Identification of the defective equipments in GIS using the self organising map
Lin, T., Aggarwal, R. K. and Kim, C. H., 2004. Identification of the defective equipments in GIS using the self organising map. Generation, Transmission and Distribution, IEE Proceedings-, 151 (5), pp. 644-650.
Related documents:This repository does not currently have the full-text of this item.
You may be able to access a copy if URLs are provided below.
Condition monitoring for gas insulated switchgear (GIS) requires an accurate and reliable identification of the defective equipment in it for maintenance purposes. In this paper, a feature extraction procedure is explored, which is based on the power spectral density (PSD) of the denoised partial discharges (PDs) emanating from the defective equipment in the GIS. Furthermore, artificial intelligence techniques, in particular, the self organising map (SOM), are investigated for their roles as classifiers to precisely identify this defective equipment, based on the PSD feature patterns. The performance of the SOM-based classifier is ascertained by using the PDs acquired from GIS in the Korean 154-kV EHV transmission networks.
|Creators||Lin, T., Aggarwal, R. K. and Kim, C. H.|
|Departments||Faculty of Engineering & Design > Electronic & Electrical Engineering|
|Additional Information||ID number: ISI:000225963700013|
Actions (login required)