Proceedings of the 2016 5th International Conference on Measurement, Instrumentation and Automation (ICMIA 2016)

Reliability-based Optimization Design of Mechanical Components with Truncated Normal Distributions

Authors
Xiangdong He, Xiaoyan Hu, Wei Qi
Corresponding Author
Xiangdong He
Available Online November 2016.
DOI
10.2991/icmia-16.2016.32How to use a DOI?
Keywords
Mechanical components, Truncated normal distribution, Maximum entropy, Reliability-based optimization design
Abstract

In some engineering applications, the probability distributions of some random variables are truncated. Under the conditions, if traditional reliability-based optimization design is directly used, difficulties may arise and this treatment may result in large errors in reliability-based optimization design. In view of above mentioned problems, the paper is to present a new reliability-based optimization design method that solves the problems with truncated normal random variables. The numerical examples are investigated to demonstrate the effectiveness and feasibility of the present method.

Copyright
© 2016, 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/).

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Volume Title
Proceedings of the 2016 5th International Conference on Measurement, Instrumentation and Automation (ICMIA 2016)
Series
Advances in Intelligent Systems Research
Publication Date
November 2016
ISBN
10.2991/icmia-16.2016.32
ISSN
1951-6851
DOI
10.2991/icmia-16.2016.32How to use a DOI?
Copyright
© 2016, 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  - Xiangdong He
AU  - Xiaoyan Hu
AU  - Wei Qi
PY  - 2016/11
DA  - 2016/11
TI  - Reliability-based Optimization Design of Mechanical Components with Truncated Normal Distributions
BT  - Proceedings of the 2016 5th International Conference on Measurement, Instrumentation and Automation (ICMIA 2016)
PB  - Atlantis Press
SP  - 174
EP  - 177
SN  - 1951-6851
UR  - https://doi.org/10.2991/icmia-16.2016.32
DO  - 10.2991/icmia-16.2016.32
ID  - He2016/11
ER  -