Top

Published in:

2015 | OriginalPaper | Chapter

10. Chaotic Property Identification and Prediction of Performance Degradation Time Series for Hydropower Unit

Author : Xueli An

Published in: Proceedings of the Second International Conference on Mechatronics and Automatic Control

Publisher: Springer International Publishing

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

The performance degradation time series of hydropower unit is reconstructed in phase space by using the chaos theory. Chaotic property of the series is found through analysis. The degradation time series is predicted based on the adding-weight one-rank local-region method. The condition monitoring data of hydropower unit are used to verify the proposed method. The results show that it is feasible to predict the performance degradation of hydropower unit by using the chaos prediction method. The proposed method has high accuracy. It is a new way to operate and maintain the hydropower unit.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

inform now

previous chapter Application of Ensemble Empirical Mode Decomposition on Stator Inter-turn Short-Circuit Fault in Doubly Fed Induction Generators

next chapter Cosimulation Method for Asynchronous Motor Based on SaberRD–Simulink

An XL, Pan LP, Zhang F, et al. Condition degradation assessment and nonlinear prediction of hydropower unit [J]. Power Syst Tech. 2013;37(5):1378–83 (In Chinese).

Li S, Zhou Y, Zhu Y. Harmonic current prediction method of combined power filter system based on weighted first-order local area theory [J]. Proc CSEE. 2004;24(6):19–23 (In Chinese).

Dong L, Wang L, Gao S. Modeling and analysis of prediction of wind power generation in the large wind farm based on chaotic time series [J]. Trans Ch Electrotech Soc. 2008;23(12):125–9 (In Chinese).

Luo H, Liu T, Li X. Chaotic forecasting method of short-term wind speed in wind farm [J]. Power Syst Tech. 2009;33(9):67–71 (In Chinese).

Cao L. Practical method for determining the minimum embedding dimension of a scalar time series [J]. Physica D. 1997;110(1–2):43–50 (In Chinese).CrossRefMATH

Wolf A, Swift J, Swinney H. Determining Lyapunov exponents from a time series [J]. Physica D. 1985;16(3):285–317 (In Chinese).CrossRefMathSciNetMATH

An X, Jiang D, Liu C, et al. Wind farm power prediction based on wavelet decomposition and chaotic time series [J]. Expert Syst Appl. 2011;38(9):11280–5.CrossRef

Friedman J. Multivariate adaptive regression splines [J]. Ann Stat. 1991;19(1):1–67 (In Chinese).CrossRefMATH

Title: Chaotic Property Identification and Prediction of Performance Degradation Time Series for Hydropower Unit
Author: Xueli An
Publisher: Springer International Publishing
Book: Proceedings of the Second International Conference on Mechatronics and Automatic Control
Print ISBN: 978-3-319-13706-3

Electronic ISBN: 978-3-319-13707-0

Copyright Year: 2015
DOI: https://doi.org/10.1007/978-3-319-13707-0_10