A method for quantifying the lifespan of aerospace BDR modules based on heterogeneous information fusion

Abstract

The present invention provides a method for quantifying the life of an aerospace BDR module based on heterogeneous information fusion, which includes S1: analyzing historical data of the aerospace BDR module; S2: performing a multi-stage FMMEA analysis on the aerospace BDR module to determine the fault elements that affect the performance of the aerospace BDR module; S3: designing an accelerated degradation experimental scheme based on key components; S4: constructing a component-level life quantification model; S5: constructing a system-level life quantification model; S6: judging whether the system-level reliability index meets the requirements; if not, returning to step S4 and reconstructing the component-level life quantification model; S7: determining the life prediction model of the aerospace BDR module. The present invention can perform reliable life prediction of the aerospace BDR module by performing FMMEA analysis on the aerospace BDR module and then performing component-level and system-level life quantification modeling. The obtained life quantification method also provides method support for guiding the life quantification of other aerospace electronic products.

Description

Technical Field

[0001] The present invention relates to the field of life prediction of aerospace electronic products, and in particular to a method for quantifying the life of an aerospace BDR module based on heterogeneous information fusion. Background Art

[0002] Space electronics are a crucial component of spacecraft, and their effective operating lifespan is a key factor in determining the lifespan of a spacecraft. Some spacecraft models have experienced premature end-of-life due to the short operating lifespan of electronic components. Furthermore, the inability to accurately control the operating lifespan of electronic components necessitates the inclusion of numerous redundant and backup electronic components. This results in system complexity, heavy weight, and high power consumption, increasing design complexity and negatively impacting spacecraft reliability.

[0003] The present invention will provide a technical method for accurately controlling the effective working life of the BDR module of spacecraft electronic products. By studying the identification technology of the life characteristics (sensitive loads and sensitive environmental factors) of electronic products and establishing a relationship model between key characteristic parameters and product life, it can support aerospace BDR module research and development units to effectively control their product life, thereby providing support for improving the reliability level of spacecraft product life. Summary of the Invention

[0004] In order to improve the research on spacecraft life prediction in my country, the present invention provides a life quantification method for aerospace BDR modules (battery discharge regulator modules) based on heterogeneous information fusion. By performing Failure Mode, Mechanism and Effects Analysis (FMMEA) on the aerospace BDR modules and then performing component-level and system-level heterogeneous information fusion life quantification modeling, the aerospace BDR modules can be reliably predicted. The obtained life quantification method also provides methodological support for guiding the life quantification of other aerospace electronic products.

[0005] The present invention provides a method for quantifying the life of an aerospace BDR module based on heterogeneous information fusion, which specifically includes the following steps:

[0006] S1: Analysis of historical data of aerospace BDR modules: Analyze and obtain the main failure modes of BDR modules, and establish a failure mode library based on the main failure modes;

[0007] S2: FMMEA analysis of multi-phase missions: Develop the basic process and implementation plan for FMMEA of multi-phase missions applicable to the space BDR module;

[0008] S3: Design an accelerated degradation test plan: Conduct accelerated degradation tests on each fault element of the aerospace BDR module;

[0009] S4. Establish component-level quantitative model: Build a component-level life quantitative model based on the data obtained from the degradation experiments of various fault elements of the aerospace BDR module;

[0010] S5. Establish a system-level life quantification model: Obtain the life of each fault element based on the component-level life quantification model, and use the short board effect to describe the system-level life;

[0011] S6. Verify system reliability: Perform reliability evaluation on the system-level life quantification model to determine whether the system-level reliability index meets the requirements. If not, return to step 4, rebuild the component-level quantification model, and iterate and update steps S4 to S6 until the system-level life quantification model meets the reliability index requirements. If the reliability index meets the requirements, the system-level life quantification model is considered to be complete.

[0012] S7. Determine and output the life quantification model of the aerospace BDR module.

[0013] Preferably, the S2 step comprises the following contents:

[0014] S21 analyzes the various failure elements of the aerospace BDR module from design, storage, transportation, launch, on-orbit operation, and scrapping in turn;

[0015] S22. Based on the failure mode library of the aerospace BDR module, sort out the possible failure modes, failure causes, and failure mechanisms of the aerospace BDR module in all mission phases, and determine the possible failure mechanisms of the aerospace BDR module;

[0016] S23. By analyzing the failure mechanisms of tasks at each stage, determine the main failure mechanism of the aerospace BDR module according to the risk level.

