多旋翼无人机PHM故障注入平台

Chen Bo, Wang Benkuan, Ma Yuntong, Peng Yu
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引用次数: 1

摘要

无人驾驶飞行器(UAV)由于其灵活性和廉价性而广泛应用于日常生活、商业和军事领域。然而,无人机事故的不断发生,使得无人机的预测与健康管理(PHM)成为人们关注的焦点,它可以通过遥测数据对无人机飞行过程中的故障进行预测和检测。PHM还可以帮助无人机自我调整以避免坠毁。然而,现有的无人机PHM模型存在一些共性问题。最突出的是它们都存在着缺乏故障数据的问题。故障数据量大,难以支持PHM建模。因此,建立故障注入平台有助于生成故障数据,提高PHM方法的性能。在这项工作中,我们提出了一个基于ArduPilot的故障注入平台。它可以模拟无人机在飞行过程中可能发生的各种传感器和执行器故障。通过地面站获取故障遥测数据,为PHM建模建立数据库。实验结果表明,该方法具有良好的故障注入性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A fault injection platform for multirotor UAV PHM
Unmanned Aerial Vehicle (UAV) is widely used in daily life, commercial and military applications, because it is flexible and cheap. But the news of UAV accidents calls people to focus on Prognostics and Health Management (PHM) for UAV, which can predict and detect faults during the UAV ’s flight through the telemetry data. PHM can also help UAV adjust itself to avoid crashes. However, the existing PHM models on UAV have some common problems. The most outstanding one is that they are all suffering from lacking fault data. The amount of fault data is difficult to support PHM modeling. Therefore, establishing a fault injection platform will help in generating fault data and improving the performance of PHM methods. In this work, we propose a platform of fault injection based on ArduPilot. It can simulate different kinds of sensor and actuator faults which may happen on UAV during flight. Through the ground station, we can obtain the telemetry data with faults which can set up a database for PHM modeling. The experiment results show that this method has a good performance for fault injection.
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