A Prediction Method for Overall Economic Value of Fault Detection and Diagnostic Tools for Rooftop and Split Systems

Fault detection and diagnostics (FDD) tools for air-conditioning application may perform well or poorly, but it is difficult to characterize this performance in a meaningful way. Some recently proposed evaluation techniques have provided various statistics to characterize FDD performance, but these results can be difficult for a potential adopter of FDD to understand. A new method of characterizing FDD performance by predicting the overall economic value of the FDD tool is proposed in this paper. It is applicable to FDD tools intended for air-cooled unitary air-conditioners, such as rooftop units (RTU) and split systems. The method gives an estimated dollar value, normalized per nominal ton of capacity, for a specific FDD tool when applied in a typical scenario. This is accomplished by considering a large set of variables that affect the tool’s value: probabilities of fault occurrence (both type and intensity) and operating conditions during FDD deployment; energy impact of each fault scenario; fault-induced loss of equipment life, and costs associated with addressing faults. Some case studies of FDD tools currently in use are presented to demonstrate the method. These tools have a surprising range of value