Classifying disc defects in optical disc drives by using time-series clustering
Optical disc drives are subject to various disturbances and faults. A special type of fault is the so-called disc defect. In this paper we present an approach for disc defect classification. It is based on hierarchical clustering of measured signals that are affected by disc defects. The time-series...
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Published in | 2004 American Control Conference Proceedings; Volume 4 of 6 Vol. 4; pp. 3100 - 3105 vol.4 |
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Main Authors | , , , |
Format | Conference Proceeding Journal Article |
Language | English |
Published |
Piscataway NJ
IEEE
01.01.2004
Evanston IL American Automatic Control Council |
Subjects | |
Online Access | Get full text |
ISBN | 9780780383357 0780383354 |
ISSN | 0743-1619 |
DOI | 10.23919/ACC.2004.1384385 |
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Abstract | Optical disc drives are subject to various disturbances and faults. A special type of fault is the so-called disc defect. In this paper we present an approach for disc defect classification. It is based on hierarchical clustering of measured signals that are affected by disc defects. The time-series are mapped into a feature space after which the feature vectors are clustered in a hierarchical fashion. Finally, signals are fitted onto the clusters to obtain single representations for each fault class. The resulting class descriptions can then be used for (on-line) classification of new disc defects. The approach is evaluated by applying it to a set of test data. |
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AbstractList | Optical disc drives are subject to various disturbances and faults. A special type of fault is the so-called disc defect. In this paper we present an approach for disc defect classification. It is based on hierarchical clustering of measured signals that are affected by disc defects. The time-series are mapped into a feature space after which the feature vectors are clustered in a hierarchical fashion. Finally, signals are fitted onto the clusters to obtain single representations for each fault class. The resulting class descriptions can then be used for (on-line) classification of new disc defects. The approach is evaluated by applying it to a set of test data. |
Author | Steinbuch, M. Goossens, H.J. Leenknegt, G.A.L. van Helvoirt, J. |
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SubjectTerms | Applied sciences Asia Computer science; control theory; systems Control theory. Systems Digital TV Drives Exact sciences and technology Fault detection Fingerprint recognition Mechanical engineering Optical beams Optical control Optical distortion Surface contamination |
Title | Classifying disc defects in optical disc drives by using time-series clustering |
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