Optimization design method for step stress accelerated degradation test based on Bayesian theory

An accelerated degradation test and Bayesian theory technology, applied in special data processing applications, calculations, electrical digital data processing, etc., can solve problems such as loss of optimization and far-reaching optimal solutions

Active Publication Date: 2012-08-01
BEIHANG UNIV
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Problems solved by technology

[0019] The present invention aims at the current traditional (local) accelerated degradation test design. When the assumed parameter value deviates greatly from the real value, the scheme obtained by the traditional (local) optimization design is far from the real optimal scheme, and the loss of The question of the

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  • Optimization design method for step stress accelerated degradation test based on Bayesian theory
  • Optimization design method for step stress accelerated degradation test based on Bayesian theory
  • Optimization design method for step stress accelerated degradation test based on Bayesian theory

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Embodiment

[0137] Based on Bayesian theory, the optimal design of a superluminescent diode (SLD) was carried out by step stress accelerated degradation test (SSADT), the steps are as follows:

[0138] Step 1. Determine the product performance degradation model and acceleration model, and then give the prior distribution of model parameters based on historical data.

[0139] First, the model and assumptions are given, as follows,

[0140] (1) Assumption:

[0141] A1: The degradation trend is monotonous and irreversible;

[0142] A2: The degradation failure mechanism does not change with stress;

[0143] A3: At normal stress level s 0 and k accelerated stress levels s 1 2 k Next, the performance degradation process Y l Obey the drift Brownian motion, the drift coefficient d(s l )>0, diffusion coefficient σ l >0, l=1, ..., k:

[0144] Y l (t) = σ l B(t)+d(s l )·t+y 0 (18)

[0145] A4: Diffusion coefficient σ l Does not change with force value, i.e., σ 0 = σ ...

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Abstract

The invention discloses an optimization design method for a step stress accelerated degradation test based on a Bayesian theory, and is applied to the technical field of the accelerated degradation test. The optimization design method comprises the steps as follows: firstly, determining product performance degradation and acceleration models, and based on the historical data, giving prior distribution of model parameters; secondly, determining an optimization design space, and forming a test scheme set; thirdly, creating an expected utility function or an expected loss function, determining optimization goals, and based on a Markov Chain Monte Carlo method, determining optimization goal values of designs in the test scheme set; and lastly, finding the optimal test scheme by using a curve fitting method. According to the optimization design method, the shortcoming of high possibility of larger deviation due to the implementation of the traditional (local) test optimization design method when the values of the model parameters are supposed to be known is avoided, and the optimization scheme obtained in the implementation of the test optimization design when the prior distribution of the model parameters is given is more reasonable and more actual.

Description

technical field [0001] The invention is a step stress accelerated degradation test optimization design method based on Bayesian theory, belongs to the technical field of accelerated degradation tests, and is used for solving technical problems in the field of reliability and system engineering. Background technique [0002] With the rapid development of science and technology, there are more and more high-reliability and long-life products, such as aerospace electronic products, optoelectronic products, etc. In order to evaluate the reliability and life of these products, Accelerated Life Testing (ALT) And accelerated degradation test (Accelerated Degradation Testing, ADT) have been developed. ALT needs to collect product failure data, but sometimes due to the characteristics of high reliability products, it is difficult to obtain enough failure data to meet the needs of ALT evaluation. ADT is based on the physical characteristics or degradation characteristics of the produ...

Claims

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Application Information

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IPC IPC(8): G06F17/50
Inventor 李晓阳葛蒸蒸范宇
Owner BEIHANG UNIV
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