Neural ordinary differential equation for sequential optimal design of fatigue test under accelerated life test analysis

Khakifirooz, Marzieh; Fathi, Michel; Lee, I-Chen; Tseng, Sheng‐Tsaing

doi:10.1016/j.ress.2023.109242

Cited by 3 publications

(1 citation statement)

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“…Compared to the constant loading method, the accelerated life testing approach significantly reduced the testing duration [7]. An optimization model was defined that takes both parametric and analytic solutions into account and minimizes the negative log-likelihood of the ALT model when the fatigue lifecycle follows a lognormal distribution [8]. The life decay characteristics identification method of power battery module based on the accelerated life test was proposed.…”

Section: Introductionmentioning

confidence: 99%

Research on gear life reliability analysis based on accelerated life test

He,

Yang,

Zhou

et al. 2024

Materialwissenschaft Werkst

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As one of the key components of marine reducer, the life reliability of gear is of great significance to the safe operation of the reducer and even the whole transmission system. However, due to economic and testing constraints, executing extensive fatigue life tests on complex and costly gears presents a formidable challenge, resulting in inadequate reliability assessments. In this paper, the gear life reliability analysis method based on the accelerated life test is proposed. By conducting the gear bending fatigue accelerated life test, the life distribution and failure mechanism are determined based on the accelerated life data. Furthermore, the gear life distribution parameters and acceleration model are solved by least squared method. This allows us to derive a reliability index specific to the service conditions, facilitating the evaluation of gear life reliability. The method proposed in this paper provides data and theoretical support for the accelerated life tests, lays a foundation for the gear reliability evaluation under small samples, and improves the efficiency of the gear fatigue life evaluation. It has significant engineering significance in saving test costs, reducing test times and shortening development cycle.

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Section: Introductionmentioning

confidence: 99%