Reliability statistical inference method based on multivariate accelerated degradation data

A technology that accelerates degradation and statistical inference. It is applied in the field of reliability engineering and can solve problems such as difficulty in reliability evaluation and limited application scope.

Inactive Publication Date: 2017-12-22
NAVAL AERONAUTICAL & ASTRONAUTICAL UNIV PLA
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Problems solved by technology

Accelerated degradation test has been widely used in product reliability evaluation because it can obtain enough performance degradation data in a shorter time. However, how to use the measured multivariate accelerated degradation data to evaluate the reliability of such products is curr

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  • Reliability statistical inference method based on multivariate accelerated degradation data
  • Reliability statistical inference method based on multivariate accelerated degradation data
  • Reliability statistical inference method based on multivariate accelerated degradation data

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[0066] Example: Thermal oxidation is the most important failure mechanism for the degradation and failure of a certain type of elastic O-shaped rubber sealing ring, which will cause the degradation of the two performance parameters of the sealing ring, compression permanent deformation and compression stress relaxation. For this rubber sealing ring, a temperature stress accelerated degradation test was carried out, and a total of 15 samples were evenly distributed under 3 groups of accelerated temperature stress: T 1 =333.15K,T 2 =363.15K,T 3 = 393.15K. Before carrying out the accelerated degradation test, the initial values ​​of compression set and compression stress relaxation of all samples were measured first. In the accelerated degradation test, the percentage changes of the two parameters of compression set and compression stress relaxation relative to the initial value of the sample were measured respectively, as performance degradation indicators. Denote the degrada...

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Abstract

The invention relates to a reliability statistical inference method based on multivariate accelerated degradation data. The method mainly comprises the following steps: (1) using a stochastic process to respectively establish an accelerated degradation model for accelerated degradation data of each performance parameter; (2) using a maximum likelihood estimation method to obtain a parameter value of each accelerated degradation model; (3) respectively establishing a marginal survival function based on a stochastic process model for each performance parameter; (4) using a Copula function to establish a correlation model between the marginal survival functions; (5) using a Monte Carlo method to estimate a correlation model parameter value; (6) constructing a reliability function under a rated stress for inferring the reliability of a product. The reliability statistical inference method based on multivariate accelerated degradation data has a wider application scope and better engineering applicability.

Description

technical field [0001] The invention belongs to the field of reliability engineering and relates to a reliability statistical inference method based on multivariate accelerated degradation data. Background technique [0002] In today's society, product replacement is accelerating, how to determine the reliability index of the product in a short period of time is very important to enhance the competitiveness of the product. Accelerated degradation tests have been widely used in product reliability assessment because they can obtain enough performance degradation data in a shorter period of time. However, how to use the measured multivariate accelerated degradation data to evaluate the reliability of such products is currently a difficult problem . Most of the existing methods assume that there is correlation between the degradation quantities at the same measurement time, and can only use the same type of degradation model to model each degradation process, which limits the ...

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Application Information

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IPC IPC(8): G06F17/18
CPCG06F17/18
Inventor 王浩伟滕克难滕飞盖炳良陈瑜
Owner NAVAL AERONAUTICAL & ASTRONAUTICAL UNIV PLA
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