More than 65% of residential Vapor Compression Cycle (VCC) systems in the U.S. suffer from improper installation issues and various faults. The inefficient operation results in unnecessary energy waste and increased occupant thermal dissatisfaction in homes. In the last two decades, automated fault detection and diagnosis (AFDD) methods have served to identify potential faults and provide essential information for repairs and fault-tolerant control strategies. However, the selection of FDD methods largely relies on the system characteristics and available sensor data. Thus, it is challenging for researchers and practitioners to select and apply existing FDD methods for residential VCC systems. This paper presents a comparative analysis of several FDD methods for residential VCC systems, including statistical rule-based charts, sensitivity ratio method, and simple rule-based method, under the same testing conditions. First, a comprehensive collection of FDD approaches for residential VCC systems is introduced with detailed descriptions of required measurements, size of data sets, selected features for identification, essential assumptions, target systems, etc. These FDD methods, compiled in Python, are compared through testing with the same lab test data from a heat pump operating in the cooling season. The performance of these FDD methods is then ranked in terms of diagnosis accuracy, false alarm rate, and sensors requirement. The preliminary test results show that applying these existing FDD methods in specific cases is challenging due to the data unavailability and inherent assumptions (e.g., some threshold values). The diagnosis accuracy for fault-free cases is found to be as high as 100%, i.e., the false alarm rate is relatively low, while the diagnosis accuracy for faulty cases is relatively low if several parameters, like classification thresholds, are set as default assumptions instead of being adapted to the specific scenario. By presenting a comparative analysis of rule-based FDD methods for residential VCC systems, this paper aims to establish a criterion for selecting which features need to be measured in a given fault scenario for different FDD methods in a cost-effective way.
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- Comparisons of Rule-Based Fault Detection and Diagnostic Methods for Residential Vapor Compression Cycle Systems
- Tao Yang - Texas A&M UniversityArkasama Bandyopadhyay - Texas A&M UniversityZheng O'Neill - Texas A&M UniversityJin Wen - Drexel UniversityAustin Rogers - Pacific Northwest National Laboratory
- ASHRAE transactions, v 128(2), pp 615-623
- Amer Soc Heating, Refrigerating And Air-Conditioning Engs
- 9
- DE-EE0008694 / Building Technologies Office at the U.S. Department of Energy through the Building America program
- Conference proceeding
- English
- Civil, Architectural, and Environmental Engineering
- WOS:001054860300076
- 2-s2.0-85170084648
- 991021960808004721
research.portal.fulldisplay.sdgs.intro
research.portal.fulldisplay.sdgs.source
research.portal.fulldisplay.incitesHighlights.intro
- esploro.research.conf.research.portal.label.prefix.inciteCollaboration
- research.portal.fulldisplay.incitesHighlights.institutionCollaboration
- esploro.research.conf.research.portal.label.prefix.inciteWOSResearchAreas
- Construction & Building Technology
- Engineering, Mechanical