Abstract
Fault detection and fault diagnosis of technical processes become more important in the course of progressive automation. Computer based fault supervision methods are developed which allow the early detection and localization of process faults during normal operation. The use of process models enables to estimate process state variables and parameters which are influenced by faults. The contribution concentrates on fault diagnosis based on process parameters. The general procedure is outlined, comprising parameter estimation, feature extraction, fault decision and classification. Experimental results are given for the detection of several faults in an electrical drive/centrifugal pump set and an steam heated heat exchanger.
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