Contrôle actif du bruit et des vibrations de la transmission principale d'un Bell 407

• Main Author: Bélanger, Pierre
• Other Authors: Berry, Alain
• Language: French
• Published: Université de Sherbrooke 2006
• Online Access: http://savoirs.usherbrooke.ca/handle/11143/1446

The main objective of this research project is to study the feasibility and effectiveness of active structural acoustic control of the main transmission of a Bell 407 under laboratory conditions. Ultimately this project should lead to a reduction of the level of noise inside the passenger area of this helicopter. This project is a collaborative program between Bell Helicopter Textron Canada Limited, the Consortium for Research and Innovation in Aerospace in Quebec (CRIAQ) and the Groupe d'Acoustique de l'Université de Sherbrooke (GAUS). The first step was the characterization of the source of noise and vibration with vibroacoustic spectra from ground and flight tests on a Bell 407. The tones associated to the transmission in the 500 Hz to 3000 Hz range were identified. Secondly, a laboratory setup was developed. Essentially, this laboratory setup is a simplified representation of the main transmission-roof-cabin system of the Bell 407. The laboratory setup was validated with various impact tests on a Bell 407. Then, a finite element model of the laboratory setup was developed under MSC.NASTRAN. This model was also experimentally validated. The finite element model of the laboratory setup was used to realize many optimal active control simulations. The objective of these simulations was to find a configuration of control actuators and error sensors effective to attenuate the mean square velocity of the receiving panel of the laboratory setup. Finally, the laboratory setup was used for the laboratory demonstration of active control. The most effective configuration obtained from the simulations was experimentally implemented. Promising active control results were obtained with 2 different algorithms, the filtered-reference least mean square (FXLMS) and the principal component least mean square (PCLMS).