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Mathematical Problems in Engineering
Volume 2015 (2015), Article ID 348729, 8 pages
Research Article

Fault Prediction Algorithm for Multiple Mode Process Based on Reconstruction Technique

School of Automation, Beijing Information Science and Technology University, Beijing 100192, China

Received 29 October 2014; Accepted 21 December 2014

Academic Editor: Gang Li

Copyright © 2015 Jie Ma and Jianan Xu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


In the framework of fault reconstruction technique, this paper studies the problems of multiple mode process fault detection, fault estimation, and fault prediction systematically based on multi-PCA model. First, a multi-PCA model is used for fault detection in steady state process under different conditions, while a weighted algorithm is applied to transition process. Then, describe the faults quantitatively and use the optimization method to derive the fault amplitude under the sense of fault reconstruction. Fault amplitude drifts under different conditions even if the same fault occurs. To solve the above problem, consistent estimation algorithm of fault amplitude under different conditions has been studied. Last, employ the support vector machine (SVM) to predict the trend of the fault amplitude. Effectiveness of the algorithms proposed in this paper has been verified using Tennessee Eastman process as the study object.