Paper Titles
Particle Swarm Optimization for Identification of PEMFC Generation System Fuzzy Model
p.260
The Design of a Device for Burning Biomass as Straw and Brushwood
p.264
Study on Electrical Ignition Characteristics of HAN-Based Liquid Propellant Spray
p.268
The Study on Control Strategy of Rail Pressure in the Starting Process for Common Rail Diesel Engine
p.273
Blade Damage Forecast Research Based on Support Vector Machine
p.278
The Effect of Gasoline/1-Butanol Blends on Spark-Ignition Engine Performance
p.283
Investigation of the Effect of Fuel Reactivity on Dual-Fuel PCI Combustion
p.287
Investigation on Improvement and Design of Automotive Muffler
p.291
The Study of HEV Special Two-Stage TWC Characteristics
p.295

Blade Damage Forecast Research Based on Support Vector Machine

Article Preview

Abstract:

By doing modal analysis of the whole wind turbine system, we can get the first twenty orders natural frequencies and corresponding mode shapes, By analyzing the dynamic characteristics of the blade, the weakness points of blade were fund. Under rotor rotating excitation in the normal state, mass eccentricity states and stiffness damage states of blade, the strain energy change rates (SECR) of nacelle are obtained. While based on the SECR of nacelle, the methods of strain energy change rate and support vector machine are introduced to indentify locate the mass eccentricity and stiffness damages of blade. The research show that mass eccentricity and stiffness damages at different location and in different degree can be efficiency identified and forecasted by means of support vector machine classification method.

You might also be interested in these eBooks
Advances in Mechanics Engineering View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 588-589)

Pages:

278-282

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.588-589.278

Citation:

Cite this paper

Online since:

November 2012

Authors:

Zhi Wei Ma, Yu Xiu Xu, Shi Rong Xing

Keywords:

Blade Damage, Strain Energy, Support Vector Machine (SVM)

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

© 2012 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

References

[1] CIANG C C, LEE J, BANG H. Structural health monitoring for a wind turbine system: A review of damage detection methods[J]. Measurement Science and Technology, 2008, 19 (12).

DOI: 10.1088/0957-0233/19/12/122001

Google Scholar

[2] He Xianfu, Lu Xia, Yang Yuejin , ect. Wind turbine design, manufacturing and operation [m]. China chemical industry press, 2009. (In Chinese).

Google Scholar

[3] BURTON T, SHARPE D, JENKINS N, et al. Wind Energy Handbook [M]. John Wiley & Sons Ltd, (2001).

Google Scholar

[4] Li Gui-bing. Index method of structural damage identification and its realization [J]. Journal of Taiyuan university, 20, 035: 613-615. (in Chinese).

Google Scholar