Fault diagnosis of wind turbine based on information entropy and neural network

Jixie Qiangdu/Journal of Mechanical Strength

Volumn 31, Issue 1, 2009, Pages 132-135

  Zhang, Laibin ^a   Cui, Houxi ^a   Wang, Zhaohui ^a   Duan, Lixiang ^a  

^a CHINA UNIVERSITY OF PETROLEUM   (China)

Author keywords

Fault diagnosis; Information entropy; Neural network; Wind turbine

Indexed keywords

EID: 61349123252     PISSN: 10019669     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (6)

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2. Yu Shaorong, Yin Yihui, Xu Bin, et al. Analysis of the random-fuzzy reliability based on the information entropy theory[J]. Journal of Mechanical Strength, 2006, 28(5): 695-698. (In Chinese)
3. Liu Changhong, Chen Qiu. Response surface method in fuzzy parameters under the entropy[J]. Journal of Mechanical Strength, 2003, 25(2): 187-189. (In Chinese)
4. Shen Tao, Huang Shuhong, Han Shoumu, et al. Extracting information entropy features for rotating machinery vibration signals[J]. Chinese Journal of Mechanical Engineering, 2001, 37(6): 94-98. (In Chinese)
5. Geng Junbao, Huang Shuhong, Chen Fei, et al. Rotating machinery fault diagnosis based on close degree to information entropy[J]. Journal of Huazhong University of Science and Technology: Nature Science Edition, 2006, 34(11): 93-95. (In Chinese)
6. Gui Zhonghua, Han Fengqin. Neural network based on wavelet packetcharacteristic entropy for fault diagnosis of draft tube[J]. Proceedings of the CSEE, 2005, 25(4): 99-102. (In Chinese)