Method for inferring change rule of material storage performance based on pseudo failure threshold random sampling

By using a pseudo-failure threshold random sampling method, high-temperature constant stress accelerated storage test and least squares fitting, the problem of difficulty in determining the material failure threshold was solved, and the accurate assessment of the material storage performance change law was achieved.

CN115422737BActive Publication Date: 2026-06-12SOUTHWEAT UNIV OF SCI & TECH
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
SOUTHWEAT UNIV OF SCI & TECH
Filing Date
2022-08-31
Publication Date
2026-06-12

AI Technical Summary

⚠Technical Problem

Existing technologies require prior determination of the product's failure threshold when assessing the performance changes of materials during long-term storage. However, in practical engineering, the failure threshold of materials is difficult to determine, making it impossible to effectively assess the degradation pattern of the material's storage performance.

⚗Method used

By employing a random sampling method based on pseudo-failure thresholds and conducting accelerated storage tests under high temperature and constant stress, a material degradation trajectory function was established. The performance degradation data was then fitted using the least squares method, and pseudo-failure thresholds were randomly selected to obtain the performance parameter degradation curves of the material under natural storage conditions.

🎯Benefits of technology

Without needing to predetermine the failure threshold, it is possible to effectively infer the changes in the storage performance of materials, thereby improving the accuracy and reliability of the assessment.

✦ Generated by Eureka AI based on patent content.

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Abstract

The present application relates to the technical field of material storage, and particularly relates to a pseudo-failure threshold random sampling material storage performance change law inference method, comprising the following steps: performing high-temperature constant stress accelerated storage test on the material, obtaining test data of different test items, modeling a performance degradation model, taking the mean value of each test item of each test point as the data of the test period, substituting into a degradation trajectory function, obtaining the estimated value of the parameter by using the least square method, taking a point on the performance parameter degradation curve of the material at temperature T0, the maximum degradation detected by the test being Dmax, randomly selecting n pseudo-failure thresholds in the interval, obtaining n groups of parameters, and then obtaining a series of points on the product key performance parameter degradation curve at temperature T0, fitting these points, and thus the performance change law of the key parameters of the product under natural storage conditions can be obtained.
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