Novelty detection and multi-class classification in power distribution voltage waveforms
作者：
Highlights：
• Accurate classification of events in waveforms from electrical distribution networks.
• Novelty detection: dynamic identification of new classes of events.
• SVDD using negative examples and maximal margin separation: better generalization.
• Experiments using real data: significant improvements in classification accuracy.
• Direct application as part of tools to assist mitigation processes in power utilities.
摘要
•Accurate classification of events in waveforms from electrical distribution networks.•Novelty detection: dynamic identification of new classes of events.•SVDD using negative examples and maximal margin separation: better generalization.•Experiments using real data: significant improvements in classification accuracy.•Direct application as part of tools to assist mitigation processes in power utilities.
论文关键词：Novelty detection,New class identification,Open set recognition,Smart grids,Waveform classification
论文评审过程：Received 17 November 2014, Revised 24 September 2015, Accepted 25 September 2015, Available online 19 October 2015, Version of Record 10 November 2015.
论文官网地址：https://doi.org/10.1016/j.eswa.2015.09.048
