Abstract: Multi factor correction is optimized for fatigue life prediction and reliability evaluation of structural components. Based on the optimization of Bayesian theory, reliability evaluation is carried out to improve the efficiency of fatigue life prediction and reliability evaluation of structural components. The research results indicate that the crack propagation length increases with the increase in loading time. The average probability density of the modified method is 3.628, while the probability density of the traditional fracture mechanics model is 1.242. Based on the multi factor modified crack propagation prediction model, the predicted data accuracy exceeds the traditional fracture mechanics model. It is consistent with the experimental results. The crack propagation prediction model based on multi factor correction can ensure the accuracy of the prediction. The reliability of the model is evaluated. The average prediction accuracy of multiple sets of data is over 90%. This research method helps predict the fatigue life of structural components and evaluate reliability to ensure the safe operation of construction machinery.

Yi Zhang. “Application of Optimizing Multifactor Correction in Fatigue Life Prediction and Reliability Evaluation of Structural Components”. International Journal of Advanced Computer Science and Applications (IJACSA) 15.7 (2024). http://dx.doi.org/10.14569/IJACSA.2024.0150726

@article{Zhang2024,
title = {Application of Optimizing Multifactor Correction in Fatigue Life Prediction and Reliability Evaluation of Structural Components},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.0150726},
url = {http://dx.doi.org/10.14569/IJACSA.2024.0150726},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {7},
author = {Yi Zhang}
}