摘要：The chiller plays an important role for providing comfort environment. Once, the incipient faults are missed, they may develop to be fatal faults and further lead to equipment damage and casualties. Nevertheless, the incipient fault in the running process of the chiller are easily neglected in noise. Moreover, the running variables of the chiller have dynamic characteristics, and each process variable is correlated with each other in each process, and a certain variable is interrelated at different times. To tackle these problems, we develop an improved canonical variable analysis (ICVA) method to detect the incipient fault in chiller units with significant dynamic characteristics. In the proposed method, the exponentially weighted moving average (EWMA) is first applied to filter the data. Then the canonical variable analysis is used to detect the fault. In this paper, ASHRAE RP-1043 experimental data are used to verify the proposed method. Simulation results show that compared with traditional CVA method, ICVA method has a higher fault detection rate for incipient fault.
