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Original paper

Nonlinear sensor fault diagnosis using mixture of probabilistic PCA models

Volume: 85, Pages: 638 - 650
Published: Sep 11, 2016
Abstract
This paper presents a methodology for sensor fault diagnosis in nonlinear systems using a Mixture of Probabilistic Principal Component Analysis (MPPCA) models. This methodology separates the measurement space into several locally linear regions, each of which is associated with a Probabilistic PCA (PPCA) model. Using the transformation associated with each PPCA model, a parity relation scheme is used to construct a residual vector. Bayesian...
Paper Details
Title
Nonlinear sensor fault diagnosis using mixture of probabilistic PCA models
Published Date
Sep 11, 2016
Volume
85
Pages
638 - 650
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