Header menu link for other important links
Global active control of harmonic noise in a vibro-acoustic cavity using Modal FxLMS algorithm
, S.V. Modak, K. Gupta
Published in Elsevier Ltd
Volume: 150
Pages: 147 - 161
The Modal FxLMS algorithm is recently proposed for reduction of global level of noise in vibro-acoustic cavities. The algorithm minimizes acoustic potential energy expressed in modal domain which allows a choice of acoustic modes whose modal amplitudes are desired to be minimized. The working of the algorithm and its effectiveness has been demonstrated previously through a numerical study and an experimental study is required to test the effectiveness of the algorithm in practice. To meet this objective this paper presents an experimental study of this algorithm for global active noise control in a rectangular box cavity. The algorithm utilizes modal filtered reference signals and modal amplitudes of the selected acoustic modes of the cavity. To identify modal filtered reference signals, modal secondary paths are utilized. In the present study, modal secondary paths are identified using experimentally identified physical secondary paths and acoustic mode shapes. Modal amplitudes of the acoustic modes are identified on the basis of acoustic pressure measurements from eight microphones suitably placed throughout the cavity. The performance of the algorithm is studied under the presence of acoustic and structural disturbances using one or two control loudspeakers. The active control is carried out at harmonic frequencies coinciding with cavity-controlled resonances and panel-controlled resonances. It is found from the experimental results that the Modal FxLMS algorithm is successful in reducing modal amplitudes of the selected acoustic modes. When all the significantly contributing acoustic modes are chosen, a reduction in global level of noise is observed at cavity as well as panel controlled resonances. © 2019 Elsevier Ltd
About the journal
JournalData powered by TypesetApplied Acoustics
PublisherData powered by TypesetElsevier Ltd