Using genetic algorithms to optimize the location of transducers for an active noise barrier

Abstract

The effectiveness of an active noise barrier is heavily dependent on the positioning of secondary sources and error sensors. Typically, these components are located at the edge of the barrier; however, research suggests that alternative distributions may improve the performance of the active barrier. This paper utilizes a genetic optimizer to determine optimal transducer locations based on specific criteria. Two approaches are employed: the Two-step approach which, first identifies optimal control source positions and then seeks the best error microphone locations, and the Multi-parameter approach, which optimizes all active noise control parameters simultaneously. The acoustic fields of primary and secondary sources are analyzed for various numbers of control sources progressively increasing from 2 to 10 units. Results indicate that the Multi-parameter approach achieves higher outcomes and requires less computational effort. This approach is more desirable than the Two-step approach. The best configuration for the active noise barrier is determined to be control sources and error microphones placed at a height below the barrier’s edge and are distributed with an interval between a half and a full wavelength. The number of error sensors should be close to the number of secondary sources and both transducers should be placed at the farthest distance from the barrier surface, but oppositely. Furthermore, the study shows that when the primary noise source is close to the barrier adjacent transducers should not be spaced uniformly.