• Journal of Internet Computing and Services
    ISSN 2287 - 1136 (Online) / ISSN 1598 - 0170 (Print)
    https://jics.or.kr/
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A study on machine learning-based anomaly detection algorithm using current data of fish-farm pump motor


Sae-yong Park, Tae Uk chang, Taeho Im, Journal of Internet Computing and Services, Vol. 24, No. 2, pp. 37-45, Apr. 2023
10.7472/jksii.2023.24.2.37, Full Text:
Keywords: Recirculating aquaculture system, electric pump, current, Anomaly Detection, ADTK

Abstract

In line with the 4th Industrial Revolution, facility maintenance technologies for building smart factories are receiving attention and are being advanced. In addition, technology is being applied to smart farms and smart fisheries following smart factories. Among them, in the case of a recirculating aquaculture system, there is a motor pump that circulates water for a stable quality environment in the tank. Motor pump maintenance activities for recirculating aquaculture system are carried out based on preventive maintenance and data obtained from vibration sensor. Preventive maintenance cannot cope with abnormalities that occur before prior planning, and vibration sensors are affected by the external environment. This paper proposes an anomaly detection algorithm that utilizes ADTK, a Python open source, for motor pump anomaly detection based on data collected through current sensors that are less affected by the external environment than noise, temperature and vibration sensors.


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Cite this article
[APA Style]
Park, S., chang, T., & Im, T. (2023). A study on machine learning-based anomaly detection algorithm using current data of fish-farm pump motor. Journal of Internet Computing and Services, 24(2), 37-45. DOI: 10.7472/jksii.2023.24.2.37.

[IEEE Style]
S. Park, T. U. chang, T. Im, "A study on machine learning-based anomaly detection algorithm using current data of fish-farm pump motor," Journal of Internet Computing and Services, vol. 24, no. 2, pp. 37-45, 2023. DOI: 10.7472/jksii.2023.24.2.37.

[ACM Style]
Sae-yong Park, Tae Uk chang, and Taeho Im. 2023. A study on machine learning-based anomaly detection algorithm using current data of fish-farm pump motor. Journal of Internet Computing and Services, 24, 2, (2023), 37-45. DOI: 10.7472/jksii.2023.24.2.37.