Research on fault diagnosis of indicator diagram based on BP neural network optimized by iterative learning control
- https://doi.org/10.2991/fmsmt-17.2017.169How to use a DOI?
- pumping unit,fault diagnosis,indicator diagram,Shape invariant moment,Fourier descriptor,Iterative learning control, BP neural network.
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.
- © 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/).
Cite this article
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 - https://doi.org/10.2991/fmsmt-17.2017.169 ID - Hao2017/04 ER -