Guidance of active noise control algorithms for practical applications

Abstract

Active noise control is a noise reduction technique of generating anti-phase sound based on superposition principle. Compared to other methods, including removal or modification of noise source and passive noise control, it has potential to reduce the resultant noise more with less effect on the other performances because it can directly control the noisy sound in target zone. In company with the development of cheap and high-performance digital signal processor and sensors and actuators, it has been actively researched for the recent applications. Under this background, a guidance of active noise control algorithms for practical application is proposed in this dissertation. The purpose of the proposed guidance is to help narrow the range of selecting algorithms and develop it in the range. To validate proposed guidance, it is applied for three applications of magnetic resonance imaging and dishwasher and vehicle. In the guidance, the structure of algorithm is determined by the noise generation process with practical limitation of each application. For two applications of magnetic resonance imaging and vehicle, the improved versions are additionally developed. Each performance is evaluated in numerical simulation and real-time experiment. The results demonstrate that algorithms selected by the proposed guidance are effective to reduce noise and the improved versions show better performance than those of the previous algorithms. It is concluded that the proposed guidance has the feasibility for practical applications.