A versatile dynamic noise control framework based on computer simulation and modeling

Abstract

This article attempts to effectively reduce the impact of active noise pollution on human life, and to make up for the traditional passive noise control technique. In low-frequency noise control, there are some shortcomings. The making of active noise control (ANC) technique, in low-frequency noise reduction, can achieve very good results. This article proposes a versatile dynamic noise control framework based on computer simulation and modeling. The research is mainly focused on the principle and application of versatile dynamic noise control framework. To accomplish this, a research method combining theoretical analysis, software simulation, and hardware realization is adopted. The derivation process of the adaptive algorithm (LMS algorithm, filter-XLMS algorithm, etc.) is introduced in detail, and the influencing factors of algorithm performance, a variable step size normalization algorithm based on relative error is proposed. Perform simulation calculations on various algorithms in MATLAB, analyze parameters such as step factor, filter order, etc., and the degree of influence on the algorithm’s convergence speed and steady-state performance. Common command set software is used, the path adaptive identification is realized, and the program design of the versatile dynamic noise control framework is used. After completion of software and hardware debugging on the experimental platform of generalized comfort, the experimental equipment layout is completed. Using the additive random noise method, the adaptive offline modeling of the first path of the versatile dynamic noise control framework is realized. Finally, utilizing the experimental platform of generalized comfort, the adaptive ANC experiment of the single-channel filtered least mean square algorithm is conducted, then the experimental data are analyzed, and at last, the actual application effect of the versatile dynamic noise control framework is verified.

Keywords

• computer simulation and modeling
• noise
• active noise control
• least mean square algorithm
• algorithm improvement