Digital Scanning of Welds and Influence of Sampling Resolution on the Predicted Fatigue Performance: Modelling, Experiment and Simulation

被引:19
作者
Hultgren, Gustav [1 ]
Myren, Leo [1 ]
Barsoum, Zuheir [1 ]
Mansour, Rami [2 ]
机构
[1] KTH Royal Inst Technol, Dept Engn Mech, Lightweight Struct, SE-10044 Stockholm, Sweden
[2] KTH Royal Inst Technol, Dept Engn Mech, Solid Mech, SE-10044 Stockholm, Sweden
关键词
probabilistic fatigue model; topographical variations; weld quality; quality assurance; PRACTICAL APPLICATION; STRENGTH; JOINTS; GEOMETRY; CUT;
D O I
10.3390/met11050822
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Digital weld quality assurance systems are increasingly used to capture local geometrical variations that can be detrimental for the fatigue strength of welded components. In this study, a method is proposed to determine the required scanning sampling resolution for proper fatigue assessment. Based on FE analysis of laser-scanned welded joints, fatigue failure probabilities are computed using a Weakest-link fatigue model with experimentally determined parameters. By down-sampling of the scanning data in the FE simulations, it is shown that the uncertainty and error in the fatigue failure probability prediction increases with decreased sampling resolution. The required sampling resolution is thereafter determined by setting an allowable error in the predicted failure probability. A sampling resolution of 200 to 250 mu m has been shown to be adequate for the fatigue-loaded welded joints investigated in the current study. The resolution requirements can be directly incorporated in production for continuous quality assurance of welded structures. The proposed probabilistic model used to derive the resolution requirement accurately captures the experimental fatigue strength distribution, with a correlation coefficient of 0.9 between model and experimental failure probabilities. This work therefore brings novelty by deriving sampling resolution requirements based on the influence of stochastic topographical variations on the fatigue strength distribution.
引用
收藏
页数:18
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