A reliability evaluation method for airborne equipment based on development test data

Abstract

The present application belongs to the field of reliability evaluation, and relates to a kind of reliability evaluation method of aviation airborne equipment based on development test data.The present application collects and records all actual use information of equipment from the first prototype production to design before finalization;The statistical failure information is discriminated, counted and classified;Reference equipment itself reliability investigation / identification test, reliability investigation / identification test of similar historical type or temperature-vibration condition in comprehensive profile determined by GJB 899A method to determine the reference environment condition of equipment;Adopt the environment conversion factor calculation method based on the acceleration life model to determine the environment conversion factor;Equivalent working time of equipment during the whole development process is converted, and AMSAA reliability growth model is used for reliability parameter evaluation.The present application effectively solves the problem of limited reliability evaluation caused by small sample, long reliability test period, limited development test data, changing technical state and changing use conditions of airborne equipment.

Description

Technical Field

[0001] This invention belongs to the field of reliability assessment, specifically, it relates to a method for assessing the reliability of airborne equipment based on research and development test data. Background Technology

[0002] Airborne equipment is a crucial component of aircraft. Over the past few decades, with continuous advancements in electronic information technology and manufacturing processes, the integration and reliability of airborne equipment have steadily increased. Reliability is a critical, universally important quality characteristic for users. For complex, critical, and repairable equipment, reliability assessments are necessary before deployment to determine if it meets tactical and technical requirements. Furthermore, reliability evaluations conducted during the development phase of airborne equipment can provide valuable insights for optimizing equipment support measures and improving equipment design, facilitating more comprehensive reliability growth management.

[0003] Currently, commonly used reliability assessment methods in the development phase of airborne equipment include reliability qualification testing, similar product analysis and evaluation, and comprehensive reliability assessment. Among these, comprehensive reliability assessment utilizes various test data from the development process, eliminating the cost of reliability test pieces and tests, and does not require data from highly similar products. It is applicable to newly developed equipment without historical information or information on similar products, and is increasingly favored.

[0004] Reliability comprehensive assessment in engineering applications faces two main challenges: the determination and analysis of environmental conditions, and the selection of assessment models. For avionics upgrade equipment with a sound development foundation and stable technical status during development, the assessment methods in GJB 899A can be referenced for reliability assessment. However, for newly developed avionics equipment, the technical status changes frequently during development, making the assessment methods in GJB 899A inaccurate and unable to fully utilize information from the entire equipment development process. Summary of the Invention

[0005] The purpose of this invention is to propose a reliability assessment method for airborne equipment based on research and development test data. By obtaining environmental reduction factors under various environments through accelerated life modeling, and integrating different test information, a reliability growth model is used for reliability assessment. This method can effectively solve the problems of limited reliability assessment and hindered reliability growth management caused by small sample sizes, long reliability test cycles, limited research and development test data, changes in technical status, and variable usage conditions. It provides strong data support for the reliability improvement and qualification of airborne equipment.

[0006] To achieve the above objectives, the present invention employs the following technical solution: a reliability assessment method for airborne equipment based on research and development test data, comprising the following steps:

[0007] Step S1: Reliability information collection, collecting and recording all actual usage information of the equipment from the production of the first prototype to the finalization of the design;

[0008] Step S2: Fault Statistical Analysis: Identify, statistically analyze, and classify fault information;

[0009] Step S3: Determine the baseline environmental conditions: Determine the baseline environmental conditions of the equipment by referring to the equipment's own reliability assessment and qualification test, the reliability assessment and qualification test of similar historical models, or the temperature-vibration conditions in the comprehensive profile determined by the GJB 899A method.

[0010] Step S4: Determine the environmental reduction factor: The environmental reduction factor is determined using the environmental reduction factor calculation method based on the accelerated life model;

[0011] Step S5: Comprehensive Reliability Assessment: Based on the reliability information of the collected test times and fault information of the equipment, the equivalent working time of the entire development process of the equipment is calculated using the environmental reduction factor, and the reliability parameters are evaluated using the AMSAA reliability growth model.

[0012] The reliability information in step S1 includes prototype debugging, environmental stress screening, testing, environmental testing, electromagnetic compatibility testing, reliability baseline testing, and field flight testing.

