Abstract
Energy waste in buildings can range from 5% to 30% due to faults and inadequate controls. To effectively mitigate energy waste and reduce maintenance costs, the development of Fault Detection and Diagnosis (FDD) algorithms for building energy systems is crucial. Diagnostic Bayesian Networks (DBNs), as graphical probability models, are particularly useful in scenarios where high-quality data is not always available. While many studies have focused on single fault detection using DBNs, the occurrence of multiple simultaneous faults is common, yet the versatility of DBNs in handling such cases is rarely explored. This study adapts a DBN, initially designed for single fault diagnosis, to perform simultaneous fault diagnosis Experiments were conducted on an air handling unit (AHU) in the Netherlands, using implemented simultaneous faults to test the model. The results suggest that the DBN can detect both single and multiple faults effectively.
Original language | English |
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Title of host publication | ASim2024, The 5th Asia Conference of the IBPSA |
Publisher | IBPSA |
Pages | 1613-1620 |
Number of pages | 8 |
Publication status | Published - 2024 |
Event | The 5th Asia Conference of International Building Performance Simulation Association 2024 - Osaka, Japan Duration: 8 Dec 2024 → 10 Dec 2024 https://www.asim2024.org/ |
Conference
Conference | The 5th Asia Conference of International Building Performance Simulation Association 2024 |
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Abbreviated title | Asim 2024 |
Country/Territory | Japan |
City | Osaka |
Period | 8/12/24 → 10/12/24 |
Internet address |
Keywords
- Fault Detection and Diagnosis
- Bayesian network
- Simultaneous faults
- AHU
- Diagnostic Bayesian Networks
- Multiple Faults Detection