A fault diagnosis expert system on building air conditioning system for construction 4.0
Building air conditioning systems are in high demand nowadays. They provide maximum comfort for occupants by reducing indoor temperature and providing acceptable indoor air quality. Air conditioning also comprising of fresh air ventilation for better air quality and ensuring relative humidty in the...
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| Format: | Thesis |
| Language: | English English |
| Published: |
2018
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| Online Access: | http://eprints.utem.edu.my/id/eprint/23244/1/A%20Fault%20Diagnosis%20Expert%20System%20On%20Building%20Air%20Conditioning%20System%20For%20Construction%204.0%20-%20Tan%20Chee%20Nian%20-%2024%20Pages.pdf http://eprints.utem.edu.my/id/eprint/23244/2/A%20fault%20diagnosis%20expert%20system%20on%20building%20air%20conditioning%20system%20for%20construction%204.0.pdf |
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| Summary: | Building air conditioning systems are in high demand nowadays. They provide maximum comfort for occupants by reducing indoor temperature and providing acceptable indoor air quality. Air conditioning also comprising of fresh air ventilation for better air quality and ensuring relative humidty in the building. Building air conditioning sytems rely heavily on technical expertise for service and maintenance which could be costly. The aim of this research project is to develop a prototype knowledge based system for the fault diagnosis of building air conditioning systems. With the developed system, the diagnosis process for building air conditioning systems can be standardised, making them faster and more precise as compared to conventional systems by 566.5%. The developed system is also useful for inexperienced personnel as it can be used as a training module as well. Hence, the development of a fault diagnosis system is a significant contribution in air conditioning service operations. In this research work, the fault diagnosis system was developed by using the Kappa-PC expert system shell. It is supported by object-orientated technology for the MS Windows environment. It uses backward chaining for inferencing. In order to select the faults of the air conditioning components, a few specifications are laid out as constraints. The constraints for this developed expert system are based on the air conditioning system design data and expert’s experience. Two case studies were also conducted to verify the capability of the developed system. |
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