Method for evaluating credibility of prior data
By constructing the acceleration factor invariance theory and gamma process modeling, identifying stress-independent and stress-dependent parameters, quantifying the parameter credibility and weighting them, the problem of mismatch between prior data and actual working conditions is solved, and the applicability and accuracy of the model in multiple stress environments are improved.
Patent Information
- Application Number
- CN202511324962.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-09-17
- Publication Date
- 2025-10-17
- Estimated Expiration
- 2045-09-17
AI Technical Summary
When processing prior data, existing technologies have the problem of mismatch between prior data and actual working conditions, which leads to reduced model accuracy. In particular, it is difficult to ensure the applicability and accuracy of the model in a multi-stress environment.
By constructing a degradation model based on the acceleration factor invariance theory, stress-independent and stress-dependent parameters are identified. Combined with gamma process modeling, the credibility of parameters under different stress levels is quantified, and weighted calculation is performed through the hazard coefficient to evaluate the comprehensive credibility of the data.
The applicability of degradation modeling in multi-stress environments and the robustness of model reasoning are improved, the risk of misjudgment is reduced, and the representativeness and reliability of accelerated degradation experimental data in Bayesian modeling are ensured.