JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2017, Vol. 47 ›› Issue (5): 123-129.doi: 10.6040/j.issn.1672-3961.0.2017.166

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A mode-correlation principal component analysis for the fault detection of marine current turbine

ZHANG Milu, WANG Tianzhen*, TANG Tianhao, XIN Bin   

  1. Department of Electrical Automation, Shanghai Maritime University, Shanghai 201306, China
  • Received:2017-02-10 Online:2017-10-20 Published:2017-02-10

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Abstract: To solve the problem of multi-mode characteristic and frequent mode changes, a detection method for marine current turbine which called mode-correlation principal component analysis was proposed. The influence of modal change on the traditional principal component analysis(PCA)was analyzed in theory. The detection problem caused by multi-mode characteristic was described. A mode normalized algorithm was proposed in the proposed method to dynamic fitting the mode. The statistical difference value of different modes was removed due to relationships between modes. Compared with other methods, the experimental platform was built to verify the effectiveness of the proposed method. Theoretical analysis and experimental results showed that the proposed method could detect the fault quickly and accurately under the condition of variable speed and variable load.

Key words: mode-correlation PCA, dynamic time warping, PCA regression, fault detection

CLC Number: 

  • TP273
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