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Knowledge-based fault detection and diagnosis in flow-injection analysis

✍ Scribed by Jens Brandt; Bernd Hitzmann

Publisher
Elsevier Science
Year
1994
Tongue
English
Weight
854 KB
Volume
291
Category
Article
ISSN
0003-2670

No coin nor oath required. For personal study only.

✦ Synopsis

The reliable operation of flow-injection analysis systems (FI systems) demands a high degree of knowledge and experience. This a priori knowledge is of great importance, especially for a fast detection and diagnosis of faults. Transferring it into the form of a knowledge-based system and combining it with information received on-line from the recorded detector signal enables automatic operational supervision of FI systems. This contribution presents a real-time knowledge-based system for the supervision of FI systems applied in on-line bioprocess monitoring. The special conditions of real-time systems are explained and the basic structure of the knowledge base is illustrated. Examples of typical faults of the FI system are given to explain how symbolic knowledge processing can be combined with numerical analysis of data to perform a fast and reliable fault detection and fault diagnosis.

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