution assumption and to re-evaluate whether the selection of the lifetime distribution model is appropriate.

8. A computer device, comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the method according to any one of claims 1-7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1-7.

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