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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)
Publication Information
Korean Journal of Air-Conditioning and Refrigeration Engineering / v.15, no.3, 2003 , pp. 159-165 More about this Journal
Abstract
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.
Keywords
Neural network algorithm; Fault detection system; Condenser fouling; Evaporator fan fault; Standard deviation; Normalized input data;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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