Heat pumps are increasingly being installed in domestic buildings, which is an opportunity to reduce the energy needed to heat and cool buildings. However, this reduction will only be possible if the equipment is maintained correctly. Fault detection and diagnosis (FDD) systems can improve the cost of operating and maintaining heating and air conditioning systems, specifically heat pump, while keeping their performance.
This article first briefly introduces the methodologies used in FDD systems for heat pumps and compare their performance. Then, an accurate description of the common faults and their effects on field vapor compression systems is made. After that, a compilation of which faults and how are emulated in both laboratory conditions and virtual environments are extensively described. The measurements needed to perform the diagnosis are analyzed along with instru-mentation needed for FDD systems.
Finally, the virtual sensors applied to heat pumps to reduce the cost asso-ciated with FDD implementation are described. This article aims to establish a criterion for selecting which faults can be tested under laboratory conditions or by simulation with a virtual model and to determine the features that identify those faults. Finally, several areas of improvement for the aspects reviewed have been identified: increase the use of performance indicators for FDD, new and updated studies about the health status of field heat pumps, testing methods that take into account the gradual and probabilistic nature of heat pump faults and further research in the use of virtual sensors in FDD systems.