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  • Eskişehir Technical University Journal of Science and Technology A - Applied Sciences Engineering
  • Volume:25 Issue:2
  • ARTIFICIAL NEURAL NETWORK BASED FAULT DETECTION AND CLASSIFICATION METHOD FOR AIR CONDITIONERS

ARTIFICIAL NEURAL NETWORK BASED FAULT DETECTION AND CLASSIFICATION METHOD FOR AIR CONDITIONERS

Authors : Cengizhan Abay, Hanife Apaydın Özkan
Pages : 240-249
Doi:10.18038/estubtda.1379759
View : 27 | Download : 47
Publication Date : 2024-06-28
Article Type : Research Paper
Abstract :Air Conditioners (AC)s are devices that balance the air exchange and humidity rate as well as provide heating/cooling functions in order to keep the temperature of the environment within the desired conditions and needs. In this study, a new fault detection and classification method for AC is proposed. The method is based on the fact that power consumptions of appliances imply significant information about the appliances’ health. Hence, according to the proposed method, power profiles of considered AC are created during its operations. Artificial Neural Network (ANN) configuration of AC is specifically designed and trained by created power profiles. Trained ANN is used to detect and classify faults in the present power profile before major malfunctions occur. Taking action against detected faults helps prevent increased power consumption and serious security issues. Performance and efficiency of the Method designed for classification and detection of errors is between 95.1% - 97.01%
Keywords : Air Conditioner, Fault detection, Fault classification, Power profile, Artificial Neural Network

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