Research on fault diagnosis of indicator diagram based on BP neural network optimized by iterative learning control

DOI

10.2991/fmsmt-17.2017.169How to use a DOI?

Keywords

pumping unit,fault diagnosis,indicator diagram,Shape invariant moment,Fourier descriptor,Iterative learning control, BP neural network.

Abstract

In this paper, an intelligent fault diagnosis method is presented to solve the problem that the accuracy of pumping unit fault diagnosis is not high. This method selects the Shape invariant moment and the Fourier descriptor to extract the characteristic parameters of the sample indicator diagram, and uses the BP neural network optimized by iterative learning control to classify and identify. Finally, the expert diagnosis method is used to compare the recognition results to obtain the diagnosis result. The experiment shows that the method is fast, accurate and intelligent.

Copyright

© 2017, 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/).

Download article (PDF)

TY  - CONF
AU  - Xiaohong Hao
AU  - Ning Zhang
PY  - 2017/04
DA  - 2017/04
TI  - Research on fault diagnosis of indicator diagram based on BP neural network optimized by iterative learning control
BT  - Proceedings of the 2017 5th International Conference on Frontiers of Manufacturing Science and Measuring Technology (FMSMT 2017)
PB  - Atlantis Press
SP  - 881
EP  - 889
SN  - 2352-5401
UR  - https://doi.org/10.2991/fmsmt-17.2017.169
DO  - 10.2991/fmsmt-17.2017.169
ID  - Hao2017/04
ER  -