Structural member crack propagation prediction method based on multi-factor fusion correction

Abstract

The invention discloses a structural member crack propagation prediction method based on multi-factor fusion correction. Under the consideration of various factors with impacts on crack propagation of a structural member, the structural member crack propagation prediction method comprises: measurement and correction of initial crack morphology features of the structural member, stress intensity of the crack root of the structural member and the residual stress; calculation of a stress ratio; calculation of dimension correction parameters; selection of correction parameters of surface manufacturing quality. With the adoption of the structural member crack propagation prediction method, the precision of the prediction result is greatly improved. Therefore, the crack propagation of the structural member can be accurately and effectively predicted.

Description

technical field [0001] The invention belongs to the field of mechanical detection, in particular to a method for predicting the crack growth of structural parts. Background technique [0002] With the progress of society, a large number of equipment are developing in the direction of large-scale. Under such a background, a small crack damage will cause a huge fracture loss, so it is necessary and urgent to predict the crack growth of equipment or components to grasp its growth law. There are many prediction theories for crack growth, but the accuracy of prediction results based solely on these theories is often poor. The main reason is that there are many external factors that will affect the prediction results. There are many factors that affect the crack growth of structural parts, usually including: structural factors, stress ratio, average stress, load type, manufacturing and processing factors, etc. There are many studies on the prediction of component crack growth in...

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Problems solved by technology

There are many studies on the prediction of component crack growth information, but most of them focus on improving the accuracy of crack growth prediction results through the correction of a single factor, so as to realize the accurate evaluation of component operating status and remaining life, so too few factors are considered and many cannot be realized. The low prediction accuracy caused by simultaneous correction under factor conditions is a common problem in this research field at present.

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