Data-driven fault detection and diagnosis for centralised chilled water air conditioning system

Sulaiman, Noor Asyikin and Chuink, Kai Wern and Zainudin, Muhammad Noorazlan Shah and Md Yusop, Azdiana and Sulaiman, Siti Fatimah and Abdullah, Md Pauzi (2022) Data-driven fault detection and diagnosis for centralised chilled water air conditioning system. Przeglad Elektrotechniczny, 1. pp. 217-221. ISSN 0033-2097

Text PE-NOOR ASYIKIN(PE6462)-FINAL DRAFT-1.PDF Download (1MB)

Abstract

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

Item Type:	Article
Uncontrolled Keywords:	Air conditioning system, Decision tree, Fault detection and diagnosis
Divisions:	Faculty of Electronics and Computer Engineering
Depositing User:	Norfaradilla Idayu Ab. Ghafar
Date Deposited:	06 Mar 2023 11:43
Last Modified:	25 May 2023 16:00
URI:	http://eprints.utem.edu.my/id/eprint/26261
Statistic Details:	View Download Statistic

Actions (login required)

View Item