The BP Information Model Based on AI-ESTATE

DOI

10.2991/meic-15.2015.196How to use a DOI?

Keywords

AI-EATATE; BP information model; BP neural network; analog circuit; fault diagnosis

Abstract

This paper proposes a new fault diagnosis strategy for analog circuit after analyzing diagnosis method based on the BP neural networks and AI-ESTATE standard. At present, The artificial intelligence algorithms such as SVM and BP has been widely adopted in analog circuit fault diagnosis, but it is not included in the IEEE AI-ESTATE standard. So there is no normalization of BP information model, and the interchange formats of the BP information model is application-dependent. Therefore, it has no portability and cannot share diagnostic knowledge and data across different platform or application in analog circuit fault diagnosis. For these problems, the BP information model based on AI-ESTATE standard is proposed. And it not only extends the standard of AI-ESTATE, but also presents a normalization of the BP information model in analog circuit fault diagnosis. The simulation result shows that the proposed BP information model can share data among different platform, while maintain the same diagnostic rate compared with the traditional method.

Copyright

© 2015, 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  - Yuehai Wang
AU  - Jiaojiao Li
PY  - 2015/04
DA  - 2015/04
TI  - The BP Information Model Based on AI-ESTATE
BT  - Proceedings of the 2015 International Conference on Mechatronics, Electronic, Industrial and Control Engineering
PB  - Atlantis Press
SP  - 856
EP  - 859
SN  - 2352-5401
UR  - https://doi.org/10.2991/meic-15.2015.196
DO  - 10.2991/meic-15.2015.196
ID  - Wang2015/04
ER  -