Fault Detection and Isolation of a Three-tank System Using Analytical Temporal Redundancy – Parity Space/Relation Based Residual Generation

Abstract

This paper investigates the fault detection and isolation technique in measurement datasets from a three-tank system using analytical model-based temporal redundancy. It is based on residual generation using a parity equations/space approach. The
paper further briefly outlines other approaches of model-based residual generation. The basic idea of parity space residual
 neration in temporal redundancy is a dynamic relationship between sensor outputs and actuator inputs (input-output model).
These residuals were then used to detect whether or not the system is faulty and indicate the location of the fault when it is faulty.
The method obtains good results by detecting and isolating faults from the considered measurement datasets generated from the system.