Architectural Engineering and Construction, Durham School of

 

Date of this Version

2016

Citation

International Refrigeration and Air Conditioning Conference. Paper 1716.

Comments

16th International Refrigeration and Air Conditioning Conference at Purdue, July 11-14, 2016

Abstract

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 airconditioners, 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.

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