Fault detection and diagnosis system for air-conditioning units using recurrent type neural network

The air-conditioning systems of buildings have been diversified in recent years, and the complexity of the systems has increased. At the same time, stability in the system and low running cost are demanded. To solve these problems, various research projects have been done. The development of the energy load prediction systems and the fault detection and diagnosis systems have received great attention. The authors propose a real time fault diagnosis system for air conditioning units (the heating unit, the cooling unit, the air intake unit, and the air-recycling unit) using a recurrent type neural network