title: Using the expected detection delay to assess the performance of different multivariate statistical process monitoring methods for multiplicative and drift faults.
abstract: Using the expected detection delay (EDD) index to measure the performance of multivariate statistical process monitoring (MSPM) methods for constant additive faults have been recently developed. This paper, based on a statistical investigation of the T2- and Q-test statistics, extends the EDD index to the multiplicative and drift fault cases. As well, it is used to assess the performance of common MSPM methods that adopt these two test statistics. Based on how to use the measurement space, these methods can be divided into two groups, those which consider the complete measurement space, for example, principal component analysis-based methods, and those which only consider some subspace that reflects changes in key performance indicators, such as partial least squares-based methods. Furthermore, a generic form for them to use T2- and Q-test statistics are given. With the extended EDD index, the performance of these methods to detect drift and multiplicative faults is assessed using both numerical simulations and the Tennessee Eastman process.
authors.affiliation: Key Laboratory for Advanced Control of Iron and Steel Process, School of Automation and Electrical Engineering, University of Science and Technology Beijing, 100083 Beijing, PR China. Electronic address: ustb.kaizhang@gmail.com.
authors.forename: Kai
authors.initials: K
authors.lastname: Zhang
authors.affiliation: Department of Chemical Engineering, University of Waterloo, 200 University Ave West, Waterloo, ON, Canada N2L 3G1.
authors.forename: Yuri A W
authors.initials: YAW
authors.lastname: Shardt
authors.affiliation: School of Information Science and Engineering, Central South University, 410083, Changsha, PR China.
authors.forename: Zhiwen
authors.initials: Z
authors.lastname: Chen
authors.affiliation: Key Laboratory for Advanced Control of Iron and Steel Process, School of Automation and Electrical Engineering, University of Science and Technology Beijing, 100083 Beijing, PR China. Electronic address: kaixiang@ustb.edu.cn.
authors.forename: Kaixiang
authors.initials: K
authors.lastname: Peng
keywords: Drift faults; Expected detection delay; Multiplicative faults; Performance assessment; Q-statistic; T(2)-statistic