Parameter selection in data-driven fault detection and diagnosis of the air conditioning system

• Main Authors: Sulaiman, Noor Asyikin, Abdullah, Md. Pauzi, Abdullah, Hayati, Zainudin, Muhammad Noorazlan Shah, Md. Yusop, Azdiana, Sulaiman, Siti Fatimah
• Format: Article
• Language: English
• Published: Institute of Advanced Engineering and Science 2022
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.utm.my/104457/1/MdPauziAbdullah2022_ParameterSelectioninDataDrivenFault.pdf; http://eprints.utm.my/104457/; http://dx.doi.org/10.11591/ijeecs.v25.i1.pp59-67

Data-driven fault detection and diagnosis system (FDD) has been proven as simple yet powerful to identify soft and abrupt faults in the air conditioning system, leading to energy saving. However, the challenge is to obtain reliable operation data from the actual building. Therefore, a lab-scaled cen...