[0017] Preferably, the S3 step includes the following contents:

[0018] S31. According to the actual working environment of the aerospace BDR module, a simulated working environment is set and the aerospace BDR module is placed in the simulated working environment;

[0019] S32. Perform an accelerated degradation experiment on each of the fault elements.

[0020] Preferably, each of the fault elements at least includes: MOSFET, resistor, capacitor, inductor, diode, and solder joint.

[0021] Preferably, the accelerated degradation test at least includes: overload and temperature fatigue accelerated degradation tests.

[0022] Preferably, the S4 step comprises the following contents:

[0023] S41. Under overload and temperature fatigue accelerated degradation test conditions, record the experimental data of MOSFET, resistors, capacitors, inductors, diodes, and solder joints;

[0024] S42. Establish a quantitative model for resistor life, and the formula is as follows:

[0025]

[0026] Among them, τ is the average life under working conditions, P, P 额 are working and rated electrical power respectively, T is the ambient temperature, a, b, and C are constants;

[0027] S43. Establish a quantitative model for capacitor life, and the formula is as follows:

[0028]

[0029] Among them, E α is the activation energy, n is the voltage stress index, L is the lifespan, V is the voltage, T is the temperature, K b =8.617333262145×10 -5 eV / K is a constant, the subscript op is the preset condition, the subscript rated is the physical quantity that has been run, E α The values ​​of and n vary with the specific conditions of the capacitor;

[0030] S44. Establish a quantitative model for solder joint life. The formula is as follows:

[0031]

[0032] Among them, α w is the characteristic life, α is the diameter of the solder joint, N0 is the number of cycles when cracks appear, and dα / dN is the crack propagation speed;

[0033] S45. Establish a quantitative model for diode life, and the formula is as follows:

[0034]

[0035] Where t is the working life at room temperature, T1~T2 is the temperature range under experimental conditions, T0 is the temperature under working conditions, T is the junction temperature of the diode at time t, Q is the activation energy, β is the heating rate, and k is a constant;

[0036] S46. Establish a quantitative model for MOSFET lifespan. The formula is as follows:

[0037] lnΔVth=nln t+m

[0038] Wherein, t is the lifetime, ΔVth is the threshold voltage change, n is the time logarithmic coefficient, and m is the time logarithmic constant. Both n and m are obtained by fitting experimental data.

[0039] Preferably, the step S5 comprises the following contents:

[0040] S51. Under the Bayesian theory framework, likelihood functions for success / failure data, failure time data, and degradation data are constructed separately. Then, the Markov Chain Monte Carlo method is used to fuse the three likelihood functions to obtain the joint posterior distribution.

[0041] S52. Based on Bayesian theory, the joint posterior distribution and component-level life quantification model are used to quantify the life of each fault element;

[0042] S53. Use the short board effect to describe system-level lifetime;

[0043] S54. Compare the life values ​​of various fault elements in the aerospace BDR module, and use the minimum life value as the predicted life of the system-level aerospace BDR module.

[0044] Preferably, the step S6 comprises the following contents:

[0045] S61. Compare the root mean square error of the system-level reliability index with the set index. The RMSE formula is as follows:

[0046]

[0047] Where q represents the number of predictions, x(i) represents the actual life of the historical data of the Aerospace BDR module, Represents the predicted life of the aerospace BDR module;

[0048] S62: If the set index is met, then go to S7; if the set index is not met, then go back to step S4 to rebuild the component-level quantitative model.

[0049] The present invention performs FMMEA analysis on aerospace BDR modules and then conducts component-level and system-level life quantification modeling to reliably predict the life of aerospace BDR modules. The obtained life quantification method also provides methodological support for guiding the life quantification of other aerospace electronic products. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 This is a flowchart of the aerospace BDR module life quantification based on heterogeneous information fusion in the present invention;

[0051] Figure 2 This is the multi-stage task FMMEA flow chart of the present invention;

[0052] Figure 3This is a flow chart of the system-level life quantification based on heterogeneous information fusion of the present invention. DETAILED DESCRIPTION

[0053] The following further describes the method for quantifying the life of aerospace BDR modules based on heterogeneous information fusion proposed by the present invention in conjunction with the accompanying drawings and specific embodiments. The advantages and features of the present invention will become more apparent from the following description.

