An automatic method to detect missing components in manufactured products

In this paper we describe a method to recognize missing components on manufactured products. The proposed approach exploits the wavelet transform to extract features from the acquired data, while the diagnosis is performed by means of a neural network. The results show that this method achieves an h...

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Bibliographic Details
Main Authors: Acciani, G., Brunetti, G., Chiarantoni, E., Fornarelli, G.
Format: Conference Proceeding
Language:English
Subjects:
Circuit testing
Data mining
Electronic equipment testing
Feature extraction
Humans
Inspection
Manufactured products
Manufacturing industries
Neural networks
Production
Online Access:Request full text
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Description
Summary:In this paper we describe a method to recognize missing components on manufactured products. The proposed approach exploits the wavelet transform to extract features from the acquired data, while the diagnosis is performed by means of a neural network. The results show that this method achieves an high recognition rate. At the same time the method allows to use a very cheap diagnostic system.
ISSN:2161-4393
2161-4407
DOI:10.1109/IJCNN.2005.1556264