The lead‐acid battery has been widely used in various fields. In civil aviation aircraft, it plays a vital role in the power system to maintain normal operation during the flight mission. Thus, an effective abnormal detection system for monitoring and diagnosing the status of aircraft lead‐acid battery is essential to ensure its safety and reliability. This paper aims to effectively identify aircraft battery faulty using unsupervised anomaly detection techniques. It introduces state‐of‐the‐art anomaly detection algorithms and evaluates their performance on a large real civil aviation battery data. The experimental results show that the latest isolation‐based anomaly detectors, iForest and iNNE, have outstanding performance on this task and have promising applicability as efficient methods for guaranteeing the lead‐acid battery quality and reliability in civil aviation aircraft.

中文翻译：

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飞机铅酸蓄电池异常检测

铅酸电池已广泛应用于各个领域。在民航飞机中，它在动力系统中起着至关重要的作用，以在飞行任务期间维持正常运行。因此，有效的监视和诊断飞机铅酸电池状态的异常检测系统对于确保其安全性和可靠性至关重要。本文旨在使用无监督的异常检测技术来有效地识别飞机电池故障。它介绍了最新的异常检测算法，并根据大量真实的民航电池数据评估了它们的性能。实验结果表明，最新的基于隔离的异常检测器iForest和iNNE