설비공학논문집 (Korean Journal of Air-Conditioning and Refrigeration Engineering)

  • 제15권3호
  • /
  • Pages.159-165
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  • 2003
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  • 1229-6422(pISSN)
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  • 2465-7611(eISSN)
대한설비공학회 (The Society of Air-Conditioning and Refrigerating Engineers of Korea)
권호 표지

정규화 입력을 사용한 신경망 알고리즘에 의한 냉동기의 부분 고장 검출

The Partial Fault Detection of an hir-Conditioning System by the Neural Network Algorithm using Normalized Input Data

  • 한도영 (국민대학교 기계·자동차공학부) ;
  • 황정욱 (국민대학교 기계공학과 대학원)
  • 발행 : 2003.03.01
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초록

The fault detection and diagnosis technology may be applied in order to decrease the energy consumption and the maintenance cost of the air-conditioning system. To detect partial faults of the air-conditioning system, a neural network algorithm may be used. In this study, the neural network algorithm using normalized input data by the standard deviation was applied. And the [7$\times$10$\times$10$\times$1] neural network structure was selected. Test results showed that the neural network algorithm using normalized input data was very effective to detect the condenser fouling and the evaporator fan fault of an air-conditioning system.

키워드

참고문헌

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