[0013] The reliability information collection step S1 includes the following steps:

[0014] Step S101: Collect prototype debugging and testing information, including equipment operating time, debugging and testing environment conditions, and fault summary information;

[0015] Step S102: Collect equipment environmental stress screening and environmental test information. Information elements include equipment part number and technical status, test conditions for each test item, test time, test results, and fault summary information.

[0016] Step S103: Collect equipment reliability assessment test information. Information elements include equipment part number and technical status, test profile, test time, test items, test results, and fault summary information.

[0017] Step S104: Collect field test flight information of the equipment. Information elements include equipment part number and technical status, test flight subjects, equipment operation status, and fault summary information.

[0018] The fault statistical analysis in step S2 includes the following steps:

[0019] Step S201: Fault identification: The criteria are as follows: For basic reliability parameter assessment, all faults attributable to the responsible party should be included in the statistics; for mission reliability parameter assessment, only faults attributable to the responsible party that affect mission completion should be included in the statistics.

[0020] Step S202: Fault Statistics: Merge and count the number of faults within the statistical range;

[0021] Step S203: Fault Classification: The fault classification method shall be performed in accordance with the method in GJB / Z 77, and the number and type information of Class A faults and Class B faults shall be counted respectively.

[0022] The principle for merging and statistically analyzing the number of faults within the statistical range in step S202 is as follows:

[0023] 5) Intermittent faults or multiple false alarms occurring in the same equipment during a single test will only be counted as one fault:

[0024] 6) When analysis confirms that multiple failure modes appearing in a single test are caused by the failure of the same component or device, the test is counted as one failure.

[0025] 7) In the event that multiple parts or components fail simultaneously, and it cannot be proven that one failure caused the other failures, each failure of a part or component shall be recorded as an independent failure.

[0026] 8) Faults that have been reported but reappear due to failure to be properly fixed or the technical status not being implemented.

[0027] This should be combined with the previously reported faults to form one fault.

[0028] Step S203 specifically involves:

[0029] 1) Systemic failure: A failure caused by an inherent factor and appearing in a specific form. It can only be eliminated by modifying the product design, production process, operating procedures or other related factors. Systemic failures are induced by simulating the cause of the failure. Corrective maintenance without improvement measures usually cannot eliminate the cause of systemic failure.

[0030] 2) Residual failures: Faults that occur randomly due to certain accidental factors, other than systemic failures, are generally difficult to repeat.

[0031] 3) Class A failures: Systemic failures and all residual failures that are determined not to be corrected due to limitations in funding, time, technical conditions, or other reasons.

[0032] 4) Class B failures: those systemic failures whose failure rate can be economically reduced.

[0033] The definition of the faults to be held responsible: Faults that meet the following conditions are recorded as faults to be held responsible: 1) Faults caused by design defects or poor manufacturing processes. Faults caused by processes in the environmental stress screening can be excluded.

[0034] 2) Failures caused by potential defects in parts and components.

[0035] 3) Software-related failures after software acceptance and delivery;

[0036] 4) Faults with unknown causes;

[0037] Other failures caused by misoperation, improper installation, monitoring equipment malfunction, or improper test conditions are recorded as non-responsibility.

[0038] Step S4, which determines the environmental reduction factor, includes the following steps:

[0039] Step S401: Calculate the reduction factor for temperature conditions using the Arrhenius accelerated life model. The calculation formula is as follows:

[0040]

[0041] In the formula:

[0042] Ea is the activation energy, which generally ranges from 0.6 to 1.2 eV. It is selected based on product characteristics and failure mechanism, and the empirical value is 0.79 eV.

[0043] KT (x，y) This is the temperature condition reduction factor;

[0044] K is the Boltzmann constant, which is 8.6171 × 10⁻⁶. -4 eV / K;

[0045] T x T y The temperature is given under conditions x and y, and the unit is °C.

[0046] Step S402: Calculate the reduction factor of the vibration condition using the inverse power law accelerated life model. The calculation formula is as follows:

[0047]

[0048] In the formula:

[0049] KV (x，y) This is the vibration condition reduction factor;

[0050] V x V y The random vibration values ​​under x and y conditions are characterized by acceleration spectral density, with units of g.2 / Hz;

[0051] m is a material constant, which is generally taken as 4 for avionics equipment;

[0052] For sinusoidal vibration conditions, V in the above equation x V y The sinusoidal vibration values ​​under x and y conditions are characterized by peak acceleration in g; the value of m is 6.

