Reliable health monitoring of mechanical components in aerial robotic systems is crucial to their safe operation. The highly constrained nature of aerial systems requires that such systems operate with a minimum of sensing and computational power. This article proposes a method for the detection and diagnosis of motor/propeller degradation on a multicopter aerial robot. The proposed method works by monitoring the accelerometer output, and effectively correlates vibration power to the motor commands, allowing it to estimate the magnitude of a propeller's unbalance mass. This is done directly in the time domain with a recursive implementation. The method makes low computational and memory demands, and relies only on the accelerometer almost universally present on aerial robots, so that it may be easily implemented on existing platforms as well as new designs. Experiments show reliable detection of a faulty propeller on three distinct multicopter platforms: two quadcopters whose masses differ by more than an order of magnitude, and a hexacopter; one vehicle has brushed motors, two have brushless motors. The proposed method requires only a minimum of assumptions about the vehicle's dynamic model, and does not, e.g., require knowledge of the vehicle's center of mass or its mass moment of inertia.

中文翻译：

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基于实时振动的多螺旋桨螺旋桨故障诊断

对空中机器人系统中机械部件进行可靠的健康监控对于它们的安全运行至关重要。空中系统的高度受限性质要求此类系统以最小的感测和计算能力运行。本文提出了一种用于检测和诊断多直升机空中机器人的电动机/螺旋桨退化的方法。所提出的方法通过监视加速度计的输出来工作，并有效地将振动功率与电动机命令相关联，从而使其能够估计螺旋桨不平衡质量的大小。这是在时域中通过递归实现直接完成的。该方法对计算和内存的要求较低，并且仅依赖于航空机器人中几乎普遍使用的加速度计，以便可以在现有平台和新设计上轻松实现。实验表明，可以在三个不同的多旋翼飞机平台上可靠地检测出故障的螺旋桨：两个质量相差一个数量级以上的四旋翼飞机和一个六旋翼飞机；一辆车有刷电机，两辆有无刷电机。所提出的方法仅需要关于车辆的动力学模型的最小假设，并且例如不需要关于车辆的质心或其质量惯性矩的知识。