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An Analysis Method for Operations of Hot Water Heaters by Artificial Neural Networks
Abstract
Authors tried to apply an Artificial Neural Network (ANN) to
estimation of state of building systems. The systems used in this study were
gas combustion water heaters. Empirical equations to estimate gas
consumption from measureble properies such as exhaust gas temperature and
electric current were obtained from experiments. Some operational modes,
which were hot water supply, additional combustion to keep water
temperature in bathtub, and anti-frozen heater for plumbing, were needed to
be identified. Electric currents, temperature of supply water and exhaust gas
had been measured as operational indices. ANN was applied to identify
modes automatically using learning algorism. The modes were porperly
identified and gas consumption was estimated in practical accuracy.
Citation
Yamaha, M.; Takahashi, M. (2004). An Analysis Method for Operations of Hot Water Heaters by Artificial Neural Networks. Energy Systems Laboratory (http://esl.tamu.edu); Texas A&M University (http://www.tamu.edu). Available electronically from https : / /hdl .handle .net /1969 .1 /5035.