Active noise control in a free field with virtual sensors

Abstract

The zone of local control around a "virtual energy density sensor" is compared with that offered by an actual energy density sensor, a single microphone, and a virtual microphone. Intended as an introduction to the concept of forward difference prediction and a precursor to evaluating the virtual sensor control algorithms in damped enclosures, this paper investigates an idealized scenario of a single primary sound source in a free-field environment. An analytical model is used to predict the performance of the virtual error sensors and compare their control performance with their physical counterparts. The model is then experimentally validated. The model shows that in general the virtual energy density sensor outperforms the actual energy density sensor, the actual microphone, and the virtual microphone in terms of centering a practically sized zone of local control around an observer who is remotely located from any physical sensors. However, in practice, the virtual sensor algorithms are shown to be sensitive (by varying degrees) to short wavelength spatial pressure variations of the primary and secondary sound fields.

Design of Remote Quiet Zones Using Spot-Type Sound Reducers

“…This arrangement is based on the assumption that, at low frequencies, the spatial rate of change of the primary sound field is small at the physical and at the virtual microphone locations [7]. In the early 2000s, Kestell et al showed that the zone of quiet could be further extended using a virtual energy density sensor from the pressure and pressure gradient [22], considering that the weighted summation of pressure and velocity is much more spatially uniform than pressure only. It should also be noted that local control using phasedarray sensors was also suggested to achieve directionally sensitive detection through acoustic beam steering techniques [23], thereby producing acoustic beams which intersect to define a quiet area far away from the sensors.…”

A Study of the Virtual Microphone Algorithm for ANC System Working in Audio Interference Environment

“…With improvements in computer science, the application of complicated ANC algorithms has become feasible. Many researchers have attempted to improve the performance of ANC algorithms for real applications [2][3][4][5][6][7][8][9][10]. Among these ANC algorithms, the filtered-X least mean squares (FXLMS) algorithm is the most popular one.…”

“…Amongst many existing virtual microphone techniques, the remote microphone technique is widely used, which uses an additional filter to estimate virtual error signal from error signal of the physical microphone. There are some successful cases of applying this virtual microphone technique in the lab [4][5][6][7][8]. Pawelczyk proposed a prototype of an active headrest system by using FXLMS and the filtered-X least mean squares virtual microphone (FXLMS-VM) algorithm [7].…”

Sensor modeling and simulation: can it pass the Turing test?

“…Kestell et al, University of Adelaide (Australia) describe active noise control under that employs virtual sensors [10]. Summarizing the pros and cons of the approach, authors report "in general the 'virtual energy density sensor' outperforms the actual energy density sensor, the actual microphone and the virtual microphone in terms of centering a practically sized zone of local control around an observer who is remotely located from any physical sensors; the virtual sensor algorithms however, are shown to be sensitive (by varying degrees) to short wavelength spatial pressure variations of the primary and secondary sound fields".…”

“…Reference source not found., in which "virtual sensors" are discussed [2]- [10], the virtual sensors described in these references are either agents that reformat (perhaps taking into account some noise and error issues) data from real sensors, or they are ad hoc efforts that were handcrafted to meet the momentary needs of a specific narrow application.…”