10 W. H. Semke et al. Part of the inspiration for this paper stems from the want to “cut the cord” that we use to measure mechanical vibration of the vehicle. Specifically, we wanted to see if good correlation between mechanical vibration and acoustic profile exists. Should a strong correlation exist, it would allow vibration analysis with a microphone as opposed to an accelerometer attached to a cable. In other works, similar ideas have been explored for different reasons. Sas et al. [8] introduces experimental and numerical analysis of a multirotor chassis, with the goal of isolating areas of lesser vibrations. Their goal was to identify places of lesser vibrations so they could mount the more sensitive electronics in those areas. Kloet et al. [9] has a journal publication identifying the ambient noise of a multirotor UAS. They map the sound profile in two planes, adjacent to the propellers, and under the propellers. Dissent on experimentation analysis was done in the scope of both U. S. A. and E. U. regulators and their views of noise pollution in civil aviation. In an interesting turn, Iannace et al. [10] offers a fault diagnosis method for UAVs using artificial neural networks. In the process of building a model, they examine different imbalances by placing makeshift (tape) weights to introduce vibration. The model was trained to recognize the acoustics of the imbalanced propeller, to a success rate of 97% in the environment they tested in. Previous work by Semke, [11], offers analysis of different types of mounting mechanisms onboard a quadcopter and the vibration characteristics of the sensor mounting mechanisms of both multirotor and fixed wing aircrafts. The vibration environment onboard fixed-wing and quadrotor sUAS and provides sensor data to assist in passive and active vibration control methodologies [12]. 2.2 Experimental Testing In contrast to many related works today, the goal is to investigate and better understand what happens when there is a damage to the propeller. A critical question we draw attention to is how much damage influences the acceleration and acoustic levels and ultimately the flight performance of the sUAS. Testing was performed on a DJI Phantom 4 Pro sUAS as shown in Fig. 2.1 Table 2.1 provides a key list of the aircraft specifications. In this paper four sets of blades were tested in the laboratory. For each type of blade, vibration and acoustic measurements were simultaneously collected. Undamaged blades were tested first, then one centimeter from a single blade tip, on one side Fig. 2.1 DJI Phantom 4 Pro UAS Table 2.1 DJI Phantom 4 Pro Specifications Weight 1388 g Diagonal Size 350mm MaxSpeed 2m/s Max Flight Time Approx. 30 minutes Hover Range Accuracy Vertical Accuracy: ±0.1 m (Vision Positioning), ±0.5 m (GPS Positioning) Horizontal Accuracy: ±0.3 m (Vision Positioning), ±1.5 m (GPS Positioning)
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