Data-driven fault detection and diagnosis for centralised chilled water air conditioning system
The air conditioning system is complex and consumes the most energy in the building. Due to its complexity, it is difficult to identify faults in the system immediately. In this project, fault detection and diagnosis system using decision tree classifier model was developed to detect and diagnose fa...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Published: |
Wydawnictwo SIGMA-NOT
2022
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| Subjects: | |
| Online Access: | http://eprints.utm.my/103892/ http://dx.doi.org/10.15199/48.2022.01.47 |
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| Institution: | Universiti Teknologi Malaysia |
| Summary: | The air conditioning system is complex and consumes the most energy in the building. Due to its complexity, it is difficult to identify faults in the system immediately. In this project, fault detection and diagnosis system using decision tree classifier model was developed to detect and diagnose faults in a chilled water air conditioning system. The developed model successfully classified normal condition and five common faults for more than 99% accuracy and precision. A graphical user interface of the system was also developed to ease the users. |
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