[0054] The present invention provides a method for quantifying the life of aerospace BDR modules based on heterogeneous information fusion, such as Figure 1 As shown, the following steps are included:

[0055] S1: Collect and mine historical failure analysis reports, field usage data, and field life test data of the faulty elements in the aerospace BDR module, analyze the main failure modes of the aerospace BDR module, and form a failure mode library for the aerospace BDR module as the main basis for fault mechanism identification. The faulty elements include: various components such as MOSFETs, resistors, capacitors, inductors, diodes, and physical connection points such as solder joints.

[0056] S2: Based on the failure mode library of the aerospace BDR module and the characteristics of the aerospace BDR module in all stages of missions, a basic process and implementation plan for the multi-stage mission failure mode, mechanism and effects analysis (FMMEA) of the aerospace BDR module is developed to determine the main failure mechanism of the aerospace BDR module, such as Figure 2 As shown, the specific steps are:

[0057] S21. From design, storage, transportation, launch, on-orbit operation to decommissioning, the phase tasks are named phase task 1 to phase task n in chronological order, and the failure elements of each phase are analyzed;

[0058] S22. Based on the failure mode library of the aerospace BDR module, sort out the possible failure modes, causes, and mechanisms of each failure element in the aerospace BDR module during all phases of the mission, and identify the possible failure mechanisms of the aerospace BDR module. Examples include package failure caused by component aging, overload, and mechanical damage, and performance degradation caused by component vibration fatigue, temperature fatigue, and impact damage.

[0059] S23. By analyzing the failure mechanisms of all phases of the mission and sorting them from high to low risk, the main failure mechanisms of the space BDR module were determined. These include package failure caused by overload of key components such as MOSFETs, resistors, capacitors, inductors, and diodes, and performance degradation caused by thermal fatigue.

[0060] S3. For space BDR modules performing missions in low orbit or its operational orbit, design accelerated degradation test plans for overload and temperature fatigue of key components such as MOSFETs, resistors, capacitors, inductors, and diodes, and conduct accelerated fatigue degradation tests on physical contacts such as solder joints. The specific steps are as follows:

[0061] S31. Considering that the aerospace BDR module is affected by environmental factors such as vibration, electrical stress, and radiation, after adopting the first-level derating and process control, conventional vibration and vacuum are set to simulate the actual working environment of the aerospace BDR module;

[0062] S32. Based on the multi-stage task failure mode, mechanism and impact analysis in step S2, and when it is determined that other failure mechanisms have little impact on the module life, conduct accelerated degradation experiments for overload and temperature fatigue.

[0063] S4. Based on the experimental data of key components such as MOSFET, resistors, capacitors, inductors, diodes, and solder joints that play a key role in the life of the aerospace BDR module, a component-level life quantification model is constructed for each key component. The specific steps are as follows:

[0064] S41. Under overload and temperature fatigue accelerated stress test conditions, record the voltage, current, power consumption and other data of key components such as MOSFET, resistors, capacitors, inductors, and diodes, and analyze the changing characteristics of voltage, current, and power consumption data;

[0065] S42. Establish a quantitative model for resistor life, and the formula is as follows:

[0066]

[0067] Among them, τ is the average life under working conditions, P, P 额 are working and rated electrical power respectively, T is the ambient temperature, a, b, and C are constants;

[0068] S43. Establish a quantitative model for capacitor life, and the formula is as follows:

[0069]

[0070] Among them, E α is the activation energy, n is the voltage stress index, L is the lifespan, V is the voltage, T is the temperature, K b =8.617333262145×10 -5 eV / K is a constant, the subscript op is the preset condition, the subscript rated is the physical quantity that has been run, E α The values ​​of and n vary with the specific conditions of the capacitor;

[0071] S44. Establish a quantitative model for the life of solder joints. The fatigue life can be considered as the sum of the fatigue crack formation life and the fatigue crack propagation life. The formula is as follows:

[0072]

[0073] Among them, α w is the characteristic life, α is the diameter of the solder joint (i.e., the length of the final crack), N0 is the number of cycles when the crack appears, and dα / dN is the crack propagation speed;

[0074] S45. Establish a quantitative model for diode life, and the formula is as follows:

[0075]

[0076] Where t is the working life at room temperature, T1~T2 is the temperature range under experimental conditions, T0 is the temperature under working conditions, T is the junction temperature of the diode at time t, Q is the activation energy, β is the heating rate, and k is a constant;

[0077] S46. Establish a quantitative model for MOSFET lifespan. The formula is as follows:

[0078] lnΔVth=nln t+m

[0079] Where t is the lifetime, ΔVth is the threshold voltage change, n is the time logarithmic coefficient, and m is the time logarithmic constant. Both n and m are obtained by fitting experimental data.

