Research on the Fitting Method for P‐S‐N Curves With Extremely Small Sample Experiment Data: Improved Backwards Statistical Inference Method

ABSTRACT This study focuses on an improved statistical processing method for extremely small sample probabilistic S‐N (P‐S‐N) curve test data and proposes an improved backwards statistical inference method. By employing a quantile consistency principle, an equivalent large sample of fatigue lives can be obtained by congregating all test data, which enables high‐precision estimation of distribution parameters with limited data at each stress level. The logarithmic life standard deviation is assumed to have a logarithmic linear relationship with the stress levels. A method for revealing the relationship is proposed, and all of the fatigue life data can be equivalently congregated to determine the P‐S‐N curve. The test results demonstrate that this improved method delivers superior fitting results compared to other methods in scenarios with extremely small sample sizes. Additionally, this method imposes no constraints on sample format and allows for flexible setting of stress levels and sample sizes.

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Publication Details

Journal
Fatigue & Fracture of Engineering Materials & Structures
Published
2025-02-05
DOI
https://doi.org/10.1111/ffe.14560
Citations
2
Primary Topic
Probabilistic and Robust Engineering Design
Type
article
Field-Weighted Citation Impact
2.80

Funders

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article

Research on the Fitting Method for P‐S‐N Curves With Extremely Small Sample Experiment Data: Improved Backwards Statistical Inference Method

Tong Mu, Liyang Xie, Jiaxin Song, Bingfeng Zhao et al.
2 citations
Fatigue & Fracture of Engineering Materials & Structures
Probabilistic and Robust Engineering Design
2.80
article

Research on the Fitting Method for P‐S‐N Curves With Extremely Small Sample Experiment Data: Improved Backwards Statistical Inference Method

Tong Mu, Liyang Xie, Jiaxin Song, Bingfeng Zhao, Xin Wang, Dongwu Gao
article en
2 citations

Abstract

ABSTRACT This study focuses on an improved statistical processing method for extremely small sample probabilistic S‐N (P‐S‐N) curve test data and proposes an improved backwards statistical inference method. By employing a quantile consistency principle, an equivalent large sample of fatigue lives can be obtained by congregating all test data, which enables high‐precision estimation of distribution parameters with limited data at each stress level. The logarithmic life standard deviation is assumed to have a logarithmic linear relationship with the stress levels. A method for revealing the relationship is proposed, and all of the fatigue life data can be equivalently congregated to determine the P‐S‐N curve. The test results demonstrate that this improved method delivers superior fitting results compared to other methods in scenarios with extremely small sample sizes. Additionally, this method imposes no constraints on sample format and allows for flexible setting of stress levels and sample sizes.

Fatigue & Fracture of Engineering Materials & StructuresVol. 48(5)
Ministry of Education of the People's Republic of China (CN), Northeastern University (CN)
National Natural Science Foundation of China, National Major Science and Technology Projects of China
Openalex Percentile: Top 10%
Probabilistic and Robust Engineering Design
2.80
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