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 timeseriesare 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 ofnew disc defects. The approach is evaluated by applying it to a set of test data.