Casestudie Breakdown prediction Contell PILOT - Transumo

Another current approach is regression. The main idea is to find a function that
describes the temperature sequence best. A found function could be used for
description as well as for prediction of future behavior ([Gentle02], p. 301). 34 Beside
these presented approaches, artificial neural networks are applied again to gain
additional knowledge (e.g. [Hawibowo97], p. 21-45). 35
The succeeding chapter 5 will introduce the identified methods within this chapter
and will test them on applicability to the setting of sensor based temperature
monitoring. Before that, the next section introduces an approach that promises to be
generalized. Hence, it should be applicable to the current problem.
4.3.2 A Generalized Approach
As already mentioned in section 4.3, Frank Daßler presents an approach that should
be able to predict future measurement values without any knowledge of the
underlying setting. The Main idea is to combine several known approaches to a new
one. ([Daßler95], p. 7-8)
The presented approach is based on the idea to solve the problem of just setting
critical limits. According to the author, these existing methods lead to three problems:
([Daßler95], p. 19)
1. Just setting critical limits leads to sudden changes of current state. As long as
a value does not exceed the predefined range, the state is classified as OK.
2. In the moment of exceeding, an immediate reaction is necessary to solve
dangerous situations.
3. Chosen limits with a lower span to reduce situations of immediate danger lead
to a higher quantity of false alarms due to outliers.
Figure 4-1 illustrates the general proceeding of the new approach, which shall be
able to solve the just mentioned problems:
34 See section 5.4 for details
35 See section 5.9.2 for details
47