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 online 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-nearestneighbor (KNN) classifiers show that the proposed methodology can be used to classify load change transients and incipient