Mathematical Model on Reliability of Variation Process of Rolling Bearing Vibration Performance

DOI

10.2991/emcm-15.2016.52How to use a DOI?

Keywords

Rolling bearings; Reliability; Variation process; Maximum entropy principle; Grey bootstrap principle

Abstract

A reliability evaluation model is created to analyze the variation process of time series based on the maximum entropy and grey bootstrap principles. The original sample data is collected by measuring the vibration acceleration of time series. Then the simulated vibration acceleration data is obtained using Monte Carlo method for different wear diameters. According to the maximum entropy principle, the estimated true value and confidence interval can be calculated for the reliability parameter of the intrinsic sequence. The grey bootstrap principle is applied to obtain a large number of sample data by resampling from the parametric sample data. The variation frequencies of time series can be achieved using Poisson counting principle. The estimated true value function and the upper and lower bound functions of reliability are achieved based on the variation frequencies. The variation probabilities can be calculated for different time series. The reliability evaluation model is proven to be able to be used to take intervention measures before the vibration performance fails, which is under the condition that the possibility distribution is unknown for sample 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  - Liang Ye
AU  - Zhen Chang
PY  - 2016/02
DA  - 2016/02
TI  - Mathematical Model on Reliability of Variation Process of Rolling Bearing Vibration Performance
BT  - Proceedings of the International Conference on Electronics, Mechanics, Culture and Medicine
PB  - Atlantis Press
SP  - 279
EP  - 283
SN  - 2352-538X
UR  - https://doi.org/10.2991/emcm-15.2016.52
DO  - 10.2991/emcm-15.2016.52
ID  - Xia2016/02
ER  -