Academic Journal
Fault detection for air conditioning system using machine learning
| العنوان: | Fault detection for air conditioning system using machine learning |
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| المؤلفون: | Sulaiman, Noor Asyikin, Abdullah, Md Pauzi, Abdullah, Hayati, Zainudin, Muhammad Noorazlan Shah, Md Yusop, Azdiana |
| المصدر: | IAES International Journal of Artificial Intelligence (IJ-AI); Vol 9, No 1: March 2020; 109-116 ; 2252-8938 ; 2089-4872 ; 10.11591/ijai.v9.i1 |
| بيانات النشر: | Institute of Advanced Engineering and Science |
| سنة النشر: | 2020 |
| مصطلحات موضوعية: | Machine Learning, Air Conditioning System, Fault detection |
| الوصف: | Air conditioning system is a complex system and consumes the most energy in a building. Any fault in the system operation such as cooling tower fan faulty, compressor failure, damper stuck, etc. could lead to energy wastage and reduction in the system’s coefficient of performance (COP). Due to the complexity of the air conditioning system, detecting those faults is hard as it requires exhaustive inspections. This paper consists of two parts; i) to investigate the impact of different faults related to the air conditioning system on COP and ii) to analyse the performances of machine learning algorithms to classify those faults. Three supervised learning classifier models were developed, which were deep learning, support vector machine (SVM) and multi-layer perceptron (MLP). The performances of each classifier were investigated in terms of six different classes of faults. Results showed that different faults give different negative impacts on the COP. Also, the three supervised learning classifier models able to classify all faults for more than 94%, and MLP produced the highest accuracy and precision among all. |
| نوع الوثيقة: | article in journal/newspaper |
| وصف الملف: | application/pdf |
| اللغة: | English |
| Relation: | https://ijai.iaescore.com/index.php/IJAI/article/view/20422/12920; https://ijai.iaescore.com/index.php/IJAI/article/view/20422 |
| DOI: | 10.11591/ijai.v9.i1.pp109-116 |
| الاتاحة: | https://ijai.iaescore.com/index.php/IJAI/article/view/20422 https://doi.org/10.11591/ijai.v9.i1.pp109-116 |
| Rights: | Copyright (c) 2020 Institute of Advanced Engineering and Science ; http://creativecommons.org/licenses/by-sa/4.0 |
| رقم الانضمام: | edsbas.3EA55D13 |
| قاعدة البيانات: | BASE |
| DOI: | 10.11591/ijai.v9.i1.pp109-116 |
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