Anomaly Detection of Storage Battery Based on Isolation Forest and Hyperparameter Tuning

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Abstract

The safety of an uninterruptible power supply (UPS) unit is very important in the operation of a telecommunication room. It is necessary to identify and replace abnormal electrical batteries of the UPS to ensure the normal operation of the equipment. In this paper, a single-model method based on isolation forest and hyperparameter tuning is proposed for detecting abnormal batteries. Experimental results show that the proposed method is efficient in offline situations. A multi-model method is also proposed to deal with the online anomaly detection problem, which is found performing well.

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Lee, C. H., Lu, X., Lin, X., Tao, H., Xue, Y., & Wu, C. (2020). Anomaly Detection of Storage Battery Based on Isolation Forest and Hyperparameter Tuning. In ACM International Conference Proceeding Series (pp. 229–233). Association for Computing Machinery. https://doi.org/10.1145/3395260.3395271

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