[0080] S5. Taking into account success / failure data, failure time data, and degradation data, a heterogeneous information fusion method is used to quantitatively model the system-level life of the aerospace BDR module. The usage of components such as MOSFETs, resistors, capacitors, inductors, and solder joints, as well as the structural layout within the module, are also considered. The short board effect is used to describe the system-level life. The specific steps are as follows:

[0081] S51. Under the Bayesian theory framework, the likelihood functions of success / failure data, failure time data, and degradation data are constructed separately. Then, the Markov Chain Monte Carlo (MCMC) method is used to fuse the three likelihood functions to obtain the joint posterior distribution, as shown in the following example: Figure 3 As shown;

[0082] S52. Based on Bayesian theory, the joint posterior distribution is used to estimate unknown parameters. Then, based on the parameter estimation results and the component-level lifetime quantification model, the lifetime of MOSFET, resistor, capacitor, inductor, diode, and solder joint failure elements is quantified.

[0083] S53. Taking into account the usage of failure elements such as MOSFETs, resistors, capacitors, inductors, diodes, and solder joints, as well as the structural layout of the internal interconnections of the aerospace BDR module, the short board effect is used to describe the system-level lifespan.

[0084] S54. Compare the theoretical lifespan values ​​of the MOSFET, resistors, capacitors, inductors, diodes, and solder joints in the aerospace BDR module, and take the minimum lifespan as the lifespan of the system-level aerospace BDR module to obtain the predicted lifespan of the aerospace BDR module.

[0085] S6. Perform reliability evaluation on the system-level life quantification model based on the predicted life of the aerospace BDR module to determine whether the system-level reliability indicators meet the requirements. If not, return to step 4, rebuild the component-level quantitative model, and iterate and update steps S4 to S6 to establish component-level and system-level quantitative models that meet the requirements. If the reliability indicators meet the requirements, the modeling is considered complete and the system-level life quantification model update is stopped. The specific steps are as follows:

[0086] S61. Compare the obtained system-level reliability index root mean square error (RMSE) with the set index. The RMSE formula is as follows:

[0087]

[0088] Where q represents the number of predictions, x(i) represents the actual life of the historical data of the Aerospace BDR module, Represents the predicted life of the aerospace BDR module;

[0089] S62: If the set indicators are met, proceed to the next step; if the set indicators are not met, re-enter step S4 to rebuild the component-level and system-level life quantification models;

[0090] S7. Record the iterative update results of the life quantification model. After the iteration stops, output the life quantification model that meets the system reliability index, and finally determine it as the life quantification model of the aerospace BDR module.

[0091] In summary, the present invention can reliably predict the life of aerospace BDR modules by performing FMMEA analysis on the modules and then performing component-level and system-level life quantification modeling. The obtained life quantification method also provides a methodological support for guiding the life quantification of other aerospace electronic products.

[0092] Although the present invention has been described in detail through the above preferred embodiments, it should be understood that the above description is not intended to limit the present invention. After reading the above description, various modifications and substitutions of the present invention will become apparent to those skilled in the art. Therefore, the scope of protection of the present invention should be defined by the appended claims.

