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k-Nearest Neighbor Imputation Method and Its Application in Fault Diagnosis of Industrial Process |
LI Yuan1,WU Jie1,WANG Guozhu2 |
(1. College of Information Engineering, Shenyang University of Chemical Technology, Shenyang 110142, China; 2. College of Information Science and Engineering, Northeastern University, Shenyang 110819, China) |
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Abstract Abstract: Aimed at the smearing effect in contribution plot method and the falt that fault variables cannot be located, this paper proposed a kNN imputation method for fault diagnosis, combining k-nearest neighbor and the contribution plot algorithm. First, PCA was adopted to build an evaluation model and calculate the combined index. Secondly, knearest neighbor imputation method and the control index were combined to extract preliminary faulty variables. Finally, the contribution plots were employed to find the fundamental faulty variables from the preliminary faults. The proposed method can avoid the influence of contribution values of normal variables effectively. A numerical example and Tennessee Eastman (TE) process were given to verify the effectiveness and accuracy of the proposed method, compared with the reconstruction-based method.
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Received: 02 December 2014
Published: 29 June 2015
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