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Leistungen
The prototype system consists of a PC for operating, classification, archiving, communication to the environmental computer network etc., and a digital signal processor based system for signal acquisition, signal processing and data reduction. The system can be operated in the production line.
Noise and vibration signals are used for the assessment of the test specimen. Order analysis is the most important signal analysis method used for feature extraction.
The dual classifier is used for a go - no go decision and the fault diagnosis (identification of defective components or special defects). One module of the dual classifier is a tolerance scheme. The interpretation of the feature vector component is supported by the evaluation of the test specimen specific component / cinematic list. A trainable system (kNN based method) improves the diagnosis output. The specific advantage of the dual classifier is that it can apply in the production line "with the first product under test" and the maintenance of the tolerance values can be decreased by the use of the trainable system.
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