Fault diagnosis has become a very important area of research during the last
decade due to the advancement of mechanical and electrical systems in
industries. The automobile is a crucial field where fault diagnosis is given a
special attention. Due to the increasing complexity and newly added features in
vehicles, a comprehensive study has to be performed in order to achieve an
appropriate diagnosis model. A diagnosis system is capable of identifying the
faults of a system by investigating the observable effects (or symptoms). The
system categorizes the fault into a diagnosis class and identifies a probable
cause based on the supplied fault symptoms. Fault categorization and
identification are done using similarity matching techniques. The development
of diagnosis classes is done by making use of previous experience, knowledge or
information within an application area. The necessary information used may come
from several sources of knowledge, such as from system analysis. In this paper
similarity matching techniques for fault diagnosis in automotive infotainment
applications are discussed.