Application of Wavelet De-Noising in Fault Diagnosis of Wind Turbine Gearboxes

Hai Jiang Kou; Hui Qun Yuan; Xiao Yu Zhao

doi:10.4028/www.scientific.net/AMR.562-564.1091

Paper Titles

Study on the Applicable Wind Speed Model of Wind Farm and High-Frequency Wind Simulation
p.1074

Study for Three-Dimensional Design of the Engine Crankshaft Piston Group
p.1079

Application of Heat Pump Technology in Coal Mine
p.1083

Research Advances of NO_x Emissions Control Technologies of Stoker Boilers
p.1087

Application of Wavelet De-Noising in Fault Diagnosis of Wind Turbine Gearboxes
p.1091

CFD Simulation Analysis of Pressure Drop in a Vertical Helical-Coil Heat Exchanger
p.1095

Performance Analysis of a New Type of Wind Resistance Brake Mechanism Based on FLUENT and ANSYS
p.1099

The Mini-Vehicle Manual Transmission Reverse-Gear Noise Analysis
p.1103

Intelligent Driver Designing for Electro-Hydraulic Proportional Valve of Engineering Machine
p.1108

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 562-564Application of Wavelet De-Noising in Fault...

Application of Wavelet De-Noising in Fault Diagnosis of Wind Turbine Gearboxes

Abstract:

Fault detection and diagnosis of a wind turbine gearbox are important to ensure the reliability and useful life of the wind turbine system. In this paper, an experimental test in wind turbine gearboxes is carried out to obtain faulted information which consists of response random non-stationary noise and the additional response due to failure. An approach, using wavelet de-noising method, is proposed for removing non-stationary noise from the recorded signals. The time domain analysis and frequency analysis are used to diagnose the fault location of the machine accurately. It is shown that wavelet de-noising method provides a better correction than conventional method in order to remove non-stationary noise. Diagnosis results indicate that the high-speed shaft of wind turbine gearboxes has a serious imbalance.

You might also be interested in these eBooks

Materials Engineering and Automatic Control

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 562-564)

Pages:

1091-1094

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.562-564.1091

Citation:

Cite this paper

Online since:

August 2012

Authors:

Hai Jiang Kou, Hui Qun Yuan, Xiao Yu Zhao

Keywords:

Condition Monitoring, Fault Diagnosis, Wavelet De-Noising, Wind Turbine Gearboxes

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] HAMEED Z, HONG Y S, CHO Y M, et al: Renewable and Sustainable Energy Reviews. Sci. Vol 13. 1(2009), pp.1-39.

Google Scholar

[2] BARSZCZ T, ROBERT B: Mechanical Systems and Signal Processing. Sci. Vol 23. 4(2009), pp.1352-1365.

Google Scholar

[3] HUANG Qian, JIANG Dongxiang, HONG Liangyou, et al: Lecture Notes in Computer Science. Ei. Vol 5264. 2(2008), pp.313-320.

Google Scholar

[4] Dalili N, Edrisy A, Carriveau R: Renewable and Sustainable Energy Reviews. Sci. Vol 13. 2(2009), pp.428-438.

DOI: 10.1016/j.rser.2007.11.009

Google Scholar

[5] Loutridis SJ: Mechanical Systems and Signal Processing. Sci. Vol 20. 5(2006), pp.1239-1253.

Google Scholar

[6] Junsheng C, Dejie Y, Yu Y: NDT & E International. Ei. Vol 38. 7(2005), pp.569-572.

Google Scholar

[7] Yang WX, Ren XM: EURASIP Journal on Applied Signal Processing. Ei. Vol 2004. 8(2004), pp.1156-1162.

Google Scholar

[8] Fan YS, Zheng GT: Mechanical Systems and Signal Processing. Sci. Vol 21. 2(2007), pp.678-687.

Google Scholar

[9] Ioannis Delakis, Omer Hammad, Kitney Richard I: Physics in Medicine and Biology. Sci. Vol 52. 13(2007), pp.3741-3751.

Google Scholar

[10] Baoping Tang, Wenyi Liu, Tao Song: Renewable Energy. Ei. Vol 35. 12(2010), pp.2862-2866.

Google Scholar