Vibration fault diagnosis of generating set based on weighted fuzzy kernel clustering

Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering

Volumn 28, Issue 35, 2008, Pages 79-83

  Li, Chao Shun ^a   Zhou, Jian Zhong ^a   An, Xue Li ^a   Xiang, Xiu Qiao ^a   Zhang, Yong Chuan ^a  

^a HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

Fault diagnosis; Feature weight; Fuzzy clustering; Generating set; Mercer kernel

Indexed keywords

CLUSTER ANALYSIS; ELECTRIC GENERATORS; FUZZY SETS; FUZZY SYSTEMS;

C-MEANS; CLUSTERIN; FAULT DIAGNOSIS; FEATURE SPACES; FEATURE WEIGHT; FUZZY KERNEL CLUSTERING; FUZZY KERNELS; GENERATING SET; MERCER KERNEL; TESTING DATUMS; TURBINE GENERATORS; VIBRATION FAULT DIAGNOSIS; WEIGHTED FUZZY CLUSTERING; WEIGHTING METHODS;

FUZZY CLUSTERING;

EID: 58149229876     PISSN: 02588013     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (16)

1. Peng Wenji, Luo Xingqi. Research on vibrant fault diagnosis of hydro-turbine generating unit based on wavelet packet analysis and support vector machine[J]. Proceedings of the CSEE, 2006, 26(24): 164-168(in Chinese).
2. Zhao Daoli, Ma Wei, Liang Wuke, et al. On data fusion fault diagnosis and simulation of hydroelectric units vibration[J]. Proceedings of the CSEE, 2005, 25(20): 137-142(in Chinese).
3. Jiang Dongxiang, Diao Jinhui, Zhao Gang, et al. Study on methods of vibration fault diagnosis based on time-frequence contour map for turbine generator unit[J]. Proceedings of the CSEE, 2005, 25(6): 146-151(in Chinese).
4. Li Chaoshun, Zhou Jianzhong, Yang Junjie, et al. Vibration fault diagnosis of turbo-generator set based on hybrid fuzzy clustering analysis[J]. Automation of Electric Power Systems, 2008, 32(5): 81-84(in Chinese).
5. Chen Tiehua, Chen Qijuan. Fuzzy clustering analysis based vibration fault diagnosis of hydroelectric generating unit[J]. Proceedings of the CSEE, 2002, 22(3): 43-47(in Chinese).
6. Wu Huiying, Shuai Renjun. Fuzzy set analysis of turbine rotator vibration malfunction[J]. Journal of Shanghai Jiaotong University, 1999, 33(8): 1051-1054(in Chinese).
7. Wang Cangqian, Liao Sien, Gu Huang, et al. Application of fuzzy clustering theory for diagnosing the vibration faults of turbogenerator units[J]. Turbine Technology, 2003, 45(4): 228-230(in Chinese).
8. Lei Yaguo, He Zhengjia, Zi Yanyang, et al. Novel hybrid clustering algorithm and its application to fault diagnosis[J]. Chinese Journal of Mechanical Engineering, 2006, 42(12): 117-121(in Chinese).
9. Zhang Li, Zhou Weida, Jiao Licheng. Kernel clustering algorithm[J]. Chinese Journal of Computers, 2002, 25(6): 587-590(in Chinese).
10. Zhang Rong, Rudnicky A I. A large scale clustering scheme for kernel k-means[C]. The Sixteenth International Conference on Pattern Recognition, Washington, DC, USA, 2002.
11. Burges C J C. Geometry and invariance in kernel based methods. Advance in kernel methods-support vector learning[M]. Cambridge, MA: MIT Press, 1999: 89-116.
12. Li Jie, Gao Xinbo, Jiao Licheng. A new feature weighted fuzzy clustering algorithm[J]. Acta Electronica Sinica, 2006, 34(1): 89-92(in Chinese).
13. Yeung D S, Wang X Z. Improving performnace of similarity-based clustering by feature weight learning[J]. IEEE Transaction on Pattern Analysis and Machine Intelligence, 2002, 24(4): 556-561.
14. Pakhira M K, Bandyopadhyay S, Maulik U. Study of some fuzzy cluster validity indices, genetic clustering and application to pixel classification[J]. Fuzzy Sets and Systems, 2005, 155(2): 191-214.
15. Das S, Abraham A, Konar A. Automatic kernel clustering with a multi-elitist particle swarm optimization algorithm[J]. Pattern Recognition Letters, 2008, 29(5): 688-699.