Identification of Shaft Centerline Orbit for Wind Power Units Based on Hopfield Neural Network Improved by Simulated Annealing
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-03-26
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
In the maintenance system of wind power units, shaft centerline orbit is an important feature to diagnosis the status of the unit.
This paper presents the diagnosis of the orbit as follows: acquire characters of orbit by the affine invariant moments, take this as the characteristic parameters of neural networks to construct the identification model, utilize Simulated Annealing (SA) Algorithm to optimize the weights matrix of Hopfield neural network, and then some typical faults were selected as examples to identify.
Experiment’s results show that SA-Hopfield identification model performed better than the previous methods.
American Psychological Association (APA)
Ren, Kun& Qu, Jihong. 2014. Identification of Shaft Centerline Orbit for Wind Power Units Based on Hopfield Neural Network Improved by Simulated Annealing. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-6.
https://search.emarefa.net/detail/BIM-481650
Modern Language Association (MLA)
Ren, Kun& Qu, Jihong. Identification of Shaft Centerline Orbit for Wind Power Units Based on Hopfield Neural Network Improved by Simulated Annealing. Mathematical Problems in Engineering No. 2014 (2014), pp.1-6.
https://search.emarefa.net/detail/BIM-481650
American Medical Association (AMA)
Ren, Kun& Qu, Jihong. Identification of Shaft Centerline Orbit for Wind Power Units Based on Hopfield Neural Network Improved by Simulated Annealing. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-6.
https://search.emarefa.net/detail/BIM-481650
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-481650