Probabilistic Performance Analysis of Fault Diagnosis Schemes

Chapter 6
Applications
6.1 Introduction
In this chapter, we explore various applications of the performance analysis framework
developed in the preceding chapters. To begin, we examine, from a high level, the various
usages of the performance metrics. Then, we demonstrate how the performance metrics
are computed for two aerospace examples. The first example is a simplified air-data sensor
system consisting of a pitot-static probe and a flight path angle measurement. The second
example is a linearized model of a vertical take-off and landing (vtol) fixed-wing aircraft. For
the first example, we consider the effects of uncertain signals, and for the second example,
we consider the effects of additive model uncertainty.
6.2 Types of Studies
Although there are many ways to interpret the performance metrics, the following types of
studies stand out as natural applications of our performance analysis framework:
1. Selecting a fault detection scheme: Given a fixed system G θ , the performance metrics
can be used to select the best fault diagnosis scheme from a finite set of schemes
{
V
(i ) = (F (i ) ,δ (i ) ) : i = 1,2,...,m } .
This type of application is most useful when the fault diagnosis schemes are designed
using disparate methodologies with incomparable design criteria.
2. Trade studies: Given a collection of systems
{
G
(i )
θ
: i = 1,2,...,m}
and a collection of fault diagnosis schemes
{
V
(i ) = (F (i ) ,δ (i ) ) : i = 1,2,...,m } ,
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