| DOI | Resolve DOI: https://doi.org/10.1016/j.autcon.2019.04.002 |
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| Author | Search for: Shi, Zixiao1; Search for: O'Brien, William |
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| Affiliation | - National Research Council of Canada. Construction
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| Format | Text, Article |
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| Abstract | This article reviews the current research on the development and implementation of automated fault detection and diagnostics (AFDD) technology for building systems. This article first examines the fundamentals of AFDD and its special requirements on building systems to provide a theoretical formulation of the problem. Some infrastructural barriers for scalable AFDD implementation are discussed. Then it reviews various methods used by previous researchers and real-life products in a typical AFDD workflow. The article compares different methods for feature generation and fault detection and fault diagnostics, and proposes ways to improve their current limitations from other research disciplines. The authors also discuss potential research topics to inspire further developed of new AFDD methodologies and make them more applicable, including: 1) fault assessments and improved information delivery; 2) benchmarking AFDD performance; 3) better interoperability of AFDD methods; and 4) cases of fault propagation and simultaneous faults. |
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| Publication date | 2019-05-03 |
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| Publisher | Elsevier |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | a74a42f9-f2d2-4ccd-87de-4b3c056d9939 |
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| Record created | 2019-05-21 |
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| Record modified | 2020-03-16 |
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