Shaping zones of quiet in a large enclosure generated by an active noise control system

Abstract

Performance of an Active Noise Control (ANC) system strongly depends on sensors and actuators spatial arrangement. It determines both achieved Noise Reduction (NR) levels and spatial distribution of obtained zones of quiet, making it an essential problem. However, if the acoustic field in the enclosure can be appropriately modelled, then optimization algorithms can be employed to find efficient configuration of the ANC system, enhancing its performance according to a formulated cost function and constraints. This paper proposes a complete method for enhancing NR levels and shaping zones of quiet generated with an ANC system by optimization of sensors and actuators arrangement. A Memetic Algorithm (MA) is utilized. The MA itself and its proposed operators are described. The optimization problem formulation is derived and discussed. As a control algorithm, Distributed Multiple Error Filtered-x Least Mean Square (DMEFxLMS) is used. Extensive simulation results are presented for an exemplary real enclosure. The model of the acoustic environment has been obtained by real-world experiments, resulting in identification of 36864 acoustic responses in total. Practically feasible cost function and constraints are evaluated. Advantages and limits of the method are pointed out and discussed.

A survey on active noise control in the past decade–Part II: Nonlinear systems

“…By introducing feedforward adaptive ANC structure to control shape and extension of ZoQ, a new avenue was proposed in [239], which has capability of creating a controllable spherical quiet zone via a compensation factor. Moreover, in [240], a ZoQ method equipped with memetic algorithm (MA) and distributed adaptation has been proposed, which holds high potential for practical applications.…”

Physical configuration-based feedforward active noise control using adaptive second-order truncated Volterra filter

“…Several other researchers have focused on exploring the optimal location of secondary sources or transducers in enclosed sound fields, and related summary can be found in several review papers. 15 In practice, noise sources and the surrounding environment are changing with time, which causes frequency, amplitude, phase and sound velocity of noise sources nonstationary. 5,16 However, the cancellation performance of the ANC system greatly depends on the accuracy of amplitude and phase of the anti-noise generated by a signal processing algorithm.…”

“…Several other researchers have focused on exploring the optimal location of secondary sources or transducers in enclosed sound fields, and related summary can be found in several review papers. 15…”

Modelling vibro–acoustic response of lightweight square aluminium panel influenced by sound source locations for active control

“…In recent years, different optimization methods have been carried out to find more effective ways to locate actuators and sensors on the vibrating structural 1 , 2 . Also, control sources 3 and microphones 4 in the acoustic field in line with the primary source, have been used to provide information about noise control results. However, a number of factors have contributed to the challenge of properly placing these secondary sources on or around the structural panel.…”