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Improved maximum likelihood method for P-S-N curve fitting method with small number specimens and application in T-welded joint.
Liu, Wenfei; Zhang, Li; He, Liwen; Liu, Hailang.
Afiliación
  • Liu W; School of Intelligent Manufacture, Taizhou University, Taizhou, 318000, China. liuwenfei45@163.com.
  • Zhang L; School of Intelligent Manufacture, Taizhou University, Taizhou, 318000, China.
  • He L; Baotou Beifang Chuangye Co., Ltd, Baotou, 014032, China.
  • Liu H; School of Intelligent Manufacture, Taizhou University, Taizhou, 318000, China.
Sci Rep ; 13(1): 19202, 2023 Nov 06.
Article en En | MEDLINE | ID: mdl-37932416
In fatigue data analysis, fitting accurate P-S-N curve is problematic if only a small number of specimen is available, especially to evaluate the relationship between the stress level and the standard deviation. This paper proposes a sample information reconstruction method that can effectively solve this problem. Based on this method and the life equivalent principle, a new maximum likelihood method (which is abbreviated to improved maximum likelihood method) is proposed for P-S-N curve fitting. T-joint specimens of Q450NQR1 steel were fabricated and tested, then the P-S-N curves was fitted by the improved maximum likelihood method, least square method, maximum likelihood method, standard BS7608 and standard IIW. Finally, P-S-N curves by three methods and two standards are compared and analyzed. The results show that the relevant parameters of the P-S-N curve with 99.9% survival probability fitted by the improved maximum likelihood method are similar to those in the two standards, and it is indicated that the improved maximum likelihood method is a better way for P-S-N curve fitting with the small number of fatigue test specimens.

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Sci Rep Año: 2023 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Sci Rep Año: 2023 Tipo del documento: Article País de afiliación: China