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

Cengizhan Abay; Hanife Apaydın Özkan

doi:10.18038/estubtda.1379759

TR EN

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

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

Project Number

23ADP186

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

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

Supporting Institution

Eskisehir Technical University

Project Number

23ADP186

References

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Details

Primary Language

English

Subjects

Control Theoryand Applications

Journal Section

Research Article

Authors

Cengizhan Abay ^*
0000-0002-7484-2687
Türkiye

Hanife Apaydın Özkan
0000-0003-2932-0166
Türkiye

Publication Date

June 28, 2024

Submission Date

November 7, 2023

Acceptance Date

June 10, 2024

Published in Issue

Year 2024 Volume: 25 Number: 2

DOI

https://doi.org/10.18038/estubtda.1379759

IZ

https://izlik.org/JA44HW76NK

APA

Abay, C., & Apaydın Özkan, H. (2024). ARTIFICIAL NEURAL NETWORK BASED FAULT DETECTION AND CLASSIFICATION METHOD FOR AIR CONDITIONERS. Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering, 25(2), 240-249. https://doi.org/10.18038/estubtda.1379759

AMA

1.Abay C, Apaydın Özkan H. ARTIFICIAL NEURAL NETWORK BASED FAULT DETECTION AND CLASSIFICATION METHOD FOR AIR CONDITIONERS. Estuscience - Se. 2024;25(2):240-249. doi:10.18038/estubtda.1379759

Chicago

Abay, Cengizhan, and Hanife Apaydın Özkan. 2024. “ARTIFICIAL NEURAL NETWORK BASED FAULT DETECTION AND CLASSIFICATION METHOD FOR AIR CONDITIONERS”. Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering 25 (2): 240-49. https://doi.org/10.18038/estubtda.1379759.

EndNote

Abay C, Apaydın Özkan H (June 1, 2024) ARTIFICIAL NEURAL NETWORK BASED FAULT DETECTION AND CLASSIFICATION METHOD FOR AIR CONDITIONERS. Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering 25 2 240–249.

IEEE

[1]C. Abay and H. Apaydın Özkan, “ARTIFICIAL NEURAL NETWORK BASED FAULT DETECTION AND CLASSIFICATION METHOD FOR AIR CONDITIONERS”, Estuscience - Se, vol. 25, no. 2, pp. 240–249, June 2024, doi: 10.18038/estubtda.1379759.

ISNAD

Abay, Cengizhan - Apaydın Özkan, Hanife. “ARTIFICIAL NEURAL NETWORK BASED FAULT DETECTION AND CLASSIFICATION METHOD FOR AIR CONDITIONERS”. Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering 25/2 (June 1, 2024): 240-249. https://doi.org/10.18038/estubtda.1379759.

JAMA

1.Abay C, Apaydın Özkan H. ARTIFICIAL NEURAL NETWORK BASED FAULT DETECTION AND CLASSIFICATION METHOD FOR AIR CONDITIONERS. Estuscience - Se. 2024;25:240–249.

MLA

Abay, Cengizhan, and Hanife Apaydın Özkan. “ARTIFICIAL NEURAL NETWORK BASED FAULT DETECTION AND CLASSIFICATION METHOD FOR AIR CONDITIONERS”. Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering, vol. 25, no. 2, June 2024, pp. 240-9, doi:10.18038/estubtda.1379759.

Vancouver

1.Cengizhan Abay, Hanife Apaydın Özkan. ARTIFICIAL NEURAL NETWORK BASED FAULT DETECTION AND CLASSIFICATION METHOD FOR AIR CONDITIONERS. Estuscience - Se. 2024 Jun. 1;25(2):240-9. doi:10.18038/estubtda.1379759

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

Abstract

Keywords

Project Number

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

Abstract

Keywords

Supporting Institution

Project Number

References

Details

Primary Language

Subjects

Journal Section

Authors

Publication Date

Submission Date

Acceptance Date

Published in Issue

DOI

IZ

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