Steam turbine fault diagnosis based on least squares support vector machine

Kongzhi yu Juece/Control and Decision

Volumn 22, Issue 7, 2007, Pages 778-782

  Yang, Kui He ^a,b   Shan, Gan Lin ^a   Zhao, Ling Ling ^b  

^a ORDNANCE ENGINEERING COLLEGE   (China)

^b HEBEI UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

Fault diagnosis; Least squares support vector machine; Probabilistic neural networks; Steam turbine; Wavelet packet analysis

Indexed keywords

LINEAR EQUATIONS; NEURAL NETWORKS; QUADRATIC PROGRAMMING; STEAM TURBINES; WAVELET ANALYSIS;

FAULT DIAGNOSIS; KERNEL FUNCTION; LEAST SQUARES; POWER SPECTRUMS; WAVELET PACKET ANALYSIS;

SUPPORT VECTOR MACHINES;

EID: 34547633329     PISSN: 10010920     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (11)

1. Vapnik V, Golowich S, Smola A. Support vector method for function approximation, regression estimation and signal processing [J]. Advances in Neural Information Processing Systems, 1996, 9 (2): 281-287.
2. Chen S, Samingan A K, Hanzo L. Support vector machine multiuser receiver for DS-CDMA signals in multipath channels [J]. IEEE Trans on Neural Networks, 2001, 12 (3): 604-611.
3. Sebald D J, Bucklew J A. Support vector machine techniques for nonlinear equalization [J]. IEEE Trans on Signal Processing, 2000, 48 (11): 3217-3226.
4. Melgani F, Bruzzone L. Classification of hyperspectral remote sensing images with support vector machines [J]. IEEE Trans on Geoscience Remote Sensing, 2004, 42 (8): 1778-1790.
5. Suykens J A K, Vandewalle J. Least squares support vector machine classifiers [J]. Neural Processing Letters, 1999, 9 (3): 293-300.
6. Lukas L, Suykens J A K, Vandewalle J. Least squares support vector machines classifiers: A multi two-spiral benchmark problem [C]. Proc of the Indonesian Student Scientific Meeting. Manchester, 2001: 289-292.
7. Suykens J A K, Lukas L, Vandewalle J. Sparse least squares support vector machine classifiers [C]. Proc of the European Symposium on Artificial Neural Networks. Bruges, 2000: 37-42.
8. Yu He-ji, Chen Chang-zheng, Zhang Xing, et al. Intelligent diagnosis based on neural networks [M]. Beijing: Metallurgy Industry Press, 2002.
9. Ye Zhi-feng, Sun Jian-guo. Probabilistic neural networks based engine fault diagnosis [J]. Aviation Transaction, 2002, 23 (2): 155-157.
10. Li Dong-hui, Liu Hao. Method and application of fault diagnosis based on probabilistic neural network [J]. Systems Engineering and Electronics, 2004, 26 (7): 997-999.
11. Hsu C W, Lin C J. A comparison of methods for multiclass support vector support vector machines [J]. IEEE Trans on Neural Networks, 2002, 13 (2): 415-425.