An Ensemble-Boosting Algorithm for Classifying Partial Discharge Defects in Electrical Assets
AbstractThis paper presents an ensemble-boosting algorithm (EBA) for classifying partial discharge (PD) patterns in the condition monitoring of insulation diagnosis applied for electrical assets. This approach presents an optimization technique for creating a sequence of artificial neural network (ANNs), where the training data for each constituent of the sequence is selected based on the performance of previous ANNs. Four different PD faults scenarios were manufactured in the high-voltage (HV) laboratory to simulate the PD faults of cylindrical voids in methacrylate, point-air-plane configuration, ceramic bushing with contaminated surface and a transformer affected by the internal PD. A PD dataset was collected, pre-processed and prepared for its use in the improved boosting algorithm using statistical techniques. In this paper, the EBA is extensively compared with the widely used single artificial neural network (SNN). Results show that the proposed approach can effectively improve the generalization capability of the PD patterns. The application of the proposed technique for both online and offline practical PD recognition is examined. View Full-Text
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Mas’ud, A.A.; Ardila-Rey, J.A.; Albarracín, R.; Muhammad-Sukki, F. An Ensemble-Boosting Algorithm for Classifying Partial Discharge Defects in Electrical Assets. Machines 2017, 5, 18.
Mas’ud AA, Ardila-Rey JA, Albarracín R, Muhammad-Sukki F. An Ensemble-Boosting Algorithm for Classifying Partial Discharge Defects in Electrical Assets. Machines. 2017; 5(3):18.Chicago/Turabian Style
Mas’ud, Abdullahi A.; Ardila-Rey, Jorge A.; Albarracín, Ricardo; Muhammad-Sukki, Firdaus. 2017. "An Ensemble-Boosting Algorithm for Classifying Partial Discharge Defects in Electrical Assets." Machines 5, no. 3: 18.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.