DocumentCode :
666892
Title :
A fault detection method based on dynamic peakvalley limit under the non-steady conditions
Author :
Tianzhen Wang ; Man Xu ; Tianhao Tang ; Jingan Han ; Xiong Hu
Author_Institution :
Dept. of Electr. Autom., Shanghai Maritime Univ., Shanghai, China
fYear :
2013
fDate :
10-13 Nov. 2013
Firstpage :
7346
Lastpage :
7351
Abstract :
The multivariate statistical methods are commonly used to fault detection through a straight limit line given by the HotellingT2. However, the traditional straight limit line is difficult to detect the fault effectively under the non-steady conditions, which the false alarm rate and missing alarm rate are high. For these problems above, a fault detection method based on dynamic peak-valley limit is proposed in this paper. The proposed method introduces relative principal component analysis to carry out the dimension reduction, and extracts principal components, then adopts moving least squares to preprocess PCs to obtain the fitting curve which is called peak-valley curve, finally uses peak and valley points to construct a control limit combined the traditional straight limit line. At the end, the proposed method is applied to wind power generation system, and the simulation results verify the effectiveness of the proposed method.
Keywords :
curve fitting; fault diagnosis; least mean squares methods; power generation control; principal component analysis; wind power plants; HotellingT2; PC preprocessing; dimension reduction; dynamic peak valley limit; false alarm rate; fault detection method; missing alarm rate; moving least squares; multivariate statistical method; nonsteady condition; peak valley curve fitting; principal component analysis; principal component extraction; straight limit line; wind power generation system; Fault detection; Fitting; Generators; Monitoring; Principal component analysis; Wind power generation; Wind speed; MLS; RPCA; T2-statistic; dynamic peak-valley limit; fault detect;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics Society, IECON 2013 - 39th Annual Conference of the IEEE
Conference_Location :
Vienna
ISSN :
1553-572X
Type :
conf
DOI :
10.1109/IECON.2013.6700355
Filename :
6700355
Link To Document :
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