Classification of load change transients and incipient abnormalities in underground cable using pattern analysis techniques

This paper presents a feasibility study on the application of pattern analysis techniques to classify load change transients and incipient abnormalities in an underground distribution cable lateral. The data were collected using an on-line monitoring system installed in a residential area in Dallas. A set of features obtained from wavelet packet analysis was evaluated. Methods of dimensionality reduction were employed to overcome the curse of dimensionality while preserving a good classification rate. The classification results using k-nearest-neighbor (KNN) classifiers show that the proposed methodology can be used to classify load change transients and incipient abnormalities.