DocumentCode
3589792
Title
A degredation interval prediction method based on RBF neural network
Author
Xiankun Zhang ; Fuqiang Sun ; Xiaoyang Li
Author_Institution
Sci. & Technol. on Reliability & Environ. Eng. Lab., Beihang Univ., Beijing, China
fYear
2014
Firstpage
310
Lastpage
315
Abstract
In the area of reliability, remaining useful lifetime (RUL) prediction can help people establish reasonable maintenance strategies and then implement maintenance activities at a right time. In this paper, RBF neural network approach is applied in the degradation prediction process of a certain microwave component. A degradation model that describes how a certain degradation parameter changes over time is established and then the performance degradation trend can be obtained based on this model. And then a confidence interval prediction can be obtained based on traditional probability theory, which proves that the results have reached a high confidence level. Finally, the BP neural network approach is introduced as a comparison, and results indicate that the proposed method has higher precision and stability.
Keywords
backpropagation; radial basis function networks; BP neural network approach; RBF neural network; RUL prediction; confidence interval prediction; degradation parameter; degradation prediction process; degredation interval prediction method; microwave component; probability theory; reasonable maintenance strategies; remaining useful lifetime; Biological neural networks; Data models; Degradation; Prediction algorithms; Predictive models; Training data; RBF neural network; RUL prediction; interval prediction; performance degradation;
fLanguage
English
Publisher
ieee
Conference_Titel
Reliability, Maintainability and Safety (ICRMS), 2014 International Conference on
Print_ISBN
978-1-4799-6631-8
Type
conf
DOI
10.1109/ICRMS.2014.7107194
Filename
7107194
Link To Document