Abstract
Propeller synchrophasing control is an active noise control method which can effectively reduce the noise in the cabin of a turboprop aircraft. The propeller signature model identified by the measured acoustic noise data is easily affected by flight speed, altitude, and the existence of the fuselage. Meanwhile, the noise excited by the propellers is nonstationary signal, which often fluctuates greatly, thus affecting the accuracy of the identification of the model. In this paper, a synchrophasing control experimental platform with a cylindrical scaled fuselage on ground is firstly established to validate the actual noise reduction in the cabin. Then, a minimum fluctuation data selection method based on wavelet filtering and three-parameter sinusoidal fitting is proposed to improve the identification accuracy of the propeller signature model. This method extracts the high-precision propeller blade passing frequency signal from the noise signal by using a wavelet filtering algorithm and selects the minimum fluctuation data segment by using a three-parameter sinusoidal fitting algorithm. The experimental results firstly show the significant noise attenuation achieved in the cabin using propeller synchrophasing control. Secondly, the propeller signature model improved by the minimum fluctuation data selection method has higher accuracy than that identified by the traditional method.
Highlights
The acoustic noise excited by rotating propellers consists of two parts: rotating noise and broadband noise
Spectrum characteristics analysis shows that the main component of the cabin noise of turboprop aircraft is the superposition of broadband noise and a series of discrete frequency noise, where the latter section plays a dominant role [2]
An experimental platform with a cylindrical scaled fuselage is built to Thethe paper is organizedof as the principle the the propeller signature is presented in validate real performance thefollows: synchrophasing control of inside cabin and the data selection method
Summary
The acoustic noise excited by rotating propellers consists of two parts: rotating noise and broadband noise. In orderfunctions to improve the as accuracy the propeller signature model, paper proposes a the wavelet to serve randomof process approximations to solve thethis probabilistic problems minimum data fluctuation in the structural analysis. In order to improve theWavelet accuracyfiltering of the propeller signature model, thislow-frequency paper proposessignals a minimum propeller noise signals, the based dominant signal filtering is the BPF. The fluctuation of the noise data in with whole cylindrical is built themethod real performance of data the synchrophasing control acquisition scaled periodfuselage is evaluated by to thevalidate proposed and the segment with the least inside the cabin and the selection method. An experimental platform with a cylindrical scaled fuselage is built to Thethe paper is organizedof as the principle the the propeller signature is presented in validate real performance thefollows: synchrophasing control of inside cabin and the data selection method.
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