Power Signal Recognition with High Order Moment Features for Non-Intrusive Load Monitoring | Zendy

Hwang-Ki Min | Zendy; Taehun An | Zendy; Seung-Won Lee | Zendy; Seong Ro Lee | Zendy; Iickho Song | Zendy

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Power Signal Recognition with High Order Moment Features for Non-Intrusive Load Monitoring

Author(s) -

Hwang-Ki Min,

Taehun An,

Seung-Won Lee,

Seong Ro Lee,

Iickho Song

Publication year - 2014

Publication title -

the journal of korean institute of communications and information sciences

Language(s) - English

Resource type - Journals

eISSN - 2287-3880

pISSN - 1226-4717

DOI - 10.7840/kics.2014.39c.7.608

Subject(s) - moment (physics) , power (physics) , signal (programming language) , feature extraction , kernel (algebra) , pattern recognition (psychology) , linear discriminant analysis , computer science , artificial intelligence , feature (linguistics) , engineering , mathematics , physics , linguistics , philosophy , classical mechanics , quantum mechanics , combinatorics , programming language

A pattern recognition (PR) system is addressed for non-intrusive load monitoring. To effectively recognize two appliances (for example, an electric iron and a cook top), we propose a novel feature extraction method based on high order moments of power signals. Simulation results confirm that the PR system with the proposed high order moment features and kernel discriminant analysis can effectively separate two appliances.

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