A Novel Condition Assessment System for Underground Distribution Applications

This paper discusses an automated measurement- based condition assessment system for underground distribution. The core components of the system include rule-based and SVM-based pattern classifiers, which utilize novel features in the time and wavelet domains to classify underground cable patterns successfully into various classes based on a measure of severity. The performance of the developed system was tested and evaluated using field data from an underground distribution system. The satisfactory classification results and applications for condition assessment are presented and discussed. The results demonstrate the ability to pick-up and follow the progressive deterioration of the underground system towards an imminent fault by monitoring its incipient behavior over time.