Steel and iron material fatigue performance prediction method based on transfer learning guided by mechanical theory

Abstract

The invention provides a steel and iron material fatigue performance prediction method based on transfer learning guided by a mechanical theory, and relates to the technical field of steel and iron material design and machine learning application. According to the method, a mechanical theory mechanism is introduced into machine learning, and the small sample problem of material high-cost attribute prediction is solved. The relationship among the steel grade components, the process and the target performance is established on the basis of mechanical theory guidance. According to the method, aiming at obtaining the target performance with high cost, the transfer learning model for accurately predicting the target performance can be established by utilizing the high correlation between the target performance and the source performance, namely based on the guidance of the mechanical theory and only utilizing dozens of groups of target performance data. According to the method, the data size requirement of machine learning for high-cost target performance is remarkably reduced, the high-cost target performance evaluation and prediction efficiency is remarkably improved, and finally the new material research and development rate is improved.

Description

technical field [0001] The invention relates to the technical field of steel material design and machine learning application, in particular to a method for predicting fatigue performance of steel materials based on transfer learning guided by mechanics theory. Background technique [0002] Fatigue failure is one of the main failure modes of engineering materials, which accounts for about 90% of mechanical failures of metal structural components. Therefore, it is crucial to evaluate and predict the fatigue performance of metallic materials. The fatigue of metallic materials can be divided into high cycle fatigue (HCF) and low cycle fatigue (LCF). For HCF, the stress-life method has been widely used in fatigue analysis, which was first proposed by Wohler and proposed the fatigue limit. Many high-strength steels usually do not exhibit a fatigue limit. The endurance limit under this condition is called fatigue strength, which is usually defined as the maximum stress amplitude...

AI Technical Summary

Problems solved by technology

[0004] Aiming at the deficiencies in the existing technology, the present invention proposes a method for predicting the fatigue performance of iron and steel materials based on mechanical theory-guided migration learning. This method introduces the mechanism of mechanical theory into machine learning and solves the problem of small samples in the prediction of high-cost properties of materials. question

Images