Simulation of active noise reduction using LMS algorithm: synthetic and field data

• Published in: Journal of physics. Conference series Vol. 1951; no. 1; pp. 12042 - 12051
• Main Authors: Feriadi, Y, Basir, Sahran, Taufiq, M, Atmojo, AY
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.06.2021
• Subjects: Active noise control; Algorithms; Convergence; Data simulation; Delay time; Least mean squares; Least mean squares algorithm; Multipurpose vehicles; Noise control; Noise reduction; Simulation
• ISSN: 1742-6588; 1742-6596; 1742-6596
• DOI: 10.1088/1742-6596/1951/1/012042

Simulation of active noise reduction using least mean squares (LMS) algorithm was carried out to support the development of the ANC (active noise control) prototype, which will be applied to a four-wheeled medium class gasoline-fueled Multi-Purpose Vehicle (MPV) with 2000-2400 cc engines. In this simulation, the LMS is applied to a set of synthetic and field data, to focus on the LMS being successfully applied to all field data, ignoring the delay time between errors and references microphone, and obtaining the optimal LMS step-size and order. Based on the simulation, positive result is shown by the LMS algorithm, where the best result, the superposition of the noise and antinoise signal attenuates and reaches convergence in about 20 ms. In addition, changes in the value of LMS orders do not significantly influence LMS predictions. On the other hand, the change in the step-size value is quite influential on the prediction, where the smaller the step-size, the longer the superposition time to reach convergence.