An investigation of acoustic testing to evaluate the flightworthiness of a small unmanned aircraft system (sUAS) is presented. This work continues from the author’s previous investigations to provide more informative data analysis to aid in the identification and severity of prop damage. Earlier work demonstrated the ability to detect prop damage using acoustic methods, which led to these enhanced studies, including the impact of prop speed and the resulting effects on the acoustic signature of the sUAS. The correlation of prop speed and the severity of the prop damage with the acoustic response provides more detailed information to enhance the damage detection methodology. Using the appropriate microphone and with a prescribed prop speed can greatly improve the non-invasive acoustic damage detection. The process may also identify other abnormalities in the aircraft that aid in flightworthiness evaluation. This additional data aids in the development of remote and autonomous damage detection algorithms, resulting in safe flight operations. These non-human-based methods are of great interest to sUAS developers, who are rapidly creating rapid-response and distributed networks of autonomous UAS.

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An Enhanced Study of an Acoustic Damage Detection Method for Unmanned Aircraft

  • William Semke,
  • Djedje-Kossu Zahui,
  • Clement Tang

摘要

An investigation of acoustic testing to evaluate the flightworthiness of a small unmanned aircraft system (sUAS) is presented. This work continues from the author’s previous investigations to provide more informative data analysis to aid in the identification and severity of prop damage. Earlier work demonstrated the ability to detect prop damage using acoustic methods, which led to these enhanced studies, including the impact of prop speed and the resulting effects on the acoustic signature of the sUAS. The correlation of prop speed and the severity of the prop damage with the acoustic response provides more detailed information to enhance the damage detection methodology. Using the appropriate microphone and with a prescribed prop speed can greatly improve the non-invasive acoustic damage detection. The process may also identify other abnormalities in the aircraft that aid in flightworthiness evaluation. This additional data aids in the development of remote and autonomous damage detection algorithms, resulting in safe flight operations. These non-human-based methods are of great interest to sUAS developers, who are rapidly creating rapid-response and distributed networks of autonomous UAS.