Combined indices for ICA and their applications to multivariate process fault diagnosis

As a development of principal component analysis (PCA) and factor analysis (FA), independent component analysis (ICA) has been applied effectively to multivariate process monitoring and fault diagnosis and has got many excellent achievements. Usually, ICA has three indices for monitoring and diagnosis, i.e., I², I_e², and SPE, and the multi-indexes make the monitoring and diagnosis inconvenient and also decentralizes the fault influence. In this paper, two combined indices for ICA are developed, both of which are weighted sums of the three indices. The statistics and physical meanings of all indices are analyzed and compared. Based on the simulation tests on a numerical example and TE process, the proposed combined indices have some advantages compared with the traditional multi-indices. Copyright © 2013 Acta Automatica Sinica. All rights reserved.