Fault diagnosis for heat pumps with parameter identification and clustering

For reducing the energy consumption of heat pumps, fault detection and diagnosis (FDD) is fundamental. The FDD system presented is based on a gray-box process model, the parameters of which are identified online. The faults are classified from the parameters using clustering methods. Known clustering techniques have been simplified and new “vector clustering” techniques have been developed for classifying gradual faults. The FDD system has been tested in various real applications, for one of which the results are presented in this work. The contribution lies on the application side with a software tool developed for the fully automated training process.