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Chapter 3
Automated Fault Diagnosis
In the previous two chapters, we have seen that the fault diagnosis approach, currently used, has
attributes that can be improved. The complexity of today’s systems hinders an effective manual
search for the root cause of failure. The shift to software not only adds to the complexity of the
system itself, but also expands the observability of that same system 1 . So, there is a lot more data
that must be interpreted. Consequently, the knowledge of the system that most troubleshooters
have is not enough for interpreting those large amounts of data. Computing is not that restricted to
problem size as humans are, and therefore automated solutions are likely to deal with the increased
complexity. In this chapter a rational for choosing a particular automated approach is established.
At the end of this chapter, a technique is chosen that is used in the new approach to fault diagnosis.
In order to motivate this decision, this chapter gives an overview of approaches to fault
diagnosis, and briefly discusses some example implementations. The first section introduces a logical
overview of the categories that a fault diagnosis approach can be in. The sections that follow
present example implementations, and use the power supply example to show how each implementation
produces a diagnosis. This way, the reader is given understanding in the drawbacks and
advantages of each approach. This understanding is useful for judging the evaluation of these approaches,
that is given in the final section of this chapter. This evaluation is done according to the
criteria of Section 2.4.1, and is used to motivate the choice for a specific implementation.
3.1 Overview Techniques
In this section the reader is given an overview of the important concepts that play a role in fault
diagnosis techniques, and uses them to categorize approaches to the diagnosis problem. The current
approach to fault diagnosis at PMS, as discussed in the previous chapter, can be placed in the
categorization that is presented in this section. Also, the examples of automated implementations
that are presented in subsequent sections can be characterized by this categorization.
Fault diagnosis process is a means to improve the dependability of a system by making it fault
tolerant. That is, the system should remain operational in the presence of faults. There are quite a
few automated fault diagnosis techniques. The only scientific attempt trying to provide an overview
is done by Dash and Venkatasubramanian [9]. Implicitly or explicitly, in all techniques the topics
logic, complexity theory and system theory play a role. Logic because diagnosing is a reasoning task.
Complexity theory because reasoning is time/space complex. System theory because diagnosing is
1 Note that an automated approach does not exclude the use of the observations that can still - and only - be obtained
manually (e.g., a LED that blinks)
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