Work

Artificial Neural Network Based Fault Detection and Classification Method for Air Conditioners

Year: 2024

Type: article

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%

Source: Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering

DOI: 10.18038/estubtda.1379759

Authors: Cengizhan Abay, Hanife Apaydın Özkan

Institution: Eskisehir Technical University

Language: English

Topic: Fault Detection and Control Systems

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Affordable and clean energy

Open Access status: diamond

Funder: Eskişehir Teknik Üniversitesi