Index of content:
Volume 118, Issue 3, September 2005
- NOISE: ITS EFFECTS AND CONTROL 
118(2005); http://dx.doi.org/10.1121/1.1992727View Description Hide Description
A method for noninvasive system identification/secondary path modeling has been developed for single- and multi-channel filtered- least-mean-square (LMS)-based active noise control(ANC). The problem of on-line secondary path modeling is recognized as one of linear dependence associated with an underdetermined system, a one-equation/two-unknown problem in which the highly correlated primary source and secondary source contributions to the error signal are not readily distinguishable. The method resolves this uniqueness issue by introducing a second equation with similar unknowns. The critical linear independence of the two equations, hence the proposed designation, is achieved with a single perturbation of the control filter output, thereby rendering the system solvable. This secondary path modeling strategy was implemented using an innovative real-time DSP control architecture and tested on a “transducerless” system devised to investigate behavior of ANC algorithms. Results of narrowband, broadband, and multi-channel tests reveal response estimates that are accurate in both magnitude and phase; bias due to primary noise and other secondary sources is notably absent in the obtained secondary path models. The rapidity with which the system is identified can also contribute to the stability and performance of filtered- LMS-based controllers.
118(2005); http://dx.doi.org/10.1121/1.1992787View Description Hide Description
In this paper active noise control strategies for noise barriers are presented which are based on the use of sensors near the noise barrier. Virtual error signals are derived from these near-field sensor signals such that reductions of the far-field sound pressure are obtained with the active system. The performance of the control algorithm is compared for far-field error signals, near-field error signals, and virtual far-field error signals, with and without additional reference sensors. The virtual error signals are obtained by using separate transfer functions for the primary sources and secondary sources. These separate transfer functions are determined in such a way that the necessity of the separation of the virtual sensors for the primary field and for the secondary field can be judged by direct comparison. The systems are evaluated for independent broadband and randomly positioned primary sources, changing source spectra, moving sources, and configurations involving a nonvanishing wind speed.