Claims

1. A method for quantifying the life of aerospace BDR modules based on heterogeneous information fusion, characterized in that: The following steps are involved: S1: Analysis of historical data of aerospace BDR modules: Analyze and obtain the failure modes of BDR modules, and establish a failure mode library based on the failure modes; S2: FMMEA analysis of multi-phase missions: Develop the basic process and implementation plan for FMMEA of multi-phase missions applicable to the space BDR module; S3: Design an accelerated degradation test plan: Conduct accelerated degradation tests on each fault element of the aerospace BDR module; S4. Establish component-level quantitative model: Build a component-level life quantitative model based on the data obtained from the degradation experiments of various fault elements of the aerospace BDR module; S5. Establish a system-level life quantification model: Obtain the life of each fault element based on the component-level life quantification model, and use the short board effect to describe the system-level life; S6. Check system reliability: perform reliability evaluation on the system-level life quantification model to determine whether the system-level reliability index meets the requirements. If not, return to step S4, rebuild the component-level quantification model, and iterate and update steps S4 to S6 until the system-level life quantification model meets the reliability index requirements. If the reliability index meets the requirements, the system-level life quantification model is considered to be completed. S7. Determine and output a life quantification model for the aerospace BDR module; Each of the fault elements at least includes: MOSFET, resistor, capacitor, inductor, diode, and solder joint; The accelerated degradation test at least includes: overload and temperature fatigue accelerated degradation test; The S4 step includes the following contents: S41. Under overload and temperature fatigue accelerated degradation test conditions, record the experimental data of MOSFET, resistors, capacitors, inductors, diodes, and solder joints; S42. Establish a quantitative model for resistor life, and the formula is as follows: Among them, τ is the average life under working conditions, P, P 额 are working and rated electrical power respectively, T is the ambient temperature, a, b, and C are constants; S43. Establish a quantitative model for capacitor life, and the formula is as follows: Among them, E α is the activation energy, n is the voltage stress index, L is the lifespan, V is the voltage, T is the ambient temperature, K b =8.617333262145×10 -5 eV / K is a constant, the subscript op is the preset condition, the subscript rated is the physical quantity that has been run, E α The values ​​of and n vary with the specific conditions of the capacitor; S44. Establish a quantitative model for solder joint life. The formula is as follows: Among them, α w is the characteristic life, α is the diameter of the solder joint, N0 is the number of cycles when cracks appear, and dα / dN is the crack propagation speed; S45. Establish a quantitative model for diode life, and the formula is as follows: Where t is the working life at room temperature, T1~T2 is the temperature range under experimental conditions, T0 is the temperature under working conditions, T is the junction temperature of the diode at time t, Q is the activation energy, β is the heating rate, and k is a constant; S46. Establish a quantitative model for MOSFET lifespan. The formula is as follows: lnΔVth=nln t+m Where t is the lifetime, ΔVth is the threshold voltage change, n is the time logarithmic coefficient, and m is the time logarithmic constant. Both n and m are obtained by fitting experimental data. The S5 step includes the following contents: S51. Under the Bayesian theory framework, likelihood functions for success / failure data, failure time data, and degradation data are constructed separately. Then, the Markov Chain Monte Carlo method is used to fuse the three likelihood functions to obtain the joint posterior distribution. S52. Based on Bayesian theory, the joint posterior distribution and component-level life quantification model are used to quantify the life of each fault element; S53. Use the short board effect to describe system-level lifetime; S54. Compare the life values ​​of various fault elements in the aerospace BDR module, and use the minimum life value as the predicted life of the system-level aerospace BDR module.

2. The method for quantifying the life of aerospace BDR modules based on heterogeneous information fusion according to claim 1, characterized in that: The S2 step includes the following contents: S21. Analyze the various failure elements of the aerospace BDR module from design, storage, transportation, launch, on-orbit operation, and scrapping in turn; S22. Based on the failure mode library of the aerospace BDR module, sort out the possible failure modes, failure causes, and failure mechanisms of the aerospace BDR module in all mission phases, and determine the possible failure mechanisms of the aerospace BDR module; S23. By analyzing the failure mechanisms of tasks at each stage, determine the main failure mechanism of the aerospace BDR module according to the risk level.

3. The method for quantifying the life of aerospace BDR modules based on heterogeneous information fusion according to claim 1, characterized in that: The S3 step includes the following: S31. According to the actual working environment of the aerospace BDR module, a simulated working environment is set and the aerospace BDR module is placed in the simulated working environment; S32. Perform an accelerated degradation experiment on each of the fault elements.

4. The method for quantifying the life of aerospace BDR modules based on heterogeneous information fusion according to claim 1, characterized in that: The S6 step includes the following contents: S61. Compare the root mean square error of the system-level reliability index with the set index. The RMSE formula is as follows: Where q represents the number of predictions, x(i) represents the actual life of the historical data of the Aerospace BDR module, Represents the predicted life of the aerospace BDR module; S62: If the set index is met, then go to S7; if the set index is not met, then go back to step S4 to rebuild the component-level quantitative model.

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