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

Chun-Hsiang Lee, Xu Lu, X. Lin, Hongfeng Tao, Yaolei Xue, Chao Wu
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引用次数: 3

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.
基于隔离森林和超参数整定的蓄电池异常检测
不间断电源(UPS)设备的安全性对通信室的运行至关重要。为了保证设备的正常运行,有必要及时识别并更换UPS的异常蓄电池。本文提出了一种基于隔离森林和超参数整定的单模型电池异常检测方法。实验结果表明,该方法在离线情况下是有效的。提出了一种多模型的在线异常检测方法,并取得了良好的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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