抄録
In a large scale system like building air-conditioning system, measured time-series data is observed from many kinds of sensors. It is difficult to detect the fault by the administrators because only the limited experts can diagnose the unusual system. For this reasons, a new method is required, which can detect the fault from the measured data using a computer automatically. This paper proposes the method of fault detection based on information extraction from measured time-series data in a building air-conditioning system. Fault in building air conditioning system make data generate condition “hunching”, which consists of repetition of rises and descents. The proposal method converts target measured time-series data into frequency components in order to extract condition “hunching”, and detect fault by Discriminant Analysis. Through practical experiments, it is confirmed that the proposal method can detect all faults as well as fault diagnosis using expert knowledge in a building air-conditioning system.
