Research on Fault Diagnosis Method Based on Rule Base Neural Network

Joint Authors

Zhang, Lin
Wang, Wen-feng
Ni, Zheng
Bo, Zhang
Yongjin, Liu
Dajiang, Zhang

Source

Journal of Control Science and Engineering

Issue

Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-7, 7 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2017-01-12

Country of Publication

Egypt

No. of Pages

7

Main Subjects

Electronic engineering
Information Technology and Computer Science

Abstract EN

The relationship between fault phenomenon and fault cause is always nonlinear, which influences the accuracy of fault location.

And neural network is effective in dealing with nonlinear problem.

In order to improve the efficiency of uncertain fault diagnosis based on neural network, a neural network fault diagnosis method based on rule base is put forward.

At first, the structure of BP neural network is built and the learning rule is given.

Then, the rule base is built by fuzzy theory.

An improved fuzzy neural construction model is designed, in which the calculated methods of node function and membership function are also given.

Simulation results confirm the effectiveness of this method.

American Psychological Association (APA)

Ni, Zheng& Zhang, Lin& Wang, Wen-feng& Bo, Zhang& Yongjin, Liu& Dajiang, Zhang. 2017. Research on Fault Diagnosis Method Based on Rule Base Neural Network. Journal of Control Science and Engineering،Vol. 2017, no. 2017, pp.1-7.
https://search.emarefa.net/detail/BIM-1173555

Modern Language Association (MLA)

Ni, Zheng…[et al.]. Research on Fault Diagnosis Method Based on Rule Base Neural Network. Journal of Control Science and Engineering No. 2017 (2017), pp.1-7.
https://search.emarefa.net/detail/BIM-1173555

American Medical Association (AMA)

Ni, Zheng& Zhang, Lin& Wang, Wen-feng& Bo, Zhang& Yongjin, Liu& Dajiang, Zhang. Research on Fault Diagnosis Method Based on Rule Base Neural Network. Journal of Control Science and Engineering. 2017. Vol. 2017, no. 2017, pp.1-7.
https://search.emarefa.net/detail/BIM-1173555

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1173555