Reliability Calculation of Product Failure Data (Part II: Experiment)

DOI

10.2991/icsnce-16.2016.82How to use a DOI?

Keywords

Rolling bearing; Failure data; K-s hypothesis testing; Standard deviation; Reliability

Abstract

On the reliability of failure data, this paper provides wide ranges of theoretical method, and determines the effectiveness of those methods about rolling bearing. Under the reference standard based on the empirical value of medium rank, the veracity about those methods apply to rolling bearing would be determined with the k-s hypothesis testing, and there have a contrastive analysis between the reliabilities and empirical values about different methods, then estimates those methods. For the result of this paper, the veracity of lognormal distribution (L) and Weibull distribution (W) has a great unsteadiness. However, the maximum entropy probability distribution (M) could reply any confirmable distributions, and be suitable for poor information as unknown as the probability distribution, apriori information and trend term. Therefore, the maximum entropy probability distribution has a better applicability for the problem of rolling bearing's reliability on failure data.

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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TY  - CONF
AU  - Xintao Xia
AU  - Yunfei Li
AU  - Zhen Chang
AU  - Bin Liu
AU  - Liang Ye
PY  - 2016/07
DA  - 2016/07
TI  - Reliability Calculation of Product Failure Data (Part II: Experiment)
BT  - Proceedings of the 2016 International Conference on Sensor Network and Computer Engineering
PB  - Atlantis Press
SP  - 423
EP  - 427
SN  - 2352-5401
UR  - https://doi.org/10.2991/icsnce-16.2016.82
DO  - 10.2991/icsnce-16.2016.82
ID  - Xia2016/07
ER  -