Prediction method of multi-functional parameter accelerated degradation testing product life based on multivariate hybrid time sequence analysis
A technology of accelerated degradation test and time series analysis, applied in the analysis of materials, measurement devices, strength characteristics, etc., can solve the problem of product life prediction and reliability evaluation that are difficult to directly apply accelerated degradation test, the overall trend is irreversible, and the life prediction results are not accurate enough, etc. question
Inactive Publication Date: 2011-05-04
BEIHANG UNIV
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[0016] The purpose of the present invention is to solve the problem that the existing degradation prediction method based on a single product performance parameter is not accurate enough for the product degradation process and life prediction results, and it is difficult to model the interactive influence of multiple performance parameter degradation processes, environmental interference, equipment control and other factors, and The performance degradation prediction method based on multiple performance parameters is difficult to be directly applied to the life prediction and reliability evaluation of accelerated degradation test products. The technical means based on multivariate mixed time series analysis is adopted to achieve multi-parameter degradation data prediction of products through accelerated degradation tests. The effect of product life and reliability evaluation that is more in line with the actual situation
That is, the overall trend of performance degradation is irreversible
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Embodiment 1
[0141] Step 1, test data collection and preprocessing;
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Abstract
The invention discloses a prediction method of multi-functional parameter accelerated degradation testing product life based on multivariate hybrid time sequence analysis, belonging to the technical field of accelerated test evaluation, comprising the steps of test data acquisition and pretreatment; multi-functional parameter time sequence modeling; multi-functional parameter degradation failure prediction; multi-functional parameter degradation accelerated modeling and multi-functional parameter product life prediction; the problem that the prediction is inaccurate since the mutual influence among a plurality of property parameter degradation processes of the product is unconsidered in the single property parameter degradation prediction of the product is solved; a multivariate hybrid time sequence model is put forward in considering monotonicity degradation trend, randomness and cyclical fluctuation in the product multi-functional parameter degradation process and the relativity of the characteristics among the property parameter; a failure criterion of the product multi-functional parameter degradation is put forward; the description to the multi-functional parameter degradation process is more comprehensive and the accuracy of the prediction result of multi-functional parameter accelerated degradation testing life is improved.
Description
technical field [0001] The invention relates to an accelerated degradation test life prediction and reliability evaluation method, belonging to the technical field of accelerated test evaluation. Background technique [0002] The emergence of more and more long-life and high-reliability products makes product life and reliability evaluation more difficult. Predicting product life and reliability based on product performance degradation information has become an effective way. In order to evaluate the reliability of these products for which failure data is difficult to obtain but performance degradation data can be obtained, a degradation test method has emerged. In order to obtain more effective product performance degradation information in a shorter time, the method of accelerated degradation test has further emerged. [0003] However, there are still some deficiencies in the existing accelerated degradation test product life prediction methods: [0004] First of all, i...
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IPC IPC(8): G01D21/00G01N3/00G06F19/00
Inventor 王立姜同敏李晓阳
Owner BEIHANG UNIV
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