Chun-Yao Lee
Chung Yuan Christian University, Taoyuan County, Taiwan
Chih-Ju Chou
National Taipei University of Technology, Taipei City, Taiwan
Chun-Chi Chen
Chung Yuan Christian University, Taoyuan County, Taiwan
Ryan Liu
University of California, Berkeley, USA
I. Hsiang Tseng
Chung Yuan Christian University, Taoyuan County, Taiwan
Yi-Xing Shen
Chung Yuan Christian University, Taoyuan County, Taiwan
ABSTRACT
This study proposes a lubrication leakage alarm approach which can detect the lubrication leakage of a gearbox by only using generator current without any additional measurement apparatus. First, in the study, the 11 current signals on each lubrication level from full to empty, at 10% intervals, were tailor-made. Second, their features are extracted, from which the criteria of detection system are selected. Finally, the k-nearest neighbor and back propagation neural network are employed to detect the lubrication leakage. The results indicate that this approach can trigger the alarm system precisely when the remaining lubrication levels are less than 30%, in which the accuracies are all reach 97.5%.
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How to cite this article
Chun-Yao Lee, Chih-Ju Chou, Chun-Chi Chen, Ryan Liu, I. Hsiang Tseng and Yi-Xing Shen, 2013. Lubrication Leakage Alarm of Wind Power Gearbox Based on K-nearest Neighbor
and Back Propagation Neural Network. Information Technology Journal, 12: 3152-3157.
DOI: 10.3923/itj.2013.3152.3157
URL: https://scialert.net/abstract/?doi=itj.2013.3152.3157
DOI: 10.3923/itj.2013.3152.3157
URL: https://scialert.net/abstract/?doi=itj.2013.3152.3157
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