[0053] The reliability comprehensive assessment in step S5 includes the following steps:

[0054] Step S501: Calculate the equivalent working time t for the entire equipment development process based on the conversion factor and the collected equipment reliability information. ss ;

[0055] Step S502: Calculate the shape parameters after parameter estimation of the first failure time of M types of B faults according to the AMSAA model;

[0056] Step S503: Calculate reliability parameters using the AMSAA reliability growth model;

[0057] Step S504: Evaluate the range level of equipment reliability parameters. When the confidence level is C, the formula for estimating the range of Mean Time Between Failures (MTBF) is as follows:

[0058]

[0059] In formulas (9) to (10):

[0060] MTBF L Lower limit of the estimated mean time between failures (MTBF);

[0061] MTBF U : Upper limit of the estimated mean time between failures (MTBF);

[0062] θ L (C′,r s ): The lower limit adjustment factor calculated using the chi-square quantile;

[0063] θ U (C′,r s ): The upper limit adjustment factor calculated using the chi-square quantile;

[0064] C ′ One-sided probability value;

[0065] r s The adjusted number of faults, i.e., the number of faults after considering fault classification and the effectiveness of corrective measures;

[0066] C: Confidence level;

[0067] Because the number of faults r calculated according to the AMSAA model s Not an integer, in calculating θ L and θ U The calculation is performed using an interpolation method based on adjacent integer fault numbers.

[0068] The equivalent working time t of step S501 ss The conversion formula is as follows:

[0069]

[0070] t ss =t sst +t ssv (5)

[0071] In formulas (3) to (5):

[0072] T0 is the reference temperature; V0 is the reference vibration condition; t T0 The operating time under the reference temperature condition; t V0 The operating time under reference vibration conditions; kT (i，0) The reduction factor under a certain temperature condition; kV (i，0) t is the reduction factor under a certain vibration condition; i t represents the working time under certain experimental conditions. sst The time converted according to the reference temperature conditions; t ssv The time t is the time converted according to the reference vibration condition. ss The total working time of the entire equipment development process is converted into the total working time under reference temperature and reference vibration conditions.

[0073] The formula for calculating the shape parameters in step S502 is as follows:

[0074] When M > 1, the shape parameter b is estimated as follows:

[0075]

[0076] When M=1, the shape parameter b is estimated as follows:

[0077]

[0078] In formulas (6) to (7): The shape parameters are those estimated using the AMSAA model; t i t represents the cumulative test time at the occurrence of the i-th failure; M represents the number of type B failures; Ts The total effective test time for the comprehensive reliability assessment after environmental considerations are calculated.

[0079] The reliability parameter in step S503 is calculated using the following formula:

[0080]

[0081] In the formula:

[0082] MTBF stands for Mean Time Between Failures.

[0083] t Ts The total effective test time for the comprehensive reliability assessment after environmental adjustments is t, which is the value in formula (5). ss ;

[0084] r s This is the adjusted number of faults, that is, the number of faults after considering fault classification and the effectiveness of correction;

[0085] K A This represents the total number of Class A failures during the development process.

[0086] K B This represents the total number of Class B failures during the development process.

[0087] d is the effectiveness coefficient for correcting Class B faults, and its value ranges from 0.55 to 0.85. In the absence of historical data, the average value of empirical data of 0.7 can be used.

[0088] M represents the number of types of Class B faults.

[0089] Technical effects of this invention: This invention proposes a reliability assessment method for airborne equipment based on research and development test data. By obtaining environmental reduction factors under various environments through accelerated life modeling, and integrating different test information, a reliability growth model is used for reliability assessment. This method can effectively solve the problems of limited reliability assessment and hindered reliability growth management caused by small sample sizes, long reliability test cycles, limited research and development test data, changes in technical status, and variable usage conditions of airborne equipment. It provides strong data support for the reliability improvement and qualification of airborne equipment. Attached Figure Description

[0090] Figure 1 This is a flowchart of the present invention. Detailed Implementation

[0091] The specific embodiments of the present invention are described below to enable those skilled in the art to understand the present invention. However, it should be understood that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the present invention as defined and determined by the appended claims. All inventions utilizing the concept of the present invention are protected.

