A fatigue life prediction method from magnetic pole material to simulation part

Author:

Pan Long12ORCID,Pang Jian Chao1,Xie Yu Jun2,Zhang Meng Xiao1,Nie Liang Liang3,Mao Yun Xian3,Zhang Zhe Feng1

Affiliation:

1. Materials Fatigue and Fracture Laboratory, Institute of Metal Research, Shenyang, China

2. Department of Mechanical Engineering, Liaoning Shihua University, Fushun, China

3. Power Generation Company, China Southern Power Grid, Guangzhou, China

Abstract

Due to the higher reliability needs of the large moving component motor-generator rotor, the assessment of the service life has drawn more and more attention. After finite element analysis of the rotor, the simulation part which can represent the magnetic pole with the most dangerous position of the rotor was designed to investigate the S–N curves. Compared with the conventional specimen, considering the main influencing factors of fatigue life for simulation part, the comprehensive factor was proposed to establish the fatigue life relationship between magnetic pole material and simulation part. It was found that the calculation method of fatigue notch factor based on the notch sensitivity factor is relatively simple and practical, and there is no significant effect of surface roughness on high and low cycle fatigues for low roughness ( R a is about 1 µm), and the dimension factor changes linearly with the scale factor. Based on those results, a fatigue life prediction method was proposed and validated, and the predicted results were in good agreement with the experimental data. This study will provide a reasonable reference to determine the fatigue life prediction of large moving components.

Funder

National Natural Science Foundation of China

Publisher

SAGE Publications

Subject

Mechanical Engineering,Mechanics of Materials,General Materials Science,Computational Mechanics

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3