Browse Publications Technical Papers 2023-01-1108

Advances in the Measurement and Human Response to Noise of Unmanned Aircraft Systems 2023-01-1108

The sound produced by Unmanned Aerial Systems (known as UAS or Drones) is often considered to be one of the main barriers (alongside privacy and safety concerns) preventing the widespread use of these vehicles in environments where they may be in close proximity to the general public. To better understand the potential environmental noise impact of commercial UAS operations, work undertaken by the University of Salford has focused on two key areas. Firstly, how to characterise and measure the sound produced by UAS during outdoor flight conditions and secondly, better understanding of the dose response of UAS noise when the listener is in either an indoor or outdoor environment. The paper describes a field measurement campaign undertaken to measure several UAS performing flyovers at different speeds and take-off weights. The methodology of the measurement campaign was strongly influenced by emerging guidance and has been used to calculate the directivity of sound propagation which may be of significant benefit when modelling environmental noise impacts. This paper also presents details of a listening experiment designed to investigate the subjective response to a number of UAS operations when the listener is simulated to be either in an indoor or outdoor position. The results of the listening experiment have been analysed using linear regression analysis to understand which ‘loudness’ metric either conventional (LAeq, LASmax or LAE) or more specialised loudness metrics such as Loudness (N5), Perceived Noise Level (PNL) or Effective Perceived Noise Level (EPNL) are most appropriate for estimating perceived ‘loudness’ and ‘annoyance’. The results of this experiment indicate that both LAeq, LASmax were equally good at predicting the perceived loudness and annoyance with an Adjusted R Squared value of 0.90 and 0.93 for loudness and annoyance respectively. Loudness metric performed marginally better with adjusted R Squared values of 0.96 and 0.90 for annoyance and loudness respectively.


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