Abstract
In this chapter, a new robust fault detection test based on calculating the inverse image of an interval function is presented. It is based on a consistency test that relies on tools from interval analysis such as set inversion or contractors to check if there exists a member in the family of models described with an interval model that can explain the measured data. The proposed test is compared to related approaches of fault detection using interval analysis. It has interesting properties and advantages over the traditional approaches that are based on the direct image. Measurement noise is treated in a straightforward manner in the inverse image test while for the direct image it can cause conservative tests. The main algorithms for implementing the new test are introduced and an example is given to demonstrate their efficiency.
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