A new multiaxial fatigue life prediction method based on grey theory under small sample condition. Issue 3 (8th December 2022)

• Record Type: Journal Article
• Authors: Pan, Xuemei; Liu, Jianhui; Li, Youtang; Hua, Feilong; Xu, Jianping; Chen, Xiaochuang
• Is Part Of: Fatigue & fracture of engineering materials & structures. Volume 46:Issue 3(2023)
• Page Start: 940
• Page End: 954
• Publication Date: 2022-12-08
• Subjects: grey relational analysis -- grey theory -- life prediction -- MGM (1, N) model -- small sample; Materials -- Fatigue -- Periodicals; Fracture mechanics -- Periodicals; 620.1123
• DOI: 10.1111/ffe.13910
• Languages: English
• ISSNs: 8756-758X

Abstract

Abstract: It is always a challenge to accurately predict the fatigue life of specimens in engineering, and it is urgent to establish a convenient and accurate approach to estimate the fatigue life of specimens with different materials under small sample conditions. To solve the above problems, a new multiaxial fatigue life prediction method is proposed based on grey theory. First, established a modified MGM (1, N ) model by fine‐adjusting the time series based on the GM (1, N ) model. Then the MGM (1, N ) model is used to compare the results with different types of parameters, and the optimal gray prediction model is established based on the gray correlation analysis. The proposed method is verified by 79 test data of 10 kinds of materials including Q355(D), and the predicted results matched well with the experimental results. It displays that the method is reliable. Finally, the predicted results with an accuracy of more than 90% were fused with the test data to obtain a more accurate S‐N field and ε‐N field of Q355(D) based on small sample by the ProFatigue program. Highlights: The modified MGM (1, N ) model is established by fine adjusting the time series. A ranking method for determining the importance of the relevant factors is given. A convenient approach for fatigue life prediction is proposed. A method for establishing the relatively accurate P‐S‐N curves or P‐ε‐N curves is given.