Proceedings of the 2017 2nd International Conference on Automation, Mechanical and Electrical Engineering (AMEE 2017)

A Review of Fatigue Life Prediction Method for Quayside Container Crane

Authors
Zhenjie Xia, Weiping Ouyang, Yannan Du
Corresponding Author
Zhenjie Xia
Available Online September 2017.
DOI
https://doi.org/10.2991/amee-17.2017.16How to use a DOI?
Keywords
fatigue; mechanics; probability statistics; new technology
Abstract

Fatigue damage is the main damage cause of crane. The prediction method of fatigue life determines the design and service life of the crane. Therefore, it is extremely important to study the fatigue life prediction method of crane. In this paper, the existing fatigue life prediction methods are summarized systematically. Fatigue life research was involved in metal material, mechanics, vibration mechanics, fatigue theory, fracture mechanics and so on, which made a difference

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

Volume Title
Proceedings of the 2017 2nd International Conference on Automation, Mechanical and Electrical Engineering (AMEE 2017)
Series
Advances in Engineering Research
Publication Date
September 2017
ISBN
978-94-6252-393-7
ISSN
2352-5401
DOI
https://doi.org/10.2991/amee-17.2017.16How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Zhenjie Xia
AU  - Weiping Ouyang
AU  - Yannan Du
PY  - 2017/09
DA  - 2017/09
TI  - A Review of Fatigue Life Prediction Method for Quayside Container Crane
BT  - Proceedings of the 2017 2nd International Conference on Automation, Mechanical and Electrical Engineering (AMEE 2017)
PB  - Atlantis Press
SP  - 77
EP  - 78
SN  - 2352-5401
UR  - https://doi.org/10.2991/amee-17.2017.16
DO  - https://doi.org/10.2991/amee-17.2017.16
ID  - Xia2017/09
ER  -