Reliability Analysis of Mechanical Products Based on Regenerative Samples

DOI

10.2991/ammee-17.2017.126How to use a DOI?

Keywords

Mechanical products; small sample; time censoring; Bootstrap; BP neural network

Abstract

Aiming at the problem of reliability estimation of mechanical products in small sample size and time censored test under Weibull distribution, this paper proposed a method which combined Bootstrap and BP neural network for reliability evaluation. Firstly, Bootstrap method was used to expand the reliability and failure time sample. Secondly, the BP neural network was trained by the expanded sample. Then the parameters of Weibull distribution can be estimated by the trained BP neural network. Finally, the reliability characteristics of the product can be obtained. In the end, an example was analyzed to illustrate the applicability of the method.

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/).

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TY  - CONF
AU  - Tengfei Chen
AU  - Erling Gong
PY  - 2017/06
DA  - 2017/06
TI  - Reliability Analysis of Mechanical Products Based on Regenerative Samples
BT  - Proceedings of the Advances in Materials, Machinery, Electrical Engineering (AMMEE 2017)
PB  - Atlantis Press
SP  - 657
EP  - 661
SN  - 2352-5401
UR  - https://doi.org/10.2991/ammee-17.2017.126
DO  - 10.2991/ammee-17.2017.126
ID  - Chen2017/06
ER  -