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

비간섭 전력 부하 감시용 고차 적률 특징을 갖는 전력 신호 인식

  • Min, Hwang-Ki (Statistical Signal Processing Laboratory, Department of Electrical Engineering, Korea Advanced Institute of Science and Technology) ;
  • An, Taehun (Statistical Signal Processing Laboratory, Department of Electrical Engineering, Korea Advanced Institute of Science and Technology) ;
  • Lee, Seungwon (Statistical Signal Processing Laboratory, Department of Electrical Engineering, Korea Advanced Institute of Science and Technology) ;
  • Lee, Seong Ro ;
  • Song, Iickho (Statistical Signal Processing Laboratory, Department of Electrical Engineering, Korea Advanced Institute of Science and Technology)
  • 민황기 (한국과학기술원 전기 및 전자공학과 통계학적 신호처리 연구실) ;
  • 안태훈 (한국과학기술원 전기 및 전자공학과 통계학적 신호처리 연구실) ;
  • 이승원 (한국과학기술원 전기 및 전자공학과 통계학적 신호처리 연구실) ;
  • 이성로 (목포대학교 정보전자공학과) ;
  • 송익호 (한국과학기술원 전기 및 전자공학과 통계학적 신호처리 연구실)
  • Received : 2014.05.08
  • Accepted : 2014.07.09
  • Published : 2014.07.31

Abstract

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.

이 논문에서는 비간섭 전력 부하 감시에 알맞은 패턴 인식 시스템을 다룬다. 전력 신호의 고차 적률 정보를 써서 전기기구를 효과적으로 분별하여 인식할 수 있는 새로운 특징 추출 방법을 제안한다. 동작 특성이 비슷한 두 전기기구를 제안한 고차 적률 특징과 커널 판별 분석을 쓰는 패턴 인식 시스템이 효과적으로 분별하여 인식할 수 있다는 것을 모의실험으로 보인다.

Keywords

References

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