The Development of Fault Diagnosis Methodologies using Hierarchical Clustering and Small World Network Stratification

Many conventional fault diagnosis techniques do not effectively and efficiently use the available information and cannot achieve a satisfactory diagnosis in high dimensional real-world problems. In this paper, the fault diagnosis method using hierarchical clustering (HC) and small world (SW) networks stratification has been proposed to utilize the available information and trace up/downward based on event hierarchy and up/downstream along the physical network. As such, one can determine if certain diagnosis is applicable globally or more depends on the nature of events or locations; consequently the diagnostic uncertainty can be reduced. Duke energy distribution outage data are used to generate examples for the purpose of illustrating the motivation, necessity, implementation planning, and potential benefits of HC-SW stratification for power distribution system outage cause identification