Estimation of the Fan Rotational Speed Using Flyover Audio Recordings

Abstract

Aircraft noise emissions affect societies around the world by impacting the population’s health and land use planning. This calls for simulation tools able to predict these types of noise emissions with high accuracy. A crucial aircraft parameter to achieve satisfying precision is the rotating frequency of the low-pressure shaft of the turbofan engine, called N1. N1 determines the engine’s power use and is here estimated acoustically from ground-based microphones. A new method for dynamic N1 estimation is presented, which is more robust as compared to earlier approaches. It makes use of different aircraft sound characteristics and combines two methods. The first method tracks multiple fan tone harmonics over time within a de-Dopplerized sound pressure spectrogram. This frequency-tracking task is solved by dynamic programming to find the global optimum. The second method relates to buzz-saw noise, and is thus applied to departures only. The buzz-saw fundamental frequency is estimated in the cepstral domain. Both submethods are separately validated and assessed with concurrent sound pressure measurements and flight deck recording data of N1. The new robust N1 estimation method will be applied in noise measurement campaigns with the goal of improving current aircraft noise emission models.