This study displays theoretical and experimental investigation on the characteristics of the relocated zone of quiet by a virtual microphone (VM) based filtered-x LMS (FxLMS) algorithm which can be embedded in a real-time digital controller for an active headrest system. The attenuation changes at the relocated zones of quiet by the variation of the distance between the ear and the error microphone are mainly examined. An active headrest system was implemented for the control experiment at a chair and consists of two (left and right) secondary loudspeakers, two error microphones, two observer microphones at ear positions in a HATS, and other electronics including a dSPACE 1401 controller. The VM based FxLMS algorithm achieved an attenuation of about 22 dB in the control experiment against a narrowband primary noise by the variation of the distance between the ear and the error microphone. The important factors for the algorithm are discussed as well.
With the advancement of the embedded processors, active noise control (ANC) to cancel an unwanted noise with antinoise by taking the principle of superposition has been studied in many industrial applications [
The virtual microphone (VM) technique that relocates the zone of quiet generated at an error microphone to the position of a virtual microphone is introduced to minimize the signal at the virtual microphone [
In this paper theoretical and experimental investigation on the characteristics of the relocated zone of quiet by a VM based FxLMS algorithm which can be embedded in a real-time digital controller for an active headrest system is considered against the narrowband swept primary noise such as accelerating car engine noise. The properties of the attenuations and responses at the relocated zones of quiet with the variation of the distance between the observer microphone at the ear position and the error microphone are analyzed in depth. In addition, the governing factors of the VM based FxLMS, such as the secondary path and the virtual secondary path models, are clarified and their effects are analyzed. The effect of the inclusion of the response difference in the algorithm, which will be symbolized as
The rest of this paper is organized as follows. In Section
In this section, the FxLMS algorithm and the VM based FxLMS algorithm are discussed for generating a quiet zone at the position of an error microphone and relocating the quiet zone to the point of a virtual microphone, respectively, in a headrest system.
As illustrated in Figure
Localization of the quiet zone by an active method. (a) Location of the quiet zones at error microphones (VM algorithm off). (b) Relocation of the quiet zone at the ear position (VM algorithm on).
The block diagram of the VM based FxLMS algorithm is shown in Figure
Block diagram of the VM based FxLMS algorithm.
As presented in Figure
Assuming that the half (left or right) side of the active headrest system has
Thus the multichannel VM based FxLMS update equation to relocate the active quiet zone to the ear can be given as [
Also the estimated virtual error signal vector
By (
As displayed in Figure
Schematic diagram of the active headrest system for control experiment.
Implementation of the active headrest system.
For the implementation of the real-time VM based FxLMS for the active headrest, a dSPACE 1401 is used as an embedded controller with some other electronics and circuits including the low pass filters with the cutoff frequency of about 2 kHz for antialiasing and reconstruction filtering of the signals, two signal conditioners (PCB 480E09), and a power amplifier as shown in Figure
The primary noise was a linearly swept narrowband signal with four-component orders of the fundamental frequency C1 (200
As shown in Figure
Impulse response functions of the secondary, virtual secondary, cross secondary, and cross virtual secondary paths at the distance
In the real-time control experiment, the two ANC algorithms of the FxLMS and the VM based FxLMS were considered for the active headrest system.
In Figures
Comparison of the measured error signals at the error microphones with the FxLMS algorithm. (a) PSD functions. (b) Attenuations.
In Figures
Comparison of the measured error signals at the observer (virtual) microphone with the FxLMS algorithm. (a) PSD functions. (b) Attenuations.
In Figures
Comparison of the measured error signals at the error microphones with the VM based FxLMS algorithm. (a) PSD functions. (b) Attenuations.
In Figures
Comparison of the measured error signals at the observer (virtual) microphone with the VM based FxLMS algorithm. (a) PSD functions. (b) Attenuations.
In Figures
Comparison of the averaged attenuations of the measured signals at the error microphone and the observer microphone against the distance
Comparison of the averaged attenuations of the measured signals at the error microphone and the observer microphone against the distance
As shown in Figure
As displayed in Figure
For the extension of the quiet zones, it is necessary to have even more exact and precise models of the secondary path and the virtual secondary path. Also more error microphones and secondary loudspeakers can provide further reduction of noise in the headrest system.
In summary of the above discussions, the accuracy of the path models of
This investigation describes a new VM based FxLMS algorithm which can be embedded in a real-time digital controller for an active headrest system. The main outcomes are summarized in the following.
Different from the FxLMS algorithm, the averaged attenuation
The suggested VM based FxLMS algorithm requires the path models of
Extending the quiet zones in the active headrest will be considered in terms of multiple error microphones and loudspeakers for the application of real headrest systems in the future.
The authors declare that they have no competing interests.
This research was supported by a grant (12-TI-C01) from the Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.