[0092] A reliability assessment method for airborne equipment based on development and testing data includes the following steps:

[0093] Step S1: Reliability Information Collection. Collect and record all actual usage information of the equipment from the production of the first prototype to the final design. Reliability information includes prototype debugging, environmental stress screening, testing, environmental testing, electromagnetic compatibility testing, reliability baseline testing, and field flight testing.

[0094] The reliability information collection step S1 includes the following steps:

[0095] Step S101: Collect prototype debugging and testing information, including equipment operating time, debugging and testing environment conditions, and fault summary information;

[0096] Step S102: Collect equipment environmental stress screening and environmental test information. Information elements include equipment part number and technical status, test conditions for each test item, test time, test results, and fault summary information.

[0097] Step S103: Collect equipment reliability assessment test information. Information elements include equipment part number and technical status, test profile, test time, test items, test results, and fault summary information.

[0098] Step S104: Collect field test flight information of the equipment. Information elements include equipment part number and technical status, test flight subjects, equipment operation status, and fault summary information.

[0099] Step S2: Fault Statistical Analysis: Identify, statistically analyze, and classify fault information.

[0100] The fault statistical analysis includes the following steps:

[0101] Step S201: Fault identification: The criteria are as follows: For basic reliability parameter assessment, all faults attributable to the responsible party should be included in the statistics; for mission reliability parameter assessment, only faults attributable to the responsible party that affect mission completion should be included in the statistics.

[0102] Step S202: Fault Statistics: The number of faults within the statistical range is merged and statistically analyzed according to the following principles:

[0103] 1) Intermittent faults or multiple false alarms occurring in the same equipment during a single test are counted as only one fault:

[0104] 2) When analysis confirms that multiple failure modes in a single test are caused by the failure of the same component or device, the test is counted as one failure.

[0105] 3) In the case of multiple components or parts failing at the same time, if it cannot be proven that one failure caused the other failures, each component or part failure shall be recorded as an independent failure.

[0106] 4) If a previously reported fault recurs due to failure to be properly repaired or the technical status not being implemented, it should be counted as one fault along with the previously reported fault.

[0107] Step S203: Fault Classification: The fault classification method shall be performed according to the method in GJB / Z 77, and the quantity and type information of Class A faults and Class B faults shall be counted respectively: Specifically:

[0108] 1) Systemic failure: A failure caused by an inherent factor and appearing in a specific form. It can only be eliminated by modifying the product design, production process, operating procedures or other related factors. Systemic failures are induced by simulating the cause of the failure. Corrective maintenance without improvement measures usually cannot eliminate the cause of systemic failure.

[0109] 2) Residual failures: Faults that occur randomly due to certain accidental factors, other than systemic failures, are generally difficult to repeat.

[0110] 3) Class A failures: Systemic failures and all residual failures that are determined not to be corrected due to limitations in funding, time, technical conditions, or other reasons.

[0111] 4) Class B Faults: Systemic faults whose failure rate can be economically reduced. Step S3: Determine the baseline environmental conditions: Determine the baseline environmental conditions of the equipment by referring to the equipment's own reliability assessment and qualification tests, the reliability assessment and qualification tests of similar historical models, or the temperature-vibration conditions in the comprehensive profile determined by the GJB899A method; for the temperature environment, count the duration of each temperature condition; for the vibration environment, count the vibration power spectral density and duration of each vibration condition. The definition of responsible and non-responsible faults: Faults meeting the following conditions are recorded as responsible faults: 1) Faults caused by design defects or poor manufacturing processes; faults caused by processes are not included in the environmental stress screening.

[0112] 2) Failures caused by potential defects in parts and components.

[0113] 3) Software-related failures after software acceptance and delivery;

[0114] 4) Faults with unknown causes;

[0115] Other failures caused by misoperation, improper installation, monitoring equipment malfunction, or improper test conditions are recorded as non-responsibility.

[0116] Step S4: Determine the environmental reduction factor: Determine the environmental reduction factor using the environmental reduction factor calculation method based on the accelerated life model; determining the environmental reduction factor includes the following steps:

[0117] Step S401: Calculate the reduction factor for temperature conditions using the Arrhenius accelerated life model. The calculation formula is as follows:

[0118]

[0119] In the formula:

[0120] Ea is the activation energy, which generally ranges from 0.6 to 1.2 eV. It is selected based on product characteristics and failure mechanism, and the empirical value is 0.79 eV.

