DocumentCode
130896
Title
Signal extraction and fault identification of steam turbine vibration
Author
Junru Gao ; Xin Meng ; Yajun Sun
Author_Institution
Hebei Univ. of Eng. Handan, Handan, China
fYear
2014
fDate
27-29 June 2014
Firstpage
481
Lastpage
483
Abstract
This paper, the vibration signal of steam turbine which are detected by fault diagnosis are influenced by environmental noise and detecting instrument itself, leading to vibration signal waveform distortion which contains a large number of non-stationary composition, and cannot effectively react turbine fault characteristics, and the coupling among different fault characteristics of unilateral fault features make it difficult to identify fault accurately. Aiming at solving this problem, this paper combine the axis of spectrum analysis with path analysis of vibration signal processing and recognition method, two kinds of detection method in the fault diagnosis process validation to ensure the accuracy of test results.
Keywords
distortion; fault diagnosis; mechanical engineering computing; signal detection; spectral analysis; steam turbines; vibrations; environmental noise; fault diagnosis; fault identification; nonstationary composition; path analysis; signal detection method; signal extraction; spectrum analysis; steam turbine vibration signal; turbine fault characteristics; unilateral fault features; vibration signal processing; vibration signal recognition; vibration signal waveform distortion; Fault diagnosis; Feature extraction; Rotors; Turbines; Vibrations; Wavelet analysis; Wavelet packets; Axis trajectory; Fault diagnosis; Spectrum; Steam turbine unit; vibration signal;
fLanguage
English
Publisher
ieee
Conference_Titel
Software Engineering and Service Science (ICSESS), 2014 5th IEEE International Conference on
Conference_Location
Beijing
ISSN
2327-0586
Print_ISBN
978-1-4799-3278-8
Type
conf
DOI
10.1109/ICSESS.2014.6933610
Filename
6933610
Link To Document