Abstract
Motivated by data-driven design of fault detection system, a recursive algorithm is developed for updating the parity relation within the framework of subspace identification methods (SIM). The presented recursive algorithm benefits from the signal processing methods for noise subspace tracking to reduce the computationally burdensome updating of singular value decomposition (SVD), which is a crucial step in SIM. Based on the recursive updated parity relation, the residual generator for the fault detection purpose is constructed and the issues of residual evaluation and threshold computation are discussed further. The adaptive process monitoring scheme that integrates the aforementioned issues, is proposed and tested on the laboratory three-tank-system.
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