Abstract
The paper deals with the application of process identification methods to injection moulding machine monitoring. Estimation of specific mathematical models from process data is used to compute variables which are not directly measurable and to indicate variations in processing conditions or machine malfunctions.The injection stage is very sensible to influences of material changes or machine settings. Thus a dynamic model of this processing step provides information about various disturbances, that cannot be reflected by the process variables alone.on-line estimation yields a very simple model characterized by few parameters. For disturbance and failure detection an algorithm must be used for feature extraction to separate certain classes of malfunction. Examples of feature display are presented, according to the various aspects of process supervision.
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