[0121] KT (x，y) This is the temperature condition reduction factor;

[0122] K is the Boltzmann constant, which is 8.6171 × 10⁻⁶. -4 eV / K;

[0123] T x T y The temperature is given under conditions x and y, and the unit is °C.

[0124] Step S402: Calculate the reduction factor of the vibration condition using the inverse power law accelerated life model. The calculation formula is as follows:

[0125]

[0126] In the formula:

[0127] KV (x，y) This is the vibration condition reduction factor;

[0128] V x V y The random vibration values ​​under x and y conditions are characterized by acceleration spectral density, with units of g. 2 / Hz;

[0129] m is a material constant, which is generally taken as 4 for avionics equipment;

[0130] For sinusoidal vibration conditions, V in the above equation x V y The sinusoidal vibration values ​​under x and y conditions are characterized by peak acceleration in g; the value of m is 6.

[0131] Step S5: Comprehensive Reliability Assessment: Based on the reliability information collected from various equipment test times and failure data, the equivalent operating time of the entire equipment development process is calculated using an environmental reduction factor. The AMSAA reliability growth model is then used to assess reliability parameters. The comprehensive reliability assessment includes the following steps:

[0132] Step S501: Calculate the equivalent working time t for the entire equipment development process based on the conversion factor and the collected equipment reliability information. ss The conversion formula is as follows:

[0133]

[0134] t ss =t sst +t ssv (5)

[0135] In formulas (3) to (5):

[0136] T0 is the reference temperature; V0 is the reference vibration condition; t T0 The operating time under the reference temperature condition; t V0 The operating time under reference vibration conditions; kT (i，0) The reduction factor under a certain temperature condition; kV (i，0) t is the reduction factor under a certain vibration condition; i t represents the working time under certain experimental conditions. sst The time converted according to the reference temperature conditions; t ssv The time t is the time converted according to the reference vibration condition. ss The total working time after converting the entire equipment development process into the reference temperature and reference vibration conditions;

[0137] Step S502: Calculate the shape parameters after parameter estimation of the first failure time of M types of Class B faults using the AMSAA model. The calculation formula is as follows:

[0138] When M > 1, the shape parameter b is estimated as follows:

[0139]

[0140] When M=1, the shape parameter b is estimated as follows:

[0141]

[0142] In formulas (6) to (7): The shape parameters are those estimated using the AMSAA model; t i t represents the cumulative test time at the occurrence of the i-th failure; M represents the number of type B failures; TsThis represents the total effective test time for the comprehensive reliability assessment after environmental adjustments. Step S503: Calculate the reliability parameters using the AMSAA reliability growth model. The calculation formula is as follows:

[0143]

[0144] In the formula:

[0145] MTBF stands for Mean Time Between Failures.

[0146] t Ts The total effective test time for the comprehensive reliability assessment after environmental adjustments is t, which is the value in formula (5). ss ;

[0147] r s This is the adjusted number of faults, that is, the number of faults after considering fault classification and the effectiveness of correction;

[0148] K A This represents the total number of Class A failures during the development process.

[0149] K B This represents the total number of Class B failures during the development process.

[0150] d is the effectiveness coefficient for correcting Class B faults, and its value ranges from 0.55 to 0.85. In the absence of historical data, the average value of empirical data of 0.7 can be used.

[0151] M represents the number of types of Class B faults;

[0152] Step S504: Evaluate the range level of equipment reliability parameters. When the confidence level is C, the formula for estimating the range of Mean Time Between Failures (MTBF) is as follows:

[0153]

[0154] In formulas (9) to (10):

[0155] MTBF L Lower limit of the estimated mean time between failures (MTBF);

[0156] MTBF U : Upper limit of the estimated mean time between failures (MTBF);

[0157] θ L (C′,r s ): The lower limit adjustment factor calculated using the chi-square quantile;

[0158] θ U (C′,r s ): The upper limit adjustment factor calculated using the chi-square quantile;

[0159] C ′ One-sided probability value;

[0160] r s The adjusted number of faults, i.e., the number of faults after considering fault classification and the effectiveness of corrective measures;

[0161] C: Confidence level.

[0162] Because the number of faults r calculated according to the AMSAA model s Not an integer, in calculating θ L and θ U The calculation is performed using an interpolation method based on adjacent integer fault numbers.

[0163] Example:

[0164] The implementation steps for reliability assessment of a certain type of integrated instrument are as follows:

[0165] Step S1: Collect all reliability information of a certain type of integrated instrument from the initial design stage to the prototype trial production stage and before design evaluation, as shown in Table 1.

[0166] Table 1. Reliability Information Collection Table for a Certain Type of Integrated Instrument

[0167]

[0168]

[0169] Step S2: Fault Statistical Analysis. From the initial design stage to the prototype manufacturing and design evaluation, a certain type of integrated instrument experienced 0 Class A faults and 2 Class B faults. There are 2 types of Class B faults, as detailed in Table 1.

[0170] Step S3: Determine the baseline environmental conditions and record the duration. A certain type of integrated instrument underwent a reliability baseline test according to the top-level requirements of the model. Therefore, the reliability baseline test profile was selected as the baseline environmental conditions, and the temperature and vibration conditions in the profile were statistically analyzed, as shown in Table 2.

[0171] Table 2. Statistical Table of Baseline Environmental Conditions

[0172]

[0173] Step S4: Determine the environmental reduction factor. The environmental reduction factor of a certain type of integrated instrument is calculated according to formula (1) to formula (2) based on the accelerated life model, as shown in Table 3.

[0174] Table 3 Environmental Expiration Factors

[0175]

[0176] Step S5: Comprehensive Reliability Assessment. Based on the collected reliability information such as test times and fault information of a certain type of integrated instrument, the equivalent working time of its entire development process is calculated to be 4979.56 hours using the environmental reduction factor. The reliability parameters are evaluated using the AMSAA reliability growth model, and the lower confidence limit is estimated to be 979.23 hours at a 60% confidence level.

[0177] The fault statistical analysis in step S2 includes the following steps:

[0178] Step S201: Fault Identification. For a certain type of integrated instrument, only basic reliability parameters need to be evaluated; therefore, only faults of responsibility are counted.

[0179] Step S202: Fault Statistics. A certain type of integrated instrument experienced a total of 3 faults from the initial design stage to the prototype trial production and design appraisal stage, of which 2 were attributable to the user. See Table 1 for details.

[0180] Step S203: Fault Classification. A certain type of integrated instrument experienced 0 Class A faults and 2 Class B faults from the initial design stage to the design appraisal stage. There are 2 types of Class B faults, as detailed in Table 1.

[0181] Step S4, determining the environmental reduction factor, includes the following steps:

[0182] Step S401: Calculate the reduction factor for temperature conditions using the Arrhenius accelerated life model. The calculation results are detailed in Table 3.

[0183] Step S402: Calculate the reduction factor of vibration conditions using the inverse power law accelerated life model. The calculation results are detailed in Table 3.

[0184] The reliability comprehensive assessment in step S5 includes the following steps:

[0185] Step S501: Based on the conversion factor and the collected reliability information, calculate the equivalent working time of the entire development process of a certain type of integrated instrument according to formula (3) to formula (5). The conversion result is 4979.56h, see Table 4 for details.

[0186] Table 4 Equivalent Time Conversion Table

[0187]

[0188]

[0189] Step S502: Calculate the first failure time of Class B faults according to formulas (6) to (7), and the shape parameters after parameter estimation using the AMSAA model. A certain type of integrated instrument t Ts =4979.56h, K A =0,K B=2, d=0.7, M=2, therefore:

[0190]

[0191] Step S503: Calculate the reliability parameters of a certain type of integrated instrument using the AMSAA reliability growth model according to formula (8):

[0192]

[0193] Step S504: Evaluate the lower confidence limit of the MTBF of a certain type of integrated instrument. Calculate the lower confidence limit of the reliability parameter according to formula (9) at a 60% confidence level:

[0194] MTBF L =MTBF×θ L (0.8,1.41)=3515.01×0.2786=979.23h.

Claims

1. A reliability assessment method for airborne equipment based on research and development test data, characterized in that, Includes the following steps: Step S1: Reliability information collection, collecting and recording all actual usage information of the equipment from the production of the first prototype to the finalization of the design; Step S2: Fault Statistical Analysis: Identify, statistically analyze, and classify fault information; Step S3: Determine the baseline environmental conditions: Determine the baseline environmental conditions of the equipment by referring to the equipment's own reliability assessment and qualification test, the reliability assessment and qualification test of similar historical models, or the temperature-vibration conditions in the comprehensive profile determined by the GJB 899A method. Step S4: Determine the environmental reduction factor: The environmental reduction factor is determined using the environmental reduction factor calculation method based on the accelerated life model; Step S5: Comprehensive Reliability Assessment: Based on the reliability information of the collected test times and fault information of the equipment, the equivalent working time of the entire development process of the equipment is calculated using the environmental reduction factor, and the reliability parameters are evaluated using the AMSAA reliability growth model.

2. The reliability assessment method for airborne equipment based on research and development test data according to claim 1, characterized in that, The reliability information in step S1 includes prototype debugging, environmental stress screening, testing, environmental testing, electromagnetic compatibility testing, reliability baseline testing, and field flight testing.

3. The reliability assessment method for airborne equipment based on research and development test data according to claim 1, characterized in that, The reliability information collection step S1 includes the following steps: Step S101: Collect prototype debugging and testing information, including equipment operating time, debugging and testing environment conditions, and fault summary information; Step S102: Collect equipment environmental stress screening and environmental test information. Information elements include equipment part number and technical status, test conditions for each test item, test time, test results, and fault summary information. Step S103: Collect equipment reliability assessment test information. Information elements include equipment part number and technical status, test profile, test time, test items, test results, and fault summary information. Step S104: Collect field test flight information of the equipment. Information elements include equipment part number and technical status, test flight subjects, equipment operation status, and fault summary information.

4. The reliability assessment method for airborne equipment based on research and development test data according to claim 1, characterized in that, The fault statistical analysis in step S2 includes the following steps: Step S201: Fault identification: The criteria are as follows: For basic reliability parameter assessment, all faults attributable to the responsible party should be included in the statistics; for mission reliability parameter assessment, only faults attributable to the responsible party that affect mission completion should be included in the statistics. Step S202: Fault Statistics: Merge and count the number of faults within the statistical range; Step S203: Fault Classification: The fault classification method shall be performed in accordance with the method in GJB / Z 77, and the number and type information of Class A faults and Class B faults shall be counted respectively.

5. The reliability assessment method for airborne equipment based on research and development test data according to claim 4, characterized in that, The principle for merging and statistically analyzing the number of faults within the statistical range in step S202 is as follows: 1) Intermittent faults or multiple false alarms occurring in the same equipment during a single test are counted as only one fault: 2) When analysis confirms that multiple failure modes in a single test are caused by the failure of the same component or device, the test is counted as one failure. 3) In the case of multiple components or parts failing at the same time, if it cannot be proven that one failure caused the other failures, each component or part failure shall be recorded as an independent failure. 4) If a previously reported fault recurs due to failure to be properly repaired or the technical status not being implemented, it should be counted as one fault along with the previously reported fault.

6. The reliability assessment method for airborne equipment based on research and development test data according to claim 4, characterized in that, Step S203 specifically involves: 1) Systemic failure: A failure caused by an inherent factor and appearing in a specific form, which can only be eliminated by modifying product design, production process, operating procedures or other related factors; Systemic failures are induced by simulating the causes of failures, and corrective maintenance without improvement measures usually cannot eliminate the causes of systemic failures. 2) Residual failures: Failures that occur randomly due to certain accidental factors, other than systemic failures, are generally difficult to repeat. 3) Class A failures: Systemic failures and all residual failures that are determined not to be corrected due to limitations in funding, time, technical conditions, or other reasons. 4) Class B failures: those systemic failures whose failure rate can be economically reduced.

7. The reliability assessment method for airborne equipment based on research and development test data according to claim 4, characterized in that, The definition of the faults to be held responsible: Faults that meet the following conditions are recorded as faults to be held responsible: 1) Faults caused by design defects or poor manufacturing processes. Faults caused by processes in the environmental stress screening can be excluded. 2) Failures caused by potential defects in parts and components. 3) Software-related failures after software acceptance and delivery; 4) Faults with unknown causes; Other failures caused by misoperation, improper installation, monitoring equipment malfunction, or improper test conditions are recorded as non-responsibility.

8. The reliability assessment method for airborne equipment based on research and development test data according to claim 1, characterized in that, Step S4, which determines the environmental reduction factor, includes the following steps: Step S401: Calculate the reduction factor for temperature conditions using the Arrhenius accelerated life model. The calculation formula is as follows: In the formula: Ea is the activation energy, which generally ranges from 0.6 to 1.2 eV. It is selected based on product characteristics and failure mechanism, and the empirical value is 0.79 eV. KT (x，y) This is the temperature condition reduction factor; K is the Boltzmann constant, which is 8.6171 × 10⁻⁶. -4 eV / K; T x T y The temperature is given under conditions x and y, and the unit is °C. Step S402: Calculate the reduction factor of the vibration condition using the inverse power law accelerated life model. The calculation formula is as follows: In the formula: KV (x，y) This is the vibration condition reduction factor; V x V y The random vibration values ​​under x and y conditions are characterized by acceleration spectral density, with units of g. 2 / Hz; m is a material constant, which is generally taken as 4 for avionics equipment; For sinusoidal vibration conditions, V in the above equation x V y The sinusoidal vibration values ​​under x and y conditions are characterized by peak acceleration in g; m is taken as 6.

9. The reliability assessment method for airborne equipment based on research and development test data according to claim 1, characterized in that, The reliability comprehensive assessment in step S5 includes the following steps: Step S501: Calculate the equivalent working time t for the entire equipment development process based on the conversion factor and the collected equipment reliability information. ss ; Step S502: Calculate the shape parameters after parameter estimation of the first failure time of M types of B faults according to the AMSAA model; Step S503: Calculate reliability parameters using the AMSAA reliability growth model; Step S504: Evaluate the range level of equipment reliability parameters. When the confidence level is C, the formula for estimating the range of Mean Time Between Failures (MTBF) is as follows: In formulas (9) to (10): MTBF L Lower limit of the estimated mean time between failures (MTBF); MTBF U : Upper limit of the estimated mean time between failures (MTBF); θ L (C′,r s ): The lower limit adjustment factor calculated using the chi-square quantile; θ U (C′,r s ): The upper limit adjustment factor calculated using the chi-square quantile; C′: One-sided probability value; r s The adjusted number of faults, i.e., the number of faults after considering fault classification and the effectiveness of corrective measures; C: Confidence level; Because the number of faults r calculated according to the AMSAA model s Not an integer, in calculating θ L and θ U The calculation is performed using an interpolation method based on adjacent integer fault numbers.

10. The airborne equipment reliability assessment method based on research and development test data according to claim 9, characterized in that, The equivalent working time t of step S501 ss The conversion formula is as follows: t ss =t sst +t ssv (5) In formulas (3) to (5): T0 is the reference temperature; V0 is the reference vibration condition; t T0 The operating time under the reference temperature condition; t V0 The operating time under reference vibration conditions; kT (i，0) The reduction factor under a certain temperature condition; kV (i，0) t is the reduction factor under a certain vibration condition; i t represents the working time under certain experimental conditions. sst The time is converted according to the reference temperature conditions; t ssv The time is the time converted according to the reference vibration conditions; t ss The total working time of the entire equipment development process is converted into the total working time under reference temperature and reference vibration conditions.

11. The method for reliability assessment of airborne equipment based on research and development test data according to claim 9, characterized in that, The formula for calculating the shape parameters in step S502 is as follows: When M > 1, the shape parameter b is estimated as follows: When M=1, the shape parameter b is estimated as follows: In formulas (6) to (7): The shape parameters are those estimated using the AMSAA model; t i The cumulative test time at the occurrence of the i-th failure; M represents the number of Class B fault types; t Ts The total effective test time for the comprehensive reliability assessment after environmental considerations are calculated.

12. The method for reliability assessment of airborne equipment based on research and development test data according to claim 9, characterized in that, The reliability parameter in step S503 is calculated using the following formula: In the formula: MTBF stands for Mean Time Between Failures. t Ts The total effective test time for the comprehensive reliability assessment after environmental adjustments is t, which is the value in formula (5). ss ; r s This is the adjusted number of faults, that is, the number of faults after considering fault classification and the effectiveness of correction; K A This represents the total number of Class A failures during the development process. K B This represents the total number of Class B failures during the development process. d is the effectiveness coefficient for correcting Class B faults, and its value ranges from 0.55 to 0.

85. In the absence of historical data, the average value of empirical data of 0.7 can be used. M represents the number of types of Class B faults.

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