Material fatigue-life predicting method based on support vector machine

A fatigue life prediction and support vector machine technology, which is applied in the direction of analyzing materials, measuring devices, instruments, etc., can solve problems such as unfavorable engineering applications, achieve the effects of prolonging service life, saving material fatigue experiments, and improving accuracy

Inactive Publication Date: 2012-09-05
SHANGHAI MARITIME UNIVERSITY
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  • Abstract
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  • Application Information

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Problems solved by technology

The fatigue life estimation of the above-mentioned patented technology is mainly based on the existing commonly used damage accumulation model, which requires a large number of material fatigue performance tests, which is not conducive to practical engineering applications

Method used

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  • Material fatigue-life predicting method based on support vector machine
  • Material fatigue-life predicting method based on support vector machine
  • Material fatigue-life predicting method based on support vector machine

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Embodiment Construction

[0034] The present invention will be further illustrated below through an implementation case.

[0035] Fatigue damage is a process in which material properties deteriorate continuously under load. Fatigue damage accumulation has nonlinear characteristics, and the damage caused by cyclic loading at a certain time should be a function of strain and material cumulative damage.

[0036] Therefore, in order to describe various fatigue damage states, the present invention uses a support vector machine to establish the nonlinear relationship between the applied load and fatigue damage, realize the nonlinear accumulation of fatigue damage, and finally predict the fatigue life.

[0037] The fatigue life prediction method based on the support vector machine of the present invention will be further described in detail in conjunction with examples below. The following examples are for illustrative purposes only and are not intended to limit the scope of the present invention.

[0038] ...

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Abstract

The invention relates to a material fatigue-life predicting method based on a support vector machine, and discloses a method for predicting the fatigue service life of a structural material, which comprises the steps of: obtaining material fatigue performance data, selecting a proper input and output parameter to construct a training sample set, establishing a fatigue-life predicting model based on the support vector machine, preprocessing a fatigue load, and calculating the fatigue life. The material fatigue-life predicting method has the advantages of realizing the nonlinear accumulation of fatigue damages by using less material fatigue performance data, and improving the accuracy of predicting the life. The method provided by the invention is suitable for the structural material fatigue life estimation and the life prolonging analysis, and has an important theoretical significance and an actual application value in formulating a reasonable maintenance plan for prolonging the service life of the material.

Description

technical field [0001] The invention relates to the field of material fatigue life prediction, in particular to an estimation method of a support vector machine for the service life of structural materials. Background technique [0002] Fatigue damage is a common failure mode in engineering structures. Accurate estimation of fatigue life has important theoretical significance and engineering practical value for eliminating hidden dangers of accidents, formulating effective maintenance plans and prolonging service life. [0003] An important problem in fatigue life prediction is how to reasonably and effectively describe the degradation process of material properties caused by fatigue damage. Researchers from various countries have proposed many theoretical models of damage accumulation from different perspectives, such as Miner's linear damage accumulation criterion, Manson's bilinear damage accumulation theory, and the Corten-Dolan model. Most of these models are only sui...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01N3/00
Inventor 刘龙轩福贞
Owner SHANGHAI MARITIME UNIVERSITY
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