In the building energy efficiency field, developing automatic and accurate fault detection and diagnosis methods is necessary in order to ensure optimal operations of systems and to save energy. In this paper first, fault detection analysis based on statistical methods where anomalies are detected through a comparison with neighborhood and averaged fault-free values and through a clustering technique is performed. Following the fault detection step, a fault diagnosis analysis based on fuzzy sets and fuzzy logic is implemented. Experimentation is carried out over a one day monitoring data set in December 2013 for the fan coil electric consumption of an actual office building located at ENEA ‘Casaccia’ Research Centre. Results show the effectiveness of proposed approaches in automatic detection and diagnosis of abnormal building fan coil electric consumption.
Lauro, F., Moretti, F., Capozzoli, A., Khan, I., Pizzuti, S., Macas, M., et al. (2014). Building fan coil electric consumption analysis with fuzzy approaches for fault detection and diagnosis. ENERGY PROCEDIA, 62, 411-420 [10.1016/j.egypro.2014.12.403].