Abnormal recognition algorithm based on manifold learning for turbopump mass data

被引:0
|
作者
Xia, Lu-Rui [1 ,2 ]
Hu, Niao-Qing [1 ]
Qin, Guo-Jun [1 ]
机构
[1] College of Mechatronic Engineering and Automation, National University of Defense Technology, Changsha 410073, China
[2] Department of Space Equipment, Academy of Equipment Command and Technology, Beijing 101416, China
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关键词
Learning algorithms - Data mining - Clustering algorithms;
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学科分类号
摘要
To extract the information from turbopump mass data and analyze its health condition, the paper presented a mass data abnormal recognition algorithm based on manifold learning. The algorithm reconstructed turbopump vibration data in high-dimensional space. Then, the diffusion map method was used to directly learn the high-dimensional data and extract intrinsic low-dimensional manifold feature in data set. The abnormal condition in turbopump mass data was discerned visually. The validation results of simulation and test data demonstrate the feasibility and effectiveness of the presented algorithm. The algorithm conquers the shortcoming of the traditional methods that are insufficient for nonlinear problems, and gives a new solution of turbopump post-test health analysis.
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页码:698 / 703
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