| Download | - View final version: A comparative investigation between rule- and inverse model-based fault detection and diagnostics for HVAC control systems (PDF, 556 KiB)
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| DOI | Resolve DOI: https://doi.org/10.1088/1742-6596/2600/2/022007 |
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| Author | Search for: Darwazeh, D.1; Search for: Gunay, B.; Search for: Rizvi, F.1; Search for: Lowcay, D.2; Search for: Shillinglaw, S.1 |
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| Affiliation | - National Research Council Canada. Construction
- National Research Council Canada. Digital Technologies
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| Format | Text, Article |
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| Abstract | Fault detection and diagnostics (FDD) tools provide valuable information regarding system faults and deviation from expected operation. Most existing FDD tools apply rule-based fault detection algorithms that generate an alarm when a rule is met; however, these tools cannot evaluate the overall performance of a system. Inverse-model-based FDD algorithms can be deployed to complement the fault alarms triggered by rule-based building energy management systems (BEMS). This paper examines the faults detected by rule- and inverse model-based algorithms used to detect faults in multiple zone variable air volume air handling unit systems. The capability of the rule- and inverse model-based algorithms in detecting and diagnosing faults is demonstrated through illustrative examples using data from three commercial buildings in New Brunswick, Canada. The results show that inverse model-based algorithms could diagnose faults that were not detected by the rule-based FDD algorithms implemented in a commercially available BEMS tool. |
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| Publication date | 2023-11-01 |
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| Publisher | IOP |
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| Licence | |
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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 | 0abfdd9e-2a5e-4c8a-8bfb-9ad62d92f763 |
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| Record created | 2024-03-08 |
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| Record modified | 2024-03-08 |
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