Outlier Detection Method for Equipment Onboard Merchant Vessels

Iori Oki, Seiji Yamada, Takashi Onoda

2023

Abstract

The equipment onboard merchant vessels are essential for safe navigation. If an equipment malfunction occurs during a voyage, it is difficult to repair it with the same speed and accuracy as on land. Therefore, it is important to It is required to be able to repair and replace the equipment with a margin of time by detecting the signs of anomalies. In this paper, we present the results of detecting signs of anomalies from various sensor data collected using One-Class SVM. It also shows the results of interpreting the signs of anomalies and detected locations using SHAP. The results show that the proposed method can detect signs of anomalies at a point about one month before the conventional method. Therefore, the proposed method is shown to be potentially useful for the maintenance of equipment on merchant vessels.

Paper Citation

in Harvard Style

Oki I., Yamada S. and Onoda T. (2023). Outlier Detection Method for Equipment Onboard Merchant Vessels. In Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-626-2, pages 649-660. DOI: 10.5220/0011665300003411

in Bibtex Style

@conference{icpram23,
author={Iori Oki and Seiji Yamada and Takashi Onoda},
title={Outlier Detection Method for Equipment Onboard Merchant Vessels},
booktitle={Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2023},
pages={649-660},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011665300003411},
isbn={978-989-758-626-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Outlier Detection Method for Equipment Onboard Merchant Vessels
SN - 978-989-758-626-2
AU - Oki I.
AU - Yamada S.
AU - Onoda T.
PY - 2023
SP - 649
EP - 660
DO - 10.5220/0011665300003411