Fault Diagnosis in the Feedback-Invariant Subspace of Closed-Loop Systems

In this paper we demonstrate that feedback control will obscure the apparent source of a fault and make fault isolation difficult. A new method is proposed whereby fault detection and diagnosis is performed in the feedback-invariant subspace of the closed-loop process output. The feedback-invariant signals are achieved by a simple orthogonal projection without the knowledge of the process or controller models. The only requirement is that the process or controller must have at least one time delay, which is generally satisfied. The feedback-invariant signals remove autocorrelation due to closed-loop dynamics, making static principal component analysis applicable for fault detection and diagnosis. A simulated example is provided to illustrate the procedure.