An improved inverse power law model for accelerated fatigue life prediction of 6061-T6 and AZ31B-F

Ge, Changyuan; Xu, Zhuang; Du, Kaifan; Zhou, Chuanli; Tan, Chenggong; Liu, Wenhu; Xu, Shengli; Wang, Bo

doi:10.1016/j.engfailanal.2022.106381

Cited by 5 publications

(1 citation statement)

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“…After a great deal of practical summary, scholars have put forward some acceleration models which are suitable for different situations. The inverse power law model is frequently employed to depict the relationship between product life characteristics and stress levels when mechanical stress or electrical stress is used as accelerated stress [15].…”

Section: Acceleration Modelmentioning

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: Acceleration Modelmentioning

confidence: 99%

Research on gear life reliability analysis based on accelerated life test

He,

Yang,

Zhou

et al. 2024

Materialwissenschaft Werkst

View full text Add to dashboard Cite

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Acceleration model considering multi‐stress coupling effect and reliability modeling method based on nonlinear Wiener process

Yi,

Wang,

Liu

et al. 2024

Quality & Reliability Eng

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Establishing an accurate accelerated degradation model is paramount for ensuring precise reliability evaluation results. Unfortunately, current accelerated degradation tests often lack test groups for investigating multi‐stress coupled phenomena. Consequently, existing multi‐stress accelerated models fail to adequately consider the impact of stress coupling when data with stress coupling information is absent. This limitation leads to the development of inaccurate models, ultimately affecting the precision of reliability assessment. To address this challenge, this paper introduces a new modeling method for multi‐stress accelerated degradation models that takes into account stress coupling effects. The proposed modeling method aims to improve the accuracy of reliability assessment under multi‐stress conditions. In the proposed model, the main effect function of stress is determined based on existing single‐stress accelerated models. The coupling effect is first examined through the Multivariate Analysis of Variance (MANOVA), and then the functional form of the coupling effect function is determined from the given candidate functions through correlation analysis. Next, the coupling effect is incorporated into a Wiener process to establish a multi‐stress accelerated degradation model, and the two‐step estimation method combining Least Squares Method (LSM) and Differential Evolution Algorithm (DEA) is proposed. The accuracy and effectiveness of the coupling effect test method, model establishment, and parameter estimation method were validated using two Monte Carlo simulation experimental data sets. Finally, the superiority of the proposed model is demonstrated through examples, providing feasible ideas and technical support for the research on multi‐stress accelerated degradation modeling considering